CN110766277B - Health assessment and diagnosis system and mobile terminal for nuclear industry field - Google Patents
Health assessment and diagnosis system and mobile terminal for nuclear industry field Download PDFInfo
- Publication number
- CN110766277B CN110766277B CN201910890436.5A CN201910890436A CN110766277B CN 110766277 B CN110766277 B CN 110766277B CN 201910890436 A CN201910890436 A CN 201910890436A CN 110766277 B CN110766277 B CN 110766277B
- Authority
- CN
- China
- Prior art keywords
- diagnosis
- equipment
- module
- data
- diagnosed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/253—Fusion techniques of extracted features
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
- G21C—NUCLEAR REACTORS
- G21C17/00—Monitoring; Testing ; Maintaining
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E30/00—Energy generation of nuclear origin
- Y02E30/30—Nuclear fission reactors
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Educational Administration (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- Plasma & Fusion (AREA)
- High Energy & Nuclear Physics (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention provides a health assessment and diagnosis system and a mobile terminal for a nuclear industry field, wherein the health assessment and diagnosis system comprises: the system comprises a feature extraction module, a knowledge base establishment module, a knowledge base binding module, a self-diagnosis module and a comprehensive health assessment module. The invention adopts a fault diagnosis technology based on multi-source information fusion, a multi-dimensional intelligent early warning technology based on a mechanism model and a multi-dimensional comprehensive health assessment technology based on equipment-level and system-level process parameters, can comprehensively reflect the comprehensive health information of a diagnosed and assessed system and equipment, can quickly locate a fault source, effectively solves the defect that the traditional diagnosis and assessment method only aims at single-dimensional parameter variables or single-type parameter variables and single-equipment and single-system information to diagnose and assess faults, and realizes the efficient prediction, quick diagnosis and comprehensive health condition assessment of multi-dimensional parameters and multi-system coupling relations of a nuclear industry production line.
Description
Technical Field
The invention relates to the technical field of nuclear industry, in particular to a health assessment and diagnosis system and a mobile terminal for a nuclear industry field.
Background
Due to the industrial particularity of the nuclear engineering production line, part of the production line processes have radioactivity, and the safe operation of part of key systems and equipment directly relates to the personnel safety, the environmental safety and the equipment safety; meanwhile, according to the guidance requirement of 'material use refinement' of the nuclear engineering production line, the normal operation and health condition of related systems and equipment are also important to the material refinement and the product quality.
The traditional nuclear engineering production line lacks effective fault diagnosis and health assessment means, system operation and equipment maintenance depend on the working experience of field personnel and the technical support of an equipment supplier, effective continuous accumulation cannot be formed, most of the information obtained by the equipment supplier or the experience of workers in different operation and maintenance groups on the field is single-dimensional parameter information or information of a single system and a single equipment, the comprehensive means of omnibearing information elements of the system and the equipment is lacked, decoupling can not be carried out on coupling between the systems, and the basis of fault diagnosis and health assessment of the system and the equipment can not be provided, and the requirements of efficient prediction, rapid diagnosis and comprehensive health assessment on the nuclear industry field are difficult to meet.
With the development of industrial automation, informatization and intelligent technologies, the research of the multi-source information fusion technology and the intelligent diagnosis technology provides an effective means for overcoming the defects of the traditional fault diagnosis mode to a certain extent, and simultaneously lays a foundation condition for introducing the fault diagnosis technology and the health assessment technology into a nuclear industry production line. Therefore, a scheme capable of meeting the requirements of efficient prediction, rapid diagnosis and comprehensive health assessment in a nuclear industry field is proposed based on a multi-source information fusion technology and an intelligent diagnosis technology, and is a problem to be solved urgently at present.
Disclosure of Invention
The invention is completed to meet the requirements of efficient prediction, rapid diagnosis and comprehensive health assessment of the production line of the nuclear industry.
The technical scheme adopted by the invention is as follows:
the invention provides a health assessment and diagnosis system for a nuclear industry field, which comprises:
the characteristic extraction module is used for carrying out data parameter characteristic extraction on process parameters of each system and equipment to be diagnosed and evaluated, vibration data of key components, audio data and image data so as to obtain process characteristic data, vibration characteristic data, audio characteristic data and image characteristic data of each system and equipment to be diagnosed and evaluated;
the knowledge base establishing module is used for establishing an equipment-level diagnosis rule knowledge base corresponding to each equipment to be diagnosed and evaluated respectively, and acquiring coupling association information and decoupling information between process systems based on the equipment-level diagnosis rule knowledge bases of different combinations so as to complete the establishment of a system-level diagnosis rule knowledge base; the system level diagnosis rule knowledge base comprises equipment level diagnosis rule knowledge base information of each system and coupling association information and decoupling information between the systems;
the knowledge base binding module is connected with the knowledge base establishing module and is used for binding each system and equipment to be diagnosed and evaluated with the corresponding system-level diagnosis rule knowledge base and equipment-level diagnosis rule knowledge base respectively;
the self-diagnosis module is respectively connected with the feature extraction module and the knowledge base establishment module and is used for mapping the process feature data, the vibration feature data, the audio feature data and the image feature data of each system and equipment to be diagnosed and evaluated to the corresponding system-level and equipment-level diagnosis rule knowledge bases to carry out rule matching and then obtaining a corresponding fault diagnosis result based on automatic processing and decision of an expert system model; and the number of the first and second groups,
and the comprehensive health assessment module is respectively connected with the self-diagnosis module and the knowledge base binding module and is used for respectively carrying out early warning and health assessment on each system to be diagnosed and assessed and equipment from three dimensions of parameter level trend prediction, equipment health assessment and system health assessment on the premise of presetting comprehensive factor analysis.
