JP2006234784A - Machine equipment abnormality diagnosis apparatus and abnormality diagnosis method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an abnormality diagnosis device and an abnormality diagnosis method for mechanical equipment capable of specifying the presence / absence of an abnormality and an abnormal part while ensuring diagnosis accuracy without being affected by noise.
An apparatus for diagnosing abnormalities in mechanical equipment, comprising at least one component 12 that rotates or slides, includes at least one detection unit 20 that outputs a signal generated from the mechanical equipment 10 as an electrical signal, Signal processing that performs frequency analysis of the waveform, compares the frequency component of the measured spectrum data obtained by frequency analysis with the frequency component caused by the component, and determines the presence or absence and abnormal part of the component based on the verification result Unit 32. The reference value used for comparison and collation is calculated based on the limited frequency range of the measured spectrum data.
[Selection] Figure 1

Description

  The present invention relates to an abnormality diagnosis apparatus and abnormality diagnosis method for rotating or sliding parts used in mechanical equipment such as a reduction gear, an electric motor, a windmill, a railway vehicle, etc. The present invention relates to an abnormality diagnosis apparatus and an abnormality diagnosis method for a mechanical facility that identifies the abnormal part.

  Conventionally, after rotating parts such as railway vehicles and wind turbines for power generation are used for a certain period, bearings and other rotating parts are regularly inspected for abnormalities such as damage and wear. This periodic inspection is carried out by disassembling the mechanical device in which the rotating parts are incorporated, and the person in charge finds damage and wear generated in the rotating parts by visual inspection. And the main defects found in the inspection are in the case of bearings, indentations caused by the biting of foreign matter, peeling due to rolling fatigue, other wear, etc., in the case of gears, missing teeth and wear, etc. In the case of a wheel, there is wear such as a flat, and in any case, if irregularities or wear that is not found in a new article is found, it is replaced with a new one.

Various methods for diagnosing abnormalities of rotating parts in an actual operating state without disassembling a mechanical device in which the rotating parts are incorporated have been proposed (see, for example, Patent Documents 1 to 3). As the most general one, as described in Patent Document 1, an accelerometer is installed in the bearing portion, the vibration acceleration of the bearing portion is measured, and further, FFT (Fast Fourier Transform) processing is performed on this signal. Thus, there is known a method of performing diagnosis by extracting a signal of vibration generation frequency components.
JP 2002-22617 A JP 2003-202276 A Japanese Patent Laid-Open No. 2004-257836

  However, in the method of disassembling the entire mechanical equipment and visually inspecting by the person in charge, the disassembling work for removing the rotating body and the sliding member from the apparatus, and the inspected rotating body and the sliding member being incorporated into the apparatus again. There has been a problem that a large amount of labor is required for the assembly work and the maintenance cost of the apparatus is greatly increased.

  Further, when reassembling, the inspection itself may cause a defect in the rotating body or the sliding member, such as attaching a dent to the rotating body or the sliding member that was not present before the inspection. Further, since a large number of bearings are visually inspected within a limited time, there is a problem that a possibility of overlooking a defect remains. Furthermore, the determination of the degree of the defect also varies depending on the individual, and parts are exchanged even if there is substantially no defect, resulting in a wasteful cost.

  Further, in the abnormality diagnosis method described in Patent Document 1, the accuracy of diagnosis deteriorates due to the influence of noise or the like depending on how the judgment reference value is set, and stable operation is hindered, such as starting an abnormality alarm based on an erroneous diagnosis. There was a problem.

  Further, in the above abnormality diagnosis method, a large amount of diagnosis results are accumulated, and it is an excessive burden to create a report based on the large amount of diagnosis results.

  The present invention has been made in view of the above-described circumstances, and an object of the present invention is mechanical equipment that can identify the presence or absence of an abnormality and an abnormal portion while ensuring diagnosis accuracy while being hardly affected by noise. An abnormality diagnosis apparatus and an abnormality diagnosis method are provided. Another object of the present invention is to provide an abnormality diagnosis apparatus and abnormality diagnosis method for mechanical equipment that can reduce the burden of creating a report of diagnosis results.

The object of the present invention is achieved by the following constitution.
(1) A machine facility abnormality diagnosis device comprising at least one component that rotates or slides,
At least one detector that outputs a signal generated from the mechanical equipment as an electrical signal;
Performing frequency analysis of the waveform of the electrical signal, comparing the frequency component of the measured spectrum data obtained by the frequency analysis with the frequency component resulting from the component, whether there is an abnormality in the component based on the verification result, and A signal processing unit for determining an abnormal site;
With
A machine facility abnormality diagnosis device, wherein a reference value used for the comparison and collation is calculated based on a limited frequency range of the measured spectrum data.
(2) An apparatus for diagnosing abnormality of mechanical equipment, comprising at least one component that rotates or slides,
At least one detector that outputs a signal generated from the mechanical equipment as an electrical signal;
Performing frequency analysis of the waveform of the electrical signal, comparing the frequency component of the measured spectrum data obtained by the frequency analysis with the frequency component resulting from the component, whether there is an abnormality in the component based on the verification result, and A signal processing unit for determining an abnormal site;
A storage unit for storing a diagnosis result diagnosed by the signal processing unit;
An output unit for outputting the diagnosis result in a predetermined format;
A report creation unit for creating a report based on at least one program, the output result output by the output unit;
An abnormality diagnosis apparatus for mechanical equipment, comprising:
(3) The signal processing unit performs at least one of amplification processing and filtering processing on the detected signal, and performs envelope processing on the processed waveform. (1) or (2) Machine equipment abnormality diagnosis device.
(4) The abnormality diagnosis device according to any one of (1) to (3), further including data transmission means for transmitting a determination result by the signal processing unit.
(5) The abnormality diagnosis apparatus according to any one of (1) to (4), further including a microcomputer that performs processing by the signal processing unit and processing for outputting the determination result to a control system.
(6) The mechanical equipment abnormality diagnosis apparatus according to any one of (1) to (5), wherein the mechanical equipment is a railway vehicle bearing device.
(7) The machine equipment abnormality diagnosis device according to any one of (1) to (5), wherein the machine equipment is a wind turbine bearing device.
(8) The machine equipment abnormality diagnosis device according to any one of (1) to (5), wherein the machine equipment is a machine tool spindle bearing device.
(9) A method for diagnosing abnormality of mechanical equipment, comprising at least one part that rotates or slides,
Detecting a signal generated from the mechanical equipment and outputting it as an electrical signal;
Analyzing the frequency of the waveform of the detected signal;
A step of comparing and collating the frequency component of the measured spectrum data obtained in the analysis step with the frequency component caused by the component;
Determining the presence / absence and abnormality of the part based on the comparison result in the comparison step;
With
The machine equipment abnormality diagnosis method, wherein the reference value used for the comparison and collation is calculated based on a limited frequency range of the measured spectrum data.
(10) A method for diagnosing abnormality in mechanical equipment, comprising at least one component that rotates or slides,
Detecting a signal generated from the mechanical equipment and outputting it as an electrical signal;
Analyzing the frequency of the waveform of the detected signal;
A step of comparing and collating the frequency component of the measured spectrum data obtained in the analysis step with the frequency component caused by the component;
Determining the presence / absence and abnormality of the part based on the comparison result in the comparison step;
Storing a diagnosis result obtained in at least one of the analysis, comparison, and determination steps;
Outputting the diagnosis result in a predetermined format;
Creating a report of the output result output by the output step based on at least one program;
An abnormality diagnosis method for mechanical equipment, comprising:

  According to the abnormality diagnosis device and abnormality diagnosis method for a mechanical device of the present invention, when comparing and collating the frequency component of the measured spectrum data with the frequency component caused by the component, the reference value used for comparison and collation is Since the calculation is made based on the limited frequency range, it is difficult to be affected by noise, the diagnostic accuracy can be improved, and the presence / absence of abnormality and the abnormal part can be specified.

  In addition, according to the abnormality diagnosis device and abnormality diagnosis method for a mechanical device of the present invention, the presence or absence of abnormality and the part of the abnormality can be determined without disassembling a mechanical device incorporating a rotating or sliding part with a simple configuration. Thus, it is possible to reduce the time and effort required for disassembling and assembling the apparatus, and it is possible to prevent damage to the parts due to disassembling and assembling.

  Furthermore, according to the abnormality diagnosis device and abnormality diagnosis method of the mechanical device of the present invention, the diagnosis result such as the presence or absence of abnormality, the portion of abnormality, the spectrum waveform at the time of diagnosis (actual spectrum data) is output in a predetermined format, Since the report is created based on the output result based on at least one program, the report creation work based on the diagnosis result is facilitated.

  Hereinafter, an abnormality diagnosis apparatus for machine equipment according to each embodiment of the present invention will be described in detail with reference to the drawings.

(First embodiment)
First, with reference to FIGS. 1-4, the abnormality diagnosis apparatus of the mechanical installation of 1st Embodiment is demonstrated. As shown in FIG. 1, the abnormality diagnosis apparatus detects a signal generated from the machine facility 10 and determines a state such as an abnormality of the machine facility 10 from an electrical signal output from the detection unit 20. The controller 30 includes a signal processing unit 32 and a control unit 34 that drives and controls the machine facility 10, and an output device 40 such as a monitor 43, an alarm device 44, and a report creation unit 45.

  The mechanical equipment 10 is provided with a rolling bearing 12 that is a rotating part. The rolling bearing 12 includes an inner ring 14 that is a rotating ring fitted around a rotating shaft (not shown), and a housing (not shown). An outer ring 16 that is a fixed ring fitted into the inner ring 14, a ball 18 that is a plurality of rolling elements disposed between the inner ring 14 and the outer ring 16, and a cage (not shown) that holds the ball 18 in a freely rolling manner. ).

  The detection unit 20 includes a sensor 22 that detects vibration generated from the mechanical equipment 10 during operation. The sensor 22 is fixed near the outer ring of the housing by bolt fixing, bonding, bolt fixing and bonding, or embedding with a molding material. In addition, in the case of bolt fixation, you may make it provide a rotation stop function. Further, when the sensor 22 is molded, the waterproof property is achieved and the vibration proofing property against external vibration is improved, so that the reliability of the sensor 22 itself can be drastically improved.

  The sensor 22 may be any sensor that can detect vibration, such as a vibration sensor, an AE (acoustic emission) sensor, an ultrasonic sensor, a shock pulse sensor, and the like, acceleration, speed, strain, stress, displacement type, etc. Any device that can convert the vibration into an electrical signal may be used. Further, when attaching to a mechanical device having a lot of noise, it is preferable to use an insulating type because it is less affected by noise. Further, when the sensor 22 uses a vibration detection element such as a piezoelectric element, the element may be molded into plastic or the like.

  Furthermore, in addition to the rolling bearing 12, the mechanical equipment 10 of the present embodiment can detect vibrations of gears and wheels (both not shown) by the sensor 22.

  The controller 30 including the signal processing unit 32 and the control unit 34 is configured by a microcomputer (IC chip, CPU, MPU, DSP, etc.), and receives an electrical signal from the sensor 22 via the data transmission means 24. .

  As shown in FIG. 2, the signal processing unit 32 includes a data storage / distribution unit 50, a rotation analysis unit 52, a filter processing unit 54, a vibration analysis unit 56, a comparison determination unit 58, and an internal data storage unit 60. The data storage / distribution unit 50 receives and temporarily stores the electrical signal from the sensor 22 and the electrical signal related to the rotational speed, and collects and distributes the signal to one of the analysis units 52 and 56 according to the type of the signal. It has a function. Various signals are A / D converted into digital signals by an A / D converter (not shown) before being sent to the data storage / distribution unit 50, amplified by an amplifier (not shown), and then sent to the data storage / distribution unit 50. Note that the order of A / D conversion and amplification may be reversed.

  The rotation analysis unit 52 calculates the rotation speed of the inner ring 14, that is, the rotation shaft, based on an output signal from a sensor (not shown) that detects the rotation speed, and transmits the calculated rotation speed to the comparison determination unit 58. . When the detection element is composed of an encoder attached to the inner ring 14 and a magnet and a magnetic detection element attached to the outer ring 16, the signal output from the detection element depends on the shape and rotational speed of the encoder. A corresponding pulse signal is obtained. The rotation analysis unit 52 has a predetermined conversion function or conversion table corresponding to the shape of the encoder, and calculates the rotation speed of the inner ring 14 and the rotation shaft from the pulse signal according to the function or table.

