CN112148733A - Method, device, electronic device and computer readable medium for determining fault type - Google Patents
Method, device, electronic device and computer readable medium for determining fault type Download PDFInfo
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Abstract
The application provides a method, a device, an electronic device and a computer readable medium for determining fault types, and belongs to the technical field of fault positioning. The method comprises the steps of obtaining a data parameter of target data in target equipment and a parameter threshold of the data parameter, wherein the data parameter and the parameter threshold have the same source identification; under the condition that the data parameter does not exceed the parameter threshold, acquiring a fault association relation, wherein the fault association relation comprises an association relation between a first parameter range and a fault type; and searching a first parameter range containing the data parameters in the fault association relation, and taking the fault type corresponding to the first parameter range as a target fault type of the target data. The method and the device can achieve early warning on the fault of the target equipment.
Description
Technical Field
The present application relates to the field of fault location technologies, and in particular, to a method, an apparatus, an electronic apparatus, and a computer-readable medium for determining a fault type.
Background
With the development of the automation industry, many industries produce and process products through automation equipment, and if the equipment fails, especially the production line equipment, great economic loss is brought to factories, so that the equipment needs to be subjected to fault detection.
The current fault detection method mainly comprises manual detection, data comparison detection and machine learning detection, but the detection methods are all detection which is carried out after the machine is determined to be in fault, so that only the loss of a factory caused by the machine fault can be reduced, the fault cannot be eliminated in advance, and the loss is avoided.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method, an apparatus, an electronic apparatus, and a computer-readable medium for determining a fault type, so as to solve the problem of early troubleshooting. The specific technical scheme is as follows:
in a first aspect, the present application provides a method for determining a target fault type, where the method includes:
acquiring a data parameter of target data in target equipment and a parameter threshold of the data parameter, wherein the data parameter and the parameter threshold have the same source identifier;
under the condition that the data parameter does not exceed the parameter threshold, acquiring a fault association relation, wherein the fault association relation comprises an association relation between a first parameter range and a fault type;
and searching a first parameter range containing the data parameters in the fault association relation, and taking the fault type corresponding to the first parameter range as a target fault type of the target data.
Optionally, before obtaining the fault association relationship, the method further includes:
acquiring fault type records and historical data from a database;
determining the fault type in the fault type record and a first parameter range of the data parameters in the historical data;
and establishing a fault association relation between the fault type and the first parameter range through data mining operation.
Optionally, after acquiring the data parameter of the target data in the target device, the method further includes: storing the target data in the database;
the method further comprises the following steps: under the condition that the target equipment is not predicted to have faults, determining the fault moment when the faults occur, and determining the fault type of the target equipment; acquiring a second parameter range of the fault moment from the database; and updating the associated parameters in the fault association relationship according to the fault type and the second parameter range.
Optionally, the determining the fault type of the target device includes:
determining a fault parameter of the target device at the fault moment;
and determining the fault type of the target equipment according to the fault parameters.
Optionally, before the obtaining of the data parameter of the target data in the target device, the method further includes:
acquiring first data and a source category of the first data;
and if the source category of the first data is a target category, taking the first data as the target data.
Optionally, before the acquiring the first data, the method further includes:
controlling the acquisition equipment to send the acquired plurality of first data to a message queue;
and sequentially reading the first data from the message queue according to the time sequence.
Optionally, after acquiring the data parameter of the target data in the target device and the parameter threshold of the data parameter, the method further includes:
determining the target data as fault data under the condition that the data parameter of the target data exceeds the parameter threshold;
storing the fault data in the database.
Optionally, the databases include a first database and a second database, where the first database is used for data storage and the second database is used for data query; the obtaining of the fault type record and the historical data from the database includes: acquiring a fault type record and historical data from the first database;
after the establishing the association relationship between the first parameter range and the fault type through the data mining operation, the method further includes: storing the association in the second database.
In a second aspect, the present application provides an apparatus for determining a target fault type, the apparatus comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a data parameter of target data in target equipment and a parameter threshold of the data parameter, and the data parameter and the parameter threshold have the same source identifier;
the second obtaining module is used for obtaining a fault association relation under the condition that the data parameter does not exceed the parameter threshold, wherein the fault association relation comprises an association relation between a first parameter range and a fault type;
and the searching module is used for searching a first parameter range containing the data parameters in the fault association relation, and taking the fault type corresponding to the first parameter range as the target fault type of the target data.
In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete mutual communication through the communication bus;
a memory for storing a computer program;
a processor for implementing any of the method steps described herein when executing the program stored in the memory.
In a fourth aspect, the present application provides a computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, performs any of the method steps.
The embodiment of the application has the following beneficial effects:
the embodiment of the application provides a method for determining a target fault type, which comprises the following steps: the server obtains data parameters of target data in the target equipment and parameter thresholds of the data parameters, obtains a fault association relation under the condition that the data parameters do not exceed the parameter thresholds, then searches a first parameter range containing the data parameters in the fault association relation, and takes fault types corresponding to the first parameter range as target fault types of the target data. According to the method and the device, the target fault type of the target data without faults is determined, so that technical personnel can predict the faults of the target equipment and correct the target data, and early warning is achieved.
Of course, not all of the above advantages need be achieved in the practice of any one product or method of the present application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a method for determining a target fault type according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a method for establishing a fault association relationship according to an embodiment of the present application;
fig. 3 is a flowchart of generating a fault association rule according to an embodiment of the present application;
fig. 4 is a flowchart of a process for determining a target fault type according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an apparatus for determining a target fault type according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides a method for determining a target fault type, which can be applied to a server and used for predicting the target fault type of target equipment.
A method for determining a target fault type provided in an embodiment of the present application will be described in detail below with reference to specific embodiments, as shown in fig. 1, the specific steps are as follows:
step 101: and acquiring a data parameter of target data in the target equipment and a parameter threshold of the data parameter.
Wherein the data parameter and the parameter threshold have the same source identification.
In the embodiment of the application, the target device is provided with a data acquisition device for acquiring target data of the target device according to a certain frequency or continuously, and then sending the target data to the server, and the server acquires data parameters in the target data. The target data carries a source identifier, and the source identifier is used for determining the source of the target data, including a base, a workshop, a production line and the like. The server also obtains the parameter threshold of the data parameter from the database, wherein the data parameter and the parameter threshold have the same source identifier, and the data parameter and the parameter threshold are guaranteed to have the same source.
Step 102: and acquiring the fault association relation under the condition that the data parameter does not exceed the parameter threshold.
And the fault association relation comprises the association relation between the first parameter range and the fault type.
In the embodiment of the application, after the server acquires the data parameters and the parameter threshold, whether the data parameters exceed the parameter threshold is judged. If the server judges that the data parameter does not exceed the parameter threshold, the data parameter is normal, the target data is normal, the server acquires the fault association relation, if the server judges that the data parameter exceeds the parameter threshold, the data parameter is abnormal, and the server stores the target data in the database.
The database comprises a first database, a second database and a third database, wherein the first database is used for storing historical data, the second database is used for data query, and the third database is used for data display and fault information pushing. Illustratively, the first database is an HBase database, the second database is a mysql database, and the third database is a redis database.
In the embodiment of the application, the server stores the target data to the second database and the third database.
Step 103: and searching a first parameter range containing data parameters in the fault association relation, and taking the fault type corresponding to the first parameter range as a target fault type of the target data.
In the embodiment of the application, the fault association relationship comprises a fault type and an association relationship with a first parameter range, after the server obtains the fault association relationship, the server searches the first parameter range containing data parameters in the fault association relationship, and then takes the fault type corresponding to the first parameter range as a target fault type of target data.
As an optional implementation manner, the server may store the data parameters of the target data and the target fault type in a third database, and send the target fault type to the target terminal, so that a technician knows the fault risk implied by the target device and performs processing to remove the fault.
In the method, the server determines the target fault type of the normal target data as the type of the fault which may occur in the target data.
As an optional implementation manner, as shown in fig. 2, before obtaining the fault association relationship, the method further includes:
step 201: and acquiring a fault type record and historical data from a database.
In the embodiment of the application, the server acquires the fault type record and the historical data from the database and converts the historical data into the data in the target format.
Step 202: a fault type in the fault type record and a first parameter range of the data parameter in the historical data are determined.
In the embodiment of the application, the server determines the fault type in the fault type record and the data parameter in the historical data, and determines the first parameter range of the data parameter.
Step 203: and establishing a fault association relation between the fault type and the first parameter range through data mining operation.
In the embodiment of the application, the server adopts a data mining algorithm in the flink to determine the internal relation between the first parameter ranges of the data parameters in the historical data, and then establishes the fault type and the fault association relation between the fault type and the first parameter ranges.
Illustratively, there are two data parameters A and B, and the server determines A<A1,B<B1When the current of the target equipment is overlarge, the fault correlation relationship is<A<A1,B<B1Excess current>。
In the application, the fault association relationship is set as a basis source for predicting the fault of the target equipment. In the application, the streaming data processing framework Flink is used for predicting the fault of the target equipment by using the fault association relation, so that real-time monitoring is realized, and the fault early warning which possibly causes the equipment fault is given out.
As an optional implementation manner, after acquiring the data parameter of the target data in the target device, the method further includes: storing the target data in a database; the method further comprises the following steps: under the condition that the target equipment fails, determining the failure moment when the failure occurs and determining the failure type of the target equipment; acquiring a second parameter range of the fault moment from the database; and updating the associated parameters in the fault association relation according to the fault type and the second parameter range.
In the embodiment of the application, after the server acquires the data parameters of the target data in the target device each time, the target data is stored in the database, so that the database contains all data of the target device.
If the target equipment fails in the operation process and the fault is not predicted in advance, the server determines the fault moment of the fault and determines the fault type of the target equipment, and then the server acquires the historical data in the database of the fault moment and acquires the second parameter range of the data parameters in the historical data. Since the fault is not predicted, the data parameter does not exist in the fault association relationship either, and the server may update the association parameter in the fault association relationship according to the fault type and the second parameter range.
According to the method and the device, the fault type judgment of the target data and the fault association relation form a closed loop, the association parameters in the fault association relation are continuously updated, the first parameter range having the association relation with the target fault type can be more accurate, and the timeliness and the accuracy of predicting the target fault type of the target equipment are improved.
If the technician determines that a new fault type exists, the fault type can be stored in a database, and the server updates the fault association relation according to the new fault type and the historical data. And the server uses the newly generated historical data in the fault association relationship, newly excavates a new association relationship, and dynamically uses the new association relationship in stream processing.
As an optional implementation, determining the fault type of the target device includes: determining a fault parameter of the target equipment at the fault moment; and determining the fault type of the target equipment according to the fault parameters.
In the embodiment of the application, after determining the fault time when the fault occurs, the server determines the fault parameter of the target device at the fault time, then determines the fault type of the target device according to the fault parameter, and takes the fault type as the fault type in the fault association relationship.
Specifically, the fault parameters are determined, and then the fault types corresponding to the fault parameters are searched in a preset fault table. The fault table comprises a plurality of corresponding relations between fault parameters and fault types.
As an optional implementation manner, before acquiring the data parameter of the target data in the target device, the method further includes: acquiring first data and a source type of the first data; and when the source category of the first data is the target category, taking the first data as target data.
The method comprises the steps that a server obtains first data and the source type of the first data, the server judges whether the source type of the first data is a target type, and if the server judges that the source type of the first data is the target type, the first data is used as target data; and if the server judges that the source type of the first data is not the target type, correspondingly processing the first data, wherein the corresponding processing comprises displaying the data in the target duration, counting the service condition of the data, pushing an abnormal index and the like.
In addition, the server stores the first data in the database, and optionally, the server stores the first data in the first database.
Illustratively, the source category may include pipelines, production plants, research and development rooms, and the like, and the target category is a pipeline, i.e., the target data is data of a target device on the pipeline.
As an optional implementation manner, before the first data is acquired, the method further includes: controlling the acquisition equipment to send the acquired plurality of first data to a message queue; and sequentially reading the first data from the message queue according to the time sequence.
The data acquisition equipment sends the acquired data of the equipment with different sources to the message queue, so that the message queue contains a plurality of pieces of first data, and the server reads the first data from the message queue in sequence according to the time sequence and operates the first data. The message queue can be kafka or rabbiting.
As an alternative embodiment, the message queue is set to the broadcast mode, and after the first data in the message queue is read by the server, the message queue is bound to a corresponding converter (exchange), so as to prevent the consumer from being unable to receive the first data.
As an optional implementation manner, in a case that the source category of the first data is the target category, after the first data is taken as the target data, the method further includes: performing data cleaning operation on target data; acquiring the target data includes: and acquiring target data subjected to data cleaning operation.
After the server takes the first data as target data, the target data is subjected to data cleaning, error data, repeated data and the like are removed, then the data format of the target data is converted into the target format, and then the target data subjected to data cleaning and data format conversion is obtained.
As an optional implementation manner, after the data cleansing operation is performed on the target data, the target data is stored in the database, specifically, the target data after the data cleansing operation is stored in the third database, which is used for displaying the data, and giving an alarm when the data is abnormal.
As an optional implementation manner, if the server determines that the data parameter exceeds the parameter threshold, it indicates that the data parameter is abnormal, and the server stores the target data in the second database and the third database.
As an optional embodiment, the database comprises a first database and a second database, wherein the first database is used for data storage, and the second database is used for data query; obtaining the fault type record and the historical data from the database includes: acquiring a fault type record and historical data from a first database; after establishing the association relationship between the first parameter range and the fault type through the data mining operation, the method further comprises the following steps: storing the association in a second database.
The server stores the first data in a first database, acquires fault type records and historical data from the first database, establishes an association relationship between a first parameter range and the fault type through data mining operation, stores the association relationship in a second database, acquires the fault association relationship from the second database, and determines a target fault type of target data.
Fig. 3 is a flow chart of generation of a fault association rule. And the server acquires the fault type record and the historical data from the HBase database, performs association analysis between the first parameter range of the data parameters and the fault type through an association analysis algorithm packet in the Flink after performing data cleaning, generates a fault association relation, and stores the fault association relation into the mysql database.
Optionally, an embodiment of the present application further provides a processing flow for determining a target fault type, as shown in fig. 4, and the specific steps are as follows.
Step 401: the data acquisition device acquires first data of the target equipment.
Step 402: the server controls the data acquisition device to send the first data to the message queue.
Step 403: and the server determines target data with a target category by using the first data in the flink real-time consumption message queue, performs database backup on the first data, and stores the first data in the HBase database.
Step 404: and the server performs data cleaning on the target data and stores the cleaned target data in a redis database.
Step 405: the server acquires a parameter threshold value from the mysql database, and if the server judges that the data parameter exceeds the parameter threshold value, the target data is stored in the mysql database and the redis database; if the server determines that the data parameter does not exceed the parameter threshold, go to step 406;
step 406: and the server acquires the fault association relation from the mysql database and determines the target fault type of the target data.
Step 407: and the server stores the target data and the target fault type into a redis database.
Step 408: the server obtains the target failure type from the redis database.
Step 409: and sending the target fault type to the target terminal.
Based on the same technical concept, an embodiment of the present application further provides an apparatus for determining a target fault type, as shown in fig. 5, the apparatus includes:
a first obtaining module 501, configured to obtain a data parameter of target data in a target device and a parameter threshold of the data parameter, where the data parameter and the parameter threshold have a same source identifier;
a second obtaining module 502, configured to obtain a fault association relationship when the data parameter does not exceed the parameter threshold, where the fault association relationship includes an association relationship between a first parameter range and a fault type;
the searching module 503 is configured to search a first parameter range including the data parameter in the fault association relationship, and use a fault type corresponding to the first parameter range as a target fault type of the target data.
Optionally, the apparatus further comprises:
the third acquisition module is used for acquiring fault type records and historical data from the database;
the first determining module is used for determining the fault type in the fault type record and a first parameter range of the data parameters in the historical data;
and the establishing module is used for establishing the fault association relationship between the fault type and the first parameter range through data mining operation.
Optionally, the apparatus further comprises:
the storage module is used for storing the target data in a database;
the second determining module is used for determining the fault moment when the fault occurs and determining the fault type of the target equipment under the condition that the fault of the target equipment is not predicted;
the fourth acquisition module is used for acquiring a second parameter range of the fault moment from the database;
and the updating module is used for updating the associated parameters in the fault association relation according to the fault type and the second parameter range.
Optionally, the second determining module includes:
the first determining unit is used for determining a fault parameter of the target equipment at the fault moment;
and the second determining unit is used for determining the fault type of the target equipment according to the fault parameters.
Optionally, the apparatus comprises:
the fifth acquisition module is used for acquiring the first data and the source type of the first data;
and the module is used for taking the first data as the target data under the condition that the source category of the first data is the target category.
Optionally, the apparatus comprises:
the control module is used for controlling the acquisition equipment to send the acquired plurality of first data to the message queue;
and the reading module is used for sequentially reading the first data from the message queue according to the time sequence.
Optionally, the apparatus comprises:
the third determining module is used for determining the target data as fault data under the condition that the data parameter of the target data exceeds the parameter threshold;
the first storage module is used for storing the fault data in the database.
Optionally, the database includes a first database and a second database, wherein the first database is used for data storage, and the second database is used for data query; the third acquisition module includes: acquiring a fault type record and historical data from a first database;
the device also includes: and the second storage module is used for storing the association relation in a second database.
Based on the same technical concept, an embodiment of the present invention further provides an electronic device, as shown in fig. 6, including a processor 601, a communication interface 602, a memory 603, and a communication bus 604, where the processor 601, the communication interface 602, and the memory 603 complete mutual communication through the communication bus 604,
a memory 603 for storing a computer program;
the processor 601 is configured to implement the above steps when executing the program stored in the memory 603.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
In a further embodiment provided by the present invention, there is also provided a computer readable storage medium having stored therein a computer program which, when executed by a processor, implements the steps of any of the methods described above.
In a further embodiment provided by the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform any of the methods of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. 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.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. A method of determining a target fault type, the method comprising:
acquiring a data parameter of target data in target equipment and a parameter threshold of the data parameter, wherein the data parameter and the parameter threshold have the same source identifier;
under the condition that the data parameter does not exceed the parameter threshold, acquiring a fault association relation, wherein the fault association relation comprises an association relation between a first parameter range and a fault type;
and searching a first parameter range containing the data parameters in the fault association relation, and taking the fault type corresponding to the first parameter range as a target fault type of the target data.
2. The method of claim 1, wherein before obtaining the fault association relationship, the method further comprises:
acquiring fault type records and historical data from a database;
determining the fault type in the fault type record and a first parameter range of the data parameters in the historical data;
and establishing a fault association relation between the fault type and the first parameter range through data mining operation.
3. The method of claim 2,
after the data parameters of the target data in the target device are obtained, the method further includes: storing the target data in the database;
the method further comprises the following steps: under the condition that the target equipment is not predicted to have faults, determining the fault moment when the faults occur, and determining the fault type of the target equipment; acquiring a second parameter range of the fault moment from the database; and updating the associated parameters in the fault association relationship according to the fault type and the second parameter range.
4. The method of claim 3, wherein the determining the type of failure of the target device comprises:
determining a fault parameter of the target device at the fault moment;
and determining the fault type of the target equipment according to the fault parameters.
5. The method of claim 1, wherein before obtaining the data parameters of the target data in the target device, the method further comprises:
acquiring first data and a source category of the first data;
and if the source category of the first data is a target category, taking the first data as the target data.
6. The method of claim 5, wherein prior to the obtaining the first data, the method further comprises:
controlling the acquisition equipment to send the acquired plurality of first data to a message queue;
and sequentially reading the first data from the message queue according to the time sequence.
7. The method of claim 2, wherein after obtaining the data parameter of the target data and the parameter threshold of the data parameter in the target device, the method further comprises:
determining the target data as fault data under the condition that the data parameter of the target data exceeds the parameter threshold;
storing the fault data in the database.
8. The method of claim 2,
the database comprises a first database and a second database, wherein the first database is used for data storage, and the second database is used for data query; the obtaining of the fault type record and the historical data from the database includes: acquiring a fault type record and historical data from the first database;
after the establishing the association relationship between the first parameter range and the fault type through the data mining operation, the method further includes: storing the association in the second database.
9. An apparatus for determining a target fault type, the apparatus comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a data parameter of target data in target equipment and a parameter threshold of the data parameter, and the data parameter and the parameter threshold have the same source identifier;
the second obtaining module is used for obtaining a fault association relation under the condition that the data parameter does not exceed the parameter threshold, wherein the fault association relation comprises an association relation between a first parameter range and a fault type;
and the searching module is used for searching a first parameter range containing the data parameters in the fault association relation, and taking the fault type corresponding to the first parameter range as the target fault type of the target data.
10. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1 to 8 when executing a program stored in the memory.
11. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of the claims 1-8.
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