New energy station fault data processing method, system, equipment and medium

Abstract

The invention belongs to the technical field of new energy, and particularly relates to a new energy station fault data processing method, system and device and a medium, and the method comprises the steps: querying historical alarm data of a new energy station according to a preset fault query condition, and obtaining the historical alarm data; acquiring a device ID and fault occurrence time corresponding to the historical alarm data; according to the equipment ID and the fault occurrence time corresponding to the historical alarm data, obtaining sub-fault data of the associated sub-fault measurement points; grouping the sub-fault data of the associated sub-fault measuring points according to the equipment ID and the fault occurrence time to obtain a sub-fault data grouping result; combining the sub-fault grouping result with the historical alarm data according to the equipment ID and the fault occurrence time to obtain a new energy station fault data processing result; according to the method, the time is determined to the time point when the specific fault occurs, so that the query time span is greatly reduced, the query efficiency is effectively improved, and the consumption of system resources is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of new energy technology, and in particular relates to a new energy station fault data processing method, system, equipment and medium. Background Art

[0002] In the field of new energy, especially in the operation and management of new energy stations, fault handling is an important link. With the continuous expansion of the scale of new energy stations and the increase in system complexity, the amount of data involved in fault handling is also increasing. Therefore, when handling faults, it is often necessary to manage the faults and find the corresponding sub-fault data for more in-depth analysis and solutions.

[0003] At present, fault-associated sub-fault data mainly includes fault data records, sub-fault data records and the association between the two; the principle is that by associating fault data and sub-fault data, the possible cause can be quickly located when a system failure occurs, thereby improving the efficiency of fault handling; however, since most existing systems do not have clear association records for faults and sub-faults, the fault handling process is incomplete, and as a result, there are problems of low efficiency and reduced query rate when dealing with large quantities of alarm data. Summary of the invention

[0004] In response to the technical problems existing in the prior art, the present invention provides a new energy station fault data processing method, system, equipment and medium to solve the technical problems that most existing systems do not have clear correlation records between faults and sub-faults, resulting in incomplete fault handling process, and then inefficiency and reduced query rate when dealing with large amounts of alarm data.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: The present invention provides a method for processing fault data of a new energy station, comprising: According to the preset fault query conditions, query the historical alarm data of the new energy station to obtain the historical alarm data; Get the device ID and fault occurrence time corresponding to the historical alarm data; According to the equipment ID and fault occurrence time corresponding to the historical alarm data, obtain the sub-fault data of the associated sub-fault measurement point; According to the device ID and the fault occurrence time, the sub-fault data of the associated sub-fault measuring points are grouped to obtain the sub-fault data grouping result; The sub-fault grouping result and the historical alarm data are combined according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

[0006] Furthermore, the preset fault query conditions include the ID of the equipment in the new energy station, the preset query time and the alarm level.

[0007] Furthermore, the historical alarm data of the new energy station is queried to obtain the historical alarm data, as follows: Using the Map function, the historical alarm data can be obtained by paging or batch query according to the total amount of historical data to be queried, combined with the ID of the equipment in the new energy station, the preset query time and the alarm level.

[0008] Furthermore, the process of obtaining the device ID and fault occurrence time corresponding to the historical alarm data is as follows: The List function is used to extract information from historical alarm data to obtain the device ID and fault occurrence time corresponding to the historical alarm data.

[0009] Furthermore, according to the device ID and fault occurrence time corresponding to the historical alarm data, the process of obtaining the sub-fault data of the associated sub-fault measuring point is as follows: Through the SELECT function, the sub-fault data of the associated sub-fault measuring point is obtained according to the device ID and fault occurrence time corresponding to the historical alarm data.

[0010] Furthermore, the sub-fault data of the associated sub-fault measuring points are grouped according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result, as follows: Generate a unique key for each sub-fault data associated with the sub-fault measurement point based on the device ID and fault occurrence time; According to the generated key, the sub-fault data with the same key are grouped together; Each group is stored in a list, and the mapping relationship between the key and the list is stored in a Map array to obtain the sub-fault data grouping result.

[0011] Further, the sub-fault grouping result is combined with the historical alarm data according to the device ID and the fault occurrence time to obtain the new energy station fault data processing result, which is specifically as follows: From the sub-fault grouping result, obtain a value associated with the device ID and a value associated with the fault occurrence time; Concatenate the value associated with the device ID and the value associated with the fault occurrence time to obtain a concatenated string; The concatenated string is used as the key, and the value associated with the key is obtained from the historical fault data to obtain the new energy station fault data processing result.

[0012] The present invention also provides a new energy station fault data processing system, comprising: The first query module is used to query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data; Information acquisition module, used to obtain the device ID and fault occurrence time corresponding to the historical alarm data; The second query module is used to obtain the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data; A data grouping module is used to group the sub-fault data of the associated sub-fault measuring points according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result; The data merging module is used to merge the sub-fault molecular results with the historical alarm data according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

[0013] The present invention also provides a new energy station fault data processing device, comprising: a processor suitable for executing a computer program; A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the new energy station fault data processing method is executed.

[0014] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the new energy station fault data processing method is implemented.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The new energy station fault data processing method provided by the present invention obtains the sub-fault data of the associated sub-fault measuring point according to the device ID and the fault occurrence time corresponding to the historical alarm data, and groups the sub-fault data of the associated sub-fault measuring point according to the device ID and the fault occurrence time and merges them with the historical alarm data to obtain the new energy station fault data processing result, so as to determine the time to the time point when the specific fault occurs, rather than querying the time range of the sub-fault data, thereby greatly reducing the query time span; compared with the prior art that requires querying the sub-fault data of the entire time range, the query efficiency is effectively improved and the consumption of system resources is reduced; secondly, by accurately determining the time point when the fault occurs, the fault and sub-fault data can be more accurately associated, the accuracy of fault processing is improved, and then the cause of the fault can be located more quickly, and corresponding solutions can be taken, thereby reducing the misjudgment rate and risk of fault processing; the present invention does not need to manually record the fault time, and automatically realizes fault association by querying and processing on the historical data page, thereby improving the integrity of system monitoring; at the same time, data association is realized by processing the fault occurrence time, and the system does not need to clearly record the association between the fault and the sub-fault, so it can be flexibly applied to different types of systems and scenarios, and can effectively improve the overall operation efficiency and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is a flow chart of the method for processing fault data of a new energy station according to Example 1; Figure 2 A structural block diagram of a new energy station fault data processing system provided in Example 2; Figure 3 This is a structural block diagram of the new energy station fault data processing equipment provided in Example 3. DETAILED DESCRIPTION

[0018] In order to make the technical problems, technical solutions and beneficial effects solved by this application clearer, the technical solutions in the embodiments of this application will be described clearly and completely in combination with the drawings in the embodiments of this application; obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0019] The present invention provides a method for processing fault data of a new energy station, comprising the following steps: Step 1: According to the preset fault query conditions, query the historical alarm data of the new energy station to obtain the historical alarm data.

[0020] Step 2: Obtain the device ID and fault occurrence time corresponding to the historical alarm data.

[0021] Step 3: According to the device ID and fault occurrence time corresponding to the historical alarm data, obtain the sub-fault data of the associated sub-fault measuring point.

[0022] Step 4: Group the sub-fault data of the associated sub-fault measuring points according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result.

[0023] Step 5: Combine the sub-fault grouping result and the historical alarm data according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

[0024] The present invention also provides a new energy station fault data processing system, comprising a first query module, an information acquisition module, a second query module, a data grouping module and a data merging module.

[0025] The first query module is used to query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data; the information acquisition module is used to obtain the equipment ID and fault occurrence time corresponding to the historical alarm data; the second query module is used to obtain the sub-fault data of the associated sub-fault measuring point according to the equipment ID and fault occurrence time corresponding to the historical alarm data; the data grouping module is used to group the sub-fault data of the associated sub-fault measuring point according to the equipment ID and fault occurrence time to obtain the sub-fault data grouping result; the data merging module is used to merge the sub-fault molecular result with the historical alarm data according to the equipment ID and fault occurrence time to obtain the new energy station fault data processing result.

[0026] The new energy station fault data processing method and system described in the present invention determine the time to the time point when the specific fault occurs, which greatly reduces the query time span, effectively improves the query efficiency, and reduces the consumption of system resources; secondly, by accurately determining the time point when the fault occurs, it is possible to more accurately associate the fault and sub-fault data, thereby improving the accuracy of fault handling, and then being able to locate the cause of the fault more quickly and take corresponding solutions, thereby reducing the misjudgment rate and risk of fault handling; the present invention realizes data association by processing the time when the fault occurs, and there is no need for the system to make clear association records between the fault and the sub-fault. It can be more flexibly applied to different types of systems and scenarios, and can effectively improve the overall operating efficiency and reliability of the system.

[0027] Example 1 As attached Figure 1 As shown, this embodiment 1 provides a method for processing fault data of a new energy station, comprising the following steps: Step 1: query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data. The preset fault query conditions include the ID of the equipment in the new energy station, the preset query time and the alarm level.

[0028] Specifically, the process of querying the historical alarm data of the new energy station and obtaining the historical alarm data includes: Using the Map function, the historical alarm data can be obtained by paging or batch query according to the total amount of historical data to be queried, combined with the ID of the equipment in the new energy station, the preset query time and the alarm level.

[0029] Taking the query process of the relational database as an example, the historical alarm data of the new energy station is queried to obtain the program code of the historical alarm data as follows: Map<String,Object> hashMap= new ConcurrentHashMap<>(map); / / Insert start and end time or other conditions hashMap.put("beginTime",beginTime); hashMap.put("endTime",endTime); List <alarmdetail>details= alarmDetailService.selectTableDataMap(hashMap).

[0030] Step 2: Divide the historical alarm data into batches to obtain several batches of historical alarm data, wherein the data volume of each batch of historical alarm data is dynamically adjusted according to the performance and requirements of the server; preferably, each batch of historical alarm data contains 500 pieces of historical alarm data.

[0031] Step 3: traverse each batch of historical alarm data to obtain the device ID and fault occurrence time corresponding to the historical alarm data. Specifically, use the List function to extract information from the historical alarm data to obtain the device ID and fault occurrence time corresponding to the historical alarm data.

[0032] Similarly, taking the relational database as an example, the List function is used to extract information from historical alarm data, and the program code for obtaining the device ID and fault occurrence time corresponding to the historical alarm data is as follows: List <alarmdetail>details It should be noted that each piece of historical alarm data contains the faulty device ID, fault occurrence time and device information.

[0033] Step 4: Obtain sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data. Specifically, through the SELECT function, obtain the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data. The SELECT function program code is shown in Table 1 below.

[0034] Table 1 SELECT function program code

[0035] Step 5: Group the sub-fault data of the associated sub-fault measuring points according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result. Specifically, the process of grouping the sub-fault data of the associated sub-fault measuring points includes: Step 51: Generate a unique key for each piece of sub-fault data associated with a sub-fault measuring point according to the device ID and the fault occurrence time.

[0036] Step 52: According to the generated key, the sub-fault data with the same key are grouped together.

[0037] Step 53: Store each group in a list, and store the mapping relationship between the key and the list in a Map array to obtain the sub-fault data grouping result.

[0038] It should be noted that the program code for grouping the sub-fault data of the associated sub-fault measuring points is as follows: dataList.parallelStream().collect(Collectors.groupingBy(o->o.get("equipmentId")+"-"+o.get("beginTime"))). Where dataList is a list containing elements, assuming that each element is a map, for example: Map<String,Object> ; parallelStream() converts a list into a parallel stream; parallel streams can use multiple threads to process elements in the stream in parallel; collect is a terminal operation that accumulates the elements in the stream into a summary result; Collectors.groupingBy is a collector used to group the elements in the stream according to the results of a preset classification function; o>o.get("equipmentId")+"-"+o.get("beginTime") is a lambda expression that serves as the classification function of the groupingBy collector; for each element o in the stream, it gets the values ​​associated with the keys "equipmentId" and "beginTime"; then, these two values ​​are concatenated into a string separated by "-" as the grouping key.

[0039] Step 6: Combine the sub-fault grouping result and the historical alarm data according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

[0040] Specifically, the merging process is as follows: From the sub-fault grouping results, obtain the value associated with the device ID and the value associated with the fault occurrence time; concatenate the value associated with the device ID and the value associated with the fault occurrence time to obtain a concatenated string; use the concatenated string as a key, obtain the value associated with the key from the historical fault data, and obtain the new energy station fault data processing result.

[0041] The program code for merging the sub-fault grouping result with the historical alarm data according to the device ID and the fault occurrence time is, for example: dataMap.get(stringObjectMap.get("equipmentId")+"-"+stringObjectMap.get("beginTime")); where stringObjectMap.get("equipmentId") gets the value associated with the key "equipmentId" from the stringObjectMap mapping, and stringObjectMap.get("beginTime") gets the value associated with the key "beginTime" from the stringObjectMap mapping; connect the two values ​​​​get above with a short dash, and finally, the connected string is used as the key of the dataMap mapping to get the value associated with it.

[0042] Example description: Taking the fault data processing process of a new energy station SCADA system as an example, the new energy station fault data processing method described in this embodiment 1 is described as follows: Assume that the device ID is 1, the sub-fault points include DA and DB, the query time is from 2024-04-01 to 2024-04-03, and the historical alarm data is shown in Table 2 below.

[0043] Table 2 Historical alarm data table

[0044] According to the device ID and fault occurrence time corresponding to the historical alarm data, the associated sub-fault measurement points are obtained; wherein the associated sub-fault measurement points include A01_DA, A01_DB, A02_DA, A02_DB, A03_DA, A03_DB; then, the sub-fault data of the associated sub-fault measurement points are obtained using the following acquisition program code; the acquisition program code is specifically: select AV, TM, GN, DSfrom Archive where gn in (A01_DA, A01_DB, A02_DA, A02_DB, A03_DA, A03_DB) and tmbetween in ('2024-04-01 00:00:00', '2024-04-02 00:00:00', 2024-04-03 00:00:00) and mode = 'span' and interval = '1s'; wherein, the sub-fault data of the associated sub-fault measurement points are shown in Table 3.

[0045] Table 3 Sub-fault data table of associated sub-fault measurement points

[0046] The sub-fault grouping result is combined with the historical alarm data according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result; wherein, the new energy station fault data processing result is as shown in Table 4.

[0047] Table 4. New energy station fault data processing results

[0048] It should be noted that in the fault data processing results of the new energy station, the merged sub-faults are spliced ​​behind the fault data, and multiple sub-fault data are spliced ​​backward in sequence; when it is necessary to perform Chinese analysis on the value of the sub-fault, the sub-fault data will be converted into Chinese description when merging the data.

[0049] The fault data processing method described in this embodiment 1 can enable collaborative users to locate the cause of the fault more quickly and take corresponding solutions, thereby reducing the misjudgment rate and risk of fault handling.

[0050] Example 2 As attached Figure 2 As shown, this embodiment 2 provides a new energy station fault data processing system, including a first query module, a batch module, an information acquisition module, a second query module, a data grouping module and a data merging module.

[0051] The first query module is used to query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data; A batching module, used to batch the historical alarm data to obtain several batches of historical alarm data; The information acquisition module is used to traverse each batch of historical alarm data and obtain the device ID and fault occurrence time corresponding to the historical alarm data; The second query module is used to obtain the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data; A data grouping module is used to group the sub-fault data of the associated sub-fault measuring points according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result; The data merging module is used to merge the sub-fault grouping results with the historical alarm data according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

[0052] Example 3 This embodiment 3 provides a new energy station fault data processing device, including: a memory for storing a computer program; a processor for implementing the steps of a new energy station fault data processing method when executing the computer program.

[0053] When the processor executes the computer program, the steps of the above-mentioned method for processing fault data of new energy stations are implemented, for example: According to the preset fault query conditions, the historical alarm data of the new energy station is queried to obtain the historical alarm data; a batch module is used to batch the historical alarm data to obtain several batches of historical alarm data; each batch of historical alarm data is traversed to obtain the device ID and fault occurrence time corresponding to the historical alarm data; according to the device ID and fault occurrence time corresponding to the historical alarm data, the sub-fault data of the associated sub-fault measuring point is obtained; according to the device ID and fault occurrence time, the sub-fault data of the associated sub-fault measuring point is grouped to obtain the sub-fault data grouping result; the sub-fault grouping result is merged with the historical alarm data according to the device ID and fault occurrence time to obtain the new energy station fault data processing result.

[0054] Alternatively, when the processor executes the computer program, the functions of each module in the above-mentioned new energy station fault data processing system are realized, for example: The first query module is used to query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data; the batch module is used to batch the historical alarm data to obtain several batches of historical alarm data; the information acquisition module is used to traverse each batch of historical alarm data to obtain the equipment ID and fault occurrence time corresponding to the historical alarm data; the second query module is used to obtain the sub-fault data of the associated sub-fault measuring point according to the equipment ID and fault occurrence time corresponding to the historical alarm data; the data grouping module is used to group the sub-fault data of the associated sub-fault measuring point according to the equipment ID and fault occurrence time to obtain the sub-fault data grouping result; the data merging module is used to merge the sub-fault grouping result with the historical alarm data according to the equipment ID and fault occurrence time to obtain the new energy station fault data processing result.

[0055] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing preset functions, and the instruction segments are used to describe the execution process of the computer program in the new energy station fault data processing device.

[0056] For example, the computer program can be divided into a first query module, a batch module, an information acquisition module, a second query module, a data grouping module and a data merging module, and the specific functions of each module are as follows: the first query module is used to query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data; the batch module is used to batch the historical alarm data to obtain several batches of historical alarm data; the information acquisition module is used to traverse each batch of historical alarm data to obtain the device ID and fault occurrence time corresponding to the historical alarm data; the second query module is used to obtain the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data; the data grouping module is used to group the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time to obtain the sub-fault data grouping result; the data merging module is used to merge the sub-fault grouping result with the historical alarm data according to the device ID and fault occurrence time to obtain the new energy station fault data processing result.

[0057] The new energy station fault data processing device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The new energy station fault data processing device may include, but is not limited to, a processor and a memory. Those skilled in the art may understand that the above are examples of new energy station fault data processing devices and do not constitute a limitation on the new energy station fault data processing device. It may include more components than the above, or a combination of certain components, or different components. For example, the new energy station fault data processing device may also include input and output devices, network access devices, buses, etc.

[0058] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The processor is the control center of the new energy station fault data processing equipment, and uses various interfaces and lines to connect various parts of the entire new energy station fault data processing equipment.

[0059] The memory can be used to store the computer program and / or module, and the processor implements various functions of the new energy station fault data processing device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory.

[0060] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0061] Example 4 This embodiment 4 also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for processing fault data of a new energy station are implemented, for example: According to the preset fault query conditions, the historical alarm data of the new energy station is queried to obtain the historical alarm data; a batch module is used to batch the historical alarm data to obtain several batches of historical alarm data; each batch of historical alarm data is traversed to obtain the device ID and fault occurrence time corresponding to the historical alarm data; according to the device ID and fault occurrence time corresponding to the historical alarm data, the sub-fault data of the associated sub-fault measuring point is obtained; according to the device ID and fault occurrence time, the sub-fault data of the associated sub-fault measuring point is grouped to obtain the sub-fault data grouping result; the sub-fault grouping result is merged with the historical alarm data according to the device ID and fault occurrence time to obtain the new energy station fault data processing result.

[0062] If the modules / units integrated in the new energy station fault data processing system are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0063] Based on this understanding, the present invention implements all or part of the processes in the above-mentioned new energy station fault data processing method, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned new energy station fault data processing method can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or preset intermediate form, etc.

[0064] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0065] It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0066] The new energy station fault data processing method described in the present invention determines the time to the time point when the specific fault occurs, rather than querying the time range of the sub-fault, which greatly reduces the query time span; compared with the prior art that needs to query the sub-fault data of the entire time range, it effectively improves the query efficiency and reduces the consumption of system resources; by accurately determining the time point when the fault occurs, it can more accurately associate the fault and sub-fault data, improve the accuracy of fault processing, and the system can locate the cause of the fault more quickly and take corresponding solutions, thereby reducing the misjudgment rate and risk of fault processing; there is no need to manually record the fault time and manually query and process on the historical data page, but automatically realize fault association, which improves the integrity of system monitoring; the method does not require the system to have clearly associated the fault and sub-fault records, but realizes data association by processing the timestamp of the fault occurrence, so it can be more flexibly applied to different types of systems and scenarios, and can effectively improve the overall operation efficiency and reliability of the system.

[0067] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention.< / alarmdetail> < / alarmdetail>

Claims

1. A method for processing fault data of a new energy station, characterized in that: include: According to the preset fault query conditions, query the historical alarm data of the new energy station to obtain the historical alarm data; Get the device ID and fault occurrence time corresponding to the historical alarm data; According to the equipment ID and fault occurrence time corresponding to the historical alarm data, obtain the sub-fault data of the associated sub-fault measurement point; According to the device ID and the fault occurrence time, the sub-fault data of the associated sub-fault measuring points are grouped to obtain the sub-fault data grouping result; The sub-fault grouping result and the historical alarm data are combined according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

2. A method for processing fault data of a new energy station according to claim 1, characterized in that: The preset fault query conditions include the ID of the equipment in the new energy station, the preset query time and the alarm level.

3. A method for processing fault data of a new energy station according to claim 2, characterized in that: The process of querying the historical alarm data of the new energy station and obtaining the historical alarm data is as follows: Using the Map function, the historical alarm data can be obtained by paging or batch query according to the total amount of historical data to be queried, combined with the ID of the equipment in the new energy station, the preset query time and the alarm level.

4. A method for processing fault data of a new energy station according to claim 1, characterized in that: The process of obtaining the device ID and fault occurrence time corresponding to the historical alarm data is as follows: The List function is used to extract information from historical alarm data to obtain the device ID and fault occurrence time corresponding to the historical alarm data.

5. A method for processing fault data of a new energy station according to claim 1, characterized in that: The process of obtaining the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data is as follows: Through the SELECT function, the sub-fault data of the associated sub-fault measuring point is obtained according to the device ID and fault occurrence time corresponding to the historical alarm data.

6. A method for processing fault data of a new energy station according to claim 1, characterized in that: The process of grouping the sub-fault data of the associated sub-fault measuring points according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result is as follows: Generate a unique key for each sub-fault data associated with the sub-fault measurement point based on the device ID and fault occurrence time; According to the generated key, the sub-fault data with the same key are grouped together; Each group is stored in a list, and the mapping relationship between the key and the list is stored in a Map array to obtain the sub-fault data grouping result.

7. A method for processing fault data of a new energy station according to claim 6, characterized in that: The process of combining the sub-fault grouping result with the historical alarm data according to the device ID and the fault occurrence time to obtain the new energy station fault data processing result is as follows: From the sub-fault grouping result, obtain a value associated with the device ID and a value associated with the fault occurrence time; Concatenate the value associated with the device ID and the value associated with the fault occurrence time to obtain a concatenated string; The concatenated string is used as the key, and the value associated with the key is obtained from the historical fault data to obtain the new energy station fault data processing result.

8. A new energy station fault data processing system, characterized in that: include: The first query module is used to query the historical alarm data of the new energy station according to the preset fault query conditions to obtain the historical alarm data; Information acquisition module, used to obtain the device ID and fault occurrence time corresponding to the historical alarm data; The second query module is used to obtain the sub-fault data of the associated sub-fault measuring point according to the device ID and fault occurrence time corresponding to the historical alarm data; A data grouping module is used to group the sub-fault data of the associated sub-fault measuring points according to the device ID and the fault occurrence time to obtain the sub-fault data grouping result; The data merging module is used to merge the sub-fault molecular results with the historical alarm data according to the equipment ID and the fault occurrence time to obtain the new energy station fault data processing result.

9. A new energy station fault data processing device, characterized in that: include: a processor suitable for executing a computer program; A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the new energy station fault data processing method according to any one of claims 1 to 7 is executed.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the new energy station fault data processing method as described in any one of claims 1 to 7 is implemented.

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