  The filter processing unit 54 extracts only a predetermined frequency band corresponding to the natural frequency from the vibration signal based on the natural frequency of the rolling bearing 12, which is a rotating component, a gear, a wheel, or the like, and extracts an unnecessary frequency band. Remove. This natural frequency can be easily obtained by vibrating the rotating part as an object to be measured by the striking method and analyzing the frequency of the vibration detector attached to the object to be measured or the sound generated by the striking. When the object to be measured is a rolling bearing, the natural frequency due to any of the inner ring, outer ring, rolling element, cage, etc. is given. In general, there are a plurality of natural frequencies of mechanical parts, and the amplitude level at the natural frequencies is high, so the sensitivity of measurement is good.

  The vibration analysis unit 56 performs frequency analysis of vibration generated in the bearing 12, the gears, and the wheels based on the output signal from the sensor 22. Specifically, the vibration analysis unit 56 is an FFT calculation unit that calculates a frequency spectrum of a vibration signal, and calculates a frequency spectrum of vibration based on an FFT algorithm. The calculated frequency spectrum is transmitted to the comparison determination unit 58. Further, the vibration analysis unit 56 may perform absolute value processing and envelope processing as preprocessing for performing FFT, and convert only to frequency components necessary for diagnosis. The vibration analysis unit 56 also outputs the envelope data after the envelope processing to the comparison determination unit 58 as necessary.

  The comparison determination unit 58 compares and collates the frequency components caused by the rolling bearing 12, the gears, and the wheels with the frequency components of the measured spectrum data of vibrations by the vibration analysis unit 56. In the present embodiment, the comparison / determination unit 58 calculates a reference value (for example, sound pressure level or voltage level) from a limited frequency range of the measured spectrum data, while rolling using the relational expressions shown in FIGS. 4 and 5. The frequency (vibration generation frequency) resulting from the scratches on the bearings and gears is calculated, the sound pressure level at the vibration generation frequency is extracted from the measured spectrum data, and compared with the reference value. Furthermore, the comparison / determination unit 58 specifies the presence / absence of an abnormality and an abnormal part based on the determination result.

  The calculation of the vibration generation frequency may be performed before this, and when the same diagnosis has been performed before, the data may be stored in the internal data storage unit 60 and used. Further, design specification data of each rotating part used for calculation is input and stored in advance.

  Then, the determination result in the comparison / determination unit 58 may be stored in the internal data storage unit 60 such as a memory or HDD, or may be transmitted to the output device 40 via the data transmission unit 42. Further, the determination result may be output to the control unit 34 that controls the operation of the drive mechanism of the mechanical equipment 10 and a control signal corresponding to the determination result may be fed back.

  Further, the output device 40 may display the determination result on the monitor 43 or the like in real time, or may notify the abnormality using an alarm device 44 such as a light or a buzzer when an abnormality is detected. .

Further, the output device 40 has a storage unit 46 for storing diagnosis results such as presence / absence of abnormality, a site of abnormality, a spectrum waveform at the time of diagnosis (actual spectrum data) obtained by the signal processing unit 32, and a predetermined diagnosis result. A data output unit 47 that outputs the output result in the form of, and a report creation unit 45 that creates a report of the output result output by the data output unit 47 based on at least one program. Thereby, the report preparation part 45 can perform the preparation work of the report based on a diagnostic result easily.
Here, the predetermined format is a format required for processing by the report creating unit 45. Note that all the target data may be output and selected / selected by the report creation unit 45, or may be output after the target data is selected / selected by the data output unit 47.

  The data transmission means 24 and 42 only need to be able to transmit and receive signals accurately, may be wired, or may be wireless using a network.

  Next, a specific example of the abnormality diagnosis processing flow based on the vibration signal will be described with reference to FIG.

  First, the sensor 31 detects the vibration of each rotating component (step S101). The detected vibration signal is converted into a digital signal by the A / D converter (step S102), amplified by a predetermined amplification factor (step S103), and then corresponding to the natural frequency of the rotating component by the filter processing unit 54. Filter processing for extracting only the predetermined frequency band is performed (step S104). Thereafter, the vibration analysis unit 56 performs envelope processing on the digital signal after the filter processing (step S105), and obtains the frequency spectrum of the digital signal after the envelope processing (step S106).

