Method and device for generating fault solution of low voltage contact cabinet

Abstract

The embodiment of the present application discloses a method and device for generating a fault solution to a low-voltage contact cabinet. The method includes: obtaining the current power distribution data and operating status data of the low-voltage contact cabinet; judging whether the low-voltage contact cabinet is currently operating normally based on the power distribution data and operating status data; when it is determined that the low-voltage contact cabinet is currently operating abnormally, inputting the power distribution data and operating status data into a fault comparison analysis model to determine fault parameters, and generating and outputting a corresponding solution based on the fault parameters. The embodiment of the present application compares the real-time power distribution data and operating status data collected from the low-voltage contact cabinet. When it is detected that the currently collected power distribution data and operating status data are abnormal, the collected data is further input into a pre-established fault comparison analysis model, and the fault parameters are determined by the fault comparison analysis model, thereby outputting a corresponding solution, which greatly saves the time of the staff and improves efficiency.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of low-voltage connection cabinets, and in particular to a method and device for generating a fault solution to a low-voltage connection cabinet. Background Art

[0002] The distribution cabinet is the final equipment of the power distribution system. It is usually used in situations where the load is relatively dispersed and there are fewer circuits. It distributes the electrical energy of a circuit of the upper-level distribution equipment to the nearest components and provides protection, monitoring and control.

[0003] The maintenance and management of existing power distribution equipment all rely on manual monitoring and operation. For example, enterprises have corresponding equipment managers, etc. However, they cannot detect faults in a timely manner, and due to the lack of real-time equipment data information, the repair and processing time of faults is long. Summary of the invention

[0004] The embodiments of the present application provide a method and device for generating a fault solution for a low-voltage contact cabinet, so as to timely analyze data and provide corresponding solutions, thereby facilitating operation by staff and improving maintenance efficiency.

[0005] In a first aspect, an embodiment of the present application provides a method for generating a low-voltage contact cabinet fault solution, comprising:

[0006] Obtain the current power distribution data and operating status data of the low-voltage contact cabinet;

[0007] Determine whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and the operating status data;

[0008] When it is determined that the low-voltage contact cabinet is currently operating abnormally, the power distribution data and the operating status data are input into the fault comparison analysis model to determine the fault parameters, and a corresponding solution is generated and output according to the fault parameters.

[0009] Further, judging whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and the operating status data includes:

[0010] Preprocessing the power distribution data and the operation status data to form a current parameter set; the current parameter set includes several items of current parameter data of different data types;

[0011] Put the current parameter set into a stored historical parameter set, wherein the historical parameter set includes several historical parameter data sets of different data segments, wherein each historical parameter data set of a data segment includes several historical parameter data of different data types, and each historical parameter data set of a data segment corresponds to an operation status result, wherein the operation status result includes abnormal and normal;

[0012] Obtain all data type names in the current parameter data, and use the data type name as a keyword to retrieve historical parameter data that matches the data type;

[0013] According to the current parameter set, the historical parameter data set of the corresponding data segment is retrieved from the historical parameter data with matching data type to obtain the operating status result corresponding to the current parameter set.

[0014] Further, when a historical parameter data set having a data segment corresponding to the current parameter set is not retrieved from the matching historical parameter data,

[0015] Obtain a historical parameter data set of a data segment closest to the current parameter set, and use the operating status result of the historical parameter data set of the data segment as the operating status result corresponding to the current parameter set.

[0016] Furthermore, the historical parameter data set of the data segment closest to the current parameter set is obtained, including:

[0017] Get the value of each current parameter data in the current parameter set, and define the historical parameter data matching the data type of the current parameter set as the target parameter data;

[0018] The value of each current parameter data is compared with the value of the corresponding data type in any target parameter data to determine the historical parameter data set of the data segment closest to the current parameter set.

