A fault diagnosis method, device and equipment of a solenoid valve and a storage medium

Abstract

The application discloses a fault diagnosis method of an electromagnetic valve, comprising the following steps: obtaining target sensing data of a vehicle sensor, and performing data conversion on the target sensing data; performing fault diagnosis on a to-be-diagnosed electromagnetic valve according to the converted target sensing data and fault diagnosis parameters of the to-be-diagnosed electromagnetic valve, and determining diagnosis data of the to-be-diagnosed electromagnetic valve; determining fault identification parameters of the to-be-diagnosed electromagnetic valve according to the diagnosis data, determining a fault electromagnetic valve from the to-be-diagnosed electromagnetic valve according to the fault identification parameters, and taking the fault identification parameters corresponding to the fault electromagnetic valve as target identification parameters; determining fault feature data of the fault electromagnetic valve according to the target identification parameters, and determining a target fault cause of the fault electromagnetic valve based on the fault feature data. The diagnosis efficiency and diagnosis accuracy of the to-be-diagnosed electromagnetic valve can be improved.

Description

Technical Field

[0001] This invention relates to the field of vehicles, and more particularly to a method, apparatus, device, and storage medium for diagnosing faults in solenoid valves. Background Technology

[0002] Currently, AMT (Automated Mechanical Transmission) is widely used in the vehicle industry. AMT determines the optimal gear based on parameters such as vehicle speed, throttle position, and driver commands. While maintaining the basic structure of traditional mechanical transmissions, AMT offers advantages such as high transmission efficiency, compact structure, low cost, ease of manufacturing, reliable operation, and convenient operation. With the widespread application of AMT in vehicles, users have increasingly higher safety requirements for vehicles equipped with AMT. Currently, diagnosing faults in solenoid valves in vehicles equipped with AMT often requires extensive manual labor, resulting in low diagnostic efficiency and accuracy. Therefore, how to accurately diagnose faults in solenoid valves in vehicles equipped with AMT while reducing labor costs is a problem that needs to be solved. Summary of the Invention

[0003] This invention provides a method, apparatus, device, and storage medium for diagnosing faults in solenoid valves, which can realize automated fault location of solenoid valves under diagnosis, and improve the diagnostic efficiency and accuracy of solenoid valves under diagnosis.

[0004] According to one aspect of the present invention, a method for diagnosing faults in a solenoid valve is provided, comprising:

[0005] Acquire target sensing data from vehicle sensors, perform data conversion on the target sensing data, and determine the fault diagnosis parameters of the solenoid valve to be diagnosed corresponding to the vehicle sensor.

[0006] Based on the fault diagnosis parameters, the solenoid valve to be diagnosed is subjected to fault diagnosis to determine the diagnostic data of the solenoid valve to be diagnosed; wherein, the diagnostic data is an eight-bit array;

[0007] Based on the diagnostic data, the fault identification parameters of the solenoid valve to be diagnosed are determined, and based on the fault identification parameters, the faulty solenoid valve is identified from the solenoid valves to be diagnosed, and the fault identification parameters corresponding to the faulty solenoid valve are used as target identification parameters.

[0008] Based on the target identification parameters, the fault characteristic data of the faulty solenoid valve is determined, and based on the fault characteristic data, the target fault cause of the faulty solenoid valve is determined.

[0009] According to another aspect of the present invention, a fault diagnosis device for a solenoid valve is provided, the device comprising:

[0010] The sensor data conversion module is used to acquire target sensor data from vehicle sensors, convert the target sensor data, and determine the fault diagnosis parameters of the solenoid valve to be diagnosed corresponding to the vehicle sensor.

[0011] The diagnostic data determination module is used to perform fault diagnosis on the solenoid valve to be diagnosed based on the fault diagnosis parameters, and determine the diagnostic data of the solenoid valve to be diagnosed; wherein, the diagnostic data is an eight-bit array;

[0012] The target identification parameter determination module is used to determine the fault identification parameters of the solenoid valve to be diagnosed based on the diagnostic data, and to determine the faulty solenoid valve from the solenoid valves to be diagnosed based on the fault identification parameters, and to use the fault identification parameters corresponding to the faulty solenoid valve as the target identification parameters.

[0013] The target fault cause determination module is used to determine the fault characteristic data of the faulty solenoid valve according to the target identification parameters, and determine the target fault cause of the faulty solenoid valve based on the fault characteristic data.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the fault diagnosis method for the solenoid valve according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the fault diagnosis method for a solenoid valve according to any embodiment of the present invention.

[0019] The technical solution of this invention involves acquiring target sensing data from vehicle sensors and converting the target sensing data; based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, performing fault diagnosis on the solenoid valve to be diagnosed and determining the diagnostic data of the solenoid valve to be diagnosed; based on the diagnostic data, determining the fault identification parameters of the solenoid valve to be diagnosed, and based on the fault identification parameters, identifying the faulty solenoid valve from the solenoid valves to be diagnosed, and using the fault identification parameters corresponding to the faulty solenoid valve as the target identification parameters; based on the target identification parameters, determining the fault characteristic data of the faulty solenoid valve, and based on the fault characteristic data, determining the target fault cause of the faulty solenoid valve. This solves the problems of being unable to accurately locate the faulty solenoid valve from vehicle solenoid valves and the low efficiency of obtaining the fault cause of the faulty solenoid valve. The above solution acquires target sensing data of the solenoid valve to be diagnosed in the vehicle from vehicle sensors, determines the diagnostic data of the solenoid valve to be diagnosed based on the target sensing data and fault diagnosis parameters, determines the fault identification parameters based on the diagnostic data, identifies the faulty solenoid valve based on the fault identification parameters, and then determines the target fault cause of the faulty solenoid valve based on the fault identification parameters of the faulty solenoid valve. This system enables fault diagnosis of the solenoid valve under test based on sensor data from vehicle sensors, thereby achieving automated fault location of the solenoid valve under test. This improves the diagnostic efficiency and accuracy of the solenoid valve under test and saves on the labor costs of fault diagnosis.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a fault diagnosis method for a solenoid valve provided in Embodiment 1 of the present invention;

[0023] Figure 2 A flowchart illustrating a fault diagnosis method for a solenoid valve provided in Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of a fault diagnosis device for a solenoid valve provided in Embodiment 3 of the present invention;

[0025] Figure 4This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "candidate" and "target," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "etc.", and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1 This is a flowchart illustrating a method for diagnosing a solenoid valve according to Embodiment 1 of the present invention. This embodiment is applicable to diagnosing solenoid valve faults, particularly in situations where fault diagnosis parameters of the solenoid valve to be diagnosed are determined based on target sensing data from vehicle sensors, diagnostic data of the solenoid valve to be diagnosed is determined based on the fault diagnosis parameters, and the faulty solenoid valve and its target cause of failure are identified from the solenoid valves to be diagnosed based on the diagnostic data. This method can be executed by a solenoid valve fault diagnosis device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0030] S110: Acquire target sensing data from vehicle sensors and perform data conversion on the target sensing data.

[0031] In this embodiment, the vehicle sensors include a pressure sensor, an oil temperature sensor, and a displacement sensor. The solenoid valve to be diagnosed refers to the solenoid valve on the automatic transmission. The target sensing data refers to the valid sensing data from the vehicle sensors. Specifically, the solenoid valve sensor of the solenoid valve to be diagnosed is identified from the vehicle sensors. Based on the solenoid valve sensor, the solenoid valve sensing data of the solenoid valve to be diagnosed is acquired. The confidence level of the solenoid valve sensing data is determined, and the solenoid valve sensing data is filtered based on the confidence level to determine the target sensing data. The method for filtering the solenoid valve sensing data can be to pre-set a confidence threshold, compare the confidence level with the confidence threshold, and determine the solenoid valve sensing data with a confidence level greater than the confidence threshold as the target sensing data. The target sensing data is then converted into actual physical values.

[0032] For example, a method for determining the fault diagnosis parameters of the solenoid valve to be diagnosed corresponding to the vehicle sensor may be: determining the non-physical values ​​in the target sensing data, performing data conversion on the non-physical values, and converting the non-physical values ​​into actual physical values.

[0033] It is understandable that converting only the non-physical values ​​in the target sensing data to determine the actual physical values ​​can improve the conversion efficiency of the target sensing data.

[0034] S120. Based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, perform fault diagnosis on the solenoid valve to be diagnosed and determine the diagnostic data of the solenoid valve to be diagnosed.

[0035] The diagnostic data is an eight-bit array.

[0036] Fault diagnosis parameters refer to data that can be used to analyze whether there is a fault in the register to be diagnosed. Fault diagnosis parameters must be actual physical values.

[0037] Specifically, by using the low-side diagnostic register corresponding to the solenoid valve under test, fault diagnosis is performed on the solenoid valve based on the fault diagnosis parameters, and the corresponding diagnostic data for the solenoid valve under test is determined. The low-side diagnostic register is the register closest to the negative terminal of the power supply; one low-side diagnostic register corresponds to one solenoid valve under test, and the low-side diagnostic register can be used to diagnose electrical faults in the solenoid valve under test.

[0038] For example, vehicle displacement sensor data can be obtained from the displacement sensor, and the fault status of each solenoid valve to be diagnosed can be determined sequentially based on the vehicle displacement sensor data and diagnostic register data; fault diagnosis based on displacement sensor information and diagnostic register information is divided into fault detection when a valve opening command is given and fault detection when a valve closing command is given.

[0039] S130. Based on the diagnostic data, determine the fault identification parameters of the solenoid valve to be diagnosed, and based on the fault identification parameters, identify the faulty solenoid valve from the solenoid valves to be diagnosed, and use the fault identification parameters corresponding to the faulty solenoid valve as the target identification parameters.

[0040] Among them, the fault identification parameter can be a decimal value converted from diagnostic data.

[0041] Specifically, the eight-bit array corresponding to the diagnostic data is converted into a decimal value. Based on the pre-set fault discrimination method, it is determined whether the solenoid valve to be diagnosed corresponding to the decimal value is a faulty solenoid valve, so as to identify the faulty solenoid valve from the solenoid valves to be diagnosed, and the fault identification parameter corresponding to the faulty solenoid valve is used as the target identification parameter.

[0042] For example, a pre-set fault diagnosis method could be: if the decimal value is a first preset value, then the solenoid valve to be diagnosed is determined to be faulty; if the decimal value is a second preset value, then the solenoid valve to be diagnosed is determined not to be faulty. Both the first and second preset values ​​are positive integers, and they are not equal.

[0043] For example, the faulty solenoid valve can be identified from the solenoid valves to be diagnosed through the following sub-steps:

[0044] S1301. When the solenoid valve to be diagnosed is opened, the high four bits of the diagnostic data are used as the fault identification parameters of the solenoid valve to be diagnosed. If the value corresponding to the high four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the high four bits is determined to be a faulty solenoid valve.

[0045] In this context, "opening of the solenoid valve to be diagnosed" means that the solenoid valve to be diagnosed receives a valve opening command. The high four bits of the diagnostic data are the first to fourth bits of the eight-bit array corresponding to the diagnostic data, from left to right.

[0046] Specifically, when the solenoid valve to be diagnosed is opened, the high four bits of the diagnostic data are used as the fault identification parameters of the solenoid valve. If the decimal value corresponding to the high four bits is greater than 1, then the solenoid valve to be diagnosed corresponding to the high four bits is determined to be a faulty solenoid valve.

[0047] For example, when the solenoid valve to be diagnosed is opened, if the decimal value corresponding to the high four bits is 0, it means that the low-side diagnostic register has not performed fault diagnosis on the solenoid valve to be diagnosed; if the decimal value corresponding to the high four bits is 1, it means that the solenoid valve to be diagnosed is not a faulty solenoid valve.

[0048] For example, upon receiving a valve opening command (i.e., when the solenoid valve to be diagnosed is opened), the solenoid valve changes from a closed state to an open state. After a period of time following the valve opening command, the change in the displacement sensor value is first checked to see if it exceeds a preset threshold. If not, it indicates that the solenoid valve to be diagnosed is uncontrolled, meaning it may have an electrical fault. In this case, the diagnostic data corresponding to the solenoid valve needs to be read to determine the specific cause of the fault. The high four bits of the diagnostic register provide fault diagnosis feedback. Combining the displacement sensor data and the diagnostic data, the fault diagnosis of the solenoid valve is performed, and the corresponding fault is reported.

[0049] S1302. When the solenoid valve to be diagnosed is closed, the lower four bits of the diagnostic data are used as the fault identification parameters of the solenoid valve to be diagnosed. If the value corresponding to the lower four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the lower four bits is determined to be a faulty solenoid valve.

[0050] In the diagnostic data, the lower four bits are the fifth to eighth bits from left to right in the eight-bit array corresponding to the diagnostic data.

[0051] Specifically, when the solenoid valve to be diagnosed is closed, the lower four bits of the diagnostic data are used as the fault identification parameters for the solenoid valve. If the decimal value corresponding to the lower four bits is greater than 1, then the solenoid valve to be diagnosed corresponding to the lower four bits is determined to be a faulty solenoid valve.

[0052] For example, when the solenoid valve to be diagnosed is closed, if the decimal value corresponding to the lower four bits is 0, it means that the lower-side diagnostic register has not performed fault diagnosis on the solenoid valve to be diagnosed; if the decimal value corresponding to the lower four bits is 1, it means that the solenoid valve to be diagnosed is not a faulty solenoid valve.

[0053] For example, when a valve close command is received (i.e., the solenoid valve to be diagnosed is closed), after a certain period of time, the change in the displacement sensor value is first checked to see if it exceeds a preset threshold. If so, it indicates that the solenoid valve to be diagnosed is uncontrolled and may have an electrical fault. In this case, the diagnostic data of the solenoid valve to be diagnosed needs to be read to determine the specific cause of the fault. The lower four bits of the diagnostic register provide fault judgment feedback. Combining the displacement sensor data and the diagnostic data, the fault of the solenoid valve to be diagnosed is determined, and the corresponding fault is reported. In addition, to prevent false alarms, after a certain period of time has passed since the fault of the solenoid valve to be diagnosed was reported, the fault is confirmed, and the fault status of the solenoid valve to be diagnosed is set to 1.

[0054] It is understandable that when the solenoid valve to be diagnosed is open, the faulty solenoid valve can be identified from the solenoid valves to be diagnosed based on the high four bits of the diagnostic data; when the solenoid valve to be diagnosed is closed, the faulty solenoid valve can be identified from the solenoid valves to be diagnosed based on the low four bits of the diagnostic data. This can improve the efficiency of identifying the faulty solenoid valve.

[0055] S140. Based on the target identification parameters, determine the fault characteristic data of the faulty solenoid valve, and based on the fault characteristic data, determine the target fault cause of the faulty solenoid valve.

[0056] Among them, the fault characteristic data is the decimal data corresponding to the target identification parameters.

[0057] For example, the target fault cause of the faulty solenoid valve can be determined from the candidate fault causes based on the fault characteristic data and the correspondence between the candidate characteristic data and the candidate fault causes; the candidate fault causes include: power short circuit fault, high temperature fault and overcurrent fault.

[0058] Specifically, the correspondence between candidate feature data and candidate fault causes can be pre-defined. Candidate feature data includes fault feature data.

[0059] When the solenoid valve to be diagnosed is open, the correspondence between candidate feature data and candidate fault causes can be as follows: Candidate feature data of 0 indicates that the low-side diagnostic register has not performed fault diagnosis on the solenoid valve to be diagnosed; candidate feature data of 1 indicates that the solenoid valve to be diagnosed is not a faulty solenoid valve; candidate feature data of 2 indicates that the solenoid valve to be diagnosed has a power short circuit fault; candidate feature data of 3 indicates that the solenoid valve to be diagnosed has a high temperature fault during overcurrent; candidate feature data of 4 indicates that the solenoid valve to be diagnosed has an overcurrent fault; candidate feature data of 5 indicates that the solenoid valve to be diagnosed has an excessively high temperature during non-overcurrent periods; candidate feature data of 6-15 are meaningless.

[0060] When the solenoid valve to be diagnosed is closed, the correspondence between candidate feature data and candidate fault causes can be as follows: candidate feature data of 0 indicates that the low-side diagnostic register has not performed fault diagnosis on the solenoid valve to be diagnosed; candidate feature data of 1 indicates that the solenoid valve to be diagnosed is not a faulty solenoid valve; candidate feature data of 2 indicates that the solenoid valve to be diagnosed has an open circuit fault; candidate feature data of 3 indicates that the solenoid valve to be diagnosed has a short circuit to ground fault; candidate feature data of 4-15 are meaningless.

[0061] The above solution can improve the efficiency of fault diagnosis for faulty solenoid valves.

[0062] Optionally, to prevent erroneous diagnosis of the solenoid valve under diagnosis, if the low-side diagnostic register continuously determines that the solenoid valve under diagnosis is faulty for a period exceeding a time threshold, the solenoid valve under diagnosis is determined to be faulty. If the solenoid valve under diagnosis is faulty, it is necessary to determine whether to return the vehicle to neutral or disengage it based on the cause of the faulty solenoid valve, and to alert the driver via the instrument panel that the vehicle solenoid valve has malfunctioned and needs to be stopped for inspection and troubleshooting, thereby ensuring the driver's safety.

[0063] The technical solution provided in this embodiment acquires target sensing data from vehicle sensors and performs data conversion on the target sensing data. Based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, a fault diagnosis is performed on the solenoid valve to be diagnosed to determine the diagnostic data of the solenoid valve to be diagnosed. Based on the diagnostic data, the fault identification parameters of the solenoid valve to be diagnosed are determined, and based on the fault identification parameters, the faulty solenoid valve is identified from the solenoid valves to be diagnosed, and the fault identification parameters corresponding to the faulty solenoid valve are used as target identification parameters. Based on the target identification parameters, the fault characteristic data of the faulty solenoid valve is determined, and based on the fault characteristic data, the target fault cause of the faulty solenoid valve is determined. This solves the problems of being unable to accurately locate the faulty solenoid valve from vehicle solenoid valves and the low efficiency of obtaining the fault cause of the faulty solenoid valve. The above solution acquires target sensing data of the solenoid valve to be diagnosed in the vehicle from vehicle sensors, determines the diagnostic data of the solenoid valve to be diagnosed based on the target sensing data and fault diagnosis parameters, determines the fault identification parameters based on the diagnostic data, identifies the faulty solenoid valve based on the fault identification parameters, and then determines the target fault cause of the faulty solenoid valve based on the fault identification parameters of the faulty solenoid valve. This system enables fault diagnosis of the solenoid valve under test based on sensor data from vehicle sensors, thereby achieving automated fault location of the solenoid valve under test. This improves the diagnostic efficiency and accuracy of the solenoid valve under test and saves on the labor costs of fault diagnosis.

[0064] Example 2

[0065] Figure 2 This is a flowchart of a fault diagnosis method for a solenoid valve provided in Embodiment 2 of the present invention. This embodiment optimizes the above embodiment and provides a preferred implementation method for acquiring target sensing data from vehicle sensors. Specifically, as shown... Figure 2 As shown, the method includes:

[0066] S210. Perform fault diagnosis on the vehicle sensors, and determine the valid and invalid sensors from the vehicle sensors based on the diagnosis results.

[0067] In this context, a valid sensor refers to a vehicle sensor that is not faulty. An invalid sensor refers to a vehicle sensor that is faulty.

[0068] Specifically, based on the solenoid valve sensing data acquired by the vehicle sensors, fault diagnosis is performed on the vehicle sensors. Normal and abnormal sensing data are identified from the solenoid valve sensing data; the vehicle sensors corresponding to normal sensing data are identified as valid sensors; and the vehicle sensors corresponding to abnormal sensing data are identified as invalid sensors.

[0069] For example, the determination of valid and invalid sensors from vehicle sensors can be achieved through the following sub-steps:

[0070] S2101. Determine the amount of sensor change at preset time intervals between vehicle sensors, and determine candidate sensors from among the vehicle sensors based on the comparison results of the amount of sensor change and the change threshold.

[0071] The sensing change is the difference between two solenoid valve sensing data acquired by the same vehicle sensor at a preset time interval. A candidate sensor is the vehicle sensor whose sensing change is less than a threshold value. The threshold value can be set according to actual needs, and different vehicle sensors have different threshold values.

[0072] Specifically, the system acquires solenoid valve sensing data from vehicle sensors in real time and calculates the sensing changes of the vehicle sensors at preset time intervals based on the solenoid valve sensing data. The sensing changes are compared with a threshold value; if the sensing changes are less than the threshold value, the vehicle sensor is identified as a candidate sensor.

[0073] S2102. Determine whether the candidate sensing data of the candidate sensor at the current moment meets the range conditions of the candidate sensor.

[0074] Among them, candidate sensor data refers to the solenoid valve sensor data collected from candidate sensor data.

[0075] For example, for oil temperature sensors and air pressure sensors, the range conditions can be set according to the hardware characteristics of the AMT system itself and the engineer's engineering experience; for displacement sensors, the range conditions can be set according to the mechanical characteristics of the transmission.

[0076] Specifically, the candidate sensor data collected by the candidate sensor at the current moment is matched with the measurement range of the candidate sensor. If the candidate sensor data is greater than the maximum measurement value in the measurement range or less than the minimum measurement value in the measurement range, it is determined that the candidate sensor data does not meet the range conditions of the candidate sensor; otherwise, it is determined that the candidate sensor data meets the range conditions of the candidate sensor.

[0077] S2103. If yes, then determine that the candidate sensor corresponding to the candidate sensing data is a valid sensor; otherwise, determine that the candidate sensor corresponding to the candidate sensing data is an invalid sensor.

[0078] Specifically, if the candidate sensing data meets the range conditions of the candidate sensor, the candidate sensor corresponding to the candidate sensing data is determined to be a valid sensor; if the candidate sensing data does not meet the range conditions of the candidate sensor, the candidate sensor corresponding to the candidate sensing data is determined to be an invalid sensor.

[0079] S220: Use the current sensing data of the effective sensor at the current moment and the previous sensing data of the invalid sensor at the previous moment as the target sensing data of the vehicle sensor.

[0080] Specifically, after identifying the valid and invalid sensors, the current sensing data of the valid sensors at the current moment is used. The previous sensing data of the invalid sensors at the previous moment is used as the current sensing data of the invalid sensors at the current moment, and the driver is notified of a sensor malfunction through the sensor alarm device.

[0081] S230, Perform data conversion on the target sensing data.

[0082] S240. Based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, perform fault diagnosis on the solenoid valve to be diagnosed and determine the diagnostic data of the solenoid valve to be diagnosed.

[0083] S250. Based on the diagnostic data, determine the fault identification parameters of the solenoid valve to be diagnosed, and based on the fault identification parameters, identify the faulty solenoid valve from the solenoid valves to be diagnosed, and use the fault identification parameters corresponding to the faulty solenoid valve as the target identification parameters.

[0084] S260. Based on the target identification parameters, determine the fault characteristic data of the faulty solenoid valve, and based on the fault characteristic data, determine the target fault cause of the faulty solenoid valve.

[0085] The technical solution of this embodiment first performs fault diagnosis on the vehicle sensors. Based on the fault diagnosis results, it identifies valid and invalid sensors. The current sensing data of the valid sensors and the previous sensing data of the invalid sensors are used as the target sensing data for the vehicle sensors. Then, based on the target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, the solenoid valve to be diagnosed is diagnosed, identifying the faulty solenoid valve and the cause of its failure. This solution, by performing fault diagnosis on the vehicle sensors before diagnosing the solenoid valve using the sensor data, and determining the target sensing data based on the fault diagnosis results, improves the reliability of the target sensing data, thereby improving the accuracy of fault diagnosis for the solenoid valve to be diagnosed.

[0086] Example 3

[0087] Figure 3This is a schematic diagram of a fault diagnosis device for a solenoid valve provided in Embodiment 3 of the present invention. This embodiment is applicable to situations involving fault diagnosis of solenoid valves. Figure 3 As shown, the fault diagnosis device for the solenoid valve includes: a sensor data conversion module 310, a diagnostic data determination module 320, a target identification parameter determination module 330, and a target fault cause determination module 340.

[0088] Among them, the sensor data conversion module 310 is used to acquire target sensor data from vehicle sensors and convert the target sensor data.

[0089] The diagnostic data determination module 320 is used to perform fault diagnosis on the solenoid valve to be diagnosed based on the converted target sensing data and the solenoid valve to be diagnosed, and to determine the diagnostic data of the solenoid valve to be diagnosed; wherein, the diagnostic data is an eight-bit array.

[0090] The target identification parameter determination module 330 is used to determine the fault identification parameters of the solenoid valve to be diagnosed based on the diagnostic data, and to identify the faulty solenoid valve from the solenoid valves to be diagnosed based on the fault identification parameters, and to use the fault identification parameters corresponding to the faulty solenoid valve as the target identification parameters.

[0091] The target fault cause determination module 340 is used to determine the fault characteristic data of the faulty solenoid valve according to the target identification parameters, and to determine the target fault cause of the faulty solenoid valve based on the fault characteristic data.

[0092] The technical solution provided in this embodiment acquires target sensing data from vehicle sensors and performs data conversion on the target sensing data. Based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, a fault diagnosis is performed on the solenoid valve to be diagnosed to determine the diagnostic data of the solenoid valve to be diagnosed. Based on the diagnostic data, the fault identification parameters of the solenoid valve to be diagnosed are determined, and based on the fault identification parameters, the faulty solenoid valve is identified from the solenoid valves to be diagnosed, and the fault identification parameters corresponding to the faulty solenoid valve are used as target identification parameters. Based on the target identification parameters, the fault characteristic data of the faulty solenoid valve is determined, and based on the fault characteristic data, the target fault cause of the faulty solenoid valve is determined. This solves the problems of being unable to accurately locate the faulty solenoid valve from vehicle solenoid valves and the low efficiency of obtaining the fault cause of the faulty solenoid valve. The above solution acquires target sensing data of the solenoid valve to be diagnosed in the vehicle from vehicle sensors, determines the diagnostic data of the solenoid valve to be diagnosed based on the target sensing data and fault diagnosis parameters, determines the fault identification parameters based on the diagnostic data, identifies the faulty solenoid valve based on the fault identification parameters, and then determines the target fault cause of the faulty solenoid valve based on the fault identification parameters of the faulty solenoid valve. This system enables fault diagnosis of the solenoid valve under test based on sensor data from vehicle sensors, thereby achieving automated fault location of the solenoid valve under test. This improves the diagnostic efficiency and accuracy of the solenoid valve under test and saves on the labor costs of fault diagnosis.

[0093] For example, the target identification parameter determination module 330 includes:

[0094] The solenoid valve opening diagnostic unit is used to use the high four bits of the diagnostic data as the fault identification parameters of the solenoid valve when the solenoid valve to be diagnosed is opened. If the value corresponding to the high four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the high four bits is determined to be a faulty solenoid valve.

[0095] The solenoid valve closure diagnostic unit is used to use the lower four bits of the diagnostic data as fault identification parameters of the solenoid valve when the solenoid valve to be diagnosed is closed. If the value corresponding to the lower four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the lower four bits is determined to be a faulty solenoid valve.

[0096] For example, the sensor data conversion module 310 includes:

[0097] The sensor diagnostic unit is used to diagnose faults in vehicle sensors and, based on the diagnostic results, identify valid and invalid sensors from the vehicle's sensor pool.

[0098] The target sensing data determination unit is used to take the current sensing data of the effective sensor at the current moment and the previous sensing data of the invalid sensor at the previous moment as the target sensing data of the vehicle sensor.

[0099] For example, the sensor diagnostic unit is specifically used for:

[0100] Determine the amount of sensor change at preset time intervals between vehicle sensors, and determine candidate sensors from the vehicle sensors based on the comparison results of the amount of sensor change and the change threshold.

[0101] Determine whether the candidate sensor's current sensing data meets the candidate sensor's range conditions;

[0102] If so, the candidate sensor corresponding to the candidate sensing data is determined to be a valid sensor; otherwise, the candidate sensor corresponding to the candidate sensing data is determined to be an invalid sensor.

[0103] For example, the sensor data conversion module 310 is specifically used for:

[0104] Identify the non-physical values ​​in the target sensing data and perform data transformation on the non-physical values ​​to convert them into actual physical values.

[0105] For example, the target fault cause determination module 340 is specifically used for:

[0106] Based on the fault characteristic data and the correspondence between candidate characteristic data and candidate fault causes, the target fault cause of the faulty solenoid valve is determined from the candidate fault causes; the candidate fault causes include: power short circuit fault, high temperature fault and overcurrent fault.

[0107] The fault diagnosis device for the solenoid valve provided in this embodiment can be applied to the fault diagnosis method for the solenoid valve provided in any of the above embodiments, and has the corresponding functions and beneficial effects.

[0108] Example 4

[0109] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0110] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0111] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0112] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a fault diagnosis method for a solenoid valve.

[0113] In some embodiments, the solenoid valve fault diagnosis method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the solenoid valve fault diagnosis method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the solenoid valve fault diagnosis method by any other suitable means (e.g., by means of firmware).

[0114] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0118] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0119] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0120] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0121] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A fault diagnosis method for a solenoid valve, characterized in that, include: Acquire target sensing data from vehicle sensors and perform data conversion on the target sensing data; Based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, the fault diagnosis of the solenoid valve to be diagnosed is performed to determine the diagnostic data of the solenoid valve to be diagnosed; wherein, the diagnostic data is an eight-bit array. Based on the diagnostic data, the fault identification parameters of the solenoid valve to be diagnosed are determined, and based on the fault identification parameters, the faulty solenoid valve is identified from the solenoid valves to be diagnosed, and the fault identification parameters corresponding to the faulty solenoid valve are used as target identification parameters. Based on the target identification parameters, the fault characteristic data of the faulty solenoid valve is determined, and based on the fault characteristic data, the target fault cause of the faulty solenoid valve is determined. Determining the fault identification parameters of the solenoid valve to be diagnosed, and identifying the faulty solenoid valve from the solenoid valves to be diagnosed based on the fault identification parameters, includes: When the solenoid valve to be diagnosed is opened, the high four bits of the diagnostic data are used as the fault identification parameters of the solenoid valve to be diagnosed. If the value corresponding to the high four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the high four bits is determined to be a faulty solenoid valve. When the solenoid valve to be diagnosed is closed, the lower four bits of the diagnostic data are used as the fault identification parameters of the solenoid valve to be diagnosed. If the value corresponding to the lower four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the lower four bits is determined to be a faulty solenoid valve.

2. The method according to claim 1, characterized in that, Acquire target sensing data from vehicle sensors, including: Perform fault diagnosis on vehicle sensors, and determine the valid and invalid sensors from the vehicle sensors based on the diagnosis results; The current sensing data of the effective sensor at the current moment, and the previous sensing data of the invalid sensor at the previous moment, are used as the target sensing data of the vehicle sensor.

3. The method according to claim 2, characterized in that, Fault diagnosis of vehicle sensors, and determination of valid and invalid sensors from the vehicle sensors based on the diagnosis results, including: Determine the amount of sensor change at preset time intervals between vehicle sensors, and determine candidate sensors from the vehicle sensors based on the comparison result of the amount of sensor change and the change threshold. Determine whether the candidate sensing data of the candidate sensor at the current moment meets the range conditions of the candidate sensor; If so, the candidate sensor corresponding to the candidate sensing data is determined to be a valid sensor; otherwise, the candidate sensor corresponding to the candidate sensing data is determined to be an invalid sensor.

4. The method according to claim 1, characterized in that, Data transformation of the target sensing data includes: The non-physical values ​​in the target sensing data are identified, and the non-physical values ​​are converted into actual physical values.

5. The method according to claim 1, characterized in that, Based on the fault characteristic data, the target fault cause of the faulty solenoid valve is determined, including: Based on the fault characteristic data and the correspondence between candidate characteristic data and candidate fault causes, the target fault cause of the faulty solenoid valve is determined from the candidate fault causes; the candidate fault causes include: power short circuit fault, high temperature fault and overcurrent fault.

6. A fault diagnosis device for a solenoid valve, characterized in that, include: The sensor data conversion module is used to acquire target sensor data from vehicle sensors and convert the target sensor data. The diagnostic data determination module is used to perform fault diagnosis on the solenoid valve to be diagnosed based on the converted target sensing data and the fault diagnosis parameters of the solenoid valve to be diagnosed, and determine the diagnostic data of the solenoid valve to be diagnosed; wherein, the diagnostic data is an eight-bit array. The target identification parameter determination module is used to determine the fault identification parameters of the solenoid valve to be diagnosed based on the diagnostic data, and to determine the faulty solenoid valve from the solenoid valves to be diagnosed based on the fault identification parameters, and to use the fault identification parameters corresponding to the faulty solenoid valve as the target identification parameters. The target fault cause determination module is used to determine the fault characteristic data of the faulty solenoid valve according to the target identification parameters, and determine the target fault cause of the faulty solenoid valve based on the fault characteristic data. The target identifier parameter determination module includes: The solenoid valve opening diagnostic unit is used to use the high four bits of the diagnostic data as the fault identification parameters of the solenoid valve when the solenoid valve to be diagnosed is opened. If the value corresponding to the high four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the high four bits is determined to be a faulty solenoid valve. The solenoid valve closure diagnostic unit is used to use the lower four bits of the diagnostic data as the fault identification parameter of the solenoid valve when the solenoid valve to be diagnosed is closed. If the value corresponding to the lower four bits is greater than 1, the solenoid valve to be diagnosed corresponding to the lower four bits is determined to be a faulty solenoid valve.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the fault diagnosis method for the solenoid valve according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the fault diagnosis method for the solenoid valve according to any one of claims 1-5.

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