CN117575469A - An intelligent warehousing supervision system and method based on intelligent data transfer analysis - Google Patents

Abstract

The invention relates to the technical field of warehouse supervision, in particular to an intelligent warehouse supervision system and method based on intelligent data analysis, comprising the following steps: the warehouse article monitoring module, the monitoring information acquisition module, the data management center, the target equipment screening module and the equipment adjustment management module are used for monitoring the goods flowing state in the warehouse in real time and carrying out information sharing interaction, the monitoring information acquisition module is used for acquiring equipment information and historical monitoring information for monitoring the goods, the data management center is used for storing and managing all acquired data, the target equipment screening module is used for analyzing the installation reasonable coefficients of different equipment and screening out equipment to be adjusted, the equipment adjustment management module is used for replacing the equipment to be adjusted, the equipment with proper working frequency is replaced by the improperly selected reading equipment in time, and unnecessary monitoring cost is reduced while the goods information and warehouse monitoring efficiency are covered and captured to the greatest extent.

Description

An intelligent warehousing supervision system and method based on intelligent data transfer data analysis

Technical field

The invention relates to the technical field of warehousing supervision, specifically an intelligent warehousing supervision system and method based on intelligent data transfer analysis.

Background technique

With the development of the logistics industry and the continuous advancement of automation technology, warehousing supervision systems have become an important means for enterprises to improve efficiency and reduce costs. As a wireless communication technology, RFID technology has the characteristics of real-time, high efficiency and automation, and is widely used. In warehousing supervision in the field of application and logistics, it can realize automatic entry, exit and positioning of goods, reduce manual operation errors and time costs, and can also be seamlessly connected with other information systems to achieve data sharing and management integration;

When using RFID reading equipment for warehousing supervision, for fixed RFID reading equipment in the warehouse, relevant personnel or machines need to transport the goods to the identification range of the reading equipment in order to successfully identify the goods information, in order to maximize coverage and To capture the incoming, outgoing and location information of goods, it is necessary to select an RFID reading device with a suitable working frequency to reduce the probability of missing goods identification. If the reading device is improperly selected, for example, an RFID reading device with a working frequency that is too high is selected. It is easy to have the problem that although the cargo tags are correctly identified, the cost of warehousing supervision increases unnecessarily. The existing technology does not require timely replacement of improperly selected RFID reading equipment to reduce unnecessary warehousing supervision costs.

Therefore, people need an intelligent warehousing supervision system and method based on intelligent digital transformation data analysis to solve the above problems.

Contents of the invention

The purpose of the present invention is to provide an intelligent warehousing supervision system and method based on intelligent data transfer data analysis to solve the problems raised in the above background technology.

In order to solve the above technical problems, the present invention provides the following technical solution: an intelligent warehousing supervision system based on intelligent data transfer data analysis. The system includes: a storage item supervision module, a supervision information collection module, a data management center, and target equipment screening. Module and device adjustment management module;

The output end of the warehouse item supervision module is connected to the input end of the supervision information collection module, the output end of the supervision information collection module is connected to the input end of the data management center, and the output end of the data management center is connected to the The input end of the target device screening module, the output end of the target device screening module is connected to the input end of the device adjustment management module;

Through the warehouse item supervision module, the flow status of goods in the warehouse is monitored in real time and information communication and interaction is performed with the supervision terminal;

Collect equipment information and historical supervision information for cargo supervision through the supervision information collection module, and transmit all collected data to the data management center;

Store and manage all collected data through the data management center;

Through the target equipment screening module, the equipment information and historical supervision information of cargo supervision are retrieved and analyzed, the reasonable installation coefficients of different equipment are analyzed and the equipment to be adjusted is screened out;

Use the equipment adjustment management module to perform replacement processing on the equipment to be adjusted, and replace the equipment to be adjusted with equipment with the best working frequency;

The equipment used for cargo supervision refers to RFID reading equipment.

