CN114236314A - Fault detection method, device, equipment and storage medium - Google Patents
Fault detection method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN114236314A CN114236314A CN202111549855.6A CN202111549855A CN114236314A CN 114236314 A CN114236314 A CN 114236314A CN 202111549855 A CN202111549855 A CN 202111549855A CN 114236314 A CN114236314 A CN 114236314A
- Authority
- CN
- China
- Prior art keywords
- equipment
- fault
- parameter
- rule
- configuration interface
- 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
- 238000001514 detection method Methods 0.000 title claims abstract description 44
- 238000004458 analytical method Methods 0.000 claims abstract description 65
- 238000000034 method Methods 0.000 claims abstract description 13
- 238000004590 computer program Methods 0.000 claims description 13
- 238000012423 maintenance Methods 0.000 description 17
- 230000002159 abnormal effect Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012360 testing method 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The application provides a fault detection method, a fault detection device, equipment and a storage medium, wherein the method comprises the following steps: selecting equipment parameters of the equipment to be detected on a parameter configuration interface; configuring a fault rule of the equipment parameter on a rule configuration interface; acquiring operation data corresponding to the equipment parameters; and performing fault analysis on the operating data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters. According to the fault detection method, the fault detection device, the equipment and the storage medium, the equipment parameters to be acquired can be selected, the corresponding fault rules are flexibly configured according to the equipment parameters, and finally fault analysis is carried out according to the fault rules of the equipment parameters and the operation data corresponding to the equipment parameters, so that fault detection of the equipment is realized.
Description
Technical Field
The present disclosure relates to the field of device fault detection, and in particular, to a method, an apparatus, a device, and a storage medium for fault detection.
Background
Through continuously measuring and monitoring the running state of the equipment, the possible abnormal conditions of the equipment in the running state can be analyzed in time, and corrective measures can be taken in advance aiming at the possible abnormal conditions in the running of the equipment, namely, maintenance personnel are informed to overhaul the equipment, so that the equipment fault caused by the abnormal conditions in the running process of the equipment can be effectively prevented to a certain extent.
In the existing fault detection method, all devices adopt the same fault detection method for fault detection, but abnormal conditions possibly occurring in different devices are different, if the same fault detection method is adopted for fault detection of the devices, the obtained fault detection result is not accurate enough, and meanwhile, because all the devices adopt the same fault detection method for fault detection, different devices cannot perform fault detection in a targeted manner, and thus the fault detection requirements of different devices are difficult to meet.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method, an apparatus, a device, and a storage medium for fault detection, so as to solve the problems in the prior art.
In a first aspect, a fault detection method is provided, including:
selecting equipment parameters of the equipment to be detected on a parameter configuration interface;
configuring a fault rule of the equipment parameter on a rule configuration interface;
acquiring operation data corresponding to the equipment parameters;
and performing fault analysis on the operating data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
According to the fault detection method, the equipment parameters of the equipment to be detected are selected on the parameter configuration interface, so that different equipment to be detected can select different equipment parameters, further, the equipment parameters can be configured according to the fault rules on the rule configuration interface, and further, different fault analyses can be performed according to different equipment parameters.
In one embodiment, the configuring, at a rule configuration interface, the fault rule of the equipment parameter includes:
and setting a normal operation interval corresponding to the equipment parameters on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameters is not in the normal operation interval corresponding to the equipment parameters.
In the embodiment, the normal operation interval corresponding to the equipment parameter is configured on the rule configuration interface, whether the operation data corresponding to the equipment parameter appears in the normal operation interval corresponding to the equipment parameter is detected, a fault analysis result is obtained, and whether the equipment has a fault is judged by detecting whether the operation data corresponding to the equipment parameter appears in the normal operation interval, so that fault analysis is realized.
In one embodiment, the configuring, at a rule configuration interface, the fault rule of the equipment parameter includes:
and configuring the jumping-out times corresponding to the normal operation interval on a rule configuration interface so as to obtain a fault analysis result when the times that the operation data corresponding to the equipment parameters are not in the normal operation interval corresponding to the equipment parameters reach the jumping-out times.
In the embodiment, the number of jumping-out times corresponding to the normal operation interval is configured on the rule configuration interface, the number of jumping-out times of the operation data corresponding to the equipment parameter is detected, the number of jumping-out times corresponding to the configured normal operation interval is compared with the number of jumping-out times corresponding to the configured normal operation interval, a fault analysis result is obtained, whether the equipment has a fault or not is judged by detecting whether the number of jumping-out times of the operation data corresponding to the equipment parameter is within the number of jumping-out times corresponding to the normal operation interval, and fault analysis is achieved.
In one embodiment, the configuring, at a rule configuration interface, the fault rule of the equipment parameter includes:
and configuring a deviation value range corresponding to the equipment parameter on a rule configuration interface, so as to determine the operation deviation value range of the equipment parameter according to the operation data corresponding to the equipment parameter, and obtaining a fault analysis result when the operation deviation value range is not in the deviation value range.
In the embodiment, the deviation value range corresponding to the equipment parameter is configured on the rule configuration interface, whether the operating data corresponding to the equipment parameter is in the deviation value range is detected, a fault analysis result is obtained, whether the deviation value of the operating data corresponding to the equipment parameter is in the deviation value range is detected, and whether the equipment has a fault is judged according to the deviation value range, so that fault analysis is realized.
In one embodiment, the configuring, at a rule configuration interface, the fault rule of the equipment parameter includes:
and configuring a historical fault range corresponding to the equipment parameter on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameter is in the historical fault range corresponding to the equipment parameter.
In the embodiment, the historical fault range corresponding to the equipment parameter is configured on the rule configuration interface, whether the operation data corresponding to the equipment parameter is in the historical fault range is detected, a fault analysis result is obtained, and whether the equipment has a fault is judged by detecting whether the operation data corresponding to the equipment parameter is in the historical fault range, so that fault analysis is realized.
In one embodiment, the selecting, on the parameter configuration interface, the device parameter of the device to be tested includes:
and selecting the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters on a parameter configuration interface.
According to the embodiment, the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters are selected on the parameter configuration interface, so that the operation data and the corresponding acquisition period which need to be acquired by the equipment to be detected are determined, effective acquisition of the data is realized, and the data acquisition efficiency is improved.
In one embodiment, the configuring, at a rule configuration interface, the fault rule of the equipment parameter includes:
and configuring a fluctuation graph rule corresponding to the equipment parameter on a rule configuration interface to generate a fluctuation graph according to the running data corresponding to the equipment parameter, and analyzing the generated fluctuation graph according to the fluctuation graph rule to obtain a fault analysis result corresponding to the equipment parameter.
In the above embodiment, the rule configuration interface configures a fluctuation graph rule corresponding to the device parameter, generates a fluctuation graph according to the fluctuation graph rule, analyzes the fluctuation graph, checks whether the operating data corresponding to the device parameter is abnormal, generates a fluctuation graph by setting the fluctuation graph rule, analyzes the fluctuation graph, and analyzes whether the device has a fault, thereby implementing fault analysis.
In a second aspect, a fault detection apparatus is provided, comprising:
the first input module is used for selecting the equipment parameters of the equipment to be detected on a parameter configuration interface;
the rule configuration module is used for configuring the fault rule of the equipment parameter on a rule configuration interface;
the acquisition module is used for acquiring and obtaining the operating data corresponding to the equipment parameters;
and the fault analysis module is used for carrying out fault analysis on the operation data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
In a third aspect, a computer device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the fault detection method as described above when executing the computer program.
In a fourth aspect, a computer readable storage medium is provided, in which computer program instructions are stored, which computer program instructions, when read and executed by a processor, perform the steps of the fault detection method as described above.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic diagram illustrating an implementation flow of a fault detection method provided in an embodiment of the present application;
FIG. 2 is a basic information interface provided by an embodiment of the present application;
FIG. 3 is a repair order interface provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a fault detection apparatus provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a computer 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.
Fig. 1 is a fault detection method provided in an embodiment of the present application, including:
and S100, selecting equipment parameters of the equipment to be detected on a parameter configuration interface.
The equipment parameters are data of the equipment to be detected, which need to be acquired, including but not limited to equipment running speed, equipment working temperature, equipment traction speed, equipment working pressure value, equipment deviation and equipment monitoring period, the parameter configuration interface at least comprises labels corresponding to the equipment parameters, the parameter configuration interfaces of different types of equipment to be detected can be the same or different, and as the labels corresponding to the equipment parameters are configured in the parameter configuration interface, when certain data (for example, equipment running speed) of the equipment to be detected needs to be acquired, the labels corresponding to the data (for example, equipment running speed) are selected.
And step S200, configuring the fault rule of the equipment parameter on a rule configuration interface.
The fault rule is a set rule for determining whether the operating data corresponding to the device parameter is abnormal, for example, a normal operating interval, a jump-out frequency and a historical fault range of the device parameter are configured on a rule configuration interface, for example, the device parameter is an operating temperature, so that the normal operating interval of the operating temperature and the historical fault range of the operating temperature are configured, for example, the normal operating interval of the operating temperature is 200 ℃ to 260 ℃, the historical fault range of the operating temperature is 280 ℃ to 300 ℃, and when the operating temperature of the device is not within the normal operating interval or the operating temperature of the device is within the historical fault range, the device is considered to be possibly faulty.
And S300, acquiring operation data corresponding to the equipment parameters.
And the operation data is data corresponding to the equipment parameters of the equipment to be detected during actual working.
And acquiring operation data corresponding to the equipment parameters, wherein the equipment parameters are the running speed of the equipment, and the running speed of the equipment in actual working is acquired.
Step S400, performing fault analysis on the operation data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
For example, the equipment parameter is the working temperature, the fault rule is the historical fault range of 280-300 ℃, the operating data corresponding to the working temperature is 240-260 ℃, and the working temperature is not in the historical fault range, so that the equipment is considered to be normal in operation and has no fault.
According to the fault detection method, the equipment parameters of the equipment to be detected are selected on the parameter configuration interface, so that different equipment to be detected can select different equipment parameters, further, the equipment parameters can be configured according to the fault rules on the rule configuration interface, and further, different fault analyses can be performed according to different equipment parameters.
In one embodiment, step S200 includes:
and setting a normal operation interval corresponding to the equipment parameters on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameters is not in the normal operation interval corresponding to the equipment parameters.
For example, the normal operation interval of the equipment operation speed is 500r/min-1000r/min, and when the equipment operation speed acquired by the equipment in the operation state is not in the normal operation interval, the equipment is considered to be in a fault. For example, the running speed of the equipment is greater than 1000r/min, or the running speed of the equipment is less than 500r/min, and at this time, the equipment is considered to be in fault.
And configuring a normal operation interval corresponding to the equipment parameters on a rule configuration interface, detecting whether the operation data corresponding to the equipment parameters are in the normal operation interval corresponding to the equipment parameters to obtain a fault analysis result, and judging whether the equipment has faults or not by detecting whether the operation data corresponding to the equipment parameters are in the normal operation interval so as to realize fault analysis.
In one embodiment, step S200 includes:
and configuring the jumping-out times corresponding to the normal operation interval on a rule configuration interface so as to obtain a fault analysis result when the times that the operation data corresponding to the equipment parameters are not in the normal operation interval corresponding to the equipment parameters reach the jumping-out times.
For example, the normal operation interval of the equipment pressure value is 0.6-1.6 MPa, the corresponding jumping-out times are 2 times, and when the times that the equipment pressure value acquired by the equipment in the operation state is not within 0.6-1.6 MPa reach 2 times, the equipment is considered to be in fault. For example, the pressure values of the equipment in the operating state are 0.5MPa, 1.8MPa and 2.0MPa for three times, and at this time, the equipment is considered to be in failure.
And on a rule configuration interface, configuring the jumping-out times corresponding to the normal operation interval, detecting the jumping-out times of the operation data corresponding to the equipment parameters, comparing the jumping-out times with the jumping-out times corresponding to the configured normal operation interval to obtain a fault analysis result, and judging whether the equipment has faults or not by detecting whether the jumping-out times of the operation data corresponding to the equipment parameters are within the jumping-out times corresponding to the normal operation interval so as to realize fault analysis.
In one embodiment, step S200 includes:
and configuring a deviation value range corresponding to the equipment parameter on a rule configuration interface, so as to determine the operation deviation value range of the equipment parameter according to the operation data corresponding to the equipment parameter, and obtaining a fault analysis result when the operation deviation value range is not in the deviation value range.
For example, the equipment parameter is equipment traction speed, the deviation value range corresponding to the equipment traction speed is configured to be 100m/min-120m/min, the monitoring period is configured to be 1 week, the equipment traction speed of the equipment in the running state is acquired, the running deviation value range is calculated, and when the running deviation value range is not in the deviation value range, the equipment is considered to possibly have faults. For example, the equipment traction speed in the first week is 300m/min-500m/min, the equipment traction speed in the second week is 400m/min-550m/min, at this time, the minimum traction speed in the first week is subtracted by the minimum traction speed in the second week, and the maximum traction speed in the first week is subtracted by the maximum traction speed in the second week, so that the operation deviation value range is 100m/min-150m/min, and the deviation value range is 100m/min-120m/min beyond, and the equipment is considered to be possibly failed.