  Next, from the relational expressions shown in FIGS. 4 and 5, the vibration generation frequency generated due to the abnormality of each rotating component is obtained based on the rotation speed signal (step S107), and each rotating component corresponding to the obtained frequency is obtained. Sound pressure level of abnormal frequency band (in the case of the rolling bearing 12, the bearing flaw component Sx, that is, the inner ring flaw component Si, the outer ring flaw component So, the rolling element flaw component Sb and the cage component Sc, The gear scratch component Sg corresponding to the meshing, and in the case of a rotating body such as a wheel, wear and unbalance component Sr) of the rotating body are obtained (step S108).

On the other hand, a reference value (for example, sound pressure level or voltage level) used for abnormality diagnosis is calculated from the frequency spectrum obtained by the vibration analysis unit 54 (step S109). Here, the reference value of the present embodiment is calculated using a limited frequency range of measured spectrum data at an arbitrary time. That is, the reference value excludes a plurality of spectra (for example, the top 10 and the bottom 10) from the obtained frequency range in order to reduce the influence of noise such as spectrum data in a predetermined frequency range, for example, DC component. May be an effective value (the square root of the root mean square of the frequency spectrum) calculated using the above-mentioned value, or may be calculated based on the effective value based on the following formulas (1) and (2). May be.
(Reference value) = (effective value) + α (1)
(Reference value) = (effective value) × β (2)
α, β: Predetermined values that are variable depending on the type of data Further, instead of the effective value, the average value or the peak value of the actually measured spectrum data at an arbitrary time may be used.

  Next, the comparison between the sound pressure level (or voltage level) of the abnormal frequency band of each rotating component calculated in step S108 and the reference value calculated in step S109 is divided for each rotating component having a different design specification. (Step S110). When all the components do not match, it is determined that there is no abnormality in the rotating component (step S111). On the other hand, if any of the components match, it is determined that there is an abnormality and the abnormal part is specified (step S112), and the collation result is output to an output device such as the control unit 34, the monitor 43, the alarm device 44, or the like. 40 (step S113). In step S113, the diagnosis results obtained in steps S111 and S112 are stored in the storage unit 46 of the output device. When creating a report, the diagnosis result stored in the storage unit 46 is sent to the data output unit 47, and the data output unit 47 selects and selects target data from the sent data (step S114). Further, the selected target data is sent to a report creation unit 45 having a report creation program to create a report based on the diagnosis result (step S115).

  As described above, in this embodiment, when the frequency component of the measured spectrum data is compared with the frequency component caused by the component, the reference value used for the comparison is an effective value based on the limited frequency range of the measured spectrum data. Therefore, the average value or the peak value is calculated, so that it is difficult to be influenced by noise such as a DC component, so that the diagnostic accuracy can be improved, and the presence or absence of abnormality and the abnormal part can be specified.

  In addition, according to the abnormality diagnosis device and abnormality diagnosis method for a mechanical device of the present invention, it is possible to specify the presence or absence of abnormality and the location of the abnormality without disassembling a mechanical device incorporating a rotating component with a simple configuration. It is possible to reduce the time and effort required for disassembling and assembling the apparatus, and it is possible to prevent damage to the parts due to disassembly and assembling.

  Furthermore, according to the abnormality diagnosis device and abnormality diagnosis method for a mechanical device of the present embodiment, the signal processing unit is configured by a microcomputer, so that the signal processing unit is unitized, and the abnormality diagnosis device can be downsized and modules Can be achieved.

  In addition, according to the abnormality diagnosis device and abnormality diagnosis method of the mechanical device of the present embodiment, the presence / absence of abnormality, the portion of abnormality, the spectrum waveform at the time of diagnosis (measured spectrum data) obtained by the signal processing unit 32 A storage unit 46 for storing the diagnosis results, a data output unit 47 for outputting the diagnosis results in a predetermined format, and a report creation for creating a report on the output results output by the data output unit 47 based on at least one program Therefore, it is possible to easily create a report by outputting a large amount of diagnostic results in a predetermined format as necessary.

  In the present embodiment, the storage unit 46 for storing the diagnosis result is provided in the output device 40. However, the storage unit 46 is provided in the controller 30, and when the report is generated, the diagnosis result is transmitted as data transmission means. The data may be transmitted to the data output unit 47 via 42.