[0019] Furthermore, the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set, including:

[0020] The data segment of the closest historical parameter data is recorded as the target data segment;

[0021] Calculate the minimum difference and the maximum difference between each current parameter data in the current parameter set and the historical parameter data of the corresponding data type in the target data segment;

[0022] Determine whether the number of all the minimum differences that are lower than the first preset value is less than the first threshold, and / or whether the number of all the maximum differences that are higher than the second preset value is less than the second threshold; when the number of the minimum differences that are lower than the first preset value is less than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is less than the second threshold, integrate the current parameter data and the target data segment into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment; otherwise, report an error.

[0023] Furthermore, when the number of minimum differences below the first preset value is greater than a first threshold, and / or the number of maximum differences above the second preset value is greater than a second threshold, the current parameter is stored and the corresponding data segment is set according to the current parameter data in the current parameter.

[0024] Furthermore, the fault comparison and analysis model is established in the following manner:

[0025] Acquire a number of historical fault data, each set of the historical fault data includes historical power distribution data, historical operation status data and operation status structure at a corresponding time point, and extract data features of each set of historical fault data;

[0026] A fault comparison and analysis model is constructed according to the data features.

[0027] In a second aspect, an embodiment of the present application provides a low-voltage contact cabinet fault solution generation device, comprising:

[0028] Data acquisition module: used to obtain the current power distribution data and operation status data of the low-voltage contact cabinet;

[0029] Data judgment module: used to judge whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and operation status data;

[0030] Solution output module: when it is determined that the low-voltage contact cabinet is currently operating abnormally, the power distribution data and operating status data are input into the fault comparison analysis model to determine the fault parameters, and the corresponding solution is generated and output according to the fault parameters.

[0031] Furthermore, in the data judgment module, a preprocessing submodule, a data input submodule, a data retrieval submodule and a data matching submodule are included. The preprocessing submodule is used to preprocess the power distribution data and the operating status data to form a current parameter set; the current parameter set contains several items of current parameter data of different data types. The data input submodule is used to put the current parameter set into a stored historical parameter set, and the historical parameter set contains several items of historical parameter data sets of different data segments, wherein each historical parameter data set of a data segment includes several historical parameter data of different data types, and each historical parameter data set of a data segment corresponds to an operating status result, and the operating status result includes abnormal and normal. The data retrieval submodule is used to obtain all data type names in the current parameter data, and use the data type name as a keyword to retrieve the historical parameter data matching the data type. The data matching submodule is used to retrieve the historical parameter data set of the corresponding data segment from the historical parameter data matching the data type according to the current parameter set, so as to obtain the operating status result corresponding to the current parameter set.

[0032] Furthermore, when a historical parameter data set corresponding to a data segment of the current parameter set is not retrieved from the matching historical parameter data, a data segment selection module is executed: it is used to obtain a historical parameter data set of a data segment closest to the current parameter set, and use the operating status result of the historical parameter data set of the data segment as the operating status result corresponding to the current parameter set.

[0033] Furthermore, in the data segment selection module, obtaining the historical parameter data set of the data segment closest to the current parameter set is implemented by the following modules:

[0034] Value acquisition submodule: used to obtain the value of each current parameter data in the current parameter set, and define the historical parameter data matching the data type of the current parameter set as the target parameter data;

[0035] Numerical comparison submodule: used to compare the numerical value of each current parameter data with the numerical value of the corresponding data type in any target parameter data to determine the historical parameter data set of the data segment closest to the current parameter set.

[0036] Furthermore, the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set, which is specifically implemented by the following modules:

[0037] Difference calculation module: used to record the data segment of the closest historical parameter data as the target data segment; calculate the minimum difference and maximum difference between each current parameter data in the current parameter set and the historical parameter data of the corresponding data type in the target data segment;

[0038] Difference judgment module: used to judge whether the number of all the minimum differences that are lower than the first preset value is less than the first threshold, and / or whether the number of all the maximum differences that are higher than the second preset value is less than the second threshold. When the number of the minimum differences that are lower than the first preset value is less than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is less than the second threshold, the current parameter data and the target data segment are integrated into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment; otherwise, an error is reported. When the number of the minimum differences that are lower than the first preset value is greater than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is greater than the second threshold, the current parameter is stored, and the corresponding data segment is set according to the current parameter data in the current parameter.