Optionally, the feature extraction module performs data parameter feature extraction on the vibration data of the key components of the systems and the devices to be diagnosed and evaluated to obtain the vibration feature data of the systems and the devices to be diagnosed and evaluated specifically includes:
the characteristic extraction module carries out filtering processing on vibration data of key components of each system and equipment to be diagnosed and evaluated so as to remove white noise;
and the characteristic extraction module is used for extracting the data parameter characteristic of the vibration data after filtering processing by adopting a frequency band energy extraction technology and an envelope demodulation technology so as to extract the vibration characteristic data of a frequency doubling amplitude, the vibration characteristic data of a frequency doubling amplitude and the vibration characteristic data of a low frequency band, a middle frequency band and a high frequency band of the bearing.
Optionally, the feature extraction module is further configured to extract common indicators; the common indicators include: kurtosis index and pulse index.
Optionally, the process parameters of the system and the equipment to be diagnosed and evaluated include: temperature, flow, pressure, power, rotor information, bearing information, sensor type, alarm type, electrical parameters, and lubrication conditions.
Optionally, the self-diagnosis module is further configured to adjust the structure of the system-level and device-level diagnosis rule knowledge base in real time according to the automatic diagnosis result and the input user verification information.
Optionally, the health assessment and diagnosis system further comprises: and the registration module is used for realizing the automatic registration of each system to be diagnosed and evaluated and equipment in the health assessment and diagnosis system.
Optionally, the health assessment and diagnosis system further comprises: a service interface; when the systems and equipment to be diagnosed and evaluated are successfully registered in the health assessment and diagnosis system, the service interface is used for being called by the online monitoring system to receive the process parameters, the vibration data, the audio data and the image data of key components of the systems and equipment to be diagnosed and evaluated, which are output by the online monitoring system and conform to the data format specified by the health assessment and diagnosis system, and sending the process parameters, the vibration data, the audio data and the image data to the feature extraction module and the knowledge base establishment module.
Optionally, the health assessment and diagnosis system further comprises: and the diagnosis report module is connected with the self-diagnosis module and used for generating a corresponding fault diagnosis evaluation report according to the fault diagnosis result output by the self-diagnosis module under the triggering of the self-diagnosis module and returning the fault diagnosis evaluation report to the online monitoring system for corresponding processing.
Optionally, the fault diagnosis evaluation report includes: basic registration information of the diagnosed equipment and system, various types of diagnosed faults and corresponding treatment measures and maintenance suggestions thereof, and the current health level of the diagnosed equipment and system.
Optionally, the health assessment and diagnosis system further comprises: and the maintainable module is respectively connected with the self-diagnosis module and the knowledge base binding module and is used for establishing an equipment-level maintainable suggestion knowledge base corresponding to different faults of the equipment to be diagnosed and evaluated according to the fault diagnosis result output by the self-diagnosis module so as to provide maintainable processing suggestions corresponding to the equipment to be diagnosed and evaluated.
Optionally, the maintainable module is further configured to combine the maintainable advice knowledge bases at different device levels into a system-level maintainable advice knowledge base according to the coupling association information and decoupling information between the system components and the system, so as to provide maintainable processing advice corresponding to each system to be diagnosed and evaluated; wherein the system-level maintainable advice knowledge base corresponds to a system-level failure.
Optionally, the analyzing of the preset comprehensive factors includes: the method comprises the following steps of process parameter analysis, vibration parameter analysis, equipment running time, equipment inspection and maintenance conditions and coupling correlation analysis between systems.
The invention also provides a mobile terminal, and the health assessment and diagnosis system for the nuclear industry field is installed in the mobile terminal.
Has the advantages that:
the health assessment and diagnosis system provided by the invention utilizes a fault diagnosis technology of multi-source information fusion, not only collects common relevant process parameters of equipment such as temperature, flow and pressure, but also collects vibration data, audio and image data of key parts of the equipment, and performs feature extraction and fusion on multi-source information of heterogeneous data, so that rapid diagnosis and accurate positioning are realized, and a maintainability suggestion is given; meanwhile, the invention combines the key systems and key devices of the nuclear engineering production line to play an important role in personnel safety, environmental safety and device safety, analyzes the object to be diagnosed from multiple dimensions such as parameter level, device level and system level, and fully considers the coupling incidence relation and decoupling relation among the systems, thereby reflecting the comprehensive health assessment information of the devices and the systems in all directions; moreover, the method effectively overcomes the defect that the traditional diagnosis and evaluation method carries out fault diagnosis and health evaluation only through single-dimensional parameter or system information island analysis, improves the accuracy and effectiveness of intelligent diagnosis and health evaluation, and provides an effective means for guaranteeing personnel safety, environmental safety, equipment safety and the like of a nuclear industry production line.
Drawings
FIG. 1 is a schematic diagram of a health assessment and diagnosis system for a nuclear industry site according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of another embodiment of a health assessment and diagnosis system for a nuclear industry site;
FIG. 3 is a diagram of an interface for real-time monitoring of parameters of a device in the nuclear industry according to an embodiment of the present invention;
FIG. 4 is a diagram of a spectral analysis of a vibration characteristic parameter of a device in the nuclear industry according to an embodiment of the present invention;
FIG. 5 is a diagram of a self-diagnosis result of an expert of a certain system in the nuclear industry according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating the process evaluation results of a system in the nuclear industry according to an embodiment of the present invention;
fig. 7 is a diagram illustrating a result of comprehensive evaluation of a certain system in the nuclear industry according to an embodiment of the present invention.
In the figure: 100-an online monitoring system; 201-register module; 202-Webservice service interface; 203-a feature extraction module; 204-knowledge base establishing module; 205-knowledge base binding module; 206-self-diagnostic module; 207-diagnostic reporting module; 208-maintainable module; 209-comprehensive health assessment module.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention is further described in detail below with reference to the accompanying drawings and examples.