  Next, with reference to FIG. 6, the abnormality diagnosis apparatus and abnormality diagnosis method for mechanical equipment according to the second embodiment of the present invention will be described in detail. In addition, about the part equivalent to 1st Embodiment, the same code | symbol is attached | subjected and description is abbreviate | omitted or simplified.

This embodiment is a single processing unit that combines a detection unit including a sensor 22 and a signal processing unit including a microcomputer 50 in an abnormality diagnosis device for a mechanical facility 70 including a plurality of rolling bearings 12 and 12. 80 is incorporated in the bearing device of the rolling bearing 12.
As a result, the abnormality diagnosis apparatus can perform management in a centralized manner, so that efficient monitoring is possible.
Further, it is preferable to incorporate a single processing unit in the bearing device because there is a merit that the entire device becomes compact. In addition, this single processing unit may be incorporated in mechanical equipment for compactness, or a single processing unit may be configured for a plurality of rolling bearings.
Other configurations and operations are the same as those in the first embodiment.

In addition, this invention is not limited to the said embodiment, In the range which does not deviate from the summary of this invention, it can change suitably.
The mechanical equipment of the present invention may be anything provided with rotating or sliding parts that are objects of abnormality diagnosis, and includes a railway vehicle bearing device, a windmill bearing device, a machine tool main shaft bearing device, and the like.

  For example, as shown in FIG. 7, the railway vehicle bearing device 90 supports the axle shaft 90 rotatably with respect to a bearing box 92 constituting a part of the railway vehicle carriage via the double-row tapered roller bearing 12. In addition, the detection units 20 and 20 are fixed to the radial load area of the bearing housing 92 and the vibration of the bearing housing 92 is detected to perform abnormality diagnosis. If the bearing raceway surface is damaged, the collision force generated when the rolling element passes through the damaged portion is larger in the load zone than in the no-load zone, so the detection unit 20 is fixed on the load zone side. This makes it possible to detect vibration with high sensitivity.

  The rotating or sliding parts may be rotating parts such as rolling bearings, gears, axles and ball screws, and sliding parts such as linear guides and linear ball bearings. Any part may be used. In addition, a rotational speed signal is used as a speed signal for calculating a frequency component resulting from damage to the rotating part, but a moving speed signal is used as a speed signal in the case of a sliding part.

  Furthermore, the signals detected by the detection unit include sound, vibration, ultrasonic waves (AE), stress, displacement, distortion, etc., and these signals have defects or abnormalities in mechanical equipment including rotating or sliding parts. In some cases, a signal component indicating the defect or abnormality is included.

  Specific examples of abnormality diagnosis of rotating parts using the machine equipment abnormality diagnosis apparatus and method of the present invention will be described below.

FIG. 8 shows the result of frequency analysis after enveloping the vibration of the housing when noise occurs during rotation of a tapered roller bearing with a defect on the outer ring raceway surface at 200 min ⁻¹ . In the figure, the solid line shows the envelope frequency spectrum based on the actually measured vibration data, the dotted line is a reference value (here, the effective value + 6 dB), the frequency component chain line due to the outer ring damage based on the rotation speed 200 min ^-1 (f shows the ₁ ~f _5). Further, the shaded range indicates the frequency range used for calculating the reference value, and is f ₁ −3 Hz to f ₅ +3 Hz in this example. From this result, it can be determined that the outer ring of the bearing is damaged because the peak exceeding the reference value matches the frequency component caused by the outer ring damage.

On the other hand, FIG. 9 shows a case where the frequency range used for calculating the reference value is the entire region with respect to the result of the frequency analysis obtained under the same conditions as in FIG. In FIG. 9, since the frequency component resulting from damage to the outer ring does not exceed the reference value, it may be determined that there is no abnormality.
Therefore, from the results of FIGS. 8 and 9, it is confirmed that the reference value used for the comparison and collation is calculated from the limited range of the measured spectrum data, so that it is difficult to be affected by the noise and a highly accurate diagnosis is possible. The

It is the schematic of the abnormality diagnosis apparatus which is 1st Embodiment of this invention. It is a block diagram of the signal processing part of FIG. It is a flowchart which shows the processing flow of the abnormality diagnosis method which is 1st Embodiment of this invention. It is a figure which shows the relationship between the site | part of the damage | wound of a bearing, and the vibration generation frequency which originates in a damage | wound. It is a figure for demonstrating the relational expression of the abnormal vibration frequency generate | occur | produced by meshing | engagement of a gearwheel. It is the schematic of the abnormality diagnosis apparatus which is 2nd Embodiment of this invention. It is sectional drawing of the bearing apparatus for rail vehicles which is a mechanical installation with which the detection part of the abnormality diagnosis apparatus was integrated. It is a figure for demonstrating the abnormality diagnosis of an Example. It is a figure for demonstrating the conventional abnormality diagnosis.