Further, the warehouse item supervision module includes a cargo label identification unit, a storage entry and exit information collection unit, and a cargo information communication unit;

The output end of the cargo label identification unit is connected to the input end of the inbound and outbound information collection unit, and the output end of the inbound and outbound information collection unit is connected to the input end of the cargo information communication unit;

The cargo label identification unit uses an RFID reading device to identify the cargo tags in the warehouse and obtain the information on the outgoing, incoming and placement location of the goods in the warehouse. The RFID reading device is a fixed RFID Readers and writers, installed in different areas of the warehouse;

The warehouse-in and warehouse-out information collection unit collects the goods' warehouse-out, warehouse-in and location information in the warehouse from the identification results;

The collected cargo information is transmitted to the supervision terminal through the cargo information communication unit.

Further, the supervision information collection module includes an equipment information collection unit and an identification data collection unit;

The input end of the equipment information collection unit is connected to the output end of the cargo information transmission unit, and the output ends of the equipment information collection unit and identification data collection unit are connected to the input end of the data management center;

The equipment information collection unit collects the working frequency of the RFID reading equipment installed in different areas of the warehouse and the maximum identification distance of the equipment;

Through the identification data collection unit, a distance sensor is installed at the installation position of the RFID reading device, and the distance sensor is used to collect the straight-line distance information between the RFID reading devices installed in different areas and the successfully identified goods in the past.

Further, the target equipment screening module includes a reasonable installation analysis unit and a equipment screening unit to be adjusted;

The input end of the properly installed analysis unit is connected to the output end of the data management center, and the output end of the properly installed analysis unit is connected to the input end of the equipment screening unit to be adjusted;

Through the installation reasonable analysis unit, the straight-line distance information between the RFID reading equipment installed in different areas when the goods were identified in the past and the successfully identified goods is retrieved, and the installation of RFID reading equipment in different areas is analyzed based on the retrieved data. Reasonable coefficient;

The device to be adjusted screening unit compares the reasonable installation coefficients of the current RFID reading devices in different areas, and selects the devices that need to be replaced and adjusted as the devices to be adjusted.

Further, the equipment adjustment management module includes a supervision information analysis unit and a reading equipment adjustment unit;

The input end of the supervision information analysis unit is connected to the output end of the equipment to be adjusted screening unit, and the output end of the supervision information analysis unit is connected to the input end of the reading equipment adjustment unit;

A working frequency analysis model is established through the supervision information analysis unit to analyze and screen the optimal working frequency of the equipment in the area where the equipment to be adjusted is located;

The device to be adjusted is replaced by the RFID reading device with the best working frequency through the reading device adjustment unit.

An intelligent warehousing supervision method based on intelligent digital transformation data analysis, including the following steps:

Z1: Real-time supervision of the flow status of goods in the warehouse and information communication interaction with the supervision terminal;

Z2: Collect equipment information and historical supervision information for cargo supervision;

Z3: Retrieve and analyze equipment information and historical supervision information for cargo supervision, and analyze the reasonable installation factors of different equipment;

Z4: Compare the reasonable installation coefficients of different equipment, and select the equipment to be adjusted based on the comparison results;

Z5: Replace the equipment to be adjusted.

Further, in step Z1: Use the RFID reading device to identify the cargo tags in the warehouse, obtain the information on the outgoing, incoming and placement location of the goods in the warehouse, and transmit the obtained cargo information to the supervision The terminal communicates and interacts with the supervision terminal;

Smart transformation refers to the investment in hardware transformation: enterprises realize "machine substitution" through equipment upgrades and intelligent transformation of production lines, and use RFID reading equipment to replace manual labor for warehousing supervision, realizing "machine substitution", that is, smart transformation At the same time, the wireless communication technology of the RFID reading device is used to share the identified cargo information with the supervision terminal in real time, which is conducive to the supervision terminal to grasp the cargo information in real time, discover the abnormality of the cargo in a timely manner and take relevant measures to solve the abnormal problem, which improves the efficiency of warehousing goods. safety.

Further, in step Z2: the working frequency set of RFID reading devices installed in different areas of the warehouse is collected as W = {W ₁ , W ₂ ,..., W _m }, corresponding to the farthest identification distance of the RFID reading device The set is d={d ₁ , d ₂ ,..., d _m }, where m represents the number of RFID reading devices installed in the warehouse. A distance sensor is installed at the location where the RFID reading device is installed, and the distance sensor is used to collect data from different areas. When the installed RFID reading device has previously identified goods, it provides information on the straight-line distance between the goods that were successfully identified.

