CN114878960A - Fault diagnosis method, storage medium, power acquisition terminal, and fault diagnosis system - Google Patents
Fault diagnosis method, storage medium, power acquisition terminal, and fault diagnosis system Download PDFInfo
- Publication number
- CN114878960A CN114878960A CN202210440509.2A CN202210440509A CN114878960A CN 114878960 A CN114878960 A CN 114878960A CN 202210440509 A CN202210440509 A CN 202210440509A CN 114878960 A CN114878960 A CN 114878960A
- Authority
- CN
- China
- Prior art keywords
- fault
- terminal
- local
- matching
- remote
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003745 diagnosis Methods 0.000 title claims abstract description 132
- 238000000034 method Methods 0.000 title claims abstract description 80
- 238000000605 extraction Methods 0.000 claims description 4
- 230000015556 catabolic process Effects 0.000 abstract 1
- 230000008569 process Effects 0.000 description 26
- 238000012423 maintenance Methods 0.000 description 9
- 238000004171 remote diagnosis Methods 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 206010033799 Paralysis Diseases 0.000 description 6
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000003306 harvesting Methods 0.000 description 2
- 229910052744 lithium Inorganic materials 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 230000019771 cognition Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Test And Diagnosis Of Digital Computers (AREA)
Abstract
The invention discloses a fault diagnosis method, medium, a power acquisition terminal and a system of the power acquisition terminal, wherein the fault diagnosis method comprises the following steps: the method comprises the steps of carrying out local matching on collected terminal fault information and fault characteristics in a local fault characteristic library of a terminal, identifying the terminal fault information according to the fault characteristics in the local fault characteristic library if the local matching is successful, determining the fault type of the power collection terminal, uploading the terminal fault information to a cloud end if the local matching is failed so as to carry out remote matching on the terminal fault information through the fault characteristics in a remote fault characteristic library configured at the cloud end, identifying the terminal fault information according to the fault characteristics in the remote fault characteristic library when the remote matching is successful, and determining the fault type of the power collection terminal, wherein the remote fault characteristic library contains the fault characteristics which are not contained in the local fault characteristic library, carrying out fault diagnosis in a mode of cooperation between the cloud end and the terminal, reducing data throughput and avoiding network breakdown.
Description
Technical Field
The present disclosure relates to the field of power supply control technologies, and in particular, to a fault diagnosis method, a storage medium, a power acquisition terminal, and a fault diagnosis system.
Background
With the popularization of the smart power grid, higher requirements are put forward on the operation stability and the fault diagnosis and repair rate of the power acquisition terminal. The current power acquisition terminals are large in deployment quantity, complex in field environment, various in manufacturer and different in type, and therefore obstacles are caused to fault diagnosis of the power acquisition terminals. When the power acquisition terminal breaks down, maintenance personnel need to be sent to go to the site to carry out fault diagnosis, the maintenance personnel analyze fault information according to cognition and maintenance experience of a fault specific terminal to judge fault reasons, after cases of different scenes, different terminals and different fault reasons are accumulated, a terminal fault library is constructed, a platform management terminal is constructed, and the collected terminal fault information is compared with fault information in the fault library to analyze the fault reasons.
The current power acquisition terminal fault diagnosis technology basically adopts the following two modes for diagnosis:
1. and performing field diagnosis, namely performing field diagnosis on the terminal fault by a maintenance worker going to a deployment field of the power acquisition terminal.
2. And (4) uniformly diagnosing the platform, wherein the platform collects the fault information of the power acquisition terminal and carries out remote fault diagnosis on the terminal.
In the process of implementing the present application, the inventors found that the above fault diagnosis method has at least the following problems:
1. the adoption of the field diagnosis mode depends on the working experience of maintenance personnel and the knowledge of a fault terminal, the subjective randomness of the mode is strong, and sometimes the fault reason is difficult to diagnose in time; and because the number of deployed terminals is large, the field environment is also different, the positions of some terminals are inconvenient to traffic, and the surrounding environment is severe, so that fault diagnosis and maintenance are not facilitated, the diagnosis difficulty is high, and the diagnosis cost is high.
2. The mode of platform unified diagnosis needs to upload a lot of information including fault information to a platform for diagnosis, so that high requirements are provided for a network channel, when a large number of terminals have faults due to natural disasters and manual operations, the platform cannot respond to the diagnosis requirements of the terminal faults in time, and the uploading of a large amount of diagnosis information occupies the network channel, so that the normal operation of other services is hindered.
It is noted that the information disclosed in this background section is only for background understanding of the concepts of the application and, therefore, it may contain information that does not form the prior art.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, a first objective of the present application is to provide a fault diagnosis method for an electric power collection terminal, which performs fault diagnosis in a cloud and terminal cooperation manner, and performs fault diagnosis for the electric power collection terminal in a manner of automatically matching fault information with fault characteristics, so as to eliminate influence caused by subjective randomness; meanwhile, the diagnosis process is divided into local diagnosis and remote diagnosis, a common fault feature library is pre-deployed locally at the edge, local identification and matching are carried out on common faults by utilizing the local diagnosis, the diagnosis efficiency is improved, and only when the generated faults cannot be diagnosed through the local common fault feature library, the feature library which is deployed at the cloud end and contains the unusual fault features is utilized for carrying out cloud end remote diagnosis, so that the data throughput is reduced, and the network paralysis is avoided.
A second object of the present application is to propose a computer-readable storage medium.
A third objective of the present application is to provide a power collecting terminal.
A fourth objective of the present application is to provide a fault diagnosis system for a power collection terminal.
In order to achieve the above object, an embodiment of a first aspect of the present application provides a method for diagnosing a fault of a power collection terminal, including: locally matching the acquired terminal fault information with fault characteristics in a local fault characteristic library of the terminal; if the local matching is successful, identifying the terminal fault information according to the fault characteristics in the local fault characteristic library, and determining the fault type of the power acquisition terminal; if the local matching fails, the terminal fault information is uploaded to a cloud end so that the terminal fault information can be remotely matched through fault features configured in a remote fault feature library of the cloud end, the terminal fault information is identified according to the fault features in the remote fault feature library when the remote matching is successful, and the fault type of the power acquisition terminal is determined, wherein the remote fault feature library contains the fault features which are not contained in the local fault feature library.
According to the fault diagnosis method of the power acquisition terminal, fault diagnosis is carried out in a mode of cooperation of a cloud end and the terminal, and fault diagnosis of the power acquisition terminal is carried out in a mode of automatically matching fault information with fault characteristics, so that influence caused by subjective randomness is eliminated; meanwhile, the diagnosis process is divided into local diagnosis and remote diagnosis, a common fault feature library is pre-deployed locally at the edge, local identification and matching are carried out on common faults by utilizing the local diagnosis, the fault diagnosis efficiency is improved depending on the condition of the existing hardware resources, and only when the generated faults cannot be diagnosed through the local common fault feature library, the cloud-end-deployed feature library containing the unusual fault features is utilized for carrying out cloud-end remote fault identification and matching, so that the data throughput is reduced, the dependence on network channels is reduced, network paralysis is avoided, and the stable operation of the terminal is ensured.
According to one embodiment of the application, when a power acquisition terminal with a fault is not configured with a local fault feature library, the local matching is carried out based on the local fault feature library configured in other power acquisition terminals of the same type, which are located in the same local area network, with the power acquisition terminal with the fault.
According to an embodiment of the present application, the local matching and the remote matching have the same matching manner, wherein the matching manner includes: respectively calculating the similarity between the terminal fault information and each fault feature; if at least one similarity not lower than a set threshold exists, determining that the matching is successful; and if all the similarity degrees are lower than the set threshold value, determining that the matching fails.
According to an embodiment of the application, the method further comprises: and if the successfully matched fault characteristics are multiple, determining the fault characteristic with the highest fault occurrence rate as the fault characteristic matched with the terminal fault information.
According to an embodiment of the present application, when the local matching is successful, the method further includes: and uploading the terminal type, the fault occurrence time and the fault type to a cloud so as to record the fault event.
According to an embodiment of the present application, when the remote matching fails, the method further includes: and inputting the terminal fault information as a new fault into the remote fault feature library through a cloud.
According to one embodiment of the application, the fault characteristics contained in the remote fault characteristic library are obtained by performing characteristic extraction on the drive fault data, the vulnerability fault data, the system fault data and the hardware fault data of all deployed types of power acquisition terminals.
According to an embodiment of the application, when the power acquisition terminal is first connected to the cloud, the method further includes: and receiving the local fault feature library issued by the cloud and configuring.
According to an embodiment of the application, the method further comprises: when the electric power acquisition terminal cannot be connected with the cloud end, the electric power acquisition terminal is connected with the fault diagnosis device through establishment, so that the electric power acquisition terminal is connected with the cloud end through the fault diagnosis device.
To achieve the above object, a second aspect of the present application provides a computer-readable storage medium, on which a fault diagnosis program of a power collection terminal is stored, the fault diagnosis program of the power collection terminal, when executed by a processor, implementing a fault diagnosis method of the power collection terminal as in the above embodiments.
In order to achieve the above object, an embodiment of a third aspect of the present application provides an electric power collection terminal, including a memory, a processor, and a fault diagnosis program of the electric power collection terminal, where the fault diagnosis program of the electric power collection terminal is stored in the memory and is executable on the processor, and when the processor executes the fault diagnosis program of the electric power collection terminal, the fault diagnosis method of the electric power collection terminal in the above embodiment is implemented.
To achieve the above object, a fourth aspect of the present application provides a fault diagnosis system for a power collection terminal, including: the system comprises a power acquisition terminal, fault diagnosis equipment and a cloud end; the power acquisition terminal is used for locally matching the acquired terminal fault information with fault features in a local fault feature library, and if the local matching is successful, identifying the terminal fault information according to the fault features in the local fault feature library to determine the fault type; if the local matching fails, uploading the terminal fault information to the cloud; the fault diagnosis equipment is used for establishing connection between the fault diagnosis equipment and the electric power acquisition terminal when the electric power acquisition terminal cannot be connected with the cloud end, so that the electric power acquisition terminal is connected with the cloud end through the fault diagnosis equipment; the cloud end is used for carrying out remote matching on the terminal fault information through fault characteristics in a configured remote fault characteristic library, identifying the terminal fault information according to the fault characteristics in the remote fault characteristic library when the remote matching is successful, and determining the fault type of the power acquisition terminal, wherein the remote fault characteristic library contains the fault characteristics which are not contained in the local fault characteristic library.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
Fig. 1 is a schematic flowchart of a fault diagnosis method of a power collection terminal according to an embodiment of the present application.
Fig. 2 is a schematic flow chart of a fault diagnosis method of a power collection terminal according to another embodiment of the present application.
Fig. 3 is a block diagram of a power collection terminal according to an embodiment of the present application.
Fig. 4 is a block diagram of a fault diagnosis system of a power collection terminal according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
A fault diagnosis method, a storage medium, a power collection terminal, and a fault diagnosis system of the embodiments of the present application are described below with reference to the drawings.
As shown in fig. 1 and 2, the fault diagnosis method of the power collecting terminal in the embodiment of the present application includes the following steps 100 to 300.
And S100, locally matching the acquired terminal fault information with fault characteristics in a local fault characteristic library of the terminal.
The power collection terminal 10 (terminal for short) is mainly used for reading electric energy data of a target object, and for example, an intelligent electric meter belongs to a power collection terminal. Usually, a plurality of power collection terminals 10 may be networked via a local area network, so as to upload regional power data. Since the power collecting terminal is the subject of diagnosis, the power collecting terminal 10 is a side terminal. Each power collection terminal 10 has a self-checking function, and when a fault occurs in the power collection terminal 10, the power collection terminal 10 determines that the fault occurs by itself through the self-checking function, and then starts a fault diagnosis process.
In the fault diagnosis process, local matching of faults is performed first. The power collecting terminal 10 collects and acquires fault information through a self-checking function or other configured functions, for example, collecting input/output states of a core circuit, on/off states between circuit modules, readings of a sensor for detecting whether a case is damaged, current values of key variables in a software program, and the like, thereby obtaining terminal fault information.
The power collecting terminal 10 is usually configured with a local fault feature library in advance, for example, the local fault feature library is deployed in a storage module of the power collecting terminal 10. The local fault feature library includes fault features of a plurality of common faults, that is, fault features of faults with a high daily occurrence probability, and therefore the local fault feature library is also called a common fault feature library. Assuming that the power supply fault of the lithium battery belongs to a common fault, the fault characteristic f1 corresponding to the common fault is as follows: if the input voltage to the power supply circuit is below the set point, the local fault signature library will store the f1 fault signature. Other common faults and their corresponding fault signatures work similarly.
After the power acquisition terminal 10 acquires the fault information of itself, the fault information is compared with each fault feature in the local fault feature library one by one. The comparison process occurs inside the power collection terminal 10, and the fault information does not need to be uploaded to other devices for comparison, so the comparison process is called local matching, and the comparison method specifically includes comparing the values/states of the information items included in the fault information with the values/states of the information items in the fault characteristics, and determining whether the fault characteristics currently participating in the comparison are matched with the fault information according to the comparison result of the information items.
It will be appreciated that for a certain power harvesting terminal t1, the fault signatures entered in the local fault signature library configured within the terminal t1 may each match the model of the terminal t 1. Because the models of the power acquisition terminals can be various, the feature library in the terminals with different models can only store fault features which can be generated by the terminals with the self models, namely the input fault features are all the fault features consistent with software and hardware information of the terminals with the self models, and the unique fault features of other models do not need to be stored, so that the requirement on storage space can be reduced, the probability of matching errors during local matching is reduced, and the efficiency of the local matching process is improved.
And S200, if the local matching is successful, identifying the terminal fault information according to the fault characteristics in the local fault characteristic library, and determining the fault type of the power acquisition terminal 10.
In the comparison process of the fault information and the fault characteristics, if the fault characteristics consistent with the fault information are found, the fact that the fault characteristics consistent with the current fault condition are stored in the local fault characteristic library is indicated, and therefore the local matching is judged to be successful. At this time, a fault feature consistent with the current fault condition is identified, and each fault feature in the local fault feature library corresponds to a corresponding fault type, where the fault feature represents a fault type of the power acquisition terminal 10, for example, if the fault feature f1 is successfully matched with the terminal fault information, it indicates that the fault type of the power acquisition terminal 10 is: and (5) power supply failure of the lithium battery.
After the local matching is successful, the fault type of the current fault of the power acquisition terminal 10 is obtained, so that the terminal can be directly repaired and reported according to the fault type without remote matching, the diagnosis efficiency is improved, the network data throughput is reduced, and the occupation of cloud resources is also reduced.
S300, as shown in fig. 2, if the local matching fails, uploading the terminal fault information to the cloud 20, so as to perform remote matching on the terminal fault information through the fault features configured in the remote fault feature library of the cloud 20, and when the remote matching is successful, identifying the terminal fault information according to the fault features in the remote fault feature library, and determining the fault type of the power acquisition terminal 10, where the remote fault feature library includes fault features that are not included in the local fault feature library.
In the comparison process of the fault information and the fault characteristics, if all the fault characteristics in the local fault characteristic library are completely inconsistent with the terminal fault information of the power acquisition terminal 10, it indicates that the current fault type of the power acquisition terminal 10 is not a common fault type deployed in the local fault characteristic library, and the fault type cannot be identified locally in the terminal, and at this time, the cloud 20 is used for performing remote matching and identification.
Specifically, after the local matching fails, the power collection terminal 10 uploads the fault information to the cloud 20, that is, the cloud platform. The cloud platform is pre-configured with a remote fault signature library, for example, the remote fault signature library is deployed in a server of the cloud platform. The remote fault feature library also contains fault features of multiple faults, and the remote fault feature library at least contains fault features not contained in multiple local fault feature libraries, for example, the remote fault feature library contains fault features belonging to very common faults, that is, fault features of faults with low daily occurrence probability or fault features of complex faults, so as to form complementation with the fault diagnosis range of the local fault feature library, and thus, not only can the faults be ensured to be diagnosed and identified at any end of the local or cloud end 20, but also the fault comparison frequency in the remote matching process can be reduced, and the matching efficiency is improved. Assuming the terminal metered fault is an uncommon fault that corresponds to a fault signature f2, the remote fault signature library will store f2 fault signatures. Other unusual fault signatures and their corresponding fault signatures work similarly.
After the cloud 20 receives the fault information sent by the terminal, the fault information is compared with each fault feature in the remote fault feature library one by one. The comparison process occurs in the cloud 20, so the comparison process is called remote matching, and the comparison manner may also be that the values/states of the information items included in the fault information and the values/states of the information items in the fault feature are respectively compared, and whether the fault feature currently participating in the comparison is matched with the fault information is determined according to the comparison result of the information items. If the fault characteristics consistent with the fault information are found, the remote fault characteristics consistent with the current fault condition are stored in the remote fault characteristics database, and therefore the remote matching is judged to be successful.
It can be understood that, for the cloud terminal 20, the fault features recorded in the remote fault feature library configured in the cloud terminal 20 may include fault features of terminals of all models, so that when the fault information is uploaded by the power acquisition terminal 10 of any model, the fault type of the terminal of the model can be correspondingly determined, and the fault diagnosis success rate is increased.
As a possible implementation manner, the fault features included in the remote fault feature library are obtained by performing feature extraction on the drive fault data, the bug fault data, the system fault data, and the hardware fault data of all the deployed models of the power acquisition terminals 10. Specifically, as shown in fig. 2, the fault diagnosis method further includes step 99. And S99, extracting the characteristics of the drive fault data, the leak fault data, the system fault data and the hardware fault data of the power acquisition terminals 10 of all models to obtain fault characteristics, constructing a remote fault characteristic library based on the obtained fault characteristics, and storing the remote fault characteristic library to the cloud 20 after constructing the remote fault characteristic library.
The fault information uploaded to the cloud 20 by the power acquisition terminal 10 may include a terminal type, and therefore, in the process of performing remote matching by the cloud 20, fault features of the same type as the terminal type in the fault information may be screened out first, and then remote matching is performed based on the screened fault features.
In addition, the remote fault feature library may also include fault features of common faults and fault features of uncommon faults, that is, all fault features of all models of terminals that may generate faults, and the remote fault feature library in this case may be referred to as a full fault feature library. By adopting the full fault feature library, when the fault features which are matched successfully are not matched correctly in the local matching process, the error can be made up through the remote fault feature library, and the stable operation of the terminal is kept. In the remote matching process, remote matching is performed on the basis of the fault characteristics of the unusual faults, and if the fault characteristics completely consistent with the uploaded terminal fault information are matched at the moment, remote matching is not required to be performed on the basis of the fault characteristics of the common faults, so that the matching efficiency is improved.
After the remote matching is successful, the fault type of the current fault of the power acquisition terminal 10 uploading the fault information is obtained, so that the power acquisition terminal 10 uploading the fault information can be repaired and recorded according to the fault type.
According to the fault diagnosis method of the power acquisition terminal 10 provided by the embodiment of the application, fault diagnosis is performed in a cloud and terminal cooperation mode, and fault diagnosis of the power acquisition terminal 10 is performed in a mode of automatically matching fault information with fault characteristics, so that influence caused by subjective randomness is eliminated; meanwhile, the diagnosis process is divided into local diagnosis and remote diagnosis, a common fault feature library is pre-deployed locally at the edge, local identification and matching are carried out on common faults by utilizing the local diagnosis, the fault diagnosis efficiency is improved depending on the condition of the existing hardware resources, and only when the generated faults cannot be diagnosed through the local common fault feature library, the cloud-end-deployed feature library containing the unusual fault features is utilized for carrying out cloud-end remote fault identification and matching, so that the data throughput is reduced, the dependence on network channels is reduced, network paralysis is avoided, and the stable operation of the terminal is ensured.
In some embodiments, when the failed power collection terminal 10 is not configured with a local fault signature library, the local matching is performed based on the local fault signature libraries configured in other power collection terminals 10 of the same type that are located in the same local area network as the failed power collection terminal 10.
There may be some power harvesting terminals 10 that do not have a local fault signature library deployed due to repair, replacement of the terminal, or other reasons. When the power acquisition terminals 10 which are not deployed with the local fault feature library have faults, local matching cannot be performed through the power acquisition terminals 10, and local matching can be achieved through other power acquisition terminals 10. Specifically, the power acquisition terminals 10 may be connected to each other through a local area network, one local area network may be connected to a plurality of power acquisition terminals 10, and all the power acquisition terminals 10 in the local area network communicate with the outside through the local area network and receive and transmit information. When the power acquisition terminal t2 without the local fault feature library is in fault, the terminal t2 may communicate with the terminal t3 located in the same local area network through the local area network, the terminal t3 and the terminal t2 are power acquisition terminals of the same model, through communication with the terminal t3, the local fault feature library deployed in the terminal t3 is used for local matching of the terminal t2, for example, the terminal fault information of the terminal t2 is sent to the terminal t3, after the local matching is completed, the matching result is fed back to the terminal t2, if the local matching is successful, the fault type of the terminal t2 is determined, if the local matching is failed, the terminal t2 continues to perform remote matching, so that local matching can be performed even when the terminal with the fault is not configured with the local fault feature library, and the matching efficiency and cloud resources which cannot be occupied are also not lost.
In some embodiments, the local matching and the remote matching have the same matching mode, wherein the matching mode includes: and respectively calculating the similarity between the terminal fault information and each fault feature, if at least one similarity not lower than a set threshold exists, determining that the matching is successful, and if all the similarities are lower than the set threshold, determining that the matching is failed.
The local matching and the remote matching can both adopt a matching algorithm based on the fault feature similarity to carry out feature matching, or only the local matching adopts the matching algorithm based on the fault feature similarity to carry out the feature matching, or only the remote matching adopts the matching algorithm based on the fault feature similarity to carry out the feature matching.
The similarity between the terminal fault information and the fault characteristics can be obtained by calculation through a data analysis algorithm. And after the similarity calculation is completed and the similarity which is the same as the fault feature quantity of the feature library is obtained, sequentially comparing all the similarity data with a set threshold value. The set threshold s is a criterion for determining whether the fault feature matches the terminal fault information, and a value of the set threshold s may be set in advance, for example, to 0.8, and the similarity is located in the interval of [0,1 ]. If the similarity corresponding to a certain fault characteristic f0 is not lower than the set threshold s, the matching is considered to be successful, and the fault type corresponding to the fault characteristic f0 is determined to be the fault type of the power acquisition terminal 10 which has a fault. However, the similarity corresponding to all the fault features is lower than the set threshold s, which indicates that the feature library does not include the same type of fault content as the fault occurring in the power collecting terminal 10, and therefore, the matching is considered to be failed. The matching mode can be only applied to local matching or remote matching, and can be applied to both local matching and remote matching.
As a possible implementation manner, the fault diagnosis method may further include: and if a plurality of fault characteristics which are not lower than the set threshold value s exist, determining the fault characteristic with the highest fault occurrence rate as the fault characteristic matched with the terminal fault information.
Because there are multiple fault types, and the fault signatures of different fault types may be similar, especially between the fault signatures corresponding to the same model of power collection terminal 10. Therefore, in the process of local matching or remote matching, more than one similarity value not lower than the set threshold s may occur. If this occurs in the local matching process, a final similarity value is selected from the similarity values satisfying the set threshold s by using the statistical data about the occurrence rate of each fault feature stored in advance in the power collection terminal 10, and the selected criterion is to compare which similarity value among the similarity values satisfying the set threshold s corresponds to the highest occurrence rate of the fault feature.
For example, in the local matching process, if the similarity values of the fault signatures f6, f19, and f42 are all higher than the set threshold s, the power collection terminal 10 acquires the occurrence rates of the fault signatures f6, f19, and f42 from the fault occurrence rate statistical table, and finds that the fault occurrence rate of the fault signature f42 is the highest, so that the fault signature f42 is taken as a fault signature successfully matched with the terminal fault information. If the fault type corresponding to the fault feature f42 is a display screen backlight fault, determining that the fault type of the power acquisition terminal 10 is the display screen backlight fault.
In some embodiments, when the local matching is successful, the fault diagnosis method may further include: the terminal type, the time of occurrence of the fault, and the fault type are uploaded to the cloud 20 to record the fault event. After each fault occurs and the local diagnosis of the fault is successful, the information related to the fault is recorded, so that statistics and analysis of data such as fault occurrence rate of common faults are facilitated, and the maintenance of the power acquisition terminal 10 is facilitated. It is understood that when the remote diagnosis is successful, the information related to the fault may also be recorded, so as to perform statistics and analysis on data such as the fault occurrence rate of the unusual fault and the complex fault, and also facilitate the maintenance of the power collecting terminal 10.
In some embodiments, when the remote matching fails, the fault diagnosis method may further include: and inputting the terminal fault information as a new fault into a remote fault feature library through the cloud 20.
When the remote matching fails, it is indicated that neither the local fault feature library nor the remote fault feature library contains the fault type of the current fault of the power acquisition terminal 10, that is, the current fault of the power acquisition terminal 10 is a new fault which has not occurred in the past or a new fault which has occurred but has not been entered into the fault feature library, so that the terminal fault information can be entered into the remote fault feature library to perfect the fault feature library and ensure the successful diagnosis when similar faults are repeated. If the new fault occurs frequently, the terminal fault information can be recorded into a local fault feature library as a common fault.
In some embodiments, when the power collecting terminal 10 first accesses the cloud 20, the fault diagnosis method may further include: and receiving and configuring the local fault feature library issued by the cloud 20.
When the power acquisition terminal 10 is first accessed to a power acquisition network, the cloud 20 acquires hardware information of the power acquisition terminal 10 and records the hardware information, and detects whether the power acquisition terminal 10 or other terminals in the same local area network are configured with a local fault feature library corresponding to the terminal model, if the power acquisition terminal 10 is not configured with the local fault feature library, the cloud 20 issues the corresponding local fault feature library to the power acquisition terminal 10 which is first accessed to the power acquisition network and other terminals in the same local area network which are not configured with the local fault feature library, and the power acquisition terminal 10 stores the local fault feature library after receiving the local fault feature library, so that the configuration rate of the local fault feature library of the power acquisition terminal 10 is improved, and local matching is facilitated.
In some embodiments, as shown in fig. 2, the fault diagnosis method may further include the following step 301.
S301, when the power collection terminal 10 cannot be connected to the cloud 20, the power collection terminal 10 is connected to the cloud 20 through the fault diagnosis device 30 by establishing a connection between the power collection terminal 10 and the fault diagnosis device 30.
If the power acquisition terminal 10 fails to communicate with the cloud 20 due to a fault, the terminal is in an off-line state, and at this time, the fault diagnosis device 30 can be used as a signal transfer device for the power acquisition terminal and the cloud, so that communication connection between the power acquisition terminal and the cloud is realized. Specifically, the fault diagnosis device 30 may be a handheld type, when the power collection terminal 10 is disconnected from the cloud 20, an alarm signal may be sent, the maintenance staff holds the fault diagnosis device 30 to reach the site of the power collection terminal 10, the connection with the power collection terminal 10 is established in a serial port, network, or bluetooth manner, and forwards fault information that the power collection terminal 10 needs to be uploaded to the cloud 20 through the fault diagnosis device 30, analyzes a fault cause that cannot be connected between the power collection terminal 10 and the cloud 20 through the fault diagnosis device 30, and forwards data that the cloud 20 issues to the power collection terminal 10 through the fault diagnosis device 30.
In addition, an embodiment of the present application also provides a computer-readable storage medium on which a fault diagnosis program of a power collection terminal is stored, which when executed by a processor, implements the fault diagnosis method of the power collection terminal as in the above-described embodiment.
According to the computer-readable storage medium provided by the embodiment of the application, the processor executes the fault diagnosis program of the power acquisition terminal stored on the storage medium, the fault diagnosis is carried out in a cloud terminal and terminal cooperation mode, and the fault diagnosis of the power acquisition terminal is carried out in a mode of automatically matching fault information with fault characteristics, so that the influence caused by subjective randomness is eliminated; meanwhile, the diagnosis process is divided into local diagnosis and remote diagnosis, a common fault feature library is pre-deployed locally at the edge, local identification and matching are carried out on common faults by utilizing the local diagnosis, the fault diagnosis efficiency is improved depending on the condition of the existing hardware resources, and only when the generated faults cannot be diagnosed through the local common fault feature library, the cloud-end-deployed feature library containing the unusual fault features is utilized for carrying out cloud-end remote fault identification and matching, so that the data throughput is reduced, the dependence on network channels is reduced, network paralysis is avoided, and the stable operation of the terminal is ensured.
In addition, as shown in fig. 3, an embodiment of the present application further provides an electric power collection terminal 10, which includes a memory 11, a processor 12, and a fault diagnosis program of the electric power collection terminal that is stored on the memory 11 and is operable on the processor 12, and when the processor 12 executes the fault diagnosis program of the electric power collection terminal, the fault diagnosis method of the electric power collection terminal in the above embodiment is implemented.
According to the power acquisition terminal 10 provided by the embodiment of the application, the processor 12 executes the fault diagnosis program stored in the memory 11, the fault diagnosis is performed in a cloud terminal and terminal cooperation mode, and the fault diagnosis of the power acquisition terminal is performed in a mode of automatically matching fault information with fault characteristics, so that the influence caused by subjective randomness is eliminated; meanwhile, the diagnosis process is divided into local diagnosis and remote diagnosis, a common fault feature library is pre-deployed locally at the edge, local identification and matching are carried out on common faults by utilizing the local diagnosis, the fault diagnosis efficiency is improved depending on the condition of the existing hardware resources, and only when the generated faults cannot be diagnosed through the local common fault feature library, the cloud-end-deployed feature library containing the unusual fault features is utilized for carrying out cloud-end remote fault identification and matching, so that the data throughput is reduced, the dependence on network channels is reduced, network paralysis is avoided, and the stable operation of the terminal is ensured.
In addition, as shown in fig. 4, an embodiment of the present application further provides a fault diagnosis system 1 of an electric power collection terminal 10, where the fault diagnosis system 1 includes the electric power collection terminal 10, a cloud 20, and a fault diagnosis device 30.
The power acquisition terminal 10 is configured to locally match the acquired terminal fault information with fault features in a local fault feature library, and if the local matching is successful, identify the terminal fault information according to the fault features in the local fault feature library to determine a fault type; and if the local matching fails, uploading the terminal fault information to the cloud.
The cloud 20 is configured to perform remote matching on the terminal fault information through the fault features in the configured remote fault feature library, and identify the terminal fault information according to the fault features in the remote fault feature library when the remote matching is successful, so as to determine the fault type of the power acquisition terminal, where the remote fault feature library includes fault features that are not included in the local fault feature library.
The fault diagnosis device 30 is configured to establish a connection between itself and the power collection terminal 10 when the power collection terminal 10 cannot be connected to the cloud 20, so that the power collection terminal 10 is connected to the cloud 20 by itself. Specifically, the connection between the fault diagnosis device 30 and the power acquisition terminal 10 may be established in a serial port, a network, or a bluetooth manner, the fault information that needs to be uploaded to the cloud terminal 20 of the power acquisition terminal 10 is forwarded through the fault diagnosis device 30, the fault reason that the power acquisition terminal 10 and the cloud terminal 20 cannot be connected is analyzed through the fault diagnosis device 30, and the data that is issued to the power acquisition terminal 10 by the cloud terminal 20 is forwarded through the fault diagnosis device 30.
According to the fault diagnosis system of the power acquisition terminal, fault diagnosis is carried out in a mode of cooperation of a cloud end and the terminal, and fault diagnosis of the power acquisition terminal is carried out in a mode of automatically matching fault information with fault characteristics, so that influence caused by subjective randomness is eliminated; meanwhile, the diagnosis process is divided into local diagnosis and remote diagnosis, a common fault feature library is pre-deployed locally at the edge, local identification and matching are carried out on common faults by utilizing the local diagnosis, the fault diagnosis efficiency is improved depending on the condition of the existing hardware resources, and only when the generated faults cannot be diagnosed through the local common fault feature library, the cloud-end-deployed feature library containing the unusual fault features is utilized for carrying out cloud-end remote fault identification and matching, so that the data throughput is reduced, the dependence on network channels is reduced, network paralysis is avoided, and the stable operation of the terminal is ensured.
In some embodiments, when the failed power acquisition terminal is not configured with the local fault feature library, the local matching is performed based on the local fault feature library configured in other power acquisition terminals of the same type in the same local area network as the failed power acquisition terminal.
In some embodiments, the local matching and the remote matching have the same matching mode, wherein the matching mode includes: respectively calculating the similarity between the terminal fault information and each fault characteristic; if at least one similarity not lower than a set threshold exists, determining that the matching is successful; and if all the similarity degrees are lower than the set threshold value, determining that the matching fails.
In some embodiments, if there are a plurality of successfully matched fault signatures, the fault signature with the highest fault occurrence rate is determined as the fault signature matched with the terminal fault information.
In some embodiments, when the local matching is successful, the power collecting terminal 10 uploads the terminal type, the fault occurrence time and the fault type to the cloud 20 to record the fault event.
In some embodiments, upon a remote matching failure, the terminal fault information is entered as a new fault into the remote fault signature library through the cloud 20.
In some embodiments, the fault features included in the remote fault feature library are obtained by performing feature extraction on the drive fault data, the bug fault data, the system fault data and the hardware fault data of all the models of the power collection terminals 10 that are deployed.
In some embodiments, when the power collection terminal 10 first accesses the cloud 20, the power collection terminal 10 receives the local fault feature library issued by the cloud 20 and performs configuration.
It should be noted that the logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus, the electronic device, and the computer-readable storage medium embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and in relation to the description, reference may be made to some portions of the description of the method embodiments.
The above description is only for the preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application are included in the protection scope of the present application.
Claims (12)
1. A fault diagnosis method of a power acquisition terminal is characterized by comprising the following steps:
locally matching the acquired terminal fault information with fault characteristics in a local fault characteristic library of the terminal;
if the local matching is successful, identifying the terminal fault information according to the fault characteristics in the local fault characteristic library, and determining the fault type of the power acquisition terminal;
if the local matching fails, the terminal fault information is uploaded to a cloud end so that the terminal fault information can be remotely matched through fault features configured in a remote fault feature library of the cloud end, the terminal fault information is identified according to the fault features in the remote fault feature library when the remote matching is successful, and the fault type of the power acquisition terminal is determined, wherein the remote fault feature library contains the fault features which are not contained in the local fault feature library.
2. The fault diagnosis method according to claim 1, wherein when the power collection terminal with the fault is not configured with the local fault feature library, the local matching is performed based on the local fault feature library configured in other power collection terminals of the same type in the same local area network as the power collection terminal with the fault.
3. The fault diagnosis method according to claim 1, wherein the local matching and the remote matching are matched in the same manner, wherein the matching manner comprises:
respectively calculating the similarity between the terminal fault information and each fault feature;
if at least one similarity not lower than a set threshold exists, determining that the matching is successful;
and if all the similarity degrees are lower than the set threshold value, determining that the matching fails.
4. The fault diagnosis method according to claim 3, characterized in that the method further comprises:
and if the successfully matched fault characteristics are multiple, determining the fault characteristic with the highest fault occurrence rate as the fault characteristic matched with the terminal fault information.
5. The fault diagnosis method according to claim 1, characterized in that, when the local matching is successful, the method further comprises:
and uploading the terminal type, the fault occurrence time and the fault type to a cloud so as to record the fault event.
6. The fault diagnosis method according to claim 1, characterized in that, when remote matching fails, the method further comprises:
and inputting the terminal fault information as a new fault into the remote fault feature library through a cloud.
7. The fault diagnosis method according to claim 1, wherein the fault features contained in the remote fault feature library are obtained by performing feature extraction on drive fault data, bug fault data, system fault data and hardware fault data of all deployed models of power acquisition terminals.
8. The fault diagnosis method according to claim 1, wherein when the power collection terminal is first connected to a cloud, the method further comprises:
and receiving the local fault feature library issued by the cloud and configuring.
9. The fault diagnosis method according to claim 1, characterized in that the method further comprises:
when the electric power acquisition terminal cannot be connected with the cloud end, the electric power acquisition terminal is connected with the fault diagnosis device through establishment, so that the electric power acquisition terminal is connected with the cloud end through the fault diagnosis device.
10. A computer-readable storage medium, characterized in that a fault diagnosis program of an electric power collection terminal is stored thereon, which when executed by a processor implements the fault diagnosis method of the electric power collection terminal according to any one of claims 1 to 9.
11. An electric power collection terminal, comprising a memory, a processor, and a fault diagnosis program of the electric power collection terminal stored on the memory and operable on the processor, wherein the processor implements the fault diagnosis method of the electric power collection terminal according to any one of claims 1 to 9 when executing the fault diagnosis program of the electric power collection terminal.
12. A fault diagnosis system of a power collecting terminal, characterized by comprising: the system comprises a power acquisition terminal, fault diagnosis equipment and a cloud end; wherein,
the power acquisition terminal is used for locally matching the acquired terminal fault information with fault characteristics in a local fault characteristic library, and if the local matching is successful, identifying the terminal fault information according to the fault characteristics in the local fault characteristic library to determine the fault type; if the local matching fails, uploading the terminal fault information to the cloud;
the fault diagnosis equipment is used for establishing connection between the fault diagnosis equipment and the electric power acquisition terminal when the electric power acquisition terminal cannot be connected with the cloud end, so that the electric power acquisition terminal is connected with the cloud end through the fault diagnosis equipment;
the cloud end is used for carrying out remote matching on the terminal fault information through fault characteristics in a configured remote fault characteristic library, identifying the terminal fault information according to the fault characteristics in the remote fault characteristic library when the remote matching is successful, and determining the fault type of the power acquisition terminal, wherein the remote fault characteristic library contains the fault characteristics which are not contained in the local fault characteristic library.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210440509.2A CN114878960A (en) | 2022-04-25 | 2022-04-25 | Fault diagnosis method, storage medium, power acquisition terminal, and fault diagnosis system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210440509.2A CN114878960A (en) | 2022-04-25 | 2022-04-25 | Fault diagnosis method, storage medium, power acquisition terminal, and fault diagnosis system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114878960A true CN114878960A (en) | 2022-08-09 |
Family
ID=82672247
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210440509.2A Pending CN114878960A (en) | 2022-04-25 | 2022-04-25 | Fault diagnosis method, storage medium, power acquisition terminal, and fault diagnosis system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114878960A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115901752A (en) * | 2022-11-03 | 2023-04-04 | 重庆忽米网络科技有限公司 | Metal spark component detection system based on industrial internet technology |
| CN117825973A (en) * | 2024-03-01 | 2024-04-05 | 深圳市健网科技有限公司 | Lithium battery state estimation method and system for distributed energy storage system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1997015009A1 (en) * | 1995-10-18 | 1997-04-24 | Systemsoft Corporation | System and method for digital data processor diagnostics |
| CN103019232A (en) * | 2012-12-18 | 2013-04-03 | 天津清源电动车辆有限责任公司 | Fault diagnosis system for automobiles |
| CN108090567A (en) * | 2018-01-19 | 2018-05-29 | 国家电网公司 | Power communication system method for diagnosing faults and device |
| CN108896320A (en) * | 2018-07-10 | 2018-11-27 | 商丘师范学院 | A kind of system and method for realizing vehicle abnormality monitoring, fault diagnosis and data upgrading |
| CN113033889A (en) * | 2021-03-19 | 2021-06-25 | 国网河北省电力有限公司邢台供电分公司 | High-voltage transmission line fault prediction method and device and terminal equipment |
-
2022
- 2022-04-25 CN CN202210440509.2A patent/CN114878960A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1997015009A1 (en) * | 1995-10-18 | 1997-04-24 | Systemsoft Corporation | System and method for digital data processor diagnostics |
| CN103019232A (en) * | 2012-12-18 | 2013-04-03 | 天津清源电动车辆有限责任公司 | Fault diagnosis system for automobiles |
| CN108090567A (en) * | 2018-01-19 | 2018-05-29 | 国家电网公司 | Power communication system method for diagnosing faults and device |
| CN108896320A (en) * | 2018-07-10 | 2018-11-27 | 商丘师范学院 | A kind of system and method for realizing vehicle abnormality monitoring, fault diagnosis and data upgrading |
| CN113033889A (en) * | 2021-03-19 | 2021-06-25 | 国网河北省电力有限公司邢台供电分公司 | High-voltage transmission line fault prediction method and device and terminal equipment |
Non-Patent Citations (2)
| Title |
|---|
| 孔莲芳 等: "基于B/S模式设备远程监测诊断系统的研究", 《制造业自动化》, vol. 25, no. 11, 30 November 2003 (2003-11-30), pages 41 - 44 * |
| 宋丹 等: "数控机床远程智能故障诊断系统设计", 《数据采集与处理》, vol. 35, no. 1, 31 December 2020 (2020-12-31), pages 173 - 180 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115901752A (en) * | 2022-11-03 | 2023-04-04 | 重庆忽米网络科技有限公司 | Metal spark component detection system based on industrial internet technology |
| CN115901752B (en) * | 2022-11-03 | 2023-11-14 | 重庆忽米网络科技有限公司 | Metal spark composition detection system based on industrial Internet technology |
| CN117825973A (en) * | 2024-03-01 | 2024-04-05 | 深圳市健网科技有限公司 | Lithium battery state estimation method and system for distributed energy storage system |
| CN117825973B (en) * | 2024-03-01 | 2024-05-17 | 深圳市健网科技有限公司 | Lithium battery state estimation method and system for distributed energy storage system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114878960A (en) | Fault diagnosis method, storage medium, power acquisition terminal, and fault diagnosis system | |
| CN107479540B (en) | Method for diagnosing faults and system | |
| CN110308385A (en) | A kind of PCBA Online Transaction Processing and method | |
| CN107483283B (en) | Communication reliability test method and device | |
| CN116360377B (en) | Data processing method for battery cell formation component capacity and distributed control system | |
| CN117289085A (en) | Multi-line fault analysis and diagnosis method and system | |
| CN111856299A (en) | Method, device and equipment for determining power supply state | |
| CN114722310B (en) | Photovoltaic power station equipment fault diagnosis method, device, equipment and medium | |
| CN112803581B (en) | Intelligent power supply control method, system and device for low-voltage contact cabinet | |
| CN116859246B (en) | Automatic identification method and system for battery cells | |
| CN113591951A (en) | Remote operation and maintenance method and system for smart television | |
| CN116881818A (en) | New energy vehicle power exchange station fault processing method and power exchange station | |
| US20220268843A1 (en) | Battery analysis apparatus and method | |
| CN113328898B (en) | Fault diagnosis method and system with autonomous learning capability | |
| CN113626236B (en) | Fault diagnosis method, device, equipment and medium for distributed file system | |
| CN115827318A (en) | Data center exception handling method and device, electronic equipment and medium | |
| CN114629785B (en) | Alarm position detection and prediction method, device, equipment and medium | |
| CN113408014A (en) | Terminal equipment identification system and method thereof | |
| CN117289143B (en) | Fault prediction method, device, equipment, system and medium | |
| CN116416083B (en) | Battery management method, device, electronic equipment and storage medium | |
| CN117289144B (en) | Fault positioning method, device, equipment, system and medium | |
| CN115789859B (en) | Air conditioner fault diagnosis method, terminal and system | |
| CN118051043A (en) | Whole vehicle detection method, device, equipment and storage medium | |
| CN108960646B (en) | Smart power grid acquisition terminal monitoring method and system | |
| CN117538771A (en) | Battery pack detection method and vehicle |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |