A diagnostic process abnormality monitoring method, device, medium, OBD module and vehicle

Abstract

The embodiment of the application discloses a kind of diagnostic process abnormality monitoring method, device, medium, OBD module and vehicle;Based on abnormality monitoring method, the leakage failure that can occur in fault diagnosis process is included in the main object of monitoring, by the signal monitoring of the object to be monitored, especially the signal monitoring of the evaporation system of fuel vehicle, on the basis of analyzing signal characteristics, with existing hardware structure, the abnormality monitoring of fault diagnosis system is realized;In addition, the related scheme is also applicable to the development of computer storage medium, OBD module and intelligent vehicle, and the upgrading of original system can be conveniently realized by the upgrading of control software.

Description

Technical Field

[0001] This invention belongs to the field of intelligent vehicle technology, and particularly relates to a method, device, medium, OBD module, and vehicle for monitoring abnormalities in the diagnostic process. Background Technology

[0002] Fault diagnosis systems, especially On-Board Diagnostic (OBD) systems for engines, are widely used, bringing convenience and performance improvements to vehicle intelligence and automation. However, misdiagnosis by fault diagnosis systems often causes problems in product application; therefore, monitoring systems for fault diagnosis systems have emerged. With the upgrading of vehicle fuel evaporation emission standards, leakage monitoring and desorption flow monitoring of evaporation systems have become two key applications.

[0003] There are three main types of leak detection solutions: 1) Actively establishing positive pressure in the fuel tank system and determining whether a leak exists based on the degree of pressure establishment, such as the fuel emission leak diagnostic module DMTL (Diagnostic Module Tank Leakage); 2) Actively establishing negative pressure in the fuel tank system and determining whether a leak exists based on its pressure holding capacity; 3) Passively relying on temperature changes to establish positive or negative pressure and determining whether a leak exists, such as the engine off natural vacuum method EONV (Engine Off Natural Vacuum) and the natural vacuum leak detection method NVLD (Natural Vacuum Leak Detection).

[0004] This invention addresses the misjudgment problem in the second approach. For example... Figure 2 , Figure 3 As shown, the inventors discovered that due to insufficient understanding of the hardware layout of the evaporation system, or limited space in the vehicle, the hardware layout of the evaporation system may be unreasonable. For example, the installation position of the relevant valves on the fuel tank may be unreasonable, the pipeline may have a large degree of bend, or the fuel tank may be easily deformed. This can lead to insufficient connectivity of the entire evaporation system and obvious throttling phenomenon. These problems may cause misdiagnosis of leaks. Summary of the Invention

[0005] This invention discloses a diagnostic process anomaly monitoring method, device, medium, OBD module, and vehicle. Based on the anomaly monitoring method, this invention includes possible leakage faults during the fault diagnosis process as the main monitoring target. By monitoring the signal of the monitored target, especially the evaporation system of fuel vehicles, and based on the analysis of signal characteristics, the anomaly monitoring of the fault diagnosis system is realized using existing hardware structure.

[0006] Furthermore, the same solutions are applicable to the development of computer storage media, OBD modules, and intelligent vehicles, and existing systems can be easily upgraded through the upgrade of control software.

[0007] Specifically, this method initializes the monitoring process by acquiring operating condition information; wherein, the operating condition information includes the working status of the actuator and several measured values ​​of the signal detection unit; its working status includes the valve opening degree and / or on / off state.

[0008] Furthermore, by determining the current monitoring process, different feature recognition routines are initiated accordingly. The monitoring process here includes a first monitoring process and a second monitoring process, which correspond to different inspection states of the object to be monitored. These inspection states can be flexibly configured based on existing hardware, as long as their core observation data can be obtained. The observation data here mainly includes pressure data at the corresponding location.

[0009] Further, the monitoring loop is entered, and the object to be monitored is continuously scanned and observed until the monitoring process ends or a corresponding abnormal status prompt is received; among them, the working status of the object to be monitored is determined by initializing feature data or solving feature data.