Further, in step Z3: when the RFID reading device installed in a random area is retrieved and the goods are identified by reading the goods tags f times in the past, the straight-line distance set between the goods successfully identified is D={D ₁ , D ₂ ,..., D _f }, the farthest identification distance of the corresponding reading device is d _i , d _i ∈d. Calculate the reasonable installation coefficient P _i of the RFID reading device installed in a random area according to the following formula:

Among them, D _j represents the straight-line distance between the RFID reading device installed in a random area and the successfully identified goods when it identified the goods by reading the goods label for the jth time in the past. All RFID reading devices are calculated in the same way. Reasonable installation coefficient;

Use big data technology to collect historical data on the past identification of goods by RFID reading equipment installed in different areas of the warehouse: the distance data between the goods and the reading equipment when goods were successfully identified in the past is used to analyze the installation of RFID reading equipment installed in different areas. Reasonable coefficient. When analyzing the reasonable coefficient of installation, the reference factor is not only the difference between the farthest recognition distance of the corresponding reading device and the actual distance at the time of reading, but also takes into account the stability of the historical distance data obtained. The larger the difference, the closer the distance between the cargo tag and the reading device is when identifying goods in the corresponding area. The higher the probability that the corresponding device can successfully identify the goods in the corresponding area by adjusting the corresponding device to a smaller operating frequency. The currently installed equipment in the corresponding area The more unreasonable the reading equipment is, combined with the analysis of the stability of historical distance data, the smaller the actual distance difference when reading, indicating that the distance between the corresponding area and the equipment when identifying goods is more concentrated and stable, and when a certain goods is identified and the equipment is The lower the probability that the distance between them is suddenly very far, the higher the probability that the corresponding equipment can successfully identify the goods in the corresponding area by adjusting the corresponding equipment to a device with a lower operating frequency, and the more unreasonable the reading equipment currently installed in the corresponding area is. Combining the above two Factors are considered and analyzed to determine the reasonable installation coefficients of RFID reading equipment installed in different areas, which improves the rationality of subsequent screening of equipment to be adjusted.

Further, in step Z4: compare the installation reasonable coefficients of all RFID reading devices, arrange the m devices in order from small to large installation reasonable coefficients and divide them into e categories, where the installation of all devices in the previous category The reasonable coefficients are all smaller than the latter category. From the random classification results obtained, the average set of reasonable coefficients for the installation of random equipment in category e is Q = {Q ₁ , Q ₂ ,..., Q _e }, according to the formula Calculate the screening reference coefficient F of a random classification result, where Q _c represents the average of the reasonable coefficients for the installation of the c-th equipment in category e in a random classification result. Calculate the screening reference coefficient of different classification results in the same way, and compare the screening Reference coefficient, select and filter the classification result with the highest reference coefficient, and select the RFID reading device in the first category from the selected classification result as the device to be adjusted;

In order to accurately and centrally screen out the equipment to be adjusted, after analyzing the reasonable installation coefficient of each equipment, the equipment is classified according to the reasonable installation coefficient, and the selection is made by calculating the difference in the reasonable installation coefficient between various types of equipment in different classification results. The greater the difference in the classification results, the greater the classification reference value for the screening of equipment to be adjusted. The installation rationality data will be obtained through classification to maximize the data reference value, realize the function of data transfer, and at the same time facilitate accurate and accurate classification. Centrally screen out the equipment to be adjusted with a small reasonable installation coefficient.

Further, in step Z5: when a random device among all the remaining devices except the device to be adjusted is retrieved. When the goods have been identified f times in the past, the straight-line distance set between the successfully identified goods is L = {L ₁ , L ₂ ,..., L _f }, calculate the previous average recognition distance of the corresponding device Among them, L _j represents the straight-line distance between the jth time the corresponding device recognized the goods in the past and the successfully identified goods. The average set of recognition distances of all remaining devices except the device to be adjusted is calculated in the same way as/> Among them, n represents the number of all remaining devices except the device to be adjusted, and the set of operating frequencies of all remaining devices is retrieved as w={w ₁ , w ₂ ,..., w _n },/> Put the data points/> Perform straight line fitting and establish an operating frequency analysis model: Y=γ1*X+γ2, where X represents the independent variable of the operating frequency analysis model, Y represents the dependent variable, γ1 represents the bias, and γ2 represents the intercept. According to the following formulas, respectively Solve for γ1 and γ2:

in, Indicates the average recognition distance of the remaining b-th device except the device to be adjusted, w _b represents the operating frequency of the remaining b-th device, and obtains the straight line between a random device to be adjusted in the past when it recognized goods and the goods that were successfully identified. Distance, by summing the straight-line distance and dividing by the number of identifications, the average identification distance of the corresponding equipment to be adjusted is K. Substituting K into the working frequency analysis model: Let Take the optimal working frequency of the equipment as γ1*K+γ2, replace the corresponding equipment to be adjusted with an RFID reading device with a working frequency of γ1*X+γ2, and perform the same replacement process for the remaining equipment to be adjusted. Replace the remaining equipment to be adjusted as RFID reading equipment with the best working frequency that should be installed in the area where the corresponding equipment is located;

In addition to the screened equipment, the installation of the remaining equipment is more reasonable and the working frequency is more appropriate. The remaining equipment data is used as a reference to establish a working frequency analysis model. When the equipment to be adjusted is used to identify the goods, the distance data between the goods and the goods is substituted into the work. Obtain the best working frequency from the frequency analysis model, and replace the equipment to be adjusted in the corresponding area with the equipment with the best working frequency. Improperly selected RFID reading equipment needs to be replaced in time to ensure maximum coverage and capture of cargo information. It reduces unnecessary warehousing supervision costs while improving warehousing supervision efficiency.

Compared with the prior art, the beneficial effects achieved by the present invention are:

The present invention uses RFID reading equipment to replace manual warehouse supervision, and realizes "machine substitution", that is, the function of intelligent change. At the same time, the wireless communication technology of the RFID reading equipment is used to share the identified cargo information with the supervision terminal in real time, which is beneficial to The supervision terminal can grasp the cargo information in real time, detect cargo abnormalities in a timely manner and take relevant measures to solve the abnormal problems, which improves the safety of warehousing goods;

Use big data technology to collect historical data on the past identification of goods by RFID reading equipment installed in different areas of the warehouse: the distance data between the goods and the reading equipment when goods were successfully identified in the past is used to analyze the installation of RFID reading equipment installed in different areas. Reasonable coefficient. When analyzing the reasonable coefficient of installation, the reference factor is not only the difference between the farthest recognition distance of the corresponding reading device and the actual distance at the time of reading, but also takes into account the stability of the obtained historical distance data to improve Subsequently, the rationality of the equipment to be adjusted is screened out based on the reasonable installation coefficient;

After analyzing the reasonable installation coefficient of each equipment, the equipment is classified according to the reasonable installation coefficient. The classification result is selected by calculating the difference in the reasonable installation coefficient between various types of equipment in different classification results. The installation rationality data will be obtained through The classification method maximizes the reference value of the data, realizes the function of data transfer, and is conducive to accurately and intensively screening out the equipment to be adjusted with a small reasonable installation coefficient;

Use the remaining equipment data as a reference to establish a working frequency analysis model. When each equipment to be adjusted is used to identify goods, the distance data between the goods and the goods is substituted into the working frequency analysis model to obtain the best working frequency, and the equipment to be adjusted in the corresponding area is replaced. For equipment with the best working frequency, improperly selected RFID reading equipment needs to be replaced in time to ensure maximum coverage, capture of cargo information and warehousing supervision efficiency, while reducing unnecessary warehousing supervision costs.

Description of the drawings

The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. In the attached picture:

Figure 1 is a structural diagram of an intelligent warehousing supervision system based on intelligent data transfer data analysis according to the present invention;

Figure 2 is a flow chart of an intelligent warehousing supervision method based on intelligent data transfer data analysis according to the present invention.

Detailed ways

The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

The present invention will be further described below in conjunction with Figures 1-2 and specific embodiments.