Explanation of symbols

10,70 Machine equipment 12 Rolling bearings (Rotating parts)
20 detection unit 22 sensor 30 controller 32 signal processing unit 34 control unit 40 output device 45 report creation unit 46 storage unit 47 data output unit 50 data accumulation / distribution unit 52 rotation analysis unit 54 filter processing unit 56 vibration analysis unit 58 comparison determination unit 60 Internal data storage

Claims (10)

An apparatus for diagnosing abnormality of mechanical equipment, comprising at least one component that rotates or slides,
At least one detector that outputs a signal generated from the mechanical equipment as an electrical signal;
Performing frequency analysis of the waveform of the electrical signal, comparing the frequency component of the measured spectrum data obtained by the frequency analysis with the frequency component resulting from the component, whether there is an abnormality in the component based on the verification result, and A signal processing unit for determining an abnormal site;
With
A machine facility abnormality diagnosis device, wherein a reference value used for the comparison and collation is calculated based on a limited frequency range of the measured spectrum data. An apparatus for diagnosing abnormality of mechanical equipment, comprising at least one component that rotates or slides,
At least one detector that outputs a signal generated from the mechanical equipment as an electrical signal;
Performing frequency analysis of the waveform of the electrical signal, comparing the frequency component of the measured spectrum data obtained by the frequency analysis with the frequency component resulting from the component, whether there is an abnormality in the component based on the verification result, and A signal processing unit for determining an abnormal site;
A storage unit for storing a diagnosis result diagnosed by the signal processing unit;
An output unit for outputting the diagnosis result in a predetermined format;
A report creation unit for creating a report based on at least one program, the output result output by the output unit;
An abnormality diagnosis apparatus for mechanical equipment, comprising:   3. The machine equipment abnormality according to claim 1, wherein the signal processing unit performs at least one of amplification processing and filtering processing on the detected signal and performs envelope processing on the processed waveform. 4. Diagnostic device.   The abnormality diagnosis apparatus according to claim 1, further comprising a data transmission unit configured to transmit a determination result by the signal processing unit.   The abnormality diagnosis apparatus according to claim 1, further comprising a microcomputer that performs processing by the signal processing unit and processing for outputting the determination result to a control system.   The apparatus for diagnosing abnormality of a mechanical facility according to any one of claims 1 to 5, wherein the mechanical facility is a railway vehicle bearing device.   The apparatus for diagnosing abnormality of mechanical equipment according to any one of claims 1 to 5, wherein the mechanical equipment is a wind turbine bearing device.   The machine equipment abnormality diagnosis device according to claim 1, wherein the machine equipment is a machine tool spindle bearing device. A machine equipment abnormality diagnosis method comprising at least one component that rotates or slides,
Detecting a signal generated from the mechanical equipment and outputting it as an electrical signal;
Analyzing the frequency of the waveform of the detected signal;
A step of comparing and collating the frequency component of the measured spectrum data obtained in the analysis step with the frequency component caused by the component;
Determining the presence / absence and abnormality of the part based on the comparison result in the comparison step;
With
The machine equipment abnormality diagnosis method, wherein the reference value used for the comparison and collation is calculated based on a limited frequency range of the measured spectrum data. A machine equipment abnormality diagnosis method comprising at least one component that rotates or slides,
Detecting a signal generated from the mechanical equipment and outputting it as an electrical signal;
Analyzing the frequency of the waveform of the detected signal;
A step of comparing and collating the frequency component of the measured spectrum data obtained in the analysis step with the frequency component caused by the component;
Determining the presence / absence and abnormality of the part based on the comparison result in the comparison step;
Storing a diagnosis result obtained in at least one of the analysis, comparison, and determination steps;
Outputting the diagnosis result in a predetermined format;
Creating a report of the output result output by the output step based on at least one program;
An abnormality diagnosis method for mechanical equipment, comprising:

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