[0010] Specifically, pressure data of at least one measurement point of the unit to be monitored is acquired by scanning at a preset first time interval or step size; the relationship between the feature data and the feature threshold is compared cyclically until the monitoring cycle ends or is exited; wherein, the feature data is a statistic and / or function of the pressure data.

[0011] Furthermore, if no abnormal information is detected when the monitoring loop ends or exits, the preset diagnostic process continues; if an abnormality is detected, the exit routine is executed.

[0012] The aforementioned actuators include a first valve and a second valve. By changing the on / off state or opening degree of the valves, the first monitoring process and the second monitoring process can be actively switched.

[0013] In engine fault detection applications, the unit to be monitored typically includes a fuel tank, carbon canister, pipelines, sensors, and actuators; the diagnostic process typically includes the fault diagnosis process built into the unit to be monitored; the method of the present invention is used to further monitor the fault diagnosis process built into the unit to be monitored, thereby avoiding misjudgment in the fault diagnosis process.

[0014] Furthermore, the monitoring process can be optimized by selecting different statistical measures or monitoring functions; the statistical measures include flow integral data and flushing time data; among them, the flow integral in the negative pressure diagnosis stage is calculated by time integration based on the gas flow rate (kg / h) in the desorption pipeline, and the flushing time is the time required for the oil tank pressure to reach the target pressure from atmospheric pressure; the statistical data amplifies or extracts the anomalies to be monitored, thereby improving the accuracy of monitoring.

[0015] Specifically, during the first monitoring process, the pressure data of the unit to be monitored gradually decreases from the atmospheric pressure in the open state until it reaches the first preset value; the unit to be monitored is in the process of establishing negative pressure or in the process of establishing negative pressure where there is a leak.

[0016] During the second monitoring process, the actuators of the monitored unit are all in the off state, and the monitored unit is in a pressure-holding state or a pressure-holding state with a leakage point.

[0017] The monitoring process can operate at different stages:

[0018] If both the first and second valves are closed and the pressure data reaches the first preset value, the monitoring unit will enter the second monitoring process.

[0019] If the first valve changes from open to closed, and the opening of the second valve gradually increases from 0 with a preset gradient, then the monitoring process is the first monitoring process; when the pressure value corresponding to the pressure data gradually decreases to the first preset value, the second valve is closed, and the second monitoring process begins.

[0020] Furthermore, in the context of engine fault diagnosis, the aforementioned first valve can typically be a carbon canister shut-off valve, which includes an open state and a closed state. Generally, the switching transition time of the carbon canister shut-off valve is required to be less than a preset time length to avoid excessive interference to the monitoring process due to valve action. In addition, the leakage of the carbon canister shut-off valve should be less than a preset value, also to reduce the excessive introduction of interference factors into the monitoring process.

[0021] The second valve here is a carbon canister valve. The opening degree of the carbon canister valve can be adjusted between 0 and a preset value to construct a gradual observation condition for the monitoring process. By observing this gradual process and extracting features, possible anomalies during the process can be determined.

[0022] Specifically, the first valve can be controlled by an electric or pneumatic on / off valve, and the second valve can be controlled by an electric or pneumatic regulating valve; the former operates in an on / off state, and the latter provides an analog quantity to the object to be monitored.

[0023] This invention also discloses an anomaly monitoring device for a diagnostic process, comprising a signal detection unit, a feature solving unit, and a monitoring output unit.

[0024] The signal detection unit provides basic data for the monitoring process; by acquiring operating condition information and related observations, it assists other components in feature extraction and identification of the process to be monitored. The operating condition information includes the working status of the actuator and the measurement values ​​of the signal detection unit; the working status includes the valve's opening degree and / or on / off state.

[0025] As mentioned above, the feature solving unit is used to determine the current monitoring process and the data characteristics unique to this monitoring process; wherein, the monitoring process includes a first monitoring process and a second monitoring process, which correspond to different working states of the process to be monitored.

[0026] Meanwhile, the monitoring output unit, while operating in a monitoring loop or during the process, determines the presence or absence of anomalies by initializing or solving feature data.

[0027] Specifically, the monitoring output unit scans and acquires pressure data of at least one measurement point of the unit to be monitored at a preset first time interval or step size, and continuously determines the presence or absence of anomalies by cyclically comparing the relationship between the feature data and the feature threshold until the monitoring cycle ends or is exited; wherein, the feature data is a statistical quantity and / or function of the pressure data; based on this scanning process, the monitoring device amplifies or extracts the anomalies of the system, so that fault information that is difficult to obtain through a single observation can be revealed.

[0028] Furthermore, if no abnormal information is detected when the monitoring output unit ends or exits the monitoring loop, the preset diagnostic process continues to be executed; if an abnormality is detected, the exit routine is executed to avoid misjudgment.

[0029] Specifically, the actuators include the first valve and the second valve; the units to be monitored include the oil tank, carbon canister, pipelines, sensors, and actuators; the diagnostic process includes the fault diagnosis process of the units to be monitored.

[0030] Furthermore, the aforementioned statistics or functions may include flow integral data and flushing time data; wherein, during the negative pressure diagnosis phase, the flow integral is calculated by integrating the time based on the gas flow rate (kg / h) in the desorption pipeline, and the flushing time is the time required for the tank pressure to reach the target pressure from atmospheric pressure;

[0031] Furthermore, in the first monitoring process, the pressure data of the unit under monitoring gradually decreases from the open atmospheric pressure until it reaches the first preset value; the unit under monitoring is in the process of establishing negative pressure or in the process of establishing negative pressure where there is a leak. In the second monitoring process, all actuators of the unit under monitoring are in the off state, and the unit under monitoring is in the pressure holding state or in the pressure holding state where there is a leak.

[0032] If both the first and second valves are closed and the pressure data reaches the first preset value, the monitoring unit enters the second monitoring process; if the first valve changes from open to closed and the opening of the second valve gradually increases from 0 with a preset gradient, the monitoring process is the first monitoring process; when the pressure value corresponding to the pressure data gradually decreases to the first preset value, the second valve is closed and the second monitoring process begins.

[0033] For applications related to engine fault diagnosis, the first valve is a carbon canister shut-off valve, which includes an open state and a closed state; the switching transition time of the carbon canister shut-off valve is less than a preset time length, and the leakage of the carbon canister shut-off valve is less than a preset value; the second valve is a carbon canister valve, the opening degree of which can be adjusted between 0 and a preset value.

[0034] Furthermore, the first valve is controlled by an electric or pneumatic on / off valve, and the second valve is controlled by an electric or pneumatic regulating valve.

[0035] Furthermore, the method of the present invention can also be used to upgrade computer storage media, so that when the medium storing computer programs is read or accessed, the method related to the present invention is implemented; for applications in the OBD field, the method of the present invention and the above-mentioned chip media are equally applicable, and for vehicle applications, the method, device, chip, and module of the present invention are equally applicable.

[0036] Since changing the hardware of the evaporation system is time-consuming and costly, and cannot be done in the short term, the monitoring method and related products disclosed in this invention can be implemented in the existing system through software upgrades and minimal hardware changes, thereby improving the monitoring level of the fault diagnosis system.

[0037] It should be noted that the terms "first," "second," and similar terms used in this article are merely for describing the constituent elements of the technical solution and do not constitute a limitation on the technical solution, nor should they be interpreted as an indication or implication of the importance of the corresponding elements; elements with terms such as "first," "second," or similar terms indicate that at least one of the elements is included in the corresponding technical solution. Attached Figure Description

[0038] To more clearly illustrate the technical solution of the present invention and facilitate a further understanding of its technical effects, features, and objectives, the present invention will be described in detail below with reference to the accompanying drawings. The drawings constitute an essential part of the specification and are used together with Embodiment 1 of the present invention to illustrate the technical solution of the present invention, but do not constitute a limitation on the present invention.

[0039] The same reference numerals in the attached diagrams represent the same parts, specifically:

[0040] Figure 1A schematic diagram illustrating the leakage monitoring principle of negative pressure in an oil tank is provided for an embodiment of the anomaly monitoring method and device of the present invention.

[0041] Figure 2 This is a comparison chart of pressure performance in diagnosing abnormalities using an embodiment of the abnormality monitoring method and device of the present invention;

[0042] Figure 3 This is an example of a sudden drop and rebound in pressure during the later stages of vacuuming in the embodiment of the abnormal monitoring method and device of the present invention;

[0043] Figure 4 This is a graph showing the pressure change rate relationship in an embodiment of the anomaly monitoring method and device of the present invention;

[0044] Figure 5 This is a graph showing the time derivative relationship of pressure change rate in an embodiment of the anomaly monitoring method and device of the present invention.

[0045] Figure 6 This is a schematic diagram of the flow integral distribution when the target pressure decreases according to an embodiment of the monitoring method and device of the present invention;

[0046] Figure 7 This is a schematic diagram of the hardware layout corresponding to an embodiment of the monitoring method and device of the present invention;

[0047] Figure 8 This is a schematic diagram of the monitoring cycle in an embodiment of the monitoring method and device of the present invention;

[0048] Figure 9 This is a block diagram of the monitoring principle and a schematic diagram of the information structure of an embodiment of the monitoring method and device of the present invention;

[0049] Figure 10 This is a schematic diagram of the structural composition of an embodiment of the monitoring device of the present invention;

[0050] in:

[0051] 001 - First monitoring process (carbon canister shut-off valve closed, carbon canister valve gradually opened; i.e., the target negative pressure establishment process),

[0052] 002 - Second monitoring process (carbon canister shut-off valve closed, carbon canister valve closed; i.e., pressure holding process),

[0053] 011-Signal Detection Unit

[0054] 055 - Feature Solving Element

[0055] 066-Monitoring Output Unit;

[0056] 100 - First pressure (target negative pressure),

[0057] 101 - First pressure curve (typical pressure curve of a healthy fuel tank when the carbon canister shut-off valve is closed and the carbon canister valve is gradually opened).

[0058] 103 - Second pressure curve (typical pressure curve for large leakage when the carbon canister shut-off valve is closed and the carbon canister valve is gradually opened),

[0059] 105 - Third pressure curve (typical curve with carbon canister shut-off valve closed, carbon canister valve closed, and leakage not less than 1mm),

[0060] 107 - Fourth pressure curve (typical pressure curve with carbon canister shut-off valve closed, carbon canister valve closed, and no leakage)

[0061] 108 - Abnormal pressure curve 1 (rapid pressure drop during the vacuuming phase, which is the first abnormal characteristic),

[0062] 109 - Abnormal pressure curve 2 (the pressure rises rapidly during the pressure holding process, which is the second abnormal feature);

[0063] 111 - Second pressure (atmospheres)

[0064] 201 - First abnormal feature (sudden pressure drop in the later stage of vacuuming),

[0065] 203 - Fifth pressure curve (diagnosis complete, carbon canister shut-off valve open),

[0066] 333 - No abnormality detected (abnormality flag reset)

[0067] 500 - Feature data refresh process / loop (refreshes data at a preset period),

[0068] The process of calculating and solving eigenvalues ​​for 510, 520, 530, and 540.

[0069] 600-Monitoring Loop (Feature Data Acquisition and Judgment Loop Steps)

[0070] 628 - Abnormal flag set,

[0071] 610, 620, 630, 640 - Monitoring anomaly determination,

[0072] Determining pressure fluctuations at points 611, 613, and 615.

[0073] 617 - Determination of the number of pressure fluctuations

[0074] 666 - Abnormal flags (or operations)

[0075] 701 - First Container (Fuel Tank)

[0076] 702 - First sensor (fuel tank pressure sensor),

[0077] 703 - First Valve (Carbon Canister Valve)

[0078] 705 - Second valve (carbon canister shut-off valve),

[0079] 709 - First adsorption and filtration device (carbon canister),

[0080] 777 - The fault diagnosis process to be monitored (e.g., a diagnostic process in OBD).

[0081] 800 - Adjacent units (e.g., engine intake unit)

[0082] 801 - Third valve (e.g., intake manifold throttle valve),

[0083] 803 - First piping (e.g., intake manifold),

[0084] 999 - Exit the routine (e.g., restart the monitoring process, exit the diagnostic process, or end the monitoring process). Detailed Implementation

[0085] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Of course, the specific embodiments described below are merely illustrative of the technical solutions of the present invention, and not intended to limit the invention. Furthermore, the parts described in the embodiments or drawings are merely illustrative examples of relevant parts of the present invention, and not the entirety of the invention.

[0086] like Figure 9 The diagram shows an abnormal monitoring method for the diagnostic process disclosed in an embodiment of the present invention, which initializes system parameters by acquiring operating condition information; the operating condition information includes the working status of the actuator and the measurement value of the signal detection unit 011; the working status includes the valve opening degree and / or switch status.

[0087] Furthermore, by determining the current monitoring process, cyclic monitoring is performed in the controllable and mutually convertible first monitoring process 001 and second monitoring process 002, and a determination flag is output.

[0088] Specifically, such as Figure 8 and Figure 9 By entering monitoring loop 600, after initializing the feature data, the feature data 510, 520, 530, 540, and 5N0 are further solved, where N is a natural number and represents the number of feature data or feature data groups.

[0089] Furthermore, pressure data 712, 722, 732, and 7M2 of at least one measurement point of the unit to be monitored 700 are acquired by scanning at a preset first time interval or step size. Here, M is a natural number, representing the number of pressure sensor measurement points. Usually, only one of these measurement points needs to be selected. The selection of each measurement point can be flexibly chosen with the aim of facilitating installation and construction and acquiring pressure and related data at the corresponding location.

[0090] Furthermore, by iteratively comparing the relationship between feature data 510, 520, 530, 540, and 5N0 and feature thresholds until the monitoring cycle ends or exits 600, monitoring support is provided for the fault diagnosis unit during daily work cycles. Among them, feature data 510, 520, 530, 540, and 5N0 are statistics and / or functions of pressure data 712, 722, 732, and 7M2, used to discover abnormal states that are difficult to detect by a single or small number of measurements through the cumulative effect of data.

[0091] Specifically, if no such event is detected when the monitoring loop ends or exits 600... Figure 2 If the error messages 101 and 107 are displayed, then continue execution as follows. Figure 4 , 5 The diagnostic process shown in steps 777 is as follows: If abnormalities 103 and 105 are detected, the exit routine 999 is executed.

[0092] The actuator includes a first valve 705 and a second valve 703; the monitored unit 700 includes an oil tank 701, a carbon canister 709, pipelines, sensors, and the actuator; the diagnostic process 777 includes a fault diagnosis process for the monitored unit 700.

[0093] Furthermore, the statistics or functions here include flow integral data and flushing time data; among them, the flow integral in the negative pressure diagnosis stage is calculated by time integration based on the gas flow rate (kg / h) in the desorption pipeline, and the flushing time is the time required for the oil tank pressure to reach the target pressure from atmospheric pressure;

[0094] Specifically, such as Figure 1 , Figure 2 As shown, in the first monitoring process 001, the pressure data 712, 722, 732, and 7M2 of the unit to be monitored 700 gradually decrease from the atmospheric pressure 111 in the open state until they reach the first preset value 100; the unit to be monitored 700 is in the negative pressure establishment process or in the negative pressure establishment process where there is a leak.

[0095] In addition, during the second monitoring process 002, the actuators of the unit to be monitored 700 are all in the off state, and the unit to be monitored 700 is in a pressure-holding state or a pressure-holding state with a leakage point.

[0096] If both the first valve 705 and the second valve 703 are in the closed state, and the pressure data 712, 722, 732, and 7M2 reach the first preset value of 100, then the monitoring unit enters the second monitoring process 002.

[0097] If the first valve 705 changes from open to closed, and the opening degree of the second valve 703 gradually increases from 0 with a preset gradient, then the monitoring process is the first monitoring process 001; when the pressure values ​​corresponding to the pressure data 712, 722, 732, and 7M2 gradually decrease to the first preset value 100, the second valve 703 is closed, and the second monitoring process 002 begins.

[0098] Among them, the first valve 705 is a carbon canister shut-off valve, which includes an open state and a closed state; the switching transition time of the carbon canister shut-off valve is less than the preset time length, and the leakage of the carbon canister shut-off valve is less than the preset value; the second valve is a carbon canister valve, and the opening degree of the carbon canister valve can be adjusted between 0 and the preset value.

[0099] Furthermore, the first valve 705 can be controlled by an electric or pneumatic switching valve, and the second valve 703 can be controlled by an electric or pneumatic regulating valve.

[0100] Furthermore, such as Figure 10 The anomaly monitoring device includes a signal detection unit 011, a feature solving unit 055, and a monitoring output unit 066.

[0101] The signal detection unit 011 acquires operating condition information, which includes the operating status of the actuator and the measured values ​​of the signal detection unit 011. The operating status includes the valve opening degree and / or on / off state.

[0102] The feature solving unit 055 determines the current monitoring process; the monitoring process includes the first monitoring process 001 and the second monitoring process 002.

[0103] Furthermore, such as Figure 8 , Figure 9 and Figure 10 When the monitoring output unit 066 is running in the monitoring cycle 600 state or process, after initializing the feature data, it solves for the feature data 510, 520, 530, 540, and 5N0, where N = 4 and N represents the number of feature data or feature data groups.

[0104] Furthermore, pressure data 712, 722, 732, 7M2 of at least one measurement point of the unit to be monitored 700 are acquired by scanning at a preset first time interval or step size, where M=1 and M represents the number of measurement points of the pressure sensor.

[0105] Furthermore, the relationship between feature data 510, 520, 530, 540, and 540 and feature thresholds is compared cyclically until the monitoring loop 600 ends or exits; wherein, feature data 510, 520, 530, 540, and 540 are statistics and / or functions of a certain pressure data in the pressure data 712, 722, 732, and 742 at multiple time points.

[0106] If no abnormal information 101 or 107 is detected when the monitoring output unit 066 ends or exits the monitoring loop 600, the preset diagnostic process 777 continues to be executed; if abnormalities 103 or 105 are detected, the exit routine 999 is executed.

[0107] Specifically, such as Figure 7 The actuator includes a first valve 705 and a second valve 703; the unit to be monitored 700 includes an oil tank 701, a carbon canister 709, pipelines, sensors, and actuators; the diagnostic process 777 includes a fault diagnosis process for the unit to be monitored 700.

[0108] Furthermore, the aforementioned statistics or functions include flow integral data and flushing time data; wherein, during the negative pressure diagnosis stage, the flow integral is calculated by integrating the time based on the gas flow rate (kg / h) in the desorption pipeline, and the flushing time is the time required for the tank pressure to reach the target pressure from atmospheric pressure;

[0109] Specifically, such as Figure 1 In the first monitoring process 001, the pressure data 712, 722, 732, and 7M2 of the unit to be monitored 700 gradually decrease from the atmospheric pressure 111 in the open state until they reach the first preset value 100; the unit to be monitored 700 is in the negative pressure establishment process or in the negative pressure establishment process where there is a leak.

[0110] In the second monitoring process 002, the actuators of the unit to be monitored 700 are all in the off state, and the unit to be monitored 700 is in a pressure-holding state or a pressure-holding state with a leakage point.

[0111] If both the first valve 705 and the second valve 703 are in the closed state, and the pressure data 712, 722, 732, and 7M2 reach the first preset value of 100, then the monitoring unit enters the second monitoring process 002.

[0112] If the first valve 705 changes from open to closed, and the opening degree of the second valve 703 gradually increases from 0 with a preset gradient, then the monitoring process is the first monitoring process 001; when the pressure values ​​corresponding to the pressure data 712, 722, 732, and 7M2 gradually decrease to the first preset value 100, the second valve 703 is closed, and the second monitoring process 002 begins.

[0113] Specifically, the first valve 705 is a carbon canister shut-off valve, which includes an open state and a closed state; the switching transition time of the carbon canister shut-off valve is less than a preset time length, and the leakage of the carbon canister shut-off valve is less than a preset value; the second valve is a carbon canister valve, and the opening degree of the carbon canister valve can be adjusted between 0 and a preset value.

[0114] The first valve 705 can be controlled by an electric or pneumatic switching valve, and the second valve 703 can be controlled by an electric or pneumatic regulating valve.

[0115] Furthermore, the methods disclosed in the embodiments of this invention can also be applied to computer storage media, OBD modules, and intelligent vehicles, which can also realize the monitoring of the fault diagnosis process and avoid the occurrence of misdiagnosis.

[0116] It should be noted that the above embodiments are only for more clearly illustrating the technical solution of the present invention. Those skilled in the art will understand that the implementation of the present invention is not limited to the above content. Any obvious changes, substitutions or replacements made based on the above content do not exceed the scope of the technical solution of the present invention. Other implementations will also fall within the scope of the present invention without departing from the concept of the present invention.

Claims

1. A method for monitoring abnormalities in a diagnostic process, characterized in that, include: Acquire operating condition information; the operating condition information includes the working status of the actuator and the measurement value of the signal detection unit (011); the working status includes the valve opening degree and / or opening and closing status; Determine the current monitoring process; the monitoring process includes a first monitoring process (001) and a second monitoring process (002); Enter the monitoring loop (600), initialize feature data or solve feature data 510, 520, 530, 540, 5N0, where N is a natural number and represents the number of feature data or feature data groups; scan and acquire pressure data 712, 722, 732, 7M2 of at least one measurement point of the unit to be monitored (700) at a preset first time interval or step size, where M is a natural number and represents the number of pressure sensor measurement points; The relationship between the feature data 510, 520, 530, 540, 5N0 and the feature threshold is compared cyclically until the monitoring loop ends or exits (600); wherein the feature data 510, 520, 530, 540, 5N0 are statistics and / or functions of the pressure data 712, 722, 732, 7M2; The actuator includes a first valve (705) and a second valve (703); The unit to be monitored (700) includes an oil tank (701), a carbon canister (709), pipelines, sensors, and the actuator; the diagnostic process (777) includes a fault diagnosis process for the unit to be monitored (700); The statistic or the function includes flow integral data and flushing time data; the flow integral is calculated by integrating the time based on the gas flow rate in the desorption pipeline, and the flushing time is the time required for the tank pressure to reach the target pressure from atmospheric pressure during the monitoring process. If both the first valve (705) and the second valve (703) are in the closed state, and the pressure data 712, 722, 732, and 7M2 reach the first preset value (100), then the monitoring unit enters the second monitoring process (002). If the first valve (705) changes from open to closed, and the opening degree of the second valve (703) gradually increases from 0 with a preset gradient, then the monitoring process is the first monitoring process (001); when the pressure values ​​corresponding to the pressure data 712, 722, 732, and 7M2 gradually decrease to the first preset value (100), the second valve (703) is closed, and the second monitoring process (002) begins.

2. The monitoring method as described in claim 1, wherein: If no abnormal information (101, 107) is detected when the monitoring loop (600) ends or exits, the preset diagnostic process (777) continues; if an abnormality (103, 105) is detected, the exit routine (999) is executed.

3. The monitoring method as described in claim 1, wherein: During the first monitoring process (001), the pressure data 712, 722, 732, and 7M2 of the unit to be monitored (700) gradually decrease from the atmospheric pressure (111) in the open state until they reach the first preset value (100); the unit to be monitored (700) is in the process of establishing negative pressure or in the process of establishing negative pressure where there is a leak. During the second monitoring process (002), the actuators of the unit to be monitored (700) are all in the off state, and the unit to be monitored (700) is in the pressure holding state or in the pressure holding state where there is a leakage point.

4. The monitoring method as described in claim 1, wherein: The first valve (705) is a carbon canister shut-off valve, which includes an open state and a closed state; the switching transition time of the carbon canister shut-off valve is less than a preset time length, and the leakage of the carbon canister shut-off valve is less than a preset value; the second valve is a carbon canister valve, and the opening degree of the carbon canister valve can be adjusted between 0 and a preset value.

5. The monitoring method as described in claim 4, wherein: The first valve (705) is controlled by an electric or pneumatic switching valve, and the second valve (703) is controlled by an electric or pneumatic regulating valve.

6. A diagnostic process abnormality monitoring device, comprising: Signal detection unit (011), feature solving unit (055), monitoring output unit (066); The signal detection unit (011) acquires operating condition information; the operating condition information includes the working status of the actuator and the measurement value of the signal detection unit (011); the working status includes the valve opening degree and / or on / off state; The feature solving unit (055) determines the current monitoring process; the monitoring process includes a first monitoring process (001) and a second monitoring process (002); When the monitoring output unit (066) is running in the monitoring cycle (600) state or process, it initializes or solves feature data 510, 520, 530, 540, 5N0, where N is a natural number and represents the number of feature data or feature data groups; it scans and acquires pressure data 712, 722, 732, 7M2 of at least one measurement point of the unit to be monitored (700) at a preset first time interval or step size, where M is a natural number and represents the number of pressure sensor measurement points; The relationship between the feature data 510, 520, 530, 540, 5N0 and the feature threshold is compared cyclically until the monitoring loop ends or exits (600); wherein the feature data 510, 520, 530, 540, 5N0 are statistics and / or functions of the pressure data 712, 722, 732, 7M2; The actuator includes a first valve (705) and a second valve (703); The unit to be monitored (700) includes an oil tank (701), a carbon canister (709), pipelines, sensors, and the actuator; the diagnostic process (777) includes a fault diagnosis process for the unit to be monitored (700); The statistics or the function include flow integral data and flushing time data; the flow integral is calculated by integrating the flow rate of the gas in the desorption pipeline over time, and the flushing time is the time required for the tank pressure to rise from atmospheric pressure to the target pressure during the monitoring process.

7. The monitoring device as described in claim 6, wherein: If no abnormal information (101, 107) is detected when the monitoring output unit (066) ends or exits the monitoring loop (600), the preset diagnostic process (777) continues to be executed; if an abnormality (103, 105) is detected, the exit routine (999) is executed.

8. The monitoring device as described in claim 6, wherein: During the first monitoring process (001), the pressure data 712, 722, 732, and 7M2 of the unit to be monitored (700) gradually decrease from the atmospheric pressure (111) in the open state until they reach the first preset value (100); the unit to be monitored (700) is in the process of establishing negative pressure or in the process of establishing negative pressure where there is a leak. During the second monitoring process (002), the actuators of the unit to be monitored (700) are all in the off state, and the unit to be monitored (700) is in the pressure holding state or in the pressure holding state where there is a leakage point.

9. The monitoring device as described in claim 6 or 8, wherein: If both the first valve (705) and the second valve (703) are in the closed state, and the pressure data 712, 722, 732, and 7M2 reach the first preset value (100), then the monitoring unit enters the second monitoring process (002). If the first valve (705) changes from open to closed, and the opening degree of the second valve (703) gradually increases from 0 with a preset gradient, then the monitoring process is the first monitoring process (001); when the pressure values ​​corresponding to the pressure data 712, 722, 732, and 7M2 gradually decrease to the first preset value (100), the second valve (703) is closed, and the second monitoring process (002) begins.

10. The monitoring device as described in claim 9, wherein: The first valve (705) is a carbon canister shut-off valve, which includes an open state and a closed state; the switching transition time of the carbon canister shut-off valve is less than a preset time length, and the leakage of the carbon canister shut-off valve is less than a preset value; the second valve is a carbon canister valve, and the opening degree of the carbon canister valve can be adjusted between 0 and a preset value. The first valve (705) is controlled by an electric or pneumatic switching valve, and the second valve (703) is controlled by an electric or pneumatic regulating valve.

11. A computer storage medium, comprising: The storage medium itself used to store computer programs; When the computer program is executed by the microprocessor, it implements any of the monitoring methods described in claims 1 to 5.

12. An OBD module, comprising: Any of the monitoring devices as described in claims 6 to 10; And / or the storage medium as described in claim 11.

13. A vehicle comprising: Any storage medium as described in claim 11; And / or the module as described in claim 12.

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