The invention belongs to the field of equipment state monitoring, fault diagnosis and equipment management. The method combines the characteristics of the process flow of the nuclear industry production line, starts from the view of guaranteeing personnel, environment and equipment safety, adopts an intelligent diagnosis expert system of fuzzy reasoning, combines a multi-dimensional information fusion technology, extracts necessary and sufficient characteristic vectors from multiple dimensions such as process parameters, vibration parameters, audio parameters, image parameters and the like, combines fuzzy logic reasoning of a rule base, accurately and quickly positions a fault source, and provides a maintainability suggestion; moreover, the coupling incidence relation and the decoupling relation between the systems are analyzed from the real states of the equipment and the systems which are comprehensively and effectively reflected in an omnibearing way, and a comprehensive health assessment report is given, so that the defects of acquisition, information processing, diagnosis and assessment by using single-dimensional parameters are effectively overcome, and an effective rapid diagnosis and comprehensive health assessment means is provided for the diagnosed objects with coupling incidence between the systems.
Aiming at the process flow characteristics of a nuclear industry production line, a multi-dimensional and omnibearing health assessment and fault diagnosis measure is provided for the nuclear industry production line, and the problems that the existing single-dimensional parameter information or the information of a single system and a single device lacks comprehensive means of omnibearing information elements of the system and the device, and cannot decouple the coupling between the systems and effectively diagnose and assess the health of the system and the device are solved. The embodiment of the invention provides a health assessment and diagnosis system for a nuclear industry field based on multi-source information fusion.
Fig. 1 is a schematic structural diagram of a health assessment and diagnosis system for a nuclear industry site according to an embodiment of the present invention. As shown in fig. 1, the health assessment and diagnosis system includes:
the feature extraction module 203 is configured to perform data parameter feature extraction on multi-dimensional data of each system and equipment to be diagnosed and evaluated, such as process parameters, vibration data of key components, audio data, and image data, to obtain process feature data, vibration feature data, audio feature data, and image feature data of each system and equipment to be diagnosed and evaluated;
a knowledge base establishing module 204, configured to establish device-level diagnosis rule knowledge bases corresponding to devices to be diagnosed and evaluated, respectively, and obtain coupling association information and decoupling information between process systems based on the device-level diagnosis rule knowledge bases of different combinations, so as to complete establishment of a system-level diagnosis rule knowledge base; the system level diagnosis rule knowledge base comprises equipment level diagnosis rule knowledge base information of each system and coupling association information and decoupling information between the systems;
the knowledge base binding module 205 is connected with the knowledge base establishing module 204 and is used for binding each system and equipment to be diagnosed and evaluated with the corresponding system-level and equipment-level diagnosis rule knowledge bases respectively;
the self-diagnosis module 206 is respectively connected with the feature extraction module 203 and the knowledge base establishment module 205, and is used for mapping the process feature data, the vibration feature data, the audio feature data and the image feature data of each system and equipment to be diagnosed and evaluated to the corresponding system-level and equipment-level diagnosis rule knowledge bases to perform rule matching, and then obtaining a corresponding fault diagnosis result based on automatic processing and decision making of an expert system model;
and the comprehensive health assessment module 209 is respectively connected with the self-diagnosis module 206 and the knowledge base binding module 205, and is used for respectively performing early warning and health assessment on each system to be diagnosed and assessed and equipment from three dimensions of parameter level trend prediction, equipment health assessment and system health assessment on the premise of presetting comprehensive factor analysis.
Wherein, the process parameters of the system and the equipment to be diagnosed and evaluated include but are not limited to: temperature, flow, pressure, rotational speed, power, rotor information, bearing information, sensor type, alarm type, electrical parameters, and lubrication conditions. The predetermined composite factor analysis includes, but is not limited to: the method comprises the following steps of process parameter analysis, vibration parameter analysis, equipment running time, equipment inspection and maintenance conditions and coupling correlation analysis between systems.
In some embodiments, the feature extraction module 203 performs data parameter feature extraction on the vibration data of the key components of each system and equipment to be diagnosed and evaluated, so as to obtain the vibration feature data of each system and equipment to be diagnosed and evaluated specifically as follows:
the feature extraction module 203 performs filtering processing on vibration data of key components of each system and equipment to be diagnosed and evaluated to remove white noise;
the feature extraction module 203 performs data parameter feature extraction on the filtered vibration data by using a frequency band energy extraction technology and an envelope demodulation technology to extract frequency doubling amplitude vibration feature data, low-frequency band, medium-frequency band and high-frequency band vibration feature data of the bearing, and other related feature data.
The frequency band energy extraction technology and the envelope demodulation technology both belong to the prior art, and are not described in detail in this embodiment. The first frequency multiplication amplitude can reflect the balance state of the rotor, the second frequency multiplication amplitude can reflect the centering state of the rotor, and the low-frequency vibration can reflect the fault of the inner ring of the bearing.
In some embodiments, the feature extraction module 203 performs data parameter feature extraction on multidimensional data (process parameters, audio data, and image data) of each system and apparatus to be diagnosed and evaluated, except for vibration data of key components, to obtain process feature data, audio feature data, and image feature data of each system and apparatus to be diagnosed and evaluated, specifically:
the feature extraction module 203 performs filtering processing on multi-dimensional data (process parameters, audio data and image data) of each system and equipment to be diagnosed and evaluated to remove white noise;
the feature extraction module 203 performs data parameter feature extraction on the filtered multidimensional data by adopting a frequency band energy extraction technology and an envelope demodulation technology to extract process feature data, audio feature data and image feature data of each system and equipment to be diagnosed and evaluated.
In this embodiment, a model mechanism analysis method may be adopted to perform feature extraction on the process feature parameters, and analyze and determine an abnormal value; audio waveform analysis and pixel ratio equivalents may be employed to perform data parameter feature extraction on the audio and image data, respectively, to determine outliers therein. The model mechanism analysis method is a mechanism analysis and characteristic parameter extraction method aiming at the process flow characteristics of the nuclear industry production line; the model mechanism modeling method can simulate and analyze the development trend of the process parameters in real time, and fully reflect the abnormal faults of the process parameters of the current system and equipment to be diagnosed according to the coupling incidence relation and the decoupling relation between the system rule mechanism models.
