Generalized frequency conversion equipment operation monitoring system based on big data analysis

Abstract

The invention discloses a generalized frequency conversion equipment operation monitoring system based on big data analysis, and belongs to the technical field of equipment operation monitoring. The method is used for solving the technical problem that in an existing scheme, the operation monitoring cooperative processing and exception processing analysis precaution effect of a frequency conversion equipment group is poor. The operation of different frequency conversion equipment in the frequency conversion equipment group is monitored and analyzed in real time, and the abnormal frequency conversion equipment obtained through monitoring and analysis and the corresponding abnormal processing are subjected to multi-dimensional abnormal influence analysis, so that diversified active supervision and processing analysis on the implementation of the existing frequency conversion equipment operation supervision scheme are realized; according to the method, multi-dimensional reliability processing analysis is carried out on abnormal processing schemes associated with operation of different frequency conversion devices in a frequency conversion device group, dynamic prompting and management are carried out on monitoring of operation of the different frequency conversion devices in a self-adaptive mode according to analysis results, and active expansion analysis is carried out on single-time supervision processing data of the different frequency conversion devices in the early stage.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of equipment operation monitoring, in particular to a generalized variable frequency equipment operation monitoring system based on big data analysis. BACKGROUND

[0002] In a broad sense, a variable frequency device generally refers to a device capable of adjusting the supply frequency of an AC motor to achieve speed regulation of the motor. Such devices are mainly used in industrial scenarios that require speed control. A frequency converter is the core component that realizes this function. It controls the speed of the motor by changing the frequency and voltage of the power supply input to the AC motor. A variable frequency device is not limited to a simple frequency converter. It can also include various sensors, controllers, and related software systems used in conjunction with it, collectively forming a complete drive control system.

[0003] Existing generalized variable frequency equipment operation monitoring solutions are mostly limited to traditional single-machine monitoring. They cannot handle cross-device coordination and active prevention for variable frequency device groups. They cannot implement a three-level defense system of device autonomy, cluster collaboration, and global optimization. The effect of collaborative processing and abnormal processing analysis and prevention of variable frequency device group operation monitoring is not good. SUMMARY

[0004] The purpose of the present application is to provide a generalized variable frequency equipment operation monitoring system based on big data analysis to solve the technical problem of poor effect of collaborative processing and abnormal processing analysis and prevention of variable frequency device group operation monitoring in existing solutions.

[0005] The purpose of the present application can be achieved by the following technical solutions:

[0006] The generalized variable frequency equipment operation monitoring system based on big data analysis comprises:

[0007] A variable frequency equipment operation local monitoring and analysis module for real-time monitoring and analysis of the operation of different variable frequency devices in a variable frequency device group, and multi-dimensional abnormal influence analysis of abnormal variable frequency devices obtained by monitoring and analysis and corresponding abnormal processing. According to the analysis result, the data associated with the abnormal processing scheme of the abnormal variable frequency device is dynamically updated.

[0008] A variable frequency equipment operation local reliable supervision module for multi-dimensional reliability processing and analysis of abnormal processing schemes associated with the operation of different variable frequency devices in a variable frequency device group, and dynamically prompting and managing the monitoring of the operation of different variable frequency devices according to the analysis result.

[0009] Preferably, the operation of different variable frequency devices in a variable frequency device group is monitored and analyzed in real time, and variable frequency devices with abnormal analysis are marked as target devices, and corresponding abnormal processing schemes are implemented for the target devices.

[0010] Preferably, when the abnormal handling scheme implemented by the target device is subjected to regulatory analysis of the processing effect, if the target device does not appear the mark of other target devices within the abnormal handling period, an abnormal solution instruction is generated;

[0011] If the mark of other target devices appears within the abnormal handling period of the target device, and is the same abnormality, a first abnormality solution verification instruction is generated;

[0012] If the mark of other target devices appears within the abnormal handling period of the target device, and is different abnormality, a second abnormality solution verification instruction is generated.

