An intelligent control system and method for engine combustion diagnostics

Abstract

The application discloses an intelligent control system and method for engine combustion diagnosis, and belongs to the technical field of engine diagnosis. The system comprises an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module and a diagnosis early warning module; the ECU automatic control module is used for automatically controlling the combustion process of the engine by the ECU; the combustion data acquisition module is used for acquiring supply data and tail gas data; the maintenance data acquisition module is used for acquiring maintenance data; the intelligent calculation module is used for calculating a target excess air coefficient and a measured excess air coefficient; the model analysis module is used for analyzing the influence of the loss of parts in the engine on the engine combustion; and the diagnosis early warning module is used for judging whether the engine is abnormal at present; the loss conditions of the parts are analyzed, and the accuracy of engine combustion diagnosis and the fault judgment capability are improved.

Description

Technical Field

[0001] This invention relates to the field of engine diagnostic technology, specifically to an intelligent control system and method for engine combustion diagnostics. Background Technology

[0002] In many fields such as transportation and industrial production, the engine is the core power unit, and its stable and efficient operation is crucial. Engine combustion, as a key link in energy conversion, directly determines the engine's power output efficiency. Therefore, accurate diagnosis of the engine combustion state is an important guarantee for achieving optimized engine control and performance improvement.

[0003] As the core component of the engine electronic control system, the ECU (Engine Control Unit) typically combines the stoichiometric air-fuel ratio, fuel trim value, and real-time engine operating data to construct a powerful diagnostic decision matrix, enabling precise control of engine combustion. However, modern ECUs, in order to meet power or emission requirements, will actively deviate from the stoichiometric air-fuel ratio. This not only interferes with engine combustion diagnosis but also increases the probability of system misjudgment. The stoichiometric air-fuel ratio is generally analyzed based on the metering ratio of fuel and air, but simply analyzing exhaust gases cannot accurately locate internal engine faults, leading to ambiguity in engine fault diagnosis and increased maintenance costs. Summary of the Invention

[0004] The purpose of this invention is to provide a technical solution to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control method for engine combustion diagnosis, comprising:

[0006] The ECU automatically controls the engine's combustion process, collecting supply data before combustion and exhaust gas data after combustion. The supply data includes the total mass of air and fuel entering the engine cylinders, and the exhaust gas data includes the components of the exhaust gas after the air and fuel in the engine cylinders react with each other during combustion.

[0007] Regular maintenance is performed on the engine, and maintenance data is collected during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine;

[0008] Based on the supply data, calculate the target excess air coefficient of the air in the engine cylinder before combustion of fuel, and based on the exhaust gas data, calculate the measured excess air coefficient of the air in the engine cylinder after combustion of fuel.

[0009] Based on maintenance data, target excess air coefficient and measured excess air coefficient, an engine diagnostic model is established to analyze the impact of wear and tear on engine combustion of each component.

[0010] Based on the established engine diagnostic model, the wear and tear of various parts in the engine is monitored in real time to determine whether there is an engine abnormality, and an alarm is issued for the abnormality and the alarm information is sent to the user.

[0011] Furthermore, the target excess air coefficient is specifically the ratio of the actual air-fuel ratio to the stoichiometric air-fuel ratio; the actual air-fuel ratio is specifically the ratio of the total mass of air entering the engine cylinder to the total mass of fuel.

[0012] Furthermore, the method for calculating the measured excess air coefficient is as follows: analyze the exhaust gas data, determine the individual gases and their corresponding volume fractions after the combustion reaction of air and fuel in the engine cylinder, and substitute the determined gases and their corresponding volume fractions into the Brettschneider formula to calculate the measured excess air coefficient after the combustion of air and fuel in the engine cylinder.

[0013] Furthermore, the method and steps for analyzing the impact of wear and tear on engine combustion of each component are as follows:

[0014] S1. Analyze the collected maintenance data to determine the number n of parts that affect engine combustion, and determine the maintenance frequency and total operation time for each part; based on the timestamp, determine the changes in the target excess air coefficient and the measured excess air coefficient before and after engine combustion under different maintenance cycles and replacement times for different parts, and obtain the deviation between the target excess air coefficient and the measured excess air coefficient.

[0015] S2. Establish an engine diagnostic model, using the maintenance cycle and replacement time of each component as independent variables, and the deviation between the target excess air coefficient and the measured excess air coefficient as the dependent variable. Analyze the impact of wear on engine combustion of each component, and fit the relationship curves between the wear of each component and engine combustion.

[0016] ;

[0017] Where CZ represents the deviation between the target excess air coefficient and the measured excess air coefficient; m represents the number of parts whose wear causes a decrease in the air-fuel ratio of the engine; w i The weight α represents the impact of component i's wear on engine combustion. i This indicates the degree to which the wear and tear of component i affects engine combustion; h iT represents the wear recovery value of part i after maintenance; M represents the total operation time of part i; and M represents the number of maintenance cycles for part i.

[0018] S3. Use the analysis results of the maintenance data in S1 as training data and substitute them into the relationship curve in S2 for fitting. According to the least squares method, determine the influence weight, influence degree and loss recovery value of different parts on engine combustion respectively.

[0019] Furthermore, the method for real-time monitoring of wear and tear on various engine components to determine if any engine malfunctions exist is as follows:

[0020] S10. Analyze the real-time maintenance data of each part, and calculate the total impact value Y0 of part wear on engine combustion through the engine diagnostic model based on the maintenance frequency and total operation time of each part; determine the real-time deviation CZ0 between the target excess air coefficient and the measured excess air coefficient based on the engine's real-time supply data and real-time exhaust gas data.

[0021] S20. Analyze historical maintenance data, target excess air coefficient, and measured excess air coefficient when engine failure occurs, and determine the alarm threshold K for the impact of component wear on the deviation between the target and measured excess air coefficients of the engine. i The engine malfunction indicates that a component failure is causing the engine failure.

[0022] S30. Detect engine malfunctions; when K... i When >|Y0-CZ0|, the engine parts are normal; when K exists... i When the value is less than or equal to |Y0-CZ0|, an engine part is abnormal, and an alarm is issued for the abnormal engine part.

[0023] Furthermore, the individual components within the engine are identified and a complete digital inventory of engine components is constructed. A corresponding maintenance cycle and replacement time threshold are configured for each individual component, and the maintenance cycle and replacement time of each component are recorded in the digital inventory. The digital inventories of each component are then integrated to obtain maintenance data during the engine maintenance process.

[0024] An intelligent control system for engine combustion diagnosis includes an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module, and a diagnostic early warning module.

[0025] The ECU automatic control module is used by the ECU to automatically control the combustion process of the engine;

[0026] The combustion data acquisition module is used to collect engine supply data before combustion and engine exhaust gas data after combustion; the supply data includes the total mass of air and fuel entering the engine cylinder; the exhaust gas data includes the exhaust gas composition after the air and fuel in the engine cylinder react with each other; and the collected supply data and exhaust gas data are sent to the intelligent computing module.

[0027] The maintenance data acquisition module is used to collect maintenance data during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine; and the collected maintenance data is sent to the model analysis module.

[0028] The intelligent computing module is used to calculate the target excess air coefficient of the air and fuel in the engine cylinder before combustion based on the supply data, and to calculate the measured excess air coefficient of the air and fuel in the engine cylinder after combustion based on the exhaust gas data; and to send the calculated target excess air coefficient and the measured excess air coefficient to the model analysis module.

[0029] The model analysis module is used to establish an engine diagnostic model based on maintenance data, target excess air coefficient and measured excess air coefficient, and to analyze the impact of wear and tear of various parts in the engine on engine combustion.

[0030] The diagnostic and early warning module is used to monitor the wear and tear of various parts in the engine in real time based on the established engine diagnostic model, determine whether there is an engine abnormality, issue an alarm for the abnormality, and send the alarm information to the user.

[0031] Furthermore, a human-machine interaction platform is provided, through which users can view alarm information; maintenance personnel can also use the human-machine interaction platform to record the maintenance cycle and replacement time of each part.

[0032] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: by establishing an engine diagnostic model, the influence of wear and tear on the deviation trend of each part in the engine is analyzed, thereby analyzing the wear and tear of each part and improving the accuracy of engine combustion diagnosis; by predicting the influence of part wear and tear on the deviation between the target excess air coefficient and the measured excess air coefficient, it is determined whether there are other factors besides part wear and tear that may affect the deviation between the target excess air coefficient and the measured excess air coefficient, thereby improving the engine fault diagnosis capability. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the structure of an intelligent control system for engine combustion diagnosis according to the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0035] Please see Figure 1 The present invention provides the following technical solution:

[0036] In this first embodiment: an intelligent control method for engine combustion diagnosis is provided, including:

[0037] The ECU automatically controls the engine's combustion process, collecting supply data before combustion and exhaust gas data after combustion. The supply data includes the total mass of air and fuel entering the engine cylinders, while the exhaust gas data includes the components of the exhaust gas after the air and fuel in the engine cylinders react with each other.

[0038] It should be noted that during the automatic control of the engine's combustion process by the ECU, when the engine's air intake increases, the ECU will calculate the corresponding basic fuel injection quantity based on the signal from the air flow sensor and the theoretical air-fuel ratio. For example, the theoretical air-fuel ratio of gasoline is 14.7:1. However, under conditions such as high engine load and acceleration, it is necessary to enrich the air-fuel mixture to increase power. This is achieved by controlling the fuel trim value to add to the mixture.

[0039] Regular maintenance is performed on the engine, and maintenance data is collected during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine.

[0040] Furthermore, the individual components within the engine are identified and a complete digital inventory of engine components is constructed. A corresponding maintenance cycle and replacement time threshold are configured for each individual component, and the maintenance cycle and replacement time of each component are recorded in the digital inventory. The digital inventories of each component are then integrated to obtain maintenance data during the engine maintenance process.

[0041] In this embodiment, the parts inside the engine include, but are not limited to, the throttle body, intake manifold, fuel injector, ignition coil, cylinder, and valve. Due to the different types and degrees of damage of the parts, maintenance personnel will selectively maintain or directly replace various parts inside the engine according to different scenarios. After the maintenance personnel complete the engine maintenance, they will fill in the maintenance status of each part in the digital list. When maintaining a part, the maintenance cycle and number of maintenance times for that part will be recorded.

[0042] Based on the supply data, calculate the target excess air coefficient of the air and fuel in the engine cylinder before combustion, and based on the exhaust gas data, calculate the measured excess air coefficient of the air and fuel in the engine cylinder after combustion.

[0043] Specifically, the target excess air coefficient is the ratio of the actual air-fuel ratio to the stoichiometric air-fuel ratio; the actual air-fuel ratio is the ratio of the total mass of air entering the engine cylinder to the total mass of fuel; wherein, the target excess air coefficient is the expected value of the excess air coefficient calculated by the ECU from the internally stored three-dimensional pulse spectrum diagram based on current driving needs, engine power and emissions optimization targets.

[0044] Specifically, the method for calculating the measured excess air coefficient is as follows: analyze the exhaust gas data, determine the individual gases and their corresponding volume fractions after the combustion reaction of air and fuel in the engine cylinder, and substitute the determined gases and their corresponding volume fractions into the Brettschneider formula to calculate the measured excess air coefficient after the combustion of air and fuel in the engine cylinder.

[0045] In this embodiment, exhaust gas data is analyzed to determine the volume fractions of carbon monoxide [CO], carbon dioxide [CO2], oxygen [O2], and hydrocarbons [HC]% after the combustion of air and fuel in the engine cylinder. These are then substituted into the Brettschneider formula to calculate the measured excess air coefficient λ. K1 and K2 represent the hydrogen-to-carbon ratio constants of the fuel, which are determined based on the fuel characteristics, specifically gasoline.

[0046] It should be noted that the target excess air coefficient is determined by the direct method, and the measured excess air coefficient is derived by the indirect method. The target excess air coefficient and the measured excess air coefficient reflect the difference between the air and fuel combustion reaction in the engine cylinder before and after combustion. Based on the different differences, the wear of various parts in the engine is analyzed, which improves the accuracy of engine fault diagnosis.

[0047] Based on maintenance data, target excess air coefficient, and measured excess air coefficient, an engine diagnostic model is established to analyze the impact of wear and tear on engine combustion.

[0048] Specifically, the steps for analyzing the impact of wear and tear on engine combustion of various components are as follows:

[0049] S1. Analyze the collected maintenance data to determine the number n of parts that affect engine combustion, and determine the maintenance frequency and total operation time for each part; based on the timestamp, determine the changes in the target excess air coefficient and the measured excess air coefficient before and after engine combustion under different maintenance cycles and replacement times for different parts, and obtain the deviation between the target excess air coefficient and the measured excess air coefficient.

[0050] S2. Establish an engine diagnostic model, using the maintenance cycle and replacement time of each component as independent variables, and the deviation between the target excess air coefficient and the measured excess air coefficient as the dependent variable. Analyze the impact of wear on engine combustion of each component, and fit the relationship curves between the wear of each component and engine combustion.

[0051] ;

[0052] Where CZ represents the deviation between the target excess air coefficient and the measured excess air coefficient; m represents the number of parts whose wear causes a decrease in the air-fuel ratio of the engine; w i The weight α represents the impact of component i's wear on engine combustion. i This indicates the degree to which the wear and tear of component i affects engine combustion; h i T represents the wear recovery value of part i after maintenance; M represents the total operation time of part i; and M represents the number of maintenance cycles for part i.

[0053] S3. Use the analysis results of the maintenance data in S1 as training data and substitute them into the relationship curve in S2 for fitting. According to the least squares method, determine the influence weight, influence degree and loss recovery value of different parts on engine combustion respectively.

[0054] It should be noted that, by establishing an engine diagnostic model and based on supply and exhaust gas data, the deviation CZ between the target excess air coefficient λ0 and the measured excess air coefficient λ is determined. Based on maintenance data, the total operating time and maintenance frequency for each type of part are determined. When a part is replaced, the total operating time for the replaced part is recalculated. Based on timestamps, the impact of different part wear conditions on the deviation between the target excess air coefficient and the measured excess air coefficient is determined. This allows for the analysis of the impact of each part wear on engine combustion, accurately locating parts that affect internal engine combustion, and improving the accuracy of engine combustion diagnosis.

[0055] It should be noted that determining the number of parts *m* that wear causes a decrease in the engine's air-fuel ratio and the number of parts *nm* that wear causes an increase in the engine's air-fuel ratio is because wear on different parts will cause the deviation between the target excess air coefficient and the measured excess air coefficient to change in different directions. For example, with fuel injectors, when wear leads to increased fuel injection, the measured excess air coefficient will decrease, and the deviation will move towards a positive value. Similarly, wear on the throttle body leads to poor sealing and increased air leakage, resulting in a larger measured excess air coefficient and a negative deviation. By analyzing the changing trend of the deviation between the target and measured excess air coefficients, the impact of wear on the deviation trend of each engine part can be analyzed, thereby allowing for the identification of abnormal conditions in each part.

[0056] Based on the established engine diagnostic model, the wear and tear of various parts in the engine is monitored in real time to determine whether there is an engine abnormality, and an alarm is issued for the abnormality and the alarm information is sent to the user.

[0057] Specifically, the steps for real-time monitoring of wear and tear on various engine components to determine if any engine malfunctions exist are as follows:

[0058] S10. Analyze the real-time maintenance data of each part, and calculate the total impact value Y0 of part wear on engine combustion through the engine diagnostic model based on the maintenance frequency and total operation time of each part; determine the real-time deviation CZ0 between the target excess air coefficient and the measured excess air coefficient based on the engine's real-time supply data and real-time exhaust gas data.

[0059] S20. Analyze historical maintenance data, target excess air coefficient, and measured excess air coefficient when engine failure occurs, and determine the alarm threshold K for the impact of component wear on the deviation between the target and measured excess air coefficients of the engine. i The engine malfunction indicates that a component failure is causing the engine failure.

[0060] S30. Detect engine malfunctions; when K... i When >|Y0-CZ0|, the engine parts are normal; when K exists... i When the value is less than or equal to |Y0-CZ0|, an engine part is abnormal, and an alarm is issued for the abnormal engine part.

[0061] It should be noted that the alarm threshold K iThe deviation between Y0 and CZ0 in historical data when engine failures occur is determined. The maintenance frequency and total operation time of each part are substituted into the relationship curve of S2. Based on the influence weight, influence degree and wear recovery value of different parts on engine combustion, the total influence value of part wear on engine combustion is calculated. The influence of part wear on the deviation between the target excess air coefficient and the measured excess air coefficient is predicted. The predicted total influence value and the real-time deviation CZ0 are analyzed to determine whether there are other factors besides part wear that affect the deviation between the target excess air coefficient and the measured excess air coefficient. Thus, the influence of other interference factors on engine combustion is considered, which improves the engine fault diagnosis capability.

[0062] Please see Figure 1 In this second embodiment: an intelligent control system for engine combustion diagnosis is provided, which includes an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module, and a diagnostic early warning module;

[0063] The ECU automatic control module is used by the ECU to automatically control the combustion process of the engine;

[0064] The combustion data acquisition module is used to collect engine supply data before combustion and engine exhaust gas data after combustion; the supply data includes the total mass of air and fuel entering the engine cylinder; the exhaust gas data includes the exhaust gas composition after the air and fuel in the engine cylinder react with each other; and the collected supply data and exhaust gas data are sent to the intelligent computing module.

[0065] The maintenance data acquisition module is used to collect maintenance data during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine; and the collected maintenance data is sent to the model analysis module.

[0066] The intelligent computing module is used to calculate the target excess air coefficient of the air and fuel in the engine cylinder before combustion based on the supply data, and to calculate the measured excess air coefficient of the air and fuel in the engine cylinder after combustion based on the exhaust gas data; and to send the calculated target excess air coefficient and the measured excess air coefficient to the model analysis module.

[0067] The model analysis module is used to establish an engine diagnostic model based on maintenance data, target excess air coefficient and measured excess air coefficient, and to analyze the impact of wear and tear of various parts in the engine on engine combustion.

[0068] The diagnostic and early warning module is used to monitor the wear and tear of various parts in the engine in real time based on the established engine diagnostic model, determine whether there is an engine abnormality, issue an alarm for the abnormality, and send the alarm information to the user.

[0069] Furthermore, a human-machine interaction platform is provided, through which users can view alarm information; maintenance personnel can also use the human-machine interaction platform to record the maintenance cycle and replacement time of each part.

[0070] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. An intelligent control method for engine combustion diagnostics, characterized by: The application relates to an engine combustion process automatic control method and device. The engine combustion process is automatically controlled by an ECU, and supply data before engine combustion and tail gas data after engine combustion are collected; the supply data comprises total air mass and total fuel mass entering an engine cylinder; and the tail gas data comprises tail gas components after air and fuel combustion in the engine cylinder; Periodic maintenance is carried out on the engine, and maintenance data in the engine maintenance process are collected; the maintenance data comprises maintenance periods and replacement times of various parts in the engine; A target excess air coefficient of air and fuel before combustion in the engine cylinder is calculated according to the supply data, and a measured excess air coefficient of air and fuel after combustion in the engine cylinder is calculated according to the tail gas data; An engine diagnosis model is established based on the maintenance data, the target excess air coefficient and the measured excess air coefficient, and the influence of wear of various parts in the engine on engine combustion is analyzed; Real-time monitoring is carried out on the wear of various parts in the engine according to the established engine diagnosis model, whether the engine is abnormal at present is judged, and an alarm is given to the engine abnormal condition, and alarm information is sent to a user.

2. The intelligent control method for engine combustion diagnosis according to claim 1, characterized in that: The target excess air coefficient is specifically a ratio of an actual air-fuel ratio to a theoretical air-fuel ratio; and the actual air-fuel ratio is specifically a ratio of the total air mass to the total fuel mass entering the engine cylinder.

3. The intelligent control method for engine combustion diagnostics of claim 1, wherein: The method for calculating the measured excess air coefficient is that each gas after air and fuel combustion in the engine cylinder and the corresponding volume fraction are determined by analyzing the tail gas data, each gas and the corresponding volume fraction are substituted into a Brettschneider formula, and the measured excess air coefficient after air and fuel combustion in the engine cylinder is calculated.

4. The intelligent control method for engine combustion diagnostics of claim 1, wherein: The method steps for analyzing the influence of wear of various parts in the engine on engine combustion are as follows: S1, the collected maintenance data are analyzed, the number n of parts that have influence on engine combustion is determined, and the maintenance times and total operation time of each part are determined; According to the time stamp, the target excess air coefficient change and the measured excess air coefficient change before and after engine combustion under the maintenance periods and replacement times of different parts are determined, and the deviation change between the target excess air coefficient and the measured excess air coefficient is obtained; S2, an engine diagnosis model is established, each part maintenance period and replacement time are taken as independent variables, the deviation between the target excess air coefficient and the measured excess air coefficient is taken as a dependent variable, the influence of wear of various parts in the engine on engine combustion is analyzed, and a relationship curve of the influence of wear of various parts in the engine on engine combustion is fitted; ； wherein, CZ represents the deviation between the target excess air coefficient and the measured excess air coefficient; m represents the number of parts whose loss will cause the air-fuel ratio in the engine to decrease; w i represents the influence weight of the loss of part i on the engine combustion; a i represents the influence degree of the loss of part i on the engine combustion; h i represents the loss recovery value of part i after maintenance; T represents the total operation time of the part; M represents the number of times of maintenance of the part; S3, the analysis result of the maintenance data in S1 is taken as training data, is substituted into the relationship curve in S2 for fitting, and the influence weight, influence degree and wear recovery value of different parts on engine combustion are determined according to the least square method.

5. The intelligent control method for engine combustion diagnostics of claim 4, wherein: The method steps for monitoring the wear of various parts in the engine and judging whether the engine is abnormal at present are as follows: S10, analyze the real-time maintenance data of each part, calculate the total influence value Y0 of part wear on engine combustion according to the maintenance frequency and total operation time of each part through the engine diagnosis model; determine the real-time deviation CZ0 between the target excess air coefficient and the measured excess air coefficient according to the real-time supply data and real-time tail gas data of the engine; S20, analyzing the historical maintenance data, the target excess air coefficient and the measured excess air coefficient when the engine fault exists, and determining an alarm threshold K of the influence of the part loss on the deviation between the target excess air coefficient and the measured excess air coefficient of the engine i ; the engine fault indicates that there is a part failure leading to the engine fault; S30, judging the engine abnormality, when K i |Y0-CZ0|, the engine part is normal; when K i ≤|Y0-CZ0|, the engine part is abnormal, and the abnormal engine part is alarmed.

6. The intelligent control method for engine combustion diagnostics of claim 1, wherein: Determine each part in the engine and build a full-part digital list of the engine, configure a corresponding maintenance period and replacement time threshold for each individual part, and record the maintenance period and replacement time of each part in the digital list. Integrate the digital list of each part to obtain the maintenance data in the engine maintenance process.

7. An intelligent control system for engine combustion diagnostics, characterized by: The system includes an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module, and a diagnosis and warning module. The ECU automatic control module is used for the ECU to automatically control the combustion process of the engine. The combustion data acquisition module is used to acquire the supply data before engine combustion and the tail gas data after engine combustion; the supply data includes the total mass of air and fuel entering the engine cylinder; the tail gas data includes the tail gas composition after the combustion reaction of air and fuel in the engine cylinder; and the acquired supply data and tail gas data are sent to the intelligent calculation module. The maintenance data acquisition module is used to acquire maintenance data in the engine maintenance process; the maintenance data includes the maintenance period and replacement time of each part in the engine; and the acquired maintenance data is sent to the model analysis module. The intelligent calculation module is used to calculate the target excess air coefficient of air and fuel before combustion in the engine cylinder according to the supply data, and calculate the measured excess air coefficient of air and fuel after combustion in the engine cylinder according to the tail gas data; and the calculated target excess air coefficient and measured excess air coefficient are sent to the model analysis module. The model analysis module is used to establish an engine diagnosis model based on the maintenance data, target excess air coefficient, and measured excess air coefficient, and analyze the influence of wear of each part in the engine on engine combustion. The diagnosis and warning module is used to monitor the wear of each part in the engine in real time according to the established engine diagnosis model, determine whether there is an engine abnormality at present, and warn the engine abnormality, and send the warning information to the user.

8. An intelligent control system for engine combustion diagnostics as claimed in claim 7 wherein: A human-computer interaction platform is provided, and the user can view the warning information through the human-computer interaction platform; wherein the maintenance personnel can record the maintenance period and replacement time of each part through the human-computer interaction platform.

Images