[0039] In a third aspect, an embodiment of the present application provides a computer device, including: a memory and one or more processors;

[0040] The memory is used to store one or more programs;

[0041] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for generating a fault solution to a low-voltage contact cabinet as described in the first aspect.

[0042] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the method for generating a fault solution to a low-voltage contact cabinet as described in the first aspect.

[0043] The embodiment of the present application compares the real-time power distribution data and operating status data collected from the low-voltage contact cabinet. When it is detected that the currently collected power distribution data and operating status data are abnormal, the collected data is further input into a previously established fault comparison and analysis model, and the fault parameters are determined by the fault comparison and analysis model, so as to output the corresponding solution, which greatly saves the detection and analysis time of the staff and improves the efficiency from the occurrence of faults to maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of a method for generating a low-voltage contact cabinet fault solution provided by an embodiment of the present application;

[0045] Figure 2 It is a structural schematic diagram of a low-voltage contact cabinet fault solution generating device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0047] Embodiment 1

[0048] Figure 1A flowchart provided in an embodiment of the present application is given. The method for generating a low-voltage contact cabinet fault solution provided in an embodiment of the present application can be executed by a low-voltage contact cabinet fault solution generating device. The low-voltage contact cabinet fault solution generating device can be implemented in hardware and / or software and integrated in a computer device.

[0049] The following description is made by taking the low-voltage contact cabinet fault solution generation device executing the low-voltage contact cabinet fault solution generation method as an example. Figure 1 , the low-voltage contact cabinet fault solution generation method includes:

[0050] S101: Obtain current power distribution data and operation status data of the low-voltage connection cabinet.

[0051] The power distribution data and operation status data of the low-voltage contact cabinet are collected in real time and used for real-time monitoring. The operation status data is determined by the equipment in the low-voltage contact cabinet, such as the processor, and includes power failure of the low-voltage contact cabinet, which is usually a relatively simple operation status.

[0052] S102: Determine whether the low-voltage interconnection cabinet is currently operating normally according to the power distribution data and the operating status data.

[0053] In step S101, through the acquired operating status data, if there is a simple abnormal operating condition problem, it can be simply and quickly determined in S101, but in this step S102, the operating status of the low-voltage contact cabinet is analyzed and determined by combining the power distribution data. In particular, the low-voltage contact cabinet may not show any operating problems on the surface, but the actual operating status and abnormal situations need to be further identified in this step.

[0054] S103: When it is determined that the low-voltage interconnection cabinet is currently operating abnormally, the power distribution data and the operating status data are input into a fault comparison analysis model to determine fault parameters, and corresponding solutions are generated and output according to the fault parameters.

[0055] In this embodiment, the fault parameters include fault type, fault severity, fault cause, etc.

[0056] The embodiment of the present application compares the real-time power distribution data and operating status data collected from the low-voltage contact cabinet. When it is detected that the currently collected power distribution data and operating status data are abnormal, the collected data is further input into a previously established fault comparison and analysis model, and the fault parameters are determined by the fault comparison and analysis model, so as to output the corresponding solution, which greatly saves the detection and analysis time of the staff and improves the efficiency from the occurrence of faults to maintenance.

[0057] In the embodiment of the present application, as a further improvement, judging whether the low-voltage interconnection cabinet is currently operating normally according to the power distribution data and the operating status data includes:

[0058] The power distribution data and the operating status data are preprocessed to form a current parameter set; the current parameter set includes several current parameter data of different data types; the current parameter set is placed in a stored historical parameter set, the historical parameter set includes several historical parameter data sets of different data segments, wherein the historical parameter data set of each data segment includes several historical parameter data of different data types, and each historical parameter data set of each data segment corresponds to an operating status result, and the operating status result includes abnormal and normal; all data type names in the current parameter data are obtained, and the historical parameter data matching the data type is retrieved using the data type name as a keyword; according to the current parameter set, the historical parameter data set of the corresponding data segment is retrieved from the historical parameter data matching the data type to obtain the operating status result corresponding to the current parameter set.

