CN118349808A - Fault detection method, device, electronic equipment, storage medium and system - Google Patents
Fault detection method, device, electronic equipment, storage medium and system Download PDFInfo
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Abstract
The invention provides a fault detection method, a fault detection device, electronic equipment, a storage medium and a storage system, which are applied to the technical field of agricultural mechanization. The method comprises the following steps: acquiring real-time operation working condition data of the combine harvester; retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
Description
Technical Field
The present invention relates to the field of agricultural mechanization technologies, and in particular, to a fault detection method, a fault detection device, an electronic device, a storage medium, and a system.
Background
The combine provides an important equipment support for harvesting grain crops. In practical application, because the working environment of the combine harvester is complex, the maturity, the water content, the density and other factors of different crops are different, and the factors such as improper operation of a driver are easy to cause the faults of key operation components such as cutting, threshing and cleaning of the combine harvester, the combined harvester is necessary to be subjected to rapid and accurate fault early warning and diagnosis in order not to influence the normal operation of the combine harvester.
In the prior art, a rotating speed sensor and a torque sensor are generally arranged on key operation components such as a feeding auger, a bridge, a threshing cylinder and the like of the combine harvester, and the change rule of the rotating speed and the torque of the operation components is monitored, so that whether the combine harvester has faults or not is analyzed, and the fault position is determined.
However, the fault diagnosis method in the prior art mainly judges according to real-time detection information of a single sensor, and when the rotation speed and the torque of key operation components of the combine harvester are suddenly changed in a normal working range, misdiagnosis is easily caused, so that the fault analysis capability of the fault diagnosis method in the prior art is poor.
Disclosure of Invention
The invention provides a fault detection method, a fault detection device, electronic equipment, storage media and a fault detection system, which are used for solving the problem of poor fault analysis capability of a fault diagnosis method in the prior art.
The invention provides a fault detection method, which comprises the following steps: acquiring real-time operation working condition data of the combine harvester; retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
According to the fault detection method provided by the invention, before the real-time operation working condition data of the combine harvester are acquired, the method further comprises the following steps: acquiring historical operation condition data and fault types of the combine harvester; performing association analysis on the fault types and the historical operation condition data to obtain operation condition change information of each fault type before occurrence of a fault and operation condition change information when the fault occurs; and establishing a fault early warning knowledge base according to the operation condition change information of all fault types before the occurrence of the fault, and establishing a fault diagnosis knowledge base according to the operation condition change information of all fault types when the fault occurs.
According to the fault detection method provided by the invention, the real-time operation working condition data comprises at least one of the following: engine speed, feeding auger speed and torque, gap bridge speed and torque, threshing cylinder speed and torque, cleaning fan speed, vibrating screen frequency, combine harvester operation speed; the target fault category includes at least one of: blockage failure, belt breakage, bearing failure.
According to the fault detection method provided by the invention, the fault early warning information is used for indicating the fault type, the fault position and the precaution measures of the combine harvester; the fault diagnosis information is used for indicating the fault type, fault position and solving measures of the combine harvester.
According to the invention, the fault detection method for acquiring real-time operation working condition data of the combine harvester comprises the following steps: and acquiring the real-time working condition data from a working condition data detection unit of the combine harvester through a data transmission module.
The invention also provides a fault detection device, comprising: the device comprises an acquisition module and a processing module; the acquisition module is used for acquiring real-time operation working condition data of the combine harvester; the processing module is used for retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation working condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
According to the fault detection device provided by the invention, the acquisition module is also used for acquiring historical operation working condition data and fault types of the combine harvester; the processing module is further used for carrying out association analysis on the fault types and the historical operation condition data to obtain operation condition change information of each fault type before the occurrence of the fault and operation condition change information when the fault occurs; and establishing a fault early warning knowledge base according to the operation condition change information of all fault types before the occurrence of the fault, and establishing a fault diagnosis knowledge base according to the operation condition change information of all fault types when the fault occurs.
According to the invention, the fault detection device provided by the invention, the real-time operation working condition data comprises at least one of the following: engine speed, feeding auger speed and torque, gap bridge speed and torque, threshing cylinder speed and torque, cleaning fan speed, vibrating screen frequency, combine harvester operation speed; the target fault category includes at least one of: blockage failure, belt breakage, bearing failure.
According to the invention, the fault early warning information is used for indicating the fault type, the fault position and the precaution measures of the combine harvester; the fault diagnosis information is used for indicating the fault type, fault position and solving measures of the combine harvester.
According to the fault detection device provided by the invention, the acquisition module is used for acquiring the real-time working condition data from the working condition data detection unit of the combine harvester through the data transmission module.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the fault detection method as described in any of the above when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the fault detection method as described in any of the above.
The invention also provides a fault detection system, which comprises a working condition data detection unit, a data transmission module and the fault detection device of the combine harvester; the fault detection device comprises a server, a combine harvester digital model, a fault early warning knowledge base and a fault diagnosis knowledge base.
The fault detection method, the fault detection device, the electronic equipment, the storage medium and the fault detection system can acquire real-time operation working condition data of the combine harvester; retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur. According to the scheme, the fault early warning knowledge base or the fault diagnosis knowledge base can be searched based on the real-time operation condition data so as to output fault early warning information or fault diagnosis information, and the fault early warning knowledge base comprises operation condition change information of different fault types before faults occur, and the fault diagnosis knowledge base comprises operation condition change information of different fault types when the faults occur, so that the phenomena of inaccurate fault diagnosis, misdiagnosis and the like based on single sensor information can be avoided, and the fault analysis capability is improved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a fault detection method according to the present invention;
FIG. 2 is a schematic diagram of a fault detection system provided by the present invention;
FIG. 3 is a second flow chart of the fault detection method according to the present invention;
FIG. 4 is a schematic diagram of a fault detection device according to the present invention;
Fig. 5 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "e.g." in an embodiment should not be taken as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
It should be noted that, in this document, 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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present invention is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
In order to clearly describe the technical solution of the embodiment of the present invention, in the embodiment of the present invention, the words "first", "second", etc. are used to distinguish identical items or similar items having substantially the same function and effect, and those skilled in the art will understand that the words "first", "second", etc. are not limited in number and execution order.
Embodiments of the invention some exemplary embodiments have been described for illustrative purposes, it being understood that the invention may be practiced otherwise than as specifically shown in the accompanying drawings.
The foregoing implementations are described in detail below with reference to specific embodiments and accompanying drawings.
As shown in fig. 1, an embodiment of the present invention provides a fault detection method that can be applied to a fault detection device. The fault detection method may include S101-S103:
s101, acquiring real-time operation working condition data of the combine harvester by a fault detection device.
Optionally, as shown in fig. 2, the embodiment of the invention further provides a fault detection system, which includes a working condition data detection unit, a data transmission unit and a fault detection device. The working condition data detection unit is a detection unit in a combine harvester entity, and can comprise an engine rotating speed sensor, a feeding screw feeder rotating speed torque sensor, a gap bridge rotating speed torque sensor, a roller rotating speed torque sensor, a cleaning fan rotating speed sensor, a vibrating screen frequency sensor, an operation speed sensor and a data acquisition module corresponding to each sensor. The data transmission unit comprises a transmission interface, a processor, a transmission module, a power management, a clock, a reset and other peripheral circuits. The fault detection device comprises a server, a combine harvester digital model, a fault early warning knowledge base and a fault diagnosis knowledge base, wherein the combine harvester digital model, the fault early warning knowledge base and the fault diagnosis knowledge base all run on the server.
Optionally, the fault detection device may acquire the real-time working condition data from the working condition data detection unit of the combine harvester through the data transmission module.
Specifically, in the operation process of the combine harvester, the working condition data detection unit can collect real-time working condition data and transmit the real-time working condition data to the data transmission unit through the bus of the data collection module, and the data transmission unit can transmit the received real-time working condition data to the server of the fault detection device.
Optionally, the real-time operation condition data may include at least one of: engine speed, feeding auger speed and torque, gap bridge speed and torque, threshing cylinder speed and torque, cleaning fan speed, vibrating screen frequency, and combine harvester operation speed.
Optionally, the transmission interface may be a CAN interface, and the transmission module may be a 4G or 5G transmission module.
S102, the fault detection device searches a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time working condition data.
Optionally, as shown in fig. 3, the fault detection device may retrieve the obtained real-time operation condition data from the fault early-warning knowledge base and the fault diagnosis knowledge base through the digital model of the combine harvester, and if the fault early-warning knowledge base matches the condition characteristics matched with the real-time operation condition data or the fault diagnosis knowledge base matches the fault characteristics matched with the real-time operation condition data, further determine the corresponding fault type.
Based on the scheme, the combine harvester does not generally have the capability of storing a large amount of historical operation information and large-scale model training and fault analysis, so that the real-time operation working condition data and the historical working condition data of the combine harvester can be subjected to multi-dimensional and multi-level analysis through the digital model of the combine harvester, further fault early warning and diagnosis can be more accurately performed, and the problem of inaccurate fault diagnosis of the existing combine harvester is solved.
Alternatively, as shown in fig. 3, before acquiring the real-time operation condition data of the combine harvester, the fault detection device may acquire the historical operation condition data of the key components of the combine harvester and the fault types that easily occur in the combine harvester; performing associated feature mining analysis on the fault types and the historical operation condition data through a digital model of the combine harvester to obtain operation condition change information of each fault type before occurrence of the fault and operation condition change information when the fault occurs; and finally, establishing a fault early warning knowledge base according to the operation condition change information of all fault types before the fault occurs, and establishing a fault diagnosis knowledge base according to the operation condition change information of all fault types when the fault occurs.
Optionally, the fault categories include at least one of: blockage failure, belt breakage, bearing failure.
Specifically, the fault detection device may perform association feature mining analysis on the operation condition data of the combine harvester and the fault type of the combine harvester by using association analysis, a neural network, a naive bayes and other machine learning algorithms, so as to obtain a change rule of the rotating speed and the torque of each key component before the typical fault occurs and a change rule of the rotating speed and the torque of each key component when the typical fault occurs, thereby establishing a fault early warning knowledge base and a fault diagnosis knowledge base.
Based on the scheme, the faults of the combine harvester generally have relevance characteristics, so that comprehensive analysis is performed based on a large amount of historical operation condition data, and the operation condition characteristics before and during the faults can be accurately mastered, thereby providing a retrieval basis for real-time fault detection.
S103, if the corresponding target fault type is retrieved from the fault early warning knowledge base, the fault detection device outputs fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, the fault detection device outputs fault diagnosis information of the target fault type.
Optionally, the target fault category includes at least one of: blockage failure, belt breakage, bearing failure.
Optionally, the fault early warning information may be used to indicate the fault type, fault location and precautions of the combine harvester; the fault diagnosis information may be used to indicate the kind of fault, the location of the fault and the resolution of the combine harvester.
Specifically, during the operation process of the combine harvester, real-time operation working condition data can be sent to the digital model of the combine harvester of the fault detection device through the data transmission module, so that the information synchronization of the entity of the combine harvester and the digital model of the combine harvester is realized. After the digital model of the combine harvester obtains real-time operation working condition data, a fault early warning knowledge base can be continuously searched, characteristic matching is carried out on the change rule of the operation working condition data of the entity key parts, when the operation working condition data of the key parts of the combine harvester is matched with the working condition change rule of the impending fault from the fault early warning knowledge base, the digital model of the combine harvester judges that a certain fault is impending to the combine harvester, corresponding fault early warning information is sent to the combine harvester for carrying out fault early warning, and a driver of the combine harvester can properly adjust the operation state of the combine harvester according to the fault early warning information, so that the fault is avoided. When the operation process of the combine harvester entity is faulty, the digital model of the combine harvester can carry out matching analysis in a fault diagnosis knowledge base according to the operation condition data of the key parts before the combine harvester is faulty, and when the operation condition data of the key parts before the combine harvester is faulty is searched to be matched with a certain fault, the fault is considered to occur, and the fault type, the fault position and the solving measures of the fault are sent to the combine harvester. The combine driver performs the next process based on the fault diagnosis information.
Optionally, after sending the fault diagnosis information, the digital model of the combine harvester can update and supplement the target fault type and the change rule of the real-time operation working condition information in the fault diagnosis knowledge base as new fault diagnosis knowledge.
In the embodiment of the invention, the fault early warning knowledge base or the fault diagnosis knowledge base can be searched based on the real-time operation condition data to output the fault early warning information or the fault diagnosis information, and the fault diagnosis knowledge base comprises the operation condition change information of different fault types before the occurrence of the fault, so that the phenomena of inaccurate fault diagnosis, even misdiagnosis and the like based on single sensor information can be avoided, and the fault analysis capability is improved.
The foregoing description of the solution provided by the embodiments of the present invention has been mainly presented in terms of a method. To achieve the above functions, it includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the fault detection method provided by the embodiment of the invention, the execution main body can be a fault detection device or a control module for fault detection in the fault detection device. In the embodiment of the invention, the fault detection device provided by the embodiment of the invention is described by taking a fault detection method executed by the fault detection device as an example.
It should be noted that, in the embodiment of the present invention, the fault detection device may be divided into functional modules according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware or in software functional modules. Optionally, the division of the modules in the embodiment of the present invention is schematic, which is merely a logic function division, and other division manners may be implemented in practice.
As shown in fig. 4, an embodiment of the present invention provides a fault detection device 400. The fault detection apparatus 400 includes: an acquisition module 401 and a processing module 402. The acquiring module 401 may be configured to acquire real-time working condition data of the combine harvester; the processing module 402 may be configured to retrieve a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time working condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
Optionally, the obtaining module 401 is further configured to obtain historical operation condition data and fault types of the combine harvester; the processing module 402 is further configured to perform a correlation analysis on the fault types and the historical operation condition data, so as to obtain operation condition change information of each fault type before occurrence of a fault and operation condition change information when occurrence of the fault; and establishing a fault early warning knowledge base according to the operation condition change information of all fault types before the occurrence of the fault, and establishing a fault diagnosis knowledge base according to the operation condition change information of all fault types when the fault occurs.
Optionally, the real-time operation condition data includes at least one of: engine speed, feeding auger speed and torque, gap bridge speed and torque, threshing cylinder speed and torque, cleaning fan speed, vibrating screen frequency, combine harvester operation speed; the target fault category includes at least one of: blockage failure, belt breakage, bearing failure.
Optionally, the fault early warning information is used for indicating the fault type, fault position and precautions of the combine harvester; the fault diagnosis information is used for indicating the fault type, fault position and solving measures of the combine harvester.
Optionally, the acquiring module 401 is configured to acquire, through a data transmission module, the real-time working condition data from a working condition data detecting unit of the combine harvester.
In the embodiment of the invention, the fault early warning knowledge base or the fault diagnosis knowledge base can be searched based on the real-time operation condition data to output the fault early warning information or the fault diagnosis information, and the fault diagnosis knowledge base comprises the operation condition change information of different fault types before the occurrence of the fault, so that the phenomena of inaccurate fault diagnosis, even misdiagnosis and the like based on single sensor information can be avoided, and the fault analysis capability is improved.
Fig. 5 illustrates a physical schematic diagram of an electronic device, as shown in fig. 5, which may include: processor 510, communication interface (Communications Interface) 520, memory 530, and communication bus 540, wherein processor 510, communication interface 520, memory 530 complete communication with each other through communication bus 540. Processor 510 may invoke logic instructions in memory 530 to perform a fault detection method comprising: acquiring real-time operation working condition data of the combine harvester; retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
Further, the logic instructions in the memory 530 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the fault detection method provided by the above methods, the method comprising: acquiring real-time operation working condition data of the combine harvester; retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the above-provided fault detection methods, the method comprising: acquiring real-time operation working condition data of the combine harvester; retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; the fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A fault detection method, comprising:
acquiring real-time operation working condition data of the combine harvester;
retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation condition data;
If the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type;
The fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
2. The method of claim 1, wherein prior to the acquiring real-time operating condition data of the combine, the method further comprises:
acquiring historical operation condition data and fault types of the combine harvester;
Performing association analysis on the fault types and the historical operation condition data to obtain operation condition change information of each fault type before occurrence of a fault and operation condition change information when the fault occurs;
And establishing a fault early warning knowledge base according to the operation condition change information of all fault types before the occurrence of the fault, and establishing a fault diagnosis knowledge base according to the operation condition change information of all fault types when the fault occurs.
3. The fault detection method of claim 1, wherein the real-time operating condition data comprises at least one of: engine speed, feeding auger speed and torque, gap bridge speed and torque, threshing cylinder speed and torque, cleaning fan speed, vibrating screen frequency, combine harvester operation speed;
the target fault category includes at least one of: blockage failure, belt breakage, bearing failure.
4. The fault detection method according to claim 1, wherein the fault pre-warning information is used to indicate a fault type, a fault location, and precautions of the combine harvester; the fault diagnosis information is used for indicating the fault type, fault position and solving measures of the combine harvester.
5. The method of claim 1, wherein the acquiring real-time operating condition data of the combine comprises:
and acquiring the real-time working condition data from a working condition data detection unit of the combine harvester through a data transmission module.
6. A fault detection device, comprising: the device comprises an acquisition module and a processing module;
the acquisition module is used for acquiring real-time operation working condition data of the combine harvester;
The processing module is used for retrieving a fault early warning knowledge base or a fault diagnosis knowledge base based on the real-time operation working condition data; if the corresponding target fault type is retrieved from the fault early warning knowledge base, outputting fault early warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type;
The fault diagnosis knowledge base comprises operation condition change information of different fault types before faults occur.
7. The fault detection device of claim 6, wherein,
The acquisition module is also used for acquiring historical operation working condition data and fault types of the combine harvester;
The processing module is further used for carrying out association analysis on the fault types and the historical operation condition data to obtain operation condition change information of each fault type before the occurrence of the fault and operation condition change information when the fault occurs; and establishing a fault early warning knowledge base according to the operation condition change information of all fault types before the occurrence of the fault, and establishing a fault diagnosis knowledge base according to the operation condition change information of all fault types when the fault occurs.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the fault detection method according to any one of claims 1 to 5 when the program is executed.
9. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps in the fault detection method according to any one of claims 1 to 5.
10. A fault detection system comprises a working condition data detection unit, a data transmission module and a fault detection device of a combine harvester; the fault detection device comprises a server, a combine harvester digital model, a fault early warning knowledge base and a fault diagnosis knowledge base.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410758234.6A CN118349808A (en) | 2024-06-13 | 2024-06-13 | Fault detection method, device, electronic equipment, storage medium and system |
Applications Claiming Priority (1)
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| US20080059839A1 (en) * | 2003-10-31 | 2008-03-06 | Imclone Systems Incorporation | Intelligent Integrated Diagnostics |
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| CN114611701A (en) * | 2022-02-25 | 2022-06-10 | 中国核电工程有限公司 | Monitoring system and method for nuclear chemical process |
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| US20080059839A1 (en) * | 2003-10-31 | 2008-03-06 | Imclone Systems Incorporation | Intelligent Integrated Diagnostics |
| CN101833497A (en) * | 2010-03-30 | 2010-09-15 | 山东高效能服务器和存储研究院 | Computer fault management system based on expert system method |
| CN103455026A (en) * | 2013-08-23 | 2013-12-18 | 王绍兰 | Method and device for diagnosis and early warning of vehicle faults |
| CN108871434A (en) * | 2018-05-30 | 2018-11-23 | 北京必创科技股份有限公司 | A kind of on-line monitoring system and method for slewing |
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