And on a rule configuration interface, configuring a deviation value range corresponding to the equipment parameters, detecting whether the operating data corresponding to the equipment parameters are in the deviation value range, obtaining a fault analysis result, detecting whether the deviation value of the operating data corresponding to the equipment parameters is in the deviation value range, and judging whether the equipment has faults or not according to the deviation value range, so that fault analysis is realized.
In one embodiment, step S200 includes:
and configuring a historical fault range corresponding to the equipment parameter on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameter is in the historical fault range corresponding to the equipment parameter.
The historical fault range corresponding to the equipment parameter can be obtained according to the historical maintenance record, for example, the historical maintenance record shows that the working temperature is maintained for 20 times at 280-290 ℃, and the working temperature is maintained for 2 times at 290-300 ℃, so that the historical fault range of the working temperature can be configured to be 280-300 ℃.
When the device is actually detected and applied, for example, the device parameter is the working temperature, the historical fault range is 280-300 ℃, the working temperature of the device in the running state is collected, and when the working temperature collected by the device in the running state is within 280-300 ℃, the device is considered to be possibly faulted. For example, the collected operating temperature of the device is 290 ℃, and thus, the device is considered to be possibly out of order.
And on a rule configuration interface, configuring a historical fault range corresponding to the equipment parameters, detecting whether the operating data corresponding to the equipment parameters is in the historical fault range to obtain a fault analysis result, and judging whether the equipment has a fault or not by detecting whether the operating data corresponding to the equipment parameters is in the historical fault range so as to realize fault analysis.
In one embodiment, step S100 includes:
and selecting the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters on a parameter configuration interface.
The equipment parameters required to be acquired by different equipment to be detected may be different, and some equipment parameters need to be compared with data in a period, so that the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters need to be recorded on a parameter configuration interface. For example, the parameter configuration interface configures the device parameter as the device traction speed, and the acquisition period corresponding to the device traction speed is one week.
And inputting the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters on a parameter configuration interface so as to determine the operation data and the corresponding acquisition period required to be acquired by the equipment to be detected, thereby realizing effective acquisition of the data.
In one embodiment, step S200 includes:
and configuring a fluctuation graph rule corresponding to the equipment parameter on a rule configuration interface to generate a fluctuation graph according to the running data corresponding to the equipment parameter, and analyzing the generated fluctuation graph according to the fluctuation graph rule to obtain a fault analysis result corresponding to the equipment parameter.
For example, the horizontal axis of the oscillogram is set as time, the vertical axis is set as operating frequency of the equipment, the frequency and duration of the frequency on the oscillogram are recorded, when the frequency on the oscillogram is increased steeply for more than 10 times within preset time (for example, the preset time is 1 hour) and the operating frequency is higher than the frequency of normal operation of the equipment, the equipment is considered to have a fault, the oscillogram is generated according to the acquired operating frequency of the equipment to be detected in the operating state, and the oscillogram is analyzed to obtain a fault result. For example, the frequency of normal operation of the equipment is 200Hz-300Hz, the operating frequency of the equipment is increased to 500Hz suddenly 3 times between 14 points and 15 points, the operating frequency of the equipment is increased to 400Hz suddenly 5 times, and the operating frequency of the equipment is increased to 600Hz suddenly 3 times, and at this time, the equipment is considered to be possibly out of order.
And configuring a fluctuation graph rule corresponding to the equipment parameter on a rule configuration interface, generating a fluctuation graph according to the fluctuation graph rule, analyzing the fluctuation graph, checking whether the running data corresponding to the equipment parameter is abnormal or not, generating the fluctuation graph by setting the fluctuation graph rule, analyzing the fluctuation graph, analyzing whether the equipment fails or not, and realizing failure analysis.
In one embodiment, before step S100, the method further includes:
and inputting basic information of the equipment to be detected on the basic information interface.
The equipment to be detected is equipment needing fault detection, basic information comprises but is not limited to equipment codes, equipment bar codes, equipment types, equipment purchase dates, equipment rated service lives, equipment manufacturers, factory addresses, equipment names, specification models, installation positions, production-in dates, use departments, equipment volumes and equipment pictures, the basic information interface at least comprises labels corresponding to the basic information, the basic information interfaces of the equipment to be detected of different types can be the same or different, and when certain basic information needs to be input, for example, when the equipment purchase dates are input, the equipment to be detected only needs to be input at the equipment purchase date labels.
And inputting basic information of the equipment to be detected in a basic information interface, as shown in fig. 2.
In one embodiment, after step S400, the method further includes:
sending the fault analysis result corresponding to the equipment parameter to a worker, and sending a maintenance application work order to a maintenance worker by the worker according to the fault analysis result corresponding to the equipment parameter;
and the maintenance personnel overhaul the equipment according to the maintenance application work order, and after the equipment overhaul is completed, the equipment maintenance record is recorded into a maintenance work order interface.
The service order interface includes a plurality of labels including, but not limited to, a service order number, a device name, a fault type, a service time, a task start time, and a service end time, as shown in FIG. 3.
For example, the fault analysis result corresponding to the equipment parameter is that the actual working temperature of the equipment (for example, the actual working temperature is 290 ℃ -300 ℃) exceeds the normal operation interval (for example, the normal operation interval is 200 ℃ -260 ℃), the equipment is considered to be possible to be in fault, a maintenance application work order is issued to a maintenance worker, the maintenance worker overhauls the equipment according to the maintenance application work order, after the equipment is overhauled, the equipment maintenance record is recorded into a maintenance work order interface, for example, the test equipment 1 is filled in an equipment name label corresponding to the maintenance work order interface, the equipment is overheated in a fault type label, and the label is filled for 30min during maintenance.
In one embodiment, as shown in fig. 4, there is provided a fault detection apparatus 500 comprising:
the first input module 501 is configured to select an apparatus parameter of the apparatus to be detected on a parameter configuration interface;
a rule configuration module 502, configured to configure a fault rule of the device parameter in a rule configuration interface;
the acquisition module 503 is configured to acquire operation data corresponding to the device parameter;
the fault analysis module 504 is configured to perform fault analysis on the operation data corresponding to the device parameter according to the fault rule of the device parameter, so as to obtain a fault analysis result corresponding to the device parameter.
In an embodiment, the rule configuration module 502 is specifically configured to:
and setting a normal operation interval corresponding to the equipment parameters on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameters is not in the normal operation interval corresponding to the equipment parameters.
In an embodiment, the rule configuration module 502 is specifically configured to:
and configuring the jumping-out times corresponding to the normal operation interval on a rule configuration interface so as to obtain a fault analysis result when the times that the operation data corresponding to the equipment parameters are not in the normal operation interval corresponding to the equipment parameters reach the jumping-out times.
In an embodiment, the rule configuration module 502 is specifically configured to:
and configuring a deviation value range corresponding to the equipment parameter on a rule configuration interface, so as to determine the operation deviation value range of the equipment parameter according to the operation data corresponding to the equipment parameter, and obtaining a fault analysis result when the operation deviation value range is not in the deviation value range.
In an embodiment, the rule configuration module 502 is specifically configured to:
and configuring a historical fault range corresponding to the equipment parameter on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameter is in the historical fault range corresponding to the equipment parameter.
In one embodiment, the first entry module 501 is specifically configured to:
and selecting the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters on a parameter configuration interface.
In an embodiment, the rule configuration module 502 is specifically configured to:
and configuring a fluctuation graph rule corresponding to the equipment parameter on a rule configuration interface to generate a fluctuation graph according to the running data corresponding to the equipment parameter, and analyzing the generated fluctuation graph according to the fluctuation graph rule to obtain a fault analysis result corresponding to the equipment parameter.
In one embodiment, as shown in fig. 5, a computer device is provided, which may be a terminal or a server in particular. The computer device comprises a processor, a memory and a network interface which are connected through a system bus, wherein the memory comprises a nonvolatile storage medium and an internal memory, the nonvolatile storage medium of the computer device stores an operating system and also stores a computer program, and when the computer program is executed by the processor, the processor can realize the fault detection method. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM). The internal memory may also have stored therein a computer program that, when executed by the processor, causes the processor to perform the fault detection method. Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The fault detection method provided by the present application may be implemented in the form of a computer program that is executable on a computer device as shown in fig. 5. A plurality of program templates constituting the failure detection means may be stored in the memory of the computer device. For example, the first entry module 501, the rule configuration module 502, and the collection module 503.
A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of:
selecting equipment parameters of the equipment to be detected on a parameter configuration interface;
configuring a fault rule of the equipment parameter on a rule configuration interface;
acquiring operation data corresponding to the equipment parameters;
and performing fault analysis on the operating data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
In one embodiment, a computer readable storage medium is provided, storing a computer program that, when executed by a processor, causes the processor to perform the steps of:
selecting equipment parameters of the equipment to be detected on a parameter configuration interface;
configuring a fault rule of the equipment parameter on a rule configuration interface;
acquiring operation data corresponding to the equipment parameters;
and performing fault analysis on the operating data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
It should be noted that the above-mentioned fault detection method, fault detection apparatus, computer device and computer readable storage medium belong to a general inventive concept, and the contents in the embodiments of the fault detection method, fault detection apparatus, computer device and computer readable storage medium are mutually applicable.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form. In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment. In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or a plurality of modules may exist separately, or two or more modules may be integrated to form an independent part. 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. The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A method of fault detection, comprising:
selecting equipment parameters of the equipment to be detected on a parameter configuration interface;
configuring a fault rule of the equipment parameter on a rule configuration interface;
acquiring operation data corresponding to the equipment parameters;
and performing fault analysis on the operating data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
2. The method according to claim 1, wherein configuring the fault rule of the device parameter in a rule configuration interface comprises:
and setting a normal operation interval corresponding to the equipment parameters on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameters is not in the normal operation interval corresponding to the equipment parameters.
3. The method according to claim 1, wherein configuring the fault rule of the device parameter in a rule configuration interface comprises:
and configuring the jumping-out times corresponding to the normal operation interval on a rule configuration interface so as to obtain a fault analysis result when the times that the operation data corresponding to the equipment parameters are not in the normal operation interval corresponding to the equipment parameters reach the jumping-out times.
4. The method according to claim 1, wherein configuring the fault rule of the device parameter in a rule configuration interface comprises:
and configuring a deviation value range corresponding to the equipment parameter on a rule configuration interface, so as to determine the operation deviation value range of the equipment parameter according to the operation data corresponding to the equipment parameter, and obtaining a fault analysis result when the operation deviation value range is not in the deviation value range.
5. The method according to claim 1, wherein configuring the fault rule of the device parameter in a rule configuration interface comprises:
and configuring a historical fault range corresponding to the equipment parameter on a rule configuration interface so as to obtain a fault analysis result when the operation data corresponding to the equipment parameter is in the historical fault range corresponding to the equipment parameter.
6. The fault detection method according to claim 1, wherein the selecting the device parameters of the device to be tested on the parameter configuration interface comprises:
and selecting the equipment parameters of the equipment to be detected and the acquisition period corresponding to the equipment parameters on a parameter configuration interface.
7. The method according to claim 1, wherein configuring the fault rule of the device parameter in a rule configuration interface comprises:
and configuring a fluctuation graph rule corresponding to the equipment parameter on a rule configuration interface to generate a fluctuation graph according to the running data corresponding to the equipment parameter, and analyzing the generated fluctuation graph according to the fluctuation graph rule to obtain a fault analysis result corresponding to the equipment parameter.
8. A fault detection device, comprising:
the first input module is used for selecting the equipment parameters of the equipment to be detected on a parameter configuration interface;
the rule configuration module is used for configuring the fault rule of the equipment parameter on a rule configuration interface;
the acquisition module is used for acquiring and obtaining the operating data corresponding to the equipment parameters;
and the fault analysis module is used for carrying out fault analysis on the operation data corresponding to the equipment parameters according to the fault rules of the equipment parameters to obtain fault analysis results corresponding to the equipment parameters.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the fault detection method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, having stored thereon computer program instructions, which, when read and executed by a processor, perform the steps of the fault detection method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111549855.6A CN114236314A (en) | 2021-12-17 | 2021-12-17 | Fault detection method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111549855.6A CN114236314A (en) | 2021-12-17 | 2021-12-17 | Fault detection method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114236314A true CN114236314A (en) | 2022-03-25 |
Family
ID=80758127
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111549855.6A Pending CN114236314A (en) | 2021-12-17 | 2021-12-17 | Fault detection method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114236314A (en) |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140366657A1 (en) * | 2013-06-12 | 2014-12-18 | Airbus Sas | Method and device for testing a component part of an aircraft |
| CN105005102A (en) * | 2015-08-03 | 2015-10-28 | 中环天仪（天津）气象仪器有限公司 | Maintenance platform for testing and diagnosis meteorological observation equipment and method thereof |
| CN105116291A (en) * | 2015-09-07 | 2015-12-02 | 国电南瑞科技股份有限公司 | Power grid operating steady state monitoring information-based fault diagnosis system and method |
| CN107167497A (en) * | 2017-06-27 | 2017-09-15 | 北京必可测科技股份有限公司 | A kind of equipment fault detection method and system |
| US20180284745A1 (en) * | 2016-05-09 | 2018-10-04 | StrongForce IoT Portfolio 2016, LLC | Methods and systems for self-organization of collected data using 3rd party data from a data marketplace in an industrial internet of things environment |
| CN109782739A (en) * | 2019-01-29 | 2019-05-21 | 中国能源建设集团广东省电力设计研究院有限公司 | Repair method, device, computer equipment and the storage medium of equipment fault |
| CN109884533A (en) * | 2019-03-11 | 2019-06-14 | 北京百度网讯科技有限公司 | The diagnostic method and device of battery failures, equipment and storage medium |
| CN109894476A (en) * | 2019-02-28 | 2019-06-18 | 北京首钢股份有限公司 | A kind of cold rolled silicon steel production line hydraulic equipment fault diagnosis method and device |
| CA3099659A1 (en) * | 2018-05-07 | 2019-11-14 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for data collection, learning, and streaming of machine signals for analytics and maintenance using the industrial internet of things |
| CN110675079A (en) * | 2019-09-30 | 2020-01-10 | 腾讯科技（深圳）有限公司 | Fault data processing method and device and computer equipment |
| CN209947082U (en) * | 2019-07-23 | 2020-01-14 | 河北上元智能科技股份有限公司 | Highway tunnel electromechanical device fault detection system |
| CN111177485A (en) * | 2019-12-16 | 2020-05-19 | 中建材智慧工业科技有限公司 | Method, device and medium for predicting device failure based on parameter rule matching |
| CN111856268A (en) * | 2019-04-24 | 2020-10-30 | 中矿龙科能源科技(北京)股份有限公司 | Motor and generator fault diagnosis system based on harmonic method |
| CN112445193A (en) * | 2019-08-14 | 2021-03-05 | 珠海格力电器股份有限公司 | Method, device and equipment for predicting air conditioner fault and storage medium |
| CN112650654A (en) * | 2020-12-11 | 2021-04-13 | 西安诺瓦星云科技股份有限公司 | Early warning method and device for display control visualization system, storage medium and processor |
| CN112668727A (en) * | 2019-09-29 | 2021-04-16 | 北京国双科技有限公司 | Method and device for detecting equipment fault |
| CN113077172A (en) * | 2021-04-19 | 2021-07-06 | 瑞湖智科数据(苏州)有限公司 | Equipment state trend analysis and fault diagnosis method |
| CN113538997A (en) * | 2021-07-14 | 2021-10-22 | 重庆电子工程职业学院 | Equipment predictive maintenance learning system |
-
2021
- 2021-12-17 CN CN202111549855.6A patent/CN114236314A/en active Pending
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140366657A1 (en) * | 2013-06-12 | 2014-12-18 | Airbus Sas | Method and device for testing a component part of an aircraft |
| CN105005102A (en) * | 2015-08-03 | 2015-10-28 | 中环天仪（天津）气象仪器有限公司 | Maintenance platform for testing and diagnosis meteorological observation equipment and method thereof |
| CN105116291A (en) * | 2015-09-07 | 2015-12-02 | 国电南瑞科技股份有限公司 | Power grid operating steady state monitoring information-based fault diagnosis system and method |
| US20180284745A1 (en) * | 2016-05-09 | 2018-10-04 | StrongForce IoT Portfolio 2016, LLC | Methods and systems for self-organization of collected data using 3rd party data from a data marketplace in an industrial internet of things environment |
| CN107167497A (en) * | 2017-06-27 | 2017-09-15 | 北京必可测科技股份有限公司 | A kind of equipment fault detection method and system |
| CA3099659A1 (en) * | 2018-05-07 | 2019-11-14 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for data collection, learning, and streaming of machine signals for analytics and maintenance using the industrial internet of things |
| CN109782739A (en) * | 2019-01-29 | 2019-05-21 | 中国能源建设集团广东省电力设计研究院有限公司 | Repair method, device, computer equipment and the storage medium of equipment fault |
| CN109894476A (en) * | 2019-02-28 | 2019-06-18 | 北京首钢股份有限公司 | A kind of cold rolled silicon steel production line hydraulic equipment fault diagnosis method and device |
| CN109884533A (en) * | 2019-03-11 | 2019-06-14 | 北京百度网讯科技有限公司 | The diagnostic method and device of battery failures, equipment and storage medium |
| CN111856268A (en) * | 2019-04-24 | 2020-10-30 | 中矿龙科能源科技(北京)股份有限公司 | Motor and generator fault diagnosis system based on harmonic method |
| CN209947082U (en) * | 2019-07-23 | 2020-01-14 | 河北上元智能科技股份有限公司 | Highway tunnel electromechanical device fault detection system |
| CN112445193A (en) * | 2019-08-14 | 2021-03-05 | 珠海格力电器股份有限公司 | Method, device and equipment for predicting air conditioner fault and storage medium |
| CN112668727A (en) * | 2019-09-29 | 2021-04-16 | 北京国双科技有限公司 | Method and device for detecting equipment fault |
| CN110675079A (en) * | 2019-09-30 | 2020-01-10 | 腾讯科技（深圳）有限公司 | Fault data processing method and device and computer equipment |
| CN111177485A (en) * | 2019-12-16 | 2020-05-19 | 中建材智慧工业科技有限公司 | Method, device and medium for predicting device failure based on parameter rule matching |
| CN112650654A (en) * | 2020-12-11 | 2021-04-13 | 西安诺瓦星云科技股份有限公司 | Early warning method and device for display control visualization system, storage medium and processor |
| CN113077172A (en) * | 2021-04-19 | 2021-07-06 | 瑞湖智科数据(苏州)有限公司 | Equipment state trend analysis and fault diagnosis method |
| CN113538997A (en) * | 2021-07-14 | 2021-10-22 | 重庆电子工程职业学院 | Equipment predictive maintenance learning system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10732619B2 (en) | Method for monitoring driving unit of car body assembly line, and device therefor | |
| JP4856396B2 (en) | Method for creating a unified quality assessment for turbine mechanical systems and the like and providing an automatic fault diagnosis tool | |
| CN107678936B (en) | Business system pre-inspection method, server and computer readable storage medium | |
| CN113965397B (en) | Credit network security management method, apparatus, computer device and storage medium | |
| CN105912413B (en) | Method and device for evaluating the availability of a system, in particular a safety-critical system | |
| CN112115005B (en) | Test data acquisition method and device, computer equipment and storage medium | |
| CN109784502B (en) | On-site maintenance processing method and system based on fault equipment | |
| CN109656205B (en) | Defective product control method and device, electronic device and readable storage medium | |
| CN109760985B (en) | Method and device for material circulation checking, electronic equipment and readable storage medium | |
| CN112527484B (en) | Workflow breakpoint continuous running method and device, computer equipment and readable storage medium | |
| CN113157524B (en) | Big data based exception problem solving method, system, equipment and storage medium | |
| CN116345690B (en) | Power monitoring false alarm identification method and system based on power supply system equipment list | |
| CN112363920A (en) | Test case repairing method and device, computer equipment and storage medium | |
| CN115759357B (en) | PSCADA data-based power supply equipment safety prediction method, system, equipment and medium | |
| CN110149421A (en) | Method for monitoring abnormality, system, device and the computer equipment of domain name system | |
| CN114201090A (en) | Product production abnormity early warning system, method, computer equipment and storage medium | |
| CN114462650A (en) | Equipment fault processing method and device, electronic equipment and storage medium | |
| CN109815124B (en) | MBSE-based interlocking function defect analysis method and device and interlocking system | |
| CN112632330A (en) | Method and device for routing inspection of ATM equipment, computer equipment and storage medium | |
| CN109754094A (en) | Electromechanical equipment intelligence O&M method, system, equipment and storage medium | |
| CN114236314A (en) | Fault detection method, device, equipment and storage medium | |
| CN111177488B (en) | Metering equipment maintenance processing method and device, computer equipment and storage medium | |
| CN112381242A (en) | Nuclear power station equipment maintenance project data processing method and system | |
| CN112395125A (en) | Method and device for notifying page error report, computer equipment and storage medium | |
| CN113626227A (en) | Abnormal log information reporting method, intelligent terminal and storage medium |
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 |