CN118349808A - Fault detection method, device, electronic equipment, storage medium and system - Google Patents

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

Fault detection method, device, electronic device, storage medium and system

Technical Field

The present invention relates to the technical field of agricultural mechanization, and in particular to a fault detection method, device, electronic equipment, storage medium and system.

Background technique

Combine harvesters provide important equipment support for harvesting grain crops. In actual applications, due to the complex working environment of combine harvesters, differences in maturity, moisture content, density, etc. of different crops, and improper operation by drivers, it is easy to cause failures in key operating parts such as cutting, threshing, and cleaning of combine harvesters. Therefore, in order not to affect the normal operation of combine harvesters, it is very necessary to conduct rapid and accurate fault warning and diagnosis of combine harvesters.

In the prior art, speed sensors and torque sensors are generally installed on key operating parts of a combine harvester, such as a feeding auger, a bridge, and a threshing drum. By monitoring the changing patterns of the speed and torque of these operating parts, it is possible to analyze whether the combine harvester has a fault and determine the fault location.

However, the fault diagnosis method of the prior art is mainly based on the real-time detection information of a single sensor. When the speed and torque of the key operating parts of the combine harvester suddenly change within the normal working range, it is very easy to cause misdiagnosis. Therefore, the fault diagnosis method of the prior art has poor fault analysis ability.

Summary of the invention

The present invention provides a fault detection method, device, electronic equipment, storage medium and system, which are used to solve the problem that the fault diagnosis method in the prior art has poor fault analysis capability.

The present invention provides a fault detection method, comprising: acquiring real-time operating condition data of a combine harvester; retrieving a fault warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data; if a corresponding target fault type is retrieved from the fault warning knowledge base, outputting fault warning information of the target fault type; if a corresponding target fault type is retrieved from the fault diagnosis knowledge base, outputting fault diagnosis information of the target fault type; wherein the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs.

According to a fault detection method provided by the present invention, before obtaining the real-time operating condition data of the combine harvester, the method also includes: obtaining the historical operating condition data and fault types of the combine harvester; correlating the fault types with the historical operating condition data to obtain the operating condition change information of each fault type before the fault occurs and the operating condition change information when the fault occurs; establishing a fault warning knowledge base based on the operating condition change information of all fault types before the fault occurs, and establishing a fault diagnosis knowledge base based on the operating condition change information of all fault types when the fault occurs.

According to a fault detection method provided by the present invention, the real-time operating condition data includes at least one of the following: engine speed, feeding auger speed and torque, bridge speed and torque, threshing drum speed and torque, cleaning fan speed, vibrating screen frequency, and combine harvester operating speed; the target fault type includes at least one of the following items: blocking fault, belt breakage, and bearing failure.

According to a fault detection method provided by the present invention, the fault warning information is used to indicate the fault type, fault location and preventive measures of the combine harvester; the fault diagnosis information is used to indicate the fault type, fault location and solution of the combine harvester.

According to a fault detection method provided by the present invention, the obtaining of real-time operating condition data of the combine harvester includes: obtaining the real-time operating condition data from a condition data detection unit of the combine harvester through a data transmission module.

The present invention also provides a fault detection device, comprising: an acquisition module and a processing module; the acquisition module is used to acquire real-time operating condition data of a combine harvester; the processing module is used to retrieve a fault warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data; if the corresponding target fault type is retrieved from the fault warning knowledge base, the fault warning information of the target fault type is output; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, the fault diagnosis information of the target fault type is output; wherein the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs.

According to a fault detection device provided by the present invention, the acquisition module is also used to obtain the historical operating condition data and fault types of the combine harvester; the processing module is also used to correlate the fault types with the historical operating condition data to obtain the operating condition change information of each fault type before the fault occurs and the operating condition change information when the fault occurs; a fault warning knowledge base is established based on the operating condition change information of all fault types before the fault occurs, and a fault diagnosis knowledge base is established based on the operating condition change information of all fault types when the fault occurs.