[0059] Since the power distribution data contains several types of data, the preprocessing process mainly organizes different types of data and operating status data into a data set, that is, a current parameter set, which includes multiple different types of current parameter data. The historical parameter set is a historical parameter data set containing different data segments, where the data segment refers to the numerical range of the data. Each different data historical parameter data set includes multiple types of historical parameter data.

[0060] In this embodiment, a keyword matching retrieval algorithm is used to search the current parameter set in the historical parameter set, for example, a full-field keyword matching. For example, the historical parameter set includes a historical parameter data set of three data segments A, B, and C, and the historical parameter data set of the A data segment includes five data types, the B data includes four data types, and the C data segment includes six data types. First, according to the keyword matching algorithm, the historical parameter data set with the same keyword is screened out from the historical parameter set, and the keyword is usually the name of each data type. In this embodiment, the historical parameter data set with the same keyword is screened out from the historical parameter set. More specifically, all data types in the selected historical parameter data set are the same as the data type of the current parameter set. After the historical parameter data set with the same keyword is screened out, the data segment is matched, and the historical parameter data set corresponding to the data segment is retrieved from the historical parameter data with the matched data type. For example, the data segment of the current parameter set is inserted into the data segment of a certain historical parameter data, indicating that the historical parameter data is corresponding and meets the requirements. If the data segment of the current parameter set is inserted into the data segment of multiple historical parameter data, the closest one is selected from the data segments of the multiple historical parameter data, and then the operation status result corresponding to the current parameter set is obtained.

[0061] Furthermore, when a historical parameter data set corresponding to a data segment of the current parameter set is not retrieved from the matching historical parameter data, a historical parameter data set of a data segment closest to the current parameter set is obtained, and the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set.

[0062] When the corresponding historical parameter data set cannot be matched, it means that there was no relevant record before, and the current parameter set cannot be directly input to obtain the corresponding result. Therefore, the operating status result corresponding to the historical parameter data set with the data segment closest to the current parameter set is selected as the operating status result corresponding to the current parameter set to complete the necessary procedures for obtaining a fault solution for the current parameter set.

[0063] As a more preferred implementation scheme of the embodiment of the present invention, the above-mentioned acquisition of the historical parameter data set of the data segment closest to the current parameter set can be specifically implemented as follows:

[0064] Get the value of each current parameter data in the current parameter set, define the historical parameter data that matches the data type of the current parameter set as the target parameter data; compare the value of each current parameter data with the value of the corresponding data type in any target parameter data to determine the historical parameter data set of the data segment closest to the current parameter set.

[0065] Specifically, for example, the current parameter set has 5 types of current parameter data, that is, 5 values, namely A, B, C, D, and E. One of the historical parameter data that matches the data type of the current parameter set includes 5 data types, that is, the target parameter data also has 5 values, namely a1, b1, c1, d1, and e1. The five data types contained in the other close historical parameter data are a2, b2, c2, d2, and e2. Compare the corresponding A with a1, A with a2, B with b1, B with b2, and so on. Each group of comparisons forms a difference, and the sum of the differences between the five data of the two groups of historical data parameters and the five data in the current parameter data is calculated respectively. The size of the sum of the two differences is compared, and the group with the smaller difference is used as the historical parameter data set of the data segment closest to the current parameter set.

[0066] On the other hand, the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set, including: recording the data segment of the closest historical parameter data as the target data segment; calculating the minimum difference and maximum difference between each current parameter data in the current parameter set and the historical parameter data of the corresponding data type in the target data segment; judging whether the number of all the minimum differences that are lower than the first preset value is less than the first threshold, and / or whether the number of all the maximum differences that are higher than the second preset value is less than the second threshold; when the number of the minimum differences that are lower than the first preset value is less than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is less than the second threshold, the current parameter data and the target data segment are integrated into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment; otherwise, an error is reported.

[0067] Since the current parameter data may have an upper limit and a lower limit, or the value of the corresponding data type in the target data segment has an upper limit and a lower limit, there is a minimum difference and a maximum difference. When a certain current parameter data has only one value, and the corresponding historical parameter data of the same type in the target data segment also has only one value, the maximum difference is equal to the minimum difference.