[0013] Preferably, when the abnormality state of the target device corresponding to the other mark is subjected to verification analysis according to the abnormality solution verification instruction, the abnormality influence set associated with the abnormal handling scheme of the target device corresponding to the first mark is obtained, and the second abnormality of the target device corresponding to the second mark is matched with the abnormality influence set;

[0014] If the second abnormality exists in the abnormality influence set, an abnormality prevention normal instruction is generated, and the corresponding abnormality prevention normal total number is increased by one;

[0015] If the second abnormality does not exist in the abnormality influence set, an abnormality prevention regulatory instruction is generated, and the operation and maintenance personnel are prompted to implement abnormality prevention management on the second abnormality and the target device corresponding to the mark, and according to the abnormality prevention management result, the abnormality coverage prevention total number associated with the abnormal handling scheme of the target device corresponding to the first mark is increased by one or the abnormality defect prevention total number is increased by one.

[0016] Preferably, all abnormality total numbers appearing in the running process of different variable frequency devices in the variable frequency device group are sequentially counted and analyzed, if all abnormality total numbers are 0, the corresponding variable frequency device is marked as a first variable frequency device;

[0017] On the contrary, the corresponding variable frequency device is marked as a second variable frequency device;

[0018] The first device total number of all first variable frequency devices and the second device total number of all second variable frequency devices are counted, the numerical values of the first device total number and the second device total number are extracted, and the processing regulatory value Cj of the variable frequency device group is obtained by calculation;

[0019] If Cj≥0, a running overall normal label is generated and a prompt is given;

[0020] On the contrary, a running overall abnormal label is generated, and an abnormal handling overall management prompt is given.

[0021] Preferably, the abnormality prevention normal total number associated with the second variable frequency device is obtained, and the difference between the abnormality prevention normal total number and all abnormality total numbers is calculated and analyzed;

[0022] If the difference is 0, the mark of the second frequency conversion equipment is maintained, and the reliability processing analysis of its own dimension is performed, and the analysis result is used to dynamically manage the abnormal prevention processing of the second frequency conversion equipment in its own dimension.

[0023] Preferably, the abnormal prevention normal total number of the second frequency conversion equipment is calculated to obtain the corresponding first abnormal processing value Cy1.

[0024] If Cy1 is less than or equal to 0, it is determined that the processing of the second frequency conversion equipment in its own dimension is reliable, and an abnormal prevention processing reliable label is generated.

[0025] On the contrary, it is determined that the processing of the second frequency conversion equipment in its own dimension is unreliable, and an abnormal prevention processing unreliable label is generated.

[0026] According to the abnormal prevention processing unreliable label, the management of the abnormal prevention processing of the second frequency conversion equipment in its own dimension is prompted.

[0027] Preferably, if the difference is not 0, the mark of the second frequency conversion equipment is updated to the third frequency conversion equipment, and the reliability processing analysis of the cooperative dimension is performed, and the analysis result is used to dynamically manage the abnormal prevention processing of the third frequency conversion equipment in the cooperative dimension.

[0028] Preferably, the abnormal prevention total number of the third frequency conversion equipment is calculated to obtain the corresponding second abnormal processing value Cy2.

[0029] According to the second abnormal processing value with the value of 1, 2 or 3, a second abnormal processing coverage unreliable label, a second abnormal processing defect unreliable label or a second abnormal processing overall unreliable label is generated, and the management of the abnormal processing coverage, the abnormal processing defect or the abnormal processing overall of the third frequency conversion equipment in the cooperative dimension is prompted according to the label.

[0030] Compared with the prior art, the present application has the following beneficial effects:

[0031] The present application realizes the diversified active supervision and processing analysis of the implementation of the existing frequency conversion equipment operation supervision scheme by monitoring and analyzing the operation of different frequency conversion equipment in the frequency conversion equipment group, analyzing the abnormal frequency conversion equipment obtained by monitoring and analysis and the corresponding abnormal processing, and realizing the diversified active supervision and processing analysis of the implementation of the existing frequency conversion equipment operation supervision scheme. Different frequency conversion equipment corresponding to single frequency conversion implementation effect can be obtained, and reliable local supervision processing data support can be provided for subsequent multi-dimensional reliability processing analysis of different frequency conversion equipment in the frequency conversion equipment group.

[0032] The application realizes active expansion analysis on single supervision processing data of different frequency conversion devices in the early stage, improves the operation monitoring collaborative processing and abnormal processing analysis prevention effect of the frequency conversion device group. BRIEF DESCRIPTION OF DRAWINGS

[0033] The application will be further described below with reference to the drawings.

[0034] Figure 1 A flowchart of the operation of the generalized frequency conversion device operation monitoring system based on big data analysis of the application. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0036] As shown in Figure 1 The application is a generalized frequency conversion device operation monitoring system based on big data analysis, comprising a frequency conversion device operation local monitoring analysis module and a frequency conversion device operation local reliable supervision module.

[0037] The frequency conversion device operation local monitoring analysis module is used for real-time monitoring analysis on the operation of different frequency conversion devices in the frequency conversion device group, and performing multi-dimensional abnormal influence analysis on abnormal frequency conversion devices obtained through monitoring analysis and corresponding abnormal processing, and dynamically updating data associated with abnormal processing schemes corresponding to abnormal frequency conversion devices according to analysis results.

[0038] The operation of different frequency conversion devices in the frequency conversion device group is monitored and analyzed in real time, and the frequency conversion device with abnormal analysis is marked as a target device, and the corresponding abnormal processing scheme is implemented on the target device corresponding to the abnormality;

[0039] It should be noted that different frequency conversion devices in the frequency conversion device group are not limited in particular, and can be generalized frequency conversion devices.

[0040] In addition, real-time monitoring analysis on the operation of different frequency conversion devices is realized based on existing operation monitoring schemes, and specific monitoring indicators are not limited; for example, input side parameters: input voltage unbalance degree, current THD (total harmonic distortion), surge current peak value.

[0041] DC bus parameters: bus voltage ripple, bus current fluctuation, bus insulation resistance;

[0042] And the abnormality processing scheme corresponding to the monitored abnormality is implemented, the abnormality obtained by the supervision is searched and traversed in the pre-constructed abnormality processing database, and the same sample abnormality is implemented according to the traversal matching The preset abnormality processing scheme;

[0043] The abnormality processing database is pre-set with a plurality of sample abnormalities, and each sample abnormality is associated with a corresponding abnormality processing scheme; a plurality of sample abnormalities and different sample abnormalities associated with abnormality processing schemes can be determined by professional technicians in the art according to historical operation and maintenance data and variable frequency monitoring design data, and specific contents are not described and limited;

[0044] And when the abnormality processing scheme corresponding to the target device is implemented, if the target device does not appear in the abnormality processing period, an abnormality solution instruction is generated;

[0045] Wherein, the abnormality processing period refers to the time period from the beginning of the target device to the end of the implementation of the abnormality processing scheme;

[0046] In addition, it can also be customized according to the actual application scene, for example, according to the starting time point of starting to implement the abnormality processing scheme, combined with the preset monitoring time length to supervise and analyze, the specific value of the monitoring time length can be set according to the application requirements of the actual application scene, which is not limited here;

[0047] If the target device appears in the abnormality processing period of other target devices, and is the same abnormality, a first abnormality solution verification instruction is generated;

[0048] If the target device appears in the abnormality processing period of other target devices, and is a different abnormality, a second abnormality solution verification instruction is generated;

[0049] According to the abnormality solution verification instruction corresponding to the abnormality state of the target device corresponding to the other mark, the abnormality influence set associated with the abnormality processing scheme of the first marked target device is obtained, and the second abnormality corresponding to the second marked target device is matched with the abnormality influence set;

[0050] Wherein, different abnormality processing schemes are associated with a corresponding abnormality influence set, and the abnormality influence set contains a plurality of passive abnormalities, and the specific number and content of the passive abnormalities can be determined according to the automatic solution test data of the target device corresponding to the previous period, and the number of passive abnormalities can be 0, that is, there is no passive abnormality in the process of abnormality processing scheme processing;

[0051] If the second exception exists in the abnormal influence set, an exception prevention normal instruction is generated, and the corresponding exception prevention normal total number is increased by one;

[0052] If the second exception does not exist in the abnormal influence set, an exception prevention supervision instruction is generated, and the operation and maintenance personnel are prompted to implement exception prevention management on the second exception and the target device corresponding to the label, and according to the exception prevention management result, the exception coverage prevention total number associated with the exception processing scheme of the first labeled target device is increased by one or the exception defect prevention total number is increased by one;

[0053] It needs to be explained that the specific management measures and content of implementing exception prevention management on the target device are not limited, which can be realized according to the existing technical solutions in the art, or implemented by the operation and maintenance personnel according to the operation and maintenance experience and work requirements; in addition, the exception prevention management result includes the exception prevention type marked by the operation and maintenance personnel, specifically including the exception coverage prevention type and the exception defect prevention type;

[0054] Among them, the exception coverage prevention type represents that the passive exception history supervision and processing of the corresponding abnormal influence set is not complete, but there is a similar passive exception; the exception defect prevention type represents that the passive exception history of the corresponding abnormal influence set is not supervised, and there is no similar passive exception.

[0055] In the embodiment of the application, by monitoring and analyzing the operation of different variable frequency devices in the variable frequency device group in real time, and performing multi-dimensional abnormal influence analysis on the abnormal variable frequency devices obtained by monitoring and analysis and the corresponding exception processing, the implementation of the existing variable frequency device operation supervision scheme is diversified active supervision and processing analysis, which can obtain the implementation effect of different variable frequency devices corresponding to single frequency conversion, and can provide reliable local supervision processing data support for subsequent multi-dimensional reliability processing analysis of different variable frequency devices in the variable frequency device group.

[0056] The variable frequency device operation local reliability supervision module is used for performing multi-dimensional reliability processing analysis on the abnormal processing scheme associated with the operation of different variable frequency devices in the variable frequency device group, and dynamically prompting and managing the monitoring of the operation of different variable frequency devices according to the analysis result; comprising:

[0057] All abnormal numbers appearing in the operation process of different variable frequency devices in the variable frequency device group are counted and analyzed in turn, and if the total number of all abnormalities is 0, the corresponding variable frequency device is marked as a first variable frequency device;

[0058] On the contrary, the corresponding variable frequency device is marked as a second variable frequency device;

[0059] The first device total number of all first variable frequency devices and the second device total number of all second variable frequency devices are counted, the numerical values of the first device total number and the second device total number are extracted, and the formula Calculate the processing supervision value Cj of the variable frequency equipment group; wherein, M1 and M2 are the first total number and the second total number of equipment respectively; A is a processing supervision standard value, and the specific value is not limited, which can be set according to the application requirements of the actual application scene, and determined according to the test data before the variable frequency equipment group is put into production;

[0060] It should be noted that the processing supervision value is used to process and calculate different data marked from the overall level, so as to digitally represent the overall running state corresponding to the variable frequency equipment group;

[0061] If Cj is greater than or equal to 0, a running overall normal label is generated and a prompt is given;

[0062] On the contrary, a running overall abnormal label is generated, and an abnormal processing overall management prompt is given;

[0063] In the embodiment of the application, by analyzing all the total number of abnormalities of the previous supervision processing, and dynamically marking different variable frequency equipment according to the analysis result, and implementing overall level data processing and analysis, the active supervision and analysis effect of the variable frequency equipment group corresponding to the overall running is improved, and data support can be provided for subsequent reliability analysis of different aspects of different variable frequency equipment.

[0064] In addition, the abnormal prevention normal total number associated with the second variable frequency equipment is obtained, and the difference between the abnormal prevention normal total number and the total number of all abnormalities is calculated and analyzed;

[0065] It should be noted that the calculation and analysis of the difference corresponding to the second variable frequency equipment can dynamically update and classify the marking of different second variable frequency equipment, and thus reliable data support can be provided for subsequent targeted processing reliability analysis of the marked second variable frequency equipment;

[0066] If the difference is 0, the marking of the second variable frequency equipment is maintained, and the reliability processing analysis of its own dimension is carried out, and the analysis result is used to dynamically manage the abnormal prevention processing of the second variable frequency equipment of its own dimension; including:

[0067] The first abnormal processing value Cy1 corresponding to the abnormal prevention normal total number of the second variable frequency equipment is calculated by the formula Cy1=N1-NB; wherein, N1 and NB are the abnormal prevention normal total number and the abnormal prevention normal standard value of the second variable frequency equipment respectively, and the specific value of the abnormal prevention normal standard value is not limited, which can be set according to the application requirements of the actual application scene, or determined according to the median of all the first abnormal processing values of the corresponding variable frequency equipment in history;

[0068] It should be noted that the first abnormal processing value is used to process and calculate all regulatory processing data of the second frequency conversion device from the self-dimension, so as to digitally represent the corresponding abnormal prevention processing state;

[0069] If Cy1≤0, it is determined that the processing of the second frequency conversion device in the self-dimension is reliable, and an abnormal prevention processing reliable label is generated;

[0070] On the contrary, it is determined that the processing of the second frequency conversion device in the self-dimension is unreliable, and an abnormal prevention processing unreliable label is generated;

[0071] According to the abnormal prevention processing unreliable label, the self-dimension abnormal prevention processing management of the second frequency conversion device is prompted;

[0072] Different from the prior art, most of the existing technical solutions still stay in the single regulatory index data analysis and prompt, and cannot actively expand the analysis of abnormal processing data. In the embodiment of the present application, the self-dimension processing reliability analysis of the classified second frequency conversion device is carried out, and the management prompt of the labeled second frequency conversion device is carried out according to the analysis result, so as to improve the active supervision and analysis prompt effect of different frequency conversion devices in the frequency conversion device group.

[0073] If the difference is not 0, the label of the second frequency conversion device is updated to the third frequency conversion device, and the reliability processing analysis of the cooperative dimension is carried out, and the dynamic management prompt of the cooperative dimension abnormal prevention processing of the third frequency conversion device is carried out according to the analysis result; including:

[0074] The values of the total number of abnormal coverage prevention and the total number of abnormal defect prevention of the third frequency conversion device are calculated by the formula to obtain the corresponding second abnormal processing value Cy2; in the formula, N2 and N3 are the total number of abnormal coverage prevention and the total number of abnormal defect prevention corresponding to the third frequency conversion device; NB' and NB" are the abnormal coverage prevention standard value and the abnormal defect prevention standard value corresponding to the third frequency conversion device, and the specific values are not limited, which can be set according to the application requirements of the actual application scene, or can be determined according to the historical test data of the corresponding frequency conversion device in different aspects;

[0075] According to the second abnormal processing value with the value of 0, 1, 2 or 3, a second abnormal processing reliable label, a second abnormal processing coverage unreliable label, a second abnormal processing defect unreliable label or a second abnormal processing overall unreliable label is generated;

[0076] According to the second abnormal processing coverage unreliable label, the second abnormal processing defect unreliable label or the second abnormal processing overall unreliable label, the management prompt of the cooperative dimension abnormal processing coverage, the abnormal processing defect or the abnormal processing overall of the third frequency conversion device is prompted.

[0077] Notable is that the reliability processing analysis of the third frequency conversion equipment marked for updating is performed in a cooperative dimension, and abnormal processing prompts of different local aspects and overall aspects are realized according to the analysis results, thereby improving the diversity and reliability of the supervision analysis of the third frequency conversion equipment marked for updating.

[0078] In the embodiment of the application, the abnormal processing scheme related to the operation of different frequency conversion equipments in the frequency conversion equipment group is subjected to multi-dimensional reliability processing analysis, and the monitoring of the operation of different frequency conversion equipments is dynamically prompted and managed adaptively according to the analysis results, thereby actively expanding the analysis of the single supervision processing data of the different frequency conversion equipments in the early stage, and improving the operation monitoring cooperative processing and abnormal processing analysis prevention effect of the frequency conversion equipment group.

[0079] In several embodiments provided in the present application, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the application are only illustrative, for example, the division of the modules is only a logical function division, and another division mode can be used in actual implementation.

[0080] The modules illustrated as separate components can or can not be physically separated, and the components illustrated as modules can or can not be physical modules, and can be located in one place or distributed on multiple network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0081] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically, or two or more modules can be integrated in one module. The above integrated module can be realized in the form of hardware or in the form of hardware plus software function module.

[0082] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the essential characteristics of the present application.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A generalized frequency conversion equipment operation monitoring system based on big data analysis, characterized by: include: The local monitoring and analysis module for frequency conversion equipment operation is used to conduct real-time monitoring and analysis of the operation of different frequency conversion equipment in the frequency conversion equipment group, and conduct multi-dimensional abnormal impact analysis on abnormal frequency conversion equipment obtained through monitoring and analysis and the corresponding abnormal treatment. Based on the analysis results, the data associated with the abnormal treatment plan corresponding to the abnormal frequency conversion equipment is dynamically updated; The local reliability supervision module for the operation of variable frequency equipment is used to perform multi-dimensional reliability processing analysis on the abnormal handling solutions associated with the operation of different variable frequency equipment in the variable frequency equipment group, and adaptively provide dynamic prompts and management for the monitoring of the operation of different variable frequency equipment based on the analysis results.

2. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 1 is characterized in that: The operation of different frequency conversion devices in the frequency conversion device group is monitored and analyzed in real time, and the frequency conversion devices with abnormalities in the analysis are marked as target devices. At the same time, corresponding abnormality handling plans are implemented for the abnormalities corresponding to the target devices.

3. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 2 is characterized in that: When monitoring and analyzing the treatment effect corresponding to the exception handling solution implemented on the target device, if the target device does not show the mark of other target devices during the exception handling period, an exception resolution instruction is generated; If a mark of another target device appears during the target device exception handling period and the mark is the same exception, a first exception resolution verification instruction is generated; If a mark of another target device appears during the target device exception processing period and it is a different exception, a second exception resolution verification instruction is generated.

4. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 3 is characterized in that: When verifying and analyzing the abnormal state corresponding to the target device with other marks according to the abnormal solution verification instruction, the abnormal impact set associated with the abnormal handling solution corresponding to the first marked target device is obtained, and the second abnormality corresponding to the later marked target device is traversed and matched with the abnormal impact set; If there is a second exception in the abnormal impact set, an abnormal prevention and normal instruction is generated, and the corresponding abnormal prevention and normal total is increased by one; If there is no second abnormality in the abnormal impact set, an abnormality prevention supervision instruction is generated, and the operation and maintenance personnel are prompted to implement abnormality prevention management for the second abnormality and the corresponding marked target equipment, and according to the abnormality prevention management result, the total number of abnormal coverage prevention associated with the abnormal handling plan of the first marked target equipment is increased by one or the total number of abnormal defect prevention is increased by one.

5. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 4 is characterized in that: Count and analyze the total number of all abnormalities that occur during the operation of different frequency conversion devices in the frequency conversion device group. If the total number of all abnormalities is 0, mark the corresponding frequency conversion device as the first frequency conversion device. Otherwise, the corresponding frequency conversion device is marked as the second frequency conversion device; Counting the total number of first devices of all first frequency conversion devices and the total number of second devices of all second frequency conversion devices, extracting the values ​​of the total number of first devices and the total number of second devices, and obtaining a processing supervision value Cj of the frequency conversion device group through calculation; If Cj≥0, generate a normal label for the overall operation and prompt; Otherwise, an overall operation exception label is generated, and overall management prompts for exception handling are provided.

6. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 5 is characterized in that: Obtaining the total number of abnormal prevention and normal values ​​associated with the second frequency conversion device, and calculating and analyzing the difference between the total number of abnormal prevention and normal values ​​and the total number of all abnormal values; If the difference is 0, the mark of the second frequency conversion device is maintained, and the reliability processing analysis of its own dimension is performed on it. The analysis result is used to perform dynamic management prompts for abnormal prevention processing of its own dimension on the second frequency conversion device.

7. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 6 is characterized in that: Obtain the corresponding first abnormal processing value Cy1 by calculating the total number of abnormal prevention and normal values ​​of the second frequency conversion device; If Cy1≤0, it is determined that the processing of the second frequency conversion device itself is reliable, and an abnormality prevention processing reliability label is generated; Otherwise, it is determined that the processing of the second frequency conversion device itself is unreliable, and an abnormal prevention processing unreliable label is generated; According to the unreliable label of abnormal prevention processing, a management prompt is provided for the second frequency conversion device to which it belongs to perform abnormal prevention processing in its own dimension.

8. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 6 is characterized in that: If the difference is not 0, the mark of the second frequency conversion device is updated to the third frequency conversion device, and a reliability processing analysis of the collaborative dimension is performed on it. The analysis results are used to provide dynamic management prompts for collaborative dimension abnormal prevention processing of the third frequency conversion device.

9. The generalized frequency conversion equipment operation monitoring system based on big data analysis according to claim 8 is characterized in that: The total number of abnormal coverage prevention times and the total number of abnormal defect prevention times of the third frequency conversion device are calculated to obtain the corresponding second abnormal processing value Cy2; According to the second exception handling value of 1, 2 or 3, a second exception handling coverage unreliable label, a second exception handling defect unreliable label or a second exception handling overall unreliable label is generated respectively, and according to the label, management prompts of collaborative dimension exception handling coverage, exception handling defects or exception handling as a whole are performed on the third frequency conversion equipment.

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