Embodiment 1: As shown in Figure 1, this embodiment provides an intelligent warehousing supervision system based on intelligent data transfer data analysis. The system includes: a warehousing item supervision module, a supervision information collection module, a data management center, and target equipment screening. Module and equipment adjustment management module, through the warehousing item supervision module, conduct real-time supervision of the flow status of goods in the warehouse and conduct information communication and interaction with the supervision terminal, and collect equipment information and historical supervision information for goods supervision through the supervision information collection module, and All collected data are transferred to the data management center, and all collected data are stored and managed through the data management center. Equipment information and historical supervision information for cargo supervision are retrieved and analyzed through the target equipment screening module, and the reasonable installation coefficients of different equipment are analyzed. And the equipment to be adjusted is screened out, and the equipment to be adjusted is replaced through the equipment adjustment management module, and the equipment to be adjusted is replaced with equipment with the best working frequency.

The warehouse item supervision module includes a cargo label identification unit, an entry and exit information collection unit, and a cargo information communication unit. The cargo label identification unit uses RFID reading equipment to identify the cargo labels in the warehouse and obtain the entry and exit of the goods in the warehouse. As well as the placement location information in the warehouse, the warehouse entry and exit information of the goods is collected from the identification results through the warehouse entry and exit information collection unit, and the collected cargo information is transmitted to the supervision terminal through the cargo information communication unit. .

The supervisory information collection module includes an equipment information collection unit and an identification data collection unit. The equipment information collection unit collects the working frequency of the RFID reading equipment installed in different areas of the warehouse and the farthest identification distance of the equipment. The identification data collection unit collects data on the RFID reading equipment. Install a distance sensor at the location where the equipment is installed, and use the distance sensor to collect the straight-line distance information between the RFID reading equipment installed in different areas and the successfully identified goods in the past.

The target equipment screening module includes an installed reasonable analysis unit and a to-be-adjusted equipment screening unit. By installing a reasonable analysis unit, the RFID reading equipment installed in different areas retrieves the straight-line distance information between the RFID reading equipment installed in different areas and the successfully identified goods in the past, based on The retrieved data analyzes the reasonable installation coefficients of RFID reading equipment in different areas. The equipment to be adjusted screening unit compares the reasonable installation coefficients of the current RFID reading equipment in different areas and selects equipment that needs to be replaced and adjusted as equipment to be adjusted.

The equipment adjustment management module includes a supervision information analysis unit and a reading equipment adjustment unit. Through the supervision information analysis unit, a working frequency analysis model is established to analyze and screen the optimal working frequency of the equipment that should be installed in the area where the equipment to be adjusted is located. By reading The device adjustment unit replaces the device to be adjusted with an RFID reading device with the best working frequency.

Embodiment 2: As shown in Figure 2, this embodiment provides an intelligent warehousing supervision method based on intelligent data transfer data analysis, which is implemented based on the intelligent warehousing supervision system in the embodiment, and specifically includes the following steps:

Z1: Real-time supervision of the flow status of goods in the warehouse and information communication interaction with the supervision terminal, using RFID reading equipment to identify the goods tags in the warehouse, and obtaining the outgoing, incoming and outgoing status of goods in the warehouse. Place the location information, transmit the obtained cargo information to the supervision terminal, and communicate and interact with the supervision terminal;

Z2: Collect equipment information and historical supervision information for cargo supervision. The working frequency set of RFID reading devices installed in different areas of the warehouse is W = {W ₁ , W ₂ ,..., W _m }, corresponding to RFID reading The set of the farthest identification distances of the equipment is d={d ₁ , d ₂ ,..., d _m }, where m represents the number of RFID reading devices installed in the warehouse, and a distance sensor is installed at the location where the RFID reading equipment is installed. , use distance sensors to collect the straight-line distance information between RFID reading devices installed in different areas when identifying goods in the past and successfully identified goods;

Z3: Retrieve and analyze the equipment information and historical supervision information for cargo supervision, analyze the reasonable installation coefficients of different equipment, and retrieve the RFID reading device installed in a random area for f times in the past to identify the goods by reading the cargo tags, and The set of straight-line distances between successfully identified goods is D = {D ₁ , D ₂ ,..., D _f }, and the farthest identification distance of the corresponding reading device is d _i , d _i ∈d, according to the formula Calculate the reasonable installation coefficient P _i of the RFID reading equipment installed in a random area;

Among them, D _j represents the straight-line distance between the RFID reading device installed in a random area and the successfully identified goods when it identified the goods by reading the goods label for the jth time in the past. All RFID reading devices are calculated in the same way. Reasonable installation coefficient;