[0068] The first preset value and the second preset value are both values ​​actively input and set in advance by personnel. Whether the number of minimum differences below the first preset value is less than the first threshold, and / or whether the number of maximum differences above the second preset value is less than the second threshold, that is, the number of values ​​in the range of the remote target data segment in the current parameter data is within the set range, and the set range is artificially set, and it is considered that the target data segment can accept the numerical deviation. Within this range, the current parameter data and the target data segment can be integrated into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment.

[0069] For example, the collected current data is a to b, a is the lower limit, b is the upper limit, and in the target data segment, the current data is c, then the difference of the current data is ca and cb, and so on, the difference between other collected data and the same type of data in the target data segment is calculated to obtain the maximum difference and the minimum difference, and the number of all maximum differences in the entire current parameter data that are higher than the second preset value and the number of minimum differences that are lower than the first preset value are counted. If ca is the minimum difference of the current data, and the value of ca is lower than the first preset value, then the number lower than the first preset value is increased by 1, and so on, and finally the comparison process in this scheme can be completed.

[0070] When the number of the minimum difference values ​​lower than the first preset value is greater than the first threshold value, and / or the number of the maximum difference values ​​higher than the second preset value is greater than the second threshold value, the current parameter is stored, and the corresponding data segment is set according to the current parameter data in the current parameter. In this embodiment, the calculation statistics are the same as above.

[0071] In the embodiment of the present invention, the method of constructing the fault comparison and analysis model is preferably:

[0072] Acquire a number of historical fault data, each group of which includes historical power distribution data, historical operating status data and operating status structure at a corresponding time point, extract data features of each group of historical fault data; and construct a fault comparison and analysis model based on the data features.

[0073] Embodiment 2

[0074] like Figure 2 As shown, the embodiment of the present application provides a low-voltage contact cabinet fault solution generation device, including a data acquisition module 201, a data judgment module 202, and a solution output module 203. Among them, the data acquisition module 201 is used to obtain the current power distribution data and operating status data of the low-voltage contact cabinet; the data judgment module 202 is used to judge whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and operating status data; the solution output module 203 is used to input the power distribution data and operating status data into the fault comparison analysis model to determine the fault parameters when it is determined that the low-voltage contact cabinet is currently operating abnormally, and generate and output the corresponding solution according to the fault parameters.

[0075] Furthermore, in the data judgment module, a preprocessing submodule, a data input submodule, a data retrieval submodule and a data matching submodule are included. Specifically, the preprocessing submodule is used to preprocess the power distribution data and the operating status data to form a current parameter set; the current parameter set contains several current parameter data of different data types. The data input submodule is used to put the current parameter set into a stored historical parameter set, and the historical parameter set contains several historical parameter data sets of different data segments, wherein each historical parameter data set of a data segment includes several historical parameter data of different data types, and each historical parameter data set of a data segment corresponds to an operating status result, and the operating status result includes abnormal and normal. The data retrieval submodule is used to obtain all data type names in the current parameter data, and use the data type name as a keyword to retrieve the historical parameter data matching the data type. The data matching submodule is used to retrieve the historical parameter data set of the corresponding data segment from the historical parameter data matching the data type according to the current parameter set, so as to obtain the operating status result corresponding to the current parameter set.

[0076] As a preferred implementation, when a historical parameter data set corresponding to a data segment of a current parameter set is not retrieved from the matching historical parameter data, a data segment selection module is executed: it is used to obtain a historical parameter data set of a data segment closest to the current parameter set, and use the operating status result of the historical parameter data set of the data segment as the operating status result corresponding to the current parameter set.

[0077] Among them, in the above data segment selection module, obtaining the historical parameter data set of the data segment closest to the current parameter set is implemented by the following modules:

[0078] Value acquisition submodule: used to obtain the value of each current parameter data in the current parameter set, and define the historical parameter data matching the data type of the current parameter set as the target parameter data;

[0079] Numerical comparison submodule: used to compare the numerical value of each current parameter data with the numerical value of the corresponding data type in any target parameter data to determine the historical parameter data set of the data segment closest to the current parameter set.

[0080] Preferably, the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set, which is specifically implemented by the following modules:

[0081] Difference calculation module: used to record the data segment of the closest historical parameter data as the target data segment; calculate the minimum difference and maximum difference between each current parameter data in the current parameter set and the historical parameter data of the corresponding data type in the target data segment;

[0082] Difference judgment module: used to judge whether the number of all the minimum differences that are lower than the first preset value is less than the first threshold, and / or whether the number of all the maximum differences that are higher than the second preset value is less than the second threshold. When the number of the minimum differences that are lower than the first preset value is less than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is less than the second threshold, the current parameter data and the target data segment are integrated into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment; otherwise, an error is reported. When the number of the minimum differences that are lower than the first preset value is greater than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is greater than the second threshold, the current parameter is stored, and the corresponding data segment is set according to the current parameter data in the current parameter.

[0083] Embodiment 3

[0084] An embodiment of the present application provides a computer device, comprising: a memory and one or more processors; the memory is used to store one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method for generating a low-voltage contact cabinet fault solution as described in the embodiment of the present invention.

[0085] Embodiment 4

[0086] An embodiment of the present application also provides a storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute a method for generating a low-voltage contact cabinet fault solution as provided in the above embodiment, wherein the method comprises: obtaining current power distribution data and operating status data of a low-voltage contact cabinet; judging whether the low-voltage contact cabinet is currently operating normally based on the power distribution data and operating status data; when it is determined that the low-voltage contact cabinet is currently operating abnormally, inputting the power distribution data and operating status data into a fault comparison analysis model to determine fault parameters, and generating and outputting a corresponding solution based on the fault parameters.

[0087] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROM, floppy disk or tape device; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or may be located in a different second computer system, which is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations (for example, in different computer systems connected by a network). The storage medium may store program instructions (for example, embodied as a computer program) that can be executed by one or more processors.

[0088] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present application, whose computer executable instructions are not limited to the cable monitoring method based on smart devices as described above, can also execute related operations in the cable monitoring method based on smart devices provided in any embodiment of the present application.

[0089] The pressure contact cabinet fault solution generating device, equipment and storage medium provided in the above embodiments can execute the pressure contact cabinet fault solution generating method provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the pressure contact cabinet fault solution generating method provided in any embodiment of the present application.

[0090] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A method for generating a low-voltage contact cabinet fault solution, characterized in that: include: Obtain the current power distribution data and operation status data of the low-voltage contact cabinet; Determine whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and the operating status data; When it is determined that the low-voltage contact cabinet is currently operating abnormally, the power distribution data and the operating status data are input into the fault comparison analysis model to determine the fault parameters, and a corresponding solution is generated and output according to the fault parameters; Wherein, judging whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and the operating status data includes: pre-processing the power distribution data and the operating status data to form a current parameter set; the current parameter set includes several current parameter data of different data types; putting the current parameter set into a stored historical parameter set, the historical parameter set includes several historical parameter data sets of different data segments, wherein the historical parameter data set of each data segment includes several historical parameter data of different data types, and each historical parameter data set of each data segment corresponds to an operating status result, and the operating status result includes abnormal and normal; obtaining all data type names in the current parameter data, and using the data type name as a keyword to retrieve historical parameter data matching the data type; according to the current parameter set, retrieving the historical parameter data set of the corresponding data segment from the historical parameter data matching the data type to obtain the operating status result corresponding to the current parameter set; When a historical parameter data set of a data segment corresponding to the current parameter set is not retrieved from the matching historical parameter data, a historical parameter data set of a data segment closest to the current parameter set is obtained, and the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set; Wherein, obtaining the historical parameter data set of the data segment closest to the current parameter set includes: obtaining the value of each current parameter data in the current parameter set, defining the historical parameter data matching the data type of the current parameter set as the target parameter data; comparing the value of each current parameter data with the value of the corresponding data type in any target parameter data, so as to determine the historical parameter data set of the data segment closest to the current parameter set; The operation status result of the historical parameter data set of the data segment is used as the operation status result corresponding to the current parameter set, including: recording the data segment of the closest historical parameter data as the target data segment; Calculate the minimum difference and maximum difference between each current parameter data in the current parameter set and the historical parameter data of the corresponding data type in the target data segment; determine whether the number of all the minimum differences that are lower than the first preset value is less than the first threshold, and / or whether the number of all the maximum differences that are higher than the second preset value is less than the second threshold; when the number of the minimum differences that are lower than the first preset value is less than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is less than the second threshold, integrate the current parameter data and the target data segment into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment; otherwise, report an error.

2. The method for generating a low-voltage contact cabinet fault solution according to claim 1, characterized in that: When the number of minimum differences below the first preset value is greater than a first threshold, and / or the number of maximum differences above the second preset value is greater than a second threshold, the current parameter is stored and the corresponding data segment is set according to the current parameter data in the current parameter.

3. The method for generating a low-voltage contact cabinet fault solution according to claim 1, characterized in that: The fault comparison analysis model is established in the following way: Acquire a number of historical fault data, each set of the historical fault data includes historical power distribution data, historical operation status data and operation status structure at a corresponding time point, and extract data features of each set of historical fault data; A fault comparison and analysis model is constructed according to the data features.

4. A device for generating a fault solution for a low-voltage contact cabinet, characterized in that: include: Data acquisition module: used to obtain the current power distribution data and operation status data of the low-voltage contact cabinet; Data judgment module: used to judge whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and operation status data; Solution output module: when it is determined that the low-voltage contact cabinet is currently operating abnormally, input the power distribution data and operating status data into the fault comparison analysis model to determine the fault parameters, and generate and output corresponding solutions according to the fault parameters; Wherein, judging whether the low-voltage contact cabinet is currently operating normally according to the power distribution data and the operating status data includes: pre-processing the power distribution data and the operating status data to form a current parameter set; the current parameter set includes several current parameter data of different data types; putting the current parameter set into a stored historical parameter set, the historical parameter set includes several historical parameter data sets of different data segments, wherein the historical parameter data set of each data segment includes several historical parameter data of different data types, and each historical parameter data set of each data segment corresponds to an operating status result, and the operating status result includes abnormal and normal; obtaining all data type names in the current parameter data, and using the data type name as a keyword to retrieve historical parameter data matching the data type; according to the current parameter set, retrieving the historical parameter data set of the corresponding data segment from the historical parameter data matching the data type to obtain the operating status result corresponding to the current parameter set; When a historical parameter data set of a data segment corresponding to the current parameter set is not retrieved from the matching historical parameter data, a historical parameter data set of a data segment closest to the current parameter set is obtained, and the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set; Wherein, obtaining the historical parameter data set of the data segment closest to the current parameter set includes: obtaining the value of each current parameter data in the current parameter set, defining the historical parameter data matching the data type of the current parameter set as the target parameter data; comparing the value of each current parameter data with the value of the corresponding data type in any target parameter data, so as to determine the historical parameter data set of the data segment closest to the current parameter set; Among them, the operating status result of the historical parameter data set of the data segment is used as the operating status result corresponding to the current parameter set, including: recording the data segment of the closest historical parameter data as the target data segment; calculating the minimum difference and maximum difference between each current parameter data in the current parameter set and the historical parameter data of the corresponding data type in the target data segment; judging whether the number of all the minimum differences that are lower than the first preset value is less than the first threshold, and / or whether the number of all the maximum differences that are higher than the second preset value is less than the second threshold; when the number of the minimum differences that are lower than the first preset value is less than the first threshold, and / or the number of the maximum differences that are higher than the second preset value is less than the second threshold, the current parameter data and the target data segment are integrated into a new data segment, and the operating status result corresponding to the new data segment is consistent with the operating status result corresponding to the target data segment; otherwise, an error is reported.

5. A computer device, characterized in that: include: memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for generating a fault solution to a low-voltage contact cabinet as described in any one of claims 1 to 3.

6. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the method for generating a fault solution to a low-voltage contact cabinet as described in any one of claims 1 to 3 when executed by a computer processor.

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