In some embodiments, the feature extraction module 203 is also configured to extract other common indicators, such as kurtosis indicators and pulse indicators.
In the embodiment, the multi-source extraction of the multi-dimensional data characteristic information also avoids the defects of fault diagnosis and health assessment of single-dimensional parameters or system information island analysis.
In some embodiments, the self-diagnosis module 206 is specifically configured to, after the multidimensional feature data (process feature data, vibration feature data, audio feature data, and image feature data) of each system and device to be diagnosed and evaluated, which is extracted by the feature extraction module 203, is input into the corresponding system-level and device-level diagnosis rule knowledge base established by the knowledge base establishment module 204, automatically match the corresponding system-level and device-level diagnosis rule knowledge base for each system or device component to be diagnosed and evaluated: if the feature vector of the multi-dimensional feature data (process feature data, vibration feature data, audio feature data and image feature data) of the diagnosed and evaluated system or equipment component is abnormal and the rule inference machine outputs no abnormality, the operation state of the system or equipment component is considered to be normal; on the contrary, if the extracted feature vectors of the multi-dimensional feature data (the process feature data, the vibration feature data, the audio feature data and the image feature data) are successfully matched with the diagnosis rule knowledge base, and the rule inference machine outputs, the early warning notice and the fault diagnosis result of the corresponding level are obtained.
In some embodiments, the self-diagnosis module 206 is further configured to adjust the structure of the system-level and device-level diagnosis rule knowledge base in real-time according to the automatic diagnosis result and the inputted user verification information.
In the embodiment, important functions of part of key systems and key equipment of the nuclear engineering production line on personnel safety, environmental safety and equipment safety are combined, objects to be diagnosed are analyzed from multiple dimensions such as parameter level, equipment level and system level, coupling incidence relation and decoupling relation among the systems are fully considered, and therefore comprehensive health assessment information of the equipment is reflected in an all-round mode, the defect that fault diagnosis and health assessment are carried out only through single-dimension parameter or system information island analysis in a traditional diagnosis and assessment method is effectively overcome, accuracy and effectiveness of intelligent diagnosis and health assessment are improved, and effective means are provided for guaranteeing personnel safety, environmental safety, equipment safety and the like of the nuclear engineering production line.
Fig. 2 is another schematic structural diagram of a health assessment and diagnosis system for a nuclear industry site according to an embodiment of the present invention, as shown in fig. 2, the health assessment and diagnosis system further includes: a registration module 201 for realizing automatic registration of each system to be diagnosed and evaluated and equipment in the health assessment and diagnosis system.
In this embodiment, the java programming technology may be used to implement automatic registration of the system and the device to be diagnosed and evaluated according to the data transmitted by the online monitoring system of the system and the device to be diagnosed and evaluated, and the information of the key components of the system and the device to be diagnosed and evaluated may also be automatically classified and registered. Of course, each system and device to be diagnosed and evaluated should be automatically mapped and bound to its corresponding system-level and device-level diagnostic rule knowledge base.
As shown in fig. 2, the health assessment and diagnosis system further includes a Webservice service interface 202. After each system and device to be diagnosed and evaluated is successfully registered in the health assessment and diagnosis system, the Webservice service interface 202 is called by the online monitoring system 100 to receive the multidimensional data (process parameters, vibration data, audio data, image data) of the system and device to be diagnosed and evaluated, which are output by the online monitoring system 100 and conform to the data format specified by the health assessment and diagnosis system, and respectively send the multidimensional data to the feature extraction module 203 and the knowledge base establishment module 204.
The online monitoring system 100 belongs to the prior art, and the structure and function thereof are not described in detail in this embodiment. In some embodiments, the online monitoring 100 system may include a data acquisition module, which may acquire multidimensional data (process parameters, vibration data, audio data, image data) of the system and equipment to be diagnosed and evaluated as needed, so as to avoid the one-sidedness of conventional single-dimensional signal source information acquisition.
In this embodiment, the health assessment and diagnosis system is independently issued in a Webservice interface service manner, the online monitoring system 100 may call the Webservice service interface 202 of the health assessment and diagnosis system with the identity of the client, and then transmit the collected multidimensional data of the system and the device to be diagnosed and assessed to the health assessment and diagnosis system according to the data format defined by the health assessment and diagnosis system. Wherein a data transmission format and specification are defined by the health assessment and diagnosis system; data information includes, but is not limited to: the temperature, flow, pressure, rotational speed, power, rotor information, bearing information, sensor type, alarm type, electrical parameters, lubrication conditions, audio data and image data of the object to be diagnosed and evaluated, as well as vibration data of the critical components. And storing the related data into a database, and calling by different functional modules.
As shown in fig. 2, the health assessment and diagnosis system further includes: and a diagnostic report module 207 connected to the self-diagnosis module 206, configured to generate a corresponding fault diagnosis evaluation report according to the fault diagnosis result output by the self-diagnosis module 206 under the trigger of the self-diagnosis module 206, and return the fault diagnosis evaluation report to the online monitoring system 100 for corresponding processing.
Specifically, the fault diagnosis evaluation report includes: basic registration information for the diagnosed equipment and systems, various types of diagnostic faults and their corresponding treatment and repair recommendations, and the current health level (e.g., good, available, maintenance needed) of the diagnosed equipment and systems. The diagnostic fault type and the corresponding treatment measures and maintenance suggestions are bound together.
As shown in fig. 2, the health assessment and diagnosis system further includes: and the maintainable module 208 is connected with the self-diagnosis module 206 and the knowledge base binding module 205, and is used for establishing an equipment-level maintainable suggestion knowledge base of the equipment to be diagnosed and evaluated, which corresponds to different faults, according to the fault diagnosis result output by the self-diagnosis module so as to give maintainable processing suggestions corresponding to each equipment to be diagnosed and evaluated.
In some embodiments, the maintainable module 208 is further configured to combine the maintainable advice knowledge bases at different device levels into a system-level maintainable advice knowledge base according to the coupling association information and decoupling information between the system components and the system, so as to provide maintainable processing advice corresponding to each system to be diagnosed and evaluated; wherein the system-level maintainable advice knowledge base corresponds to a system-level failure.
In the embodiment, when a system-level and device-level diagnosis rule knowledge base and a maintainable suggestion knowledge base are established, a Jess rule engine and an improved Rete algorithm can be introduced, so that the health assessment and diagnosis system has high reasoning efficiency.
In this embodiment, a diagnosis rule knowledge base and a maintainability suggestion knowledge base may be respectively established for multidimensional parameters such as a process parameter, a vibration parameter, an audio parameter, and an image parameter of a nuclear industry production line. The coupling relation between the systems is restrained, coupled and decoupled by the reasoning rules of the fuzzy reasoning machine in the diagnosis rule knowledge base. A knowledge base of self-diagnostic rules for typical components of the device to be diagnosed, such as rotors, bearings, can be established, for example, based on the open source clisp programming language. Of course, when the diagnosis rule knowledge base is established, multidimensional feature data (process feature data, vibration feature data, audio feature data, image feature data) should be comprehensively considered and adopted as fault symptom information. Moreover, after the diagnostic rule knowledge base and the maintainability suggestion knowledge base are established, mapping and binding of the system, the equipment, the diagnostic rule knowledge base and the maintainability suggestion knowledge base are required to be completed according to the inference rule.
Fig. 3 is a diagram of a parameter real-time monitoring interface of a certain device in the nuclear industry according to an embodiment of the present invention, specifically illustrating a system-level and device-level parameter real-time monitoring interface of the health assessment and diagnosis system for a particular device in the nuclear industry. Wherein right-click hits parameters may associate trend analysis and trend prediction functions. The trend analysis and trend prediction function is one of the important functions of the comprehensive health evaluation module and is also an important embodiment of the multidimensional intelligent prediction early warning technology.
Fig. 4 is a diagram of a spectrum analysis of a vibration characteristic parameter of a certain device in the nuclear industry according to an embodiment of the present invention, specifically illustrating a spectrum analysis diagram of the vibration characteristic parameter extracted by the characteristic extraction module for a certain special device in the nuclear industry by the health assessment and diagnosis system. Processing and analyzing data, namely, firstly, carrying out centralized acquisition and pretreatment on the data through a field data acquisition device of an embedded system; and then, extracting important information characteristics through a characteristic extraction module, and performing frequency spectrum analysis, Fourier transform analysis, envelope spectrum analysis and the like on the characteristic parameters so as to meet the requirements of advance of the subsequent characteristic parameters and fusion of multi-source information.
Fig. 5 is a diagram of a self-diagnosis result of an expert in a certain system in the nuclear industry according to an embodiment of the present invention, specifically illustrating a diagram of a self-diagnosis result of a certain system in the nuclear industry for the health assessment and diagnosis system. The contents in the self-diagnosis result map include: the self-diagnosis module can automatically give the fault, the occurrence time and the fault diagnosis confidence of the system and the equipment to be diagnosed at present from the equipment level and the system level, and provides a detailed diagnosis report and a report form viewing and exporting link. And the self-diagnosis module is respectively connected with the feature extraction module and the equipment knowledge base module, and carries out automatic processing decision by using expert intelligent diagnosis and maintainable technology so as to obtain corresponding fault diagnosis results.
FIG. 6 is a diagram illustrating the process evaluation result of a system in the nuclear industry according to an embodiment of the present invention,
fig. 7 is a diagram illustrating a result of comprehensive evaluation of a certain system in the nuclear industry according to an embodiment of the present invention. Fig. 6 and 7 show the process evaluation and the comprehensive evaluation results of the health assessment and diagnosis system for a certain production line system of the nuclear industry, respectively. As shown in fig. 6, the contents of the process evaluation results include: basic information of process evaluation, evaluation grade, evaluation suggestion, evaluation index and description and the like. As shown in fig. 7, the contents of the comprehensive evaluation result include: basic information (system overall operation time, fault-free operation time), comprehensive evaluation state, item evaluation state and evaluation suggestion, and composition weight of item evaluation is given. The comprehensive evaluation function is one of the important functions of the comprehensive health assessment module. The comprehensive health assessment is an important embodiment of a multi-source information evaluation technology, and is a comprehensive application of characteristic parameter extraction, multi-source information fusion and intelligent diagnosis results.
The embodiment of the invention adopts a fault diagnosis technology based on multi-source information fusion, a multi-dimensional intelligent early warning technology based on a mechanism model and a multi-dimensional comprehensive health assessment technology based on equipment-level and system-level process parameters (including process parameters, vibration parameters, audio and image parameters), can comprehensively reflect the comprehensive health information of a diagnosed and assessed system and equipment, can quickly locate a fault source and give corresponding maintainable suggestions and measures, effectively solves the defect that the traditional diagnosis and assessment method only aims at single-dimensional parameter variables or single-type parameter variables and single-equipment and single-system information to diagnose and assess faults, and realizes the high-efficiency prediction, quick diagnosis and comprehensive health condition assessment of multi-dimensional parameters and multi-system coupling relations of a nuclear industry production line.
The embodiment of the invention also provides a mobile terminal (not shown in the figure), and the health assessment and diagnosis system for the nuclear industry field is installed in the mobile terminal. The mobile terminal is used for viewing the parameter information and the processing result displayed by the health assessment and diagnosis system, the health condition, the development trend and the comprehensive assessment report of the system and the equipment which are assessed and diagnosed at present at any time and any place.