According to a fault detection device provided by the present invention, the real-time operating condition data includes at least one of the following: engine speed, feeding auger speed and torque, bridge speed and torque, threshing drum speed and torque, cleaning fan speed, vibrating screen frequency, and combine harvester operating speed; the target fault type includes at least one of the following items: blocking fault, belt breakage, and bearing failure.

According to a fault detection device provided by the present invention, the fault warning information is used to indicate the fault type, fault location and preventive measures of the combine harvester; the fault diagnosis information is used to indicate the fault type, fault location and solution of the combine harvester.

According to the fault detection device provided by the present invention, the acquisition module is used to acquire the real-time operating condition data from the operating condition data detection unit of the combine harvester through the data transmission module.

The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-mentioned fault detection methods are implemented.

The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned fault detection methods are implemented.

The present invention also provides a fault detection system, including a combine harvester working condition data detection unit, a data transmission module and the above-mentioned fault detection device; the fault detection device includes a server, a combine harvester digital model, a fault warning knowledge base and a fault diagnosis knowledge base.

The fault detection method, device, electronic device, storage medium and system provided by the present invention can obtain the real-time working condition data of the combine harvester; retrieve the fault warning knowledge base or fault diagnosis knowledge base based on the real-time working condition data; if the corresponding target fault type is retrieved in the fault warning knowledge base, the fault warning information of the target fault type is output; if the corresponding target fault type is retrieved in the fault diagnosis knowledge base, the fault diagnosis information of the target fault type is output; wherein the fault warning knowledge base includes the working condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes the working condition change information of different fault types when the fault occurs. Through this scheme, the fault warning knowledge base or the fault diagnosis knowledge base can be retrieved based on the real-time working condition data to output the fault warning information or the fault diagnosis information. Since the fault warning knowledge base includes the working condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes the working condition change information of different fault types when the fault occurs, it is possible to avoid the phenomenon of inaccurate or even misdiagnosis of faults based on single sensor information, thereby improving the fault analysis capability.

BRIEF DESCRIPTION OF THE DRAWINGS

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

FIG1 is a schematic diagram of a flow chart of a fault detection method provided by the present invention;

FIG2 is a schematic diagram of the structure of a fault detection system provided by the present invention;

FIG3 is a second flow chart of the fault detection method provided by the present invention;

FIG4 is a schematic diagram of the structure of a fault detection device provided by the present invention;

FIG. 5 is a schematic diagram of the structure of an electronic device provided by the present invention.

Detailed ways

In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises one..." does not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present invention is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", etc. are used to distinguish between the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. are not limiting the quantity and execution order.

The embodiments of the present invention describe some exemplary embodiments for the purpose of explanation. It should be understood that the present invention can be implemented in other ways that are not specifically shown in the drawings.

The above implementation is described in detail below with reference to specific embodiments and drawings.

As shown in FIG1 , an embodiment of the present invention provides a fault detection method, which can be applied to a fault detection device. The fault detection method may include S101-S103:

S101. A fault detection device obtains real-time operating condition data of a combine harvester.

Optionally, as shown in FIG2 , an embodiment of the present 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 the combine harvester entity, and the working condition data detection unit may include an engine speed sensor, a feeding auger speed torque sensor, a bridge speed torque sensor, a drum speed torque sensor, a cleaning fan speed sensor, a vibrating screen frequency sensor, an operating speed sensor, and a data acquisition module corresponding to each sensor. The data transmission unit includes a transmission interface, a processor, a transmission module, and peripheral circuits such as power management, clock, and reset. The fault detection device includes a server, a digital model of the combine harvester, a fault warning knowledge base, and a fault diagnosis knowledge base, and the digital model of the combine harvester, the fault warning knowledge base, and the fault diagnosis knowledge base all run on the server.

Optionally, the fault detection device may obtain the real-time operating condition data from the operating condition data detection unit of the combine harvester through a data transmission module.

Specifically, during the operation of the combine harvester, the operating condition data detection unit can collect real-time operating condition data and transmit it to the data transmission unit through the bus of the data acquisition module. The data transmission unit can transmit the received real-time operating condition data to the server of the fault detection device.

Optionally, the above-mentioned real-time operating condition data may include at least one of the following: engine speed, feeding auger speed and torque, bridge speed and torque, threshing drum speed and torque, cleaning fan speed, vibrating screen frequency, and combine harvester operating 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 warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data.

Optionally, as shown in Figure 3, the fault detection device can retrieve the real-time operating condition data from the fault warning knowledge base and the fault diagnosis knowledge base through the digital model of the combine harvester. If the operating condition characteristics that match the real-time operating condition data are matched in the fault warning knowledge base, or the fault characteristics that match the real-time operating condition data are matched in the fault diagnosis knowledge base, the corresponding fault type is further determined.

Based on the above scheme, since the combine harvester itself generally does not have the ability to store a large amount of historical operation information and large-scale model training and fault analysis, the combine harvester digital model can be used to perform multi-dimensional and multi-level analysis on the real-time operating condition data and historical operating condition data of the combine harvester, thereby more accurately performing fault warning and diagnosis, in order to solve the problem of inaccurate fault diagnosis of existing combine harvesters.

Optionally, as shown in FIG3 , before obtaining the real-time operating condition data of the combine harvester, the fault detection device may obtain the historical operating condition data of the key components of the combine harvester and the types of faults that are prone to occur in the combine harvester; and perform correlation feature mining analysis on the types of faults and the historical operating condition data through a digital model of the combine harvester to obtain the operating condition change information of each fault type before the fault occurs and the operating condition change information when the fault occurs; finally, a fault warning knowledge base is established based on the operating condition change information of all fault types before the fault occurs, and a fault diagnosis knowledge base is established based on the operating condition change information of all fault types when the fault occurs.

Optionally, the above fault types include at least one of the following: a blocking fault, a belt breakage, and a bearing failure.

Specifically, the fault detection device can use machine learning algorithms such as association analysis, neural networks, and naive Bayes to perform correlation feature mining analysis on the combine harvester operating condition data and the types of combine harvester faults, so as to obtain the change rules of the speed and torque of each key component before a typical fault occurs, and the change rules of the speed and torque of each key component when a typical fault occurs, thereby establishing a fault warning knowledge base and a fault diagnosis knowledge base.

Based on the above scheme, since the failures of combine harvesters generally have correlation characteristics, comprehensive analysis based on a large amount of historical operating condition data can accurately grasp the operating condition characteristics before and when the failure occurs, thereby providing a retrieval basis for real-time fault detection.

S103. If the corresponding target fault type is retrieved from the fault warning knowledge base, the fault detection device outputs fault 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 above target fault type includes at least one of the following items: blocking fault, belt breakage, and bearing failure.

Optionally, the above-mentioned fault warning information can be used to indicate the fault type, fault location and preventive measures of the combine harvester; the fault diagnosis information can be used to indicate the fault type, fault location and solution of the combine harvester.

Specifically, during the operation of the combine harvester, its real-time operating condition data can be sent to the digital model of the combine harvester in the fault detection device through the data transmission module to achieve information synchronization between the combine harvester entity and the digital model of the combine harvester. After obtaining the real-time operating condition data, the digital model of the combine harvester can continuously search the fault warning knowledge base and perform feature matching on the change law of the operating condition data of the key components of the entity. When the operating condition data of the key components of the combine harvester matched from the fault warning knowledge base conforms to the change law of the working condition of the impending fault, the digital model of the combine harvester determines that the combine harvester is about to have a certain fault, and sends the corresponding fault warning information to the combine harvester for fault warning. The combine harvester driver can appropriately adjust the operating state of the combine harvester according to the fault warning information to avoid the fault. When a combine harvester entity fails during operation, the digital model of the combine harvester can perform matching analysis in the fault diagnosis knowledge base based on the operating condition data of the key components of the combine harvester before the failure. When the operating condition data of the key components of the combine harvester before the failure matches a certain fault, the fault is considered to have occurred, and the fault type, fault location and solution of the fault are sent to the combine harvester. The combine harvester driver takes the next step based on the fault diagnosis information.

Optionally, after sending the fault diagnosis information, the combine harvester digital model may update and supplement the target fault type and the changing rules of the real-time operating condition information in the fault diagnosis knowledge base as new fault diagnosis knowledge.

In an embodiment of the present invention, a fault warning knowledge base or a fault diagnosis knowledge base can be retrieved based on real-time operating condition data to output fault warning information or fault diagnosis information. Since the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs, it is possible to avoid inaccurate or even misdiagnosis of faults based on single sensor information, thereby improving the fault analysis capability.

The above mainly introduces the solution provided by the embodiment of the present invention from the perspective of the method. In order to achieve the above functions, it includes hardware structures and/or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment disclosed in this article, the embodiment of the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

The fault detection method provided in the embodiment of the present invention may be executed by a fault detection device or a control module for fault detection in the fault detection device. In the embodiment of the present invention, the fault detection device provided in the embodiment of the present invention is described by taking the fault detection device executing the fault detection method as an example.

It should be noted that the embodiment of the present invention can divide the functional modules of the fault detection device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present invention is schematic and is only a logical function division. There may be other division methods in actual implementation.

As shown in FIG4 , an embodiment of the present invention provides a fault detection device 400. The fault detection device 400 includes: an acquisition module 401 and a processing module 402. The acquisition module 401 can be used to acquire real-time operating condition data of the combine harvester; the processing module 402 can be used to retrieve a fault warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data; if the corresponding target fault type is retrieved from the fault warning knowledge base, the fault warning information of the target fault type is output; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, the fault diagnosis information of the target fault type is output; wherein, the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs.

Optionally, the acquisition module 401 is also used to obtain historical operating condition data and fault types of the combine harvester; the processing module 402 is also used to correlate the fault types with the historical operating condition data to obtain the operating condition change information of each fault type before the fault occurs and the operating condition change information when the fault occurs; a fault warning knowledge base is established based on the operating condition change information of all fault types before the fault occurs, and a fault diagnosis knowledge base is established based on the operating condition change information of all fault types when the fault occurs.

Optionally, the real-time operating condition data includes at least one of the following: engine speed, feed auger speed and torque, bridge speed and torque, threshing drum speed and torque, cleaning fan speed, vibrating screen frequency, and combine harvester operating speed; the target fault type includes at least one of the following: blockage fault, belt breakage, and bearing failure.

Optionally, the fault warning information is used to indicate the fault type, fault location and preventive measures of the combine harvester; the fault diagnosis information is used to indicate the fault type, fault location and solution of the combine harvester.

Optionally, the acquisition module 401 is used to acquire the real-time operating condition data from the operating condition data detection unit of the combine harvester through a data transmission module.

In an embodiment of the present invention, a fault warning knowledge base or a fault diagnosis knowledge base can be retrieved based on real-time operating condition data to output fault warning information or fault diagnosis information. Since the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs, it is possible to avoid inaccurate or even misdiagnosis of faults based on single sensor information, thereby improving the fault analysis capability.

FIG5 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG5 , the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the fault detection method, which includes: obtaining the real-time operating condition data of the combine harvester; retrieving a fault warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data; if the corresponding target fault type is retrieved from the fault warning knowledge base, then outputting the fault warning information of the target fault type; if the corresponding target fault type is retrieved from the fault diagnosis knowledge base, then outputting the fault diagnosis information of the target fault type; wherein the fault warning knowledge base includes the operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes the operating condition change information of different fault types when the fault occurs.

In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the fault detection method provided by the above-mentioned methods, and the method includes: obtaining real-time operating condition data of the combine harvester; retrieving a fault warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data; if the corresponding target fault type is retrieved in the fault warning knowledge base, outputting the fault warning information of the target fault type; if the corresponding target fault type is retrieved in the fault diagnosis knowledge base, outputting the fault diagnosis information of the target fault type; wherein the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs.

On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned fault detection methods, the methods comprising: obtaining real-time operating condition data of a combine harvester; retrieving a fault warning knowledge base or a fault diagnosis knowledge base based on the real-time operating condition data; if the corresponding target fault type is retrieved from the fault warning knowledge base, outputting fault 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; wherein the fault warning knowledge base includes operating condition change information of different fault types before the fault occurs, and the fault diagnosis knowledge base includes operating condition change information of different fault types when the fault occurs.

The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM/RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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.