Z4: Compare the reasonable installation coefficients of different equipment, screen out the equipment to be adjusted based on the comparison results, compare the reasonable installation coefficients of all RFID reading devices, arrange the m devices in ascending order of reasonable installation coefficients and divide them into categories e , among which, the reasonable installation coefficients of all equipment in the former category are smaller than those in the latter category. From the random classification results obtained, the average set of reasonable installation coefficients of random equipment in category e is Q = {Q ₁ , Q ₂ ,…,Q _e }, according to the formula Calculate the screening reference coefficient F of a random classification result, where Q _c represents the average of the reasonable coefficients for the installation of the c-th equipment in category e in a random classification result. Calculate the screening reference coefficient of different classification results in the same way, and compare the screening Reference coefficient, select and filter the classification result with the highest reference coefficient, and select the RFID reading device in the first category from the selected classification result as the device to be adjusted;

Z5: When the equipment to be adjusted is replaced, a random device among all the remaining equipment except the equipment to be adjusted is retrieved. When the equipment has identified the goods f times in the past, the straight-line distance set between the equipment and the successfully identified goods is L = {L ₁ , L ₂ ,..., L _f }, calculate the previous average recognition distance of the corresponding device Among them, L _j represents the straight-line distance between the jth time the corresponding device recognized the goods in the past and the successfully identified goods. The average set of recognition distances of all remaining devices except the device to be adjusted is calculated in the same way as/> Among them, n represents the number of all remaining devices except the device to be adjusted, and the set of operating frequencies of all remaining devices is retrieved as w={w ₁ , w ₂ ,..., w _n }, Put the data points/> Perform straight line fitting and establish an operating frequency analysis model: Y=γ1*X+γ2, where X represents the independent variable of the operating frequency analysis model, Y represents the dependent variable, γ1 represents the bias, and γ2 represents the intercept. According to the formula/> Solve γ1 and γ2 respectively, where,/> Indicates the average recognition distance of the remaining b-th device except the device to be adjusted, w _b represents the operating frequency of the remaining b-th device, and obtains the straight line between a random device to be adjusted in the past when it recognized goods and the goods that were successfully identified. Distance, by summing the straight-line distance and dividing by the number of identifications, the average identification distance of the corresponding equipment to be adjusted is K. Substituting K into the working frequency analysis model: Let Take the optimal working frequency of the device as γ1*K+γ2, and replace the corresponding device to be adjusted with an RFID reading device with a working frequency of γ1*X+γ2;

For example: the average set of recognition distances of all remaining devices except the device to be adjusted is obtained: The unit is: meter. The set of operating frequencies of all remaining devices is retrieved as w={w ₁ , w ₂ , w ₃ , w ₄ , w ₅ }={860, 865, 872, 900, 880}. The unit is : MHz, perform straight line fitting on the above data points, and obtain the working frequency analysis model as: Y=γ1*X+γ2=34.75X+826.75, obtain the difference between the past identification of goods by a random device to be adjusted and the successful identification of goods The straight-line distance of For γ1*K+γ2≈896, replace the corresponding device to be adjusted with an RFID reading device with an operating frequency of 896MHz.

It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that these entities or operations are mutually exclusive. any such actual relationship or sequence exists between them. Furthermore, the terms "comprises," "comprises," or any other variations thereof are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also those not expressly listed other elements, or elements inherent to the process, method, article or equipment.

Finally, it should be noted that the above are only preferred examples of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still Modify the technical solutions described in the foregoing embodiments, or make equivalent replacements for some of the technical features. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims (10)

1. An intelligent warehouse supervision system based on intelligent data analysis, which is characterized in that: the system comprises: the warehouse article monitoring system comprises a warehouse article monitoring module, a monitoring information acquisition module, a data management center, a target equipment screening module and an equipment adjustment management module;

the output end of the warehouse article supervision module is connected with the input end of the supervision information acquisition module, the output end of the supervision information acquisition module is connected with the input end of the data management center, the output end of the data management center is connected with the input end of the target equipment screening module, and the output end of the target equipment screening module is connected with the input end of the equipment adjustment management module;

the goods flowing state in the warehouse is monitored in real time through the warehouse goods monitoring module, and information communication interaction is carried out between the goods flowing state and the monitoring terminal;

acquiring equipment information and historical supervision information for goods supervision through the supervision information acquisition module, and transmitting all acquired data to the data management center;

storing and managing all collected data through the data management center;

the target equipment screening module is used for retrieving and analyzing equipment information and historical supervision information of cargo supervision, analyzing installation reasonable coefficients of different equipment and screening out equipment to be adjusted;

and the equipment to be adjusted is replaced by the equipment with the optimal working frequency through the equipment adjustment management module.

2. An intelligent warehouse supervisory system based on intelligent change data analysis as set forth in claim 1 wherein: the warehouse article supervision module comprises a goods label identification unit, a warehouse in-warehouse out information acquisition unit and a goods information communication unit;

the output end of the goods tag identification unit is connected with the input end of the warehouse-in and warehouse-out information acquisition unit, and the output end of the warehouse-in and warehouse-out information acquisition unit is connected with the input end of the goods information communication unit;

the goods label identification unit is used for identifying the goods label in the warehouse by using RFID reading equipment, and the information of the delivery, the storage and the placement of the goods in the warehouse are obtained;

collecting the ex-warehouse and the warehouse-in of goods from the identification result through the in-warehouse and out-warehouse information collecting unit so as to obtain the position information in the warehouse;

and transmitting the acquired cargo information to a supervision terminal through the cargo information communication unit.

3. An intelligent warehouse supervisory system based on intelligent data analysis as set forth in claim 2 wherein: the supervision information acquisition module comprises an equipment information acquisition unit and an identification data acquisition unit;

the input end of the equipment information acquisition unit is connected with the output end of the cargo information transmission unit, and the output ends of the equipment information acquisition unit and the identification data acquisition unit are connected with the input end of the data management center;

collecting working frequencies of RFID reading devices installed in different areas in a warehouse and the farthest identification distance of the devices through the device information collecting unit;

the distance sensor is arranged at the position where the RFID reading device is arranged through the identification data acquisition unit, and the distance sensor is used for acquiring the linear distance information between the RFID reading device arranged in different areas and the goods which are successfully identified when the goods are identified in the past.

4. An intelligent warehouse supervisory system based on intelligent data analysis as set forth in claim 3 wherein: the target equipment screening module comprises an installation reasonable analysis unit and an equipment screening unit to be adjusted;

the input end of the reasonable installation analysis unit is connected with the output end of the data management center, and the output end of the reasonable installation analysis unit is connected with the input end of the equipment screening unit to be adjusted;

when the RFID reading equipment installed in different areas is used for identifying cargoes in the past, the reasonable installation analysis unit is used for analyzing the reasonable installation coefficients of the RFID reading equipment in different areas according to the acquired data;

and comparing the installation reasonable coefficients of the RFID reading devices in different areas by the device to be adjusted screening unit, and screening out the devices needing to be replaced and adjusted as the devices to be adjusted.

5. The intelligent warehouse management system based on intelligent change data analysis of claim 4, wherein: the device adjustment management module comprises a supervision information analysis unit and a reading device adjustment unit;

the input end of the supervision information analysis unit is connected with the output end of the equipment screening unit to be adjusted, and the output end of the supervision information analysis unit is connected with the input end of the reading equipment adjusting unit;

establishing a working frequency analysis model through the supervision information analysis unit, and analyzing the screened optimal working frequency of equipment to be installed in the area where the equipment to be adjusted is located;

and replacing the device to be adjusted with the RFID reading device with the optimal working frequency through the reading device adjusting unit.

6. An intelligent warehouse supervision method based on intelligent data analysis is characterized in that: the method comprises the following steps:

z1: carrying out real-time supervision on the goods flowing state in the warehouse and carrying out information communication interaction with a supervision terminal;

z2: collecting equipment information and historical supervision information for cargo supervision;

z3: the method comprises the steps of calling and analyzing equipment information and historical supervision information of cargo supervision, and analyzing installation reasonable coefficients of different equipment;

z4: comparing the installation reasonable coefficients of different devices, and screening out the devices to be adjusted according to the comparison result;

z5: and carrying out replacement treatment on the equipment to be adjusted.

7. The intelligent warehouse supervision method based on intelligent data analysis according to claim 6, wherein: in step Z1: and identifying the goods labels in the warehouse by using RFID reading equipment, acquiring the information of the delivery, the warehouse entry and the placement position of the goods in the warehouse, transmitting the acquired goods information to the supervision terminal, and carrying out communication interaction with the supervision terminal.

8. The intelligent warehouse supervision method based on intelligent data analysis according to claim 7, wherein: in step Z2: the working frequency set of the RFID reading equipment installed in different areas in the warehouse is W= { W ₁ ，W ₂ ，…，W _m The set of furthest identification distances for the corresponding RFID reader device is d= { d } ₁ ，d ₂ ，…，d _m Where m represents the number of RFID reading devices installed in the warehouse, a distance sensor is installed at the position where the RFID reading devices are installed, and RFID readings installed in different areas are acquired by using the distance sensorWhen the equipment identifies goods in the past, the linear distance information between the equipment and the goods successfully identified;

in step Z3: when the RFID reading device installed in a random area is called to identify goods through reading the goods label f times in the past, the set of straight line distances between the RFID reading device and the goods successfully identified is D= { D ₁ ，D ₂ ，…，D _f The furthest identifying distance of the corresponding reading device is d _i ，d _i E d, calculating the installation rational coefficient P of the RFID reading device installed in a random area according to the following formula _i ：

Wherein D is _j When the RFID reading equipment installed in a random area identifies goods through the jth time of reading the goods label, the linear distance between the RFID reading equipment and the goods successfully identified is calculated in the same way, so that the installation reasonable coefficients of all the RFID reading equipment are obtained.

9. The intelligent warehouse supervision method based on intelligent data analysis according to claim 8, wherein: in step Z4: comparing the installation reasonable coefficients of all RFID reading devices, arranging m devices according to the order of the installation reasonable coefficients from small to large, and dividing the m devices into e types, wherein the installation reasonable coefficients of all devices in the former type are smaller than those of the latter type, and acquiring a random classification result, wherein the average value set of the installation reasonable coefficients of the random type devices in the e types is Q= { Q ₁ ，Q ₂ ，…，Q _e According to the formula }Calculating a screening reference coefficient F of a random classification result, wherein Q _c Representing the average value of the installation reasonable coefficients of the c-th equipment in the e class in one classification result, calculating the screening reference coefficients of different classification results in the same way, and comparing the screening reference coefficientsAnd selecting one classification result with the highest screening reference coefficient, and screening the RFID reading equipment in the first class from the selected classification result as equipment to be adjusted.

10. The intelligent warehouse supervision method based on intelligent data analysis according to claim 9, wherein: in step Z5: when the goods are identified f times before being called to random one of all the devices except the device to be regulated, the straight line distance set between the random one of the devices and the goods which are successfully identified is L= { L ₁ ，L ₂ ，…，L _f Calculating to obtain the past average value of the identification distance of the corresponding equipment Wherein L is _j Representing the straight line distance between the j-th goods identification and the goods successfully identified by the corresponding equipment, and calculating the average value set of the identification distances of all the rest equipment except the equipment to be adjusted to be>Where n represents the number of all devices except the device to be adjusted, and the set of operating frequencies of all the remaining devices is called as w= { w ₁ ，w ₂ ，…，w _n }，/>Data points are processedPerforming straight line fitting, and establishing a working frequency analysis model: y=γ 1*X +γ2, where X represents an independent variable of the operating frequency analysis model, Y represents an dependent variable, γ1 represents a bias, γ2 represents an intercept, and γ1 and γ2 are solved according to the following equations, respectively:

wherein,representing the mean value, w, of the identification distance of the b-th device remaining except the device to be adjusted _b The working frequency of the remained b-th equipment is represented, the linear distance between the goods to be adjusted and the goods to be successfully identified when the goods to be adjusted are identified in the past is obtained, the identification distance mean value of the corresponding equipment to be adjusted is obtained by dividing the identification times after the linear distance is summed, and the K is substituted into the working frequency analysis model: let x=k, obtain the optimal operating frequency of the RFID reading device to be installed corresponding to the area where the device to be adjusted is located is γ 1*K +γ2, and replace the RFID reading device with the operating frequency of γ 1*X +γ2.