In this embodiment, by installing the health assessment and diagnosis system in the mobile terminal, information interaction on each mobile terminal device can be realized, for example, the mobile terminal is used to perform operation information monitoring of the system and device to be diagnosed and review of various diagnosis and assessment reports.
It can be seen that the present invention comprises the following key technologies: the system comprises a multi-source information comprehensive evaluation technology, an expert intelligent diagnosis and maintainability technology, a multi-dimensional intelligent prediction early warning technology, a mobile internet of things technology and the like.
The multi-source information comprehensive evaluation technology comprises the following steps: multidimensional data (process parameters, vibration data, audio data, image data) of the system or device to be diagnosed and evaluated, data information including but not limited to: the method comprises the steps of carrying out feature extraction, fusion and rule reasoning on temperature, flow, pressure, rotating speed, power, rotor information, bearing information, sensor type, alarm type, electrical parameters, lubrication condition, audio data and image data of an object to be diagnosed and evaluated and vibration data of key components, carrying out item evaluation, and obtaining the comprehensive health state of a system or equipment to be diagnosed and evaluated according to the overall evaluation results of multiple items of evaluation.
Expert intelligent diagnosis and maintainable technology: respectively establishing a diagnostic rule knowledge base and a maintainable suggestion knowledge base specific to a nuclear engineering project aiming at different diagnostic targets of key equipment and systems; and a Jess rule engine and an improved Rete algorithm are introduced, so that the health assessment and diagnosis system has high reasoning efficiency.
Multidimensional intelligent prediction early warning technology: by combining the process characteristics of a nuclear industry production line and utilizing technologies such as multi-parameter variable comprehensive analysis, system level and equipment level mechanism modeling and the like, the important parameter development trend, the equipment health condition development trend and the system health condition development trend of a system or equipment to be diagnosed are predicted in real time, and diagnosis deviation and evaluation defects caused by information locality of single-dimensional parameters or single-system information are made up; meanwhile, the problems of system-level early warning, grading warning and the like caused by complex coupling association and decoupling of the nuclear industry production line can be effectively solved, the fault source is quickly positioned, and maintainability suggestions are given.
The mobile internet of things technology: the real-time information interaction of the health assessment and diagnosis system on each mobile terminal device is realized, and the health assessment and diagnosis system comprises but is not limited to: and monitoring the running information of the system and the equipment to be diagnosed and consulting various diagnosis and evaluation reports by using the mobile terminal.
The invention combines the process characteristics of the nuclear industry production line, develops a diagnosis rule knowledge base and a maintainability suggestion knowledge base corresponding to the system and the equipment to be diagnosed and evaluated based on the fault symptom information of the multi-dimensional characteristic data (process characteristic data, vibration characteristic data, audio characteristic data and image characteristic data) of the system and the equipment to be diagnosed and evaluated from the safety perspective, provides a health assessment and diagnosis system for the nuclear industry site by means of a network programming correlation technique, can effectively replace manual diagnosis, and can comprehensively reflect the health condition of the system and the equipment to be diagnosed by effectively utilizing the multi-dimensional characteristic data (process characteristic data, vibration characteristic data, audio characteristic data and image characteristic data) of the system and the equipment to be diagnosed and realize the rapid diagnosis of the system and the equipment to be diagnosed, Accurate positioning and comprehensive health assessment.
In conclusion, the invention adopts the construction concept of the comprehensive information platform, is based on the expert intelligent diagnosis and maintainable technology, the multidimensional intelligent prediction and early warning technology, the multi-information fusion comprehensive evaluation technology and the mobile Internet of things technology, combines the radioactive process characteristics of partial processes of the nuclear industry production line, carries out real-time online diagnosis on the system and equipment to be diagnosed from the safety aspects of personnel safety, environmental safety, equipment safety and the like, gives out the comprehensive health state of the system and equipment to be diagnosed from a plurality of dimensions of a system level, an equipment level and the like, solves the problems of real-time multi-source information fault diagnosis and comprehensive health evaluation of the key system and equipment of the nuclear industry production line, can quickly judge the cause and accurate parts of fault generation, prevents the occurrence of malignant accidents, provides an effective means for the personnel safety and safe production of the nuclear industry production line, prolongs the service life of the equipment, reducing the number of unplanned shutdowns provides technical support.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.
Claims (13)
1. A health assessment and diagnosis system for a nuclear industry site, comprising:
the characteristic extraction module is used for carrying out data parameter characteristic extraction on process parameters of each system and equipment to be diagnosed and evaluated, vibration data of key components, audio data and image data so as to obtain process characteristic data, vibration characteristic data, audio characteristic data and image characteristic data of each system and equipment to be diagnosed and evaluated;
the knowledge base establishing module is used for establishing an equipment-level diagnosis rule knowledge base corresponding to each equipment to be diagnosed and evaluated respectively, and acquiring coupling association information and decoupling information between process systems based on the equipment-level diagnosis rule knowledge bases of different combinations so as to complete the establishment of a system-level diagnosis rule knowledge base; the system level diagnosis rule knowledge base comprises equipment level diagnosis rule knowledge base information of each system and coupling association information and decoupling information between the systems;
the knowledge base binding module is connected with the knowledge base establishing module and is used for binding each system and equipment to be diagnosed and evaluated with the corresponding system-level diagnosis rule knowledge base and equipment-level diagnosis rule knowledge base respectively;
the self-diagnosis module is respectively connected with the feature extraction module and the knowledge base establishment module and is used for mapping the process feature data, the vibration feature data, the audio feature data and the image feature data of each system to be diagnosed and evaluated and equipment to the corresponding system-level and equipment-level diagnosis rule knowledge bases to carry out rule matching, and if the matching is successful, the early warning notice and the fault diagnosis result of the corresponding level are obtained based on the automatic processing decision of the expert system model; and the number of the first and second groups,
and the comprehensive health assessment module is respectively connected with the self-diagnosis module and the knowledge base binding module and is used for respectively carrying out early warning and health assessment on each system to be diagnosed and assessed and equipment from three dimensions of parameter level trend prediction, equipment health assessment and system health assessment on the premise of presetting comprehensive factor analysis.
2. The health assessment and diagnosis system according to claim 1, wherein the feature extraction module performs data parameter feature extraction on the vibration data of the key components of each system and equipment to be diagnosed and assessed to obtain the vibration feature data of each system and equipment to be diagnosed and assessed specifically comprises:
the characteristic extraction module carries out filtering processing on vibration data of key components of each system and equipment to be diagnosed and evaluated so as to remove white noise;
and the characteristic extraction module is used for extracting the data parameter characteristic of the vibration data after filtering processing by adopting a frequency band energy extraction technology and an envelope demodulation technology so as to extract the vibration characteristic data of a frequency doubling amplitude, the vibration characteristic data of a frequency doubling amplitude and the vibration characteristic data of a low frequency band, a middle frequency band and a high frequency band of the bearing.
3. The health assessment and diagnosis system according to claim 2, wherein said feature extraction module is further configured to extract common indicators; the common indicators include: kurtosis index and pulse index.
4. The health assessment and diagnosis system according to claim 1, wherein the process parameters of the system and equipment to be diagnosed and assessed include: temperature, flow, pressure, power, rotor information, bearing information, sensor type, alarm type, electrical parameters, and lubrication conditions.
5. The health assessment and diagnosis system according to claim 1, wherein said self-diagnosis module is further configured to adjust the structure of the system-level and device-level diagnosis rule knowledge base in real-time according to the automatic diagnosis result and the inputted user verification information.
6. The health assessment and diagnosis system according to claim 1, further comprising: and the registration module is used for realizing the automatic registration of each system to be diagnosed and evaluated and equipment in the health assessment and diagnosis system.
7. The health assessment and diagnosis system according to claim 6, further comprising: a service interface; when the systems and equipment to be diagnosed and evaluated are successfully registered in the health assessment and diagnosis system, the service interface is used for being called by the online monitoring system to receive the process parameters, the vibration data, the audio data and the image data of key components of the systems and equipment to be diagnosed and evaluated, which are output by the online monitoring system and conform to the data format specified by the health assessment and diagnosis system, and sending the process parameters, the vibration data, the audio data and the image data to the feature extraction module and the knowledge base establishment module.
8. The health assessment and diagnosis system according to claim 7, further comprising: and the diagnosis report module is connected with the self-diagnosis module and used for generating a corresponding fault diagnosis evaluation report according to the fault diagnosis result output by the self-diagnosis module under the triggering of the self-diagnosis module and returning the fault diagnosis evaluation report to the online monitoring system for corresponding processing.
9. The health assessment and diagnosis system according to claim 8, wherein said fault diagnosis assessment report comprises: basic registration information of the diagnosed equipment and system, various types of diagnosed faults and corresponding treatment measures and maintenance suggestions thereof, and the current health level of the diagnosed equipment and system.
10. The health assessment and diagnosis system according to claim 1, further comprising: and the maintainable module is respectively connected with the self-diagnosis module and the knowledge base binding module and is used for establishing an equipment-level maintainable suggestion knowledge base corresponding to different faults of the equipment to be diagnosed and evaluated according to the fault diagnosis result output by the self-diagnosis module so as to provide maintainable processing suggestions corresponding to the equipment to be diagnosed and evaluated.
11. The health assessment and diagnosis system according to claim 10, wherein the maintainable module is further configured to combine the maintainable advice knowledge bases at different device levels into a system-level maintainable advice knowledge base according to the coupling association information and decoupling information between the system components and the system, so as to provide maintainable processing advice corresponding to each system to be diagnosed and assessed; wherein the system-level maintainable advice knowledge base corresponds to a system-level failure.
12. The health assessment and diagnosis system according to claim 1, wherein said predetermined comprehensive factor analysis comprises: the method comprises the following steps of process parameter analysis, vibration parameter analysis, equipment running time, equipment inspection and maintenance conditions and coupling correlation analysis between systems.
13. A mobile terminal characterized in that the health assessment and diagnosis system for a nuclear industry site as claimed in any one of claims 1 to 12 is installed therein.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2018217350858 | 2018-10-24 | ||
| CN201821735085 | 2018-10-24 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110766277A CN110766277A (en) | 2020-02-07 |
| CN110766277B true CN110766277B (en) | 2022-08-09 |
Family
ID=69329733
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910890436.5A Active CN110766277B (en) | 2018-10-24 | 2019-09-20 | Health assessment and diagnosis system and mobile terminal for nuclear industry field |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110766277B (en) |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112257988A (en) * | 2020-09-29 | 2021-01-22 | 中广核工程有限公司 | Complex accident feature identification and risk early warning system and method for nuclear power plant |
| CN112308300A (en) * | 2020-10-19 | 2021-02-02 | 中国电子科技集团公司第三十八研究所 | Large-scale electronic product state prediction management system |
| CN112184055A (en) * | 2020-10-19 | 2021-01-05 | 深圳蜂巢互联科技有限公司 | Online investigation report automatic generation equipment for manufacturing industry |
| CN112581729B (en) * | 2020-12-14 | 2023-01-20 | 中冶京诚工程技术有限公司 | Alarm diagnosis method and system for production line |
| CN112561310B (en) * | 2020-12-14 | 2024-11-05 | 中冶京诚工程技术有限公司 | Health evaluation diagnosis method and system for production line |
| CN112863546A (en) * | 2021-01-21 | 2021-05-28 | 安徽理工大学 | Belt conveyor health analysis method based on audio characteristic decision |
| CN112836833B (en) * | 2021-02-10 | 2023-10-13 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Health state evaluation method for spaceflight measurement and control data transmission integrated equipment |
| CN114063601A (en) * | 2021-11-12 | 2022-02-18 | 江苏核电有限公司 | Equipment state diagnosis system and method based on artificial intelligence |
| CN114997554B (en) * | 2022-03-21 | 2024-03-12 | 湖北文理学院 | Evaluation method, device and storage medium for health condition of complex mechanical equipment |
| CN115469643A (en) * | 2022-09-15 | 2022-12-13 | 中国核动力研究设计院 | Nuclear power station rotating machinery health management method, system and medium |
| CN115829335B (en) * | 2023-02-16 | 2023-05-16 | 山东和顺腾达高科技材料有限公司 | Production line execution risk assessment system for aluminum profile machining |
| CN116958084B (en) * | 2023-07-20 | 2024-07-19 | 上海韦地科技集团有限公司 | Intelligent image sensing system and method based on large nuclear industry data |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2518470A1 (en) * | 2009-12-25 | 2012-10-31 | Mitsubishi Heavy Industries, Ltd. | Nuclear-power-plant soundness evaluation system |
| WO2014054051A1 (en) * | 2012-10-03 | 2014-04-10 | Forbes Marshall Pvt. Ltd. | Health monitoring system for a process plant and a method thereof |
| KR20140055292A (en) * | 2012-10-31 | 2014-05-09 | 한국수력원자력 주식회사 | System and method for relating between failed component and performance criteria of manintenance rule by using component database of functional importance determination of nuclear power plant |
| CN104299659A (en) * | 2013-07-16 | 2015-01-21 | 中广核工程有限公司 | Method, device and system for monitoring running state of nuclear power plant |
| CN105551549A (en) * | 2015-12-07 | 2016-05-04 | 中广核工程有限公司 | Method and system for on-line monitoring of running state of nuclear power equipment |
| CN106597965A (en) * | 2016-12-07 | 2017-04-26 | 中国船舶重工集团公司第七〇九研究所 | Nuclear power apparatus running state monitoring system and monitoring method |
| CN107767975A (en) * | 2017-10-17 | 2018-03-06 | 中北大学 | A kind of nuclear power unit closes the monitoring and fault diagnosis method of heavy parts capability and performance |
-
2019
- 2019-09-20 CN CN201910890436.5A patent/CN110766277B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2518470A1 (en) * | 2009-12-25 | 2012-10-31 | Mitsubishi Heavy Industries, Ltd. | Nuclear-power-plant soundness evaluation system |
| WO2014054051A1 (en) * | 2012-10-03 | 2014-04-10 | Forbes Marshall Pvt. Ltd. | Health monitoring system for a process plant and a method thereof |
| KR20140055292A (en) * | 2012-10-31 | 2014-05-09 | 한국수력원자력 주식회사 | System and method for relating between failed component and performance criteria of manintenance rule by using component database of functional importance determination of nuclear power plant |
| CN104299659A (en) * | 2013-07-16 | 2015-01-21 | 中广核工程有限公司 | Method, device and system for monitoring running state of nuclear power plant |
| CN105551549A (en) * | 2015-12-07 | 2016-05-04 | 中广核工程有限公司 | Method and system for on-line monitoring of running state of nuclear power equipment |
| CN106597965A (en) * | 2016-12-07 | 2017-04-26 | 中国船舶重工集团公司第七〇九研究所 | Nuclear power apparatus running state monitoring system and monitoring method |
| CN107767975A (en) * | 2017-10-17 | 2018-03-06 | 中北大学 | A kind of nuclear power unit closes the monitoring and fault diagnosis method of heavy parts capability and performance |
Non-Patent Citations (1)
| Title |
|---|
| 健康状态评估方法及应用研究;吴波;《计算机测量与控制》;20091225(第12期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110766277A (en) | 2020-02-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110766277B (en) | Health assessment and diagnosis system and mobile terminal for nuclear industry field | |
| CN110647133B (en) | Rail transit equipment state detection maintenance method and system | |
| CN105809255B (en) | A kind of thermal power plant's rotating machinery health control method and system based on Internet of Things | |
| US9921577B2 (en) | Method and system for diagnostic rules for heavy duty gas turbines | |
| CN109800127A (en) | A kind of system fault diagnosis intelligence O&M method and system based on machine learning | |
| CN102880115B (en) | A kind of numerically controlled machine remote cooperative diagnosis system based on Internet of Things | |
| CN109242104A (en) | A kind of system for analyzing real-time discovering device failure exception using data | |
| CN111509847A (en) | Intelligent detection system and method for power grid unit state | |
| CN111098463A (en) | Injection molding machine fault diagnosis system and diagnosis method | |
| CN113962299A (en) | Intelligent operation monitoring and fault diagnosis general model for nuclear power equipment | |
| CN111255674B (en) | System and method for detecting state of rotating mechanical equipment | |
| CN112124229A (en) | Remote real-time fault diagnosis method for emergency pump truck | |
| CN112541563A (en) | Rotary equipment vibration prediction management system based on edge calculation technology | |
| CN116228186A (en) | Ship cabin intelligent operation and maintenance system based on human engineering | |
| CN104035433B (en) | Remote precise diagnosis and maintenance system and method of industrial devices | |
| CN110543658A (en) | Power plant equipment diagnosis method based on big data | |
| CN111753603A (en) | EDG fault diagnosis system of emergency generator set | |
| CN114280383B (en) | Health detection device and health detection method for large ground station antenna | |
| CN102929241B (en) | Safe operation guide system of purified terephthalic acid device and application of safe operation guide system | |
| CN107918339A (en) | Photovoltaic O＆M intelligence cloud platform and its control method | |
| CN117672255B (en) | Abnormal equipment identification method and system based on artificial intelligence and equipment operation sound | |
| CN113313365A (en) | Degradation early warning method and device for primary air fan | |
| CN111539642B (en) | Object-oriented power plant data acquisition and processing system and method thereof | |
| CN115186007A (en) | Airborne data identification real-time display method and system for monitoring and reminding | |
| CN114066163A (en) | Power equipment state analysis method and device based on three-layer architecture mode |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |