Automobile engine failure detection method

A technology of automobile engine and detection method, which is applied in the direction of computer parts, instruments, character and pattern recognition, etc., can solve the problems of high cost and slow speed of engine failure detection, and achieve strong failure detection ability, low misjudgment rate, and diagnosis high rate effect

Active Publication Date: 2017-01-18
WENZHOU UNIVERSITY
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Problems solved by technology

[0007] The above methods have high cost and slow speed for engine failure detection, and stil

Method used

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  • Automobile engine failure detection method
  • Automobile engine failure detection method
  • Automobile engine failure detection method

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Embodiment Construction

[0033] see figure 1 , figure 2 and image 3 , a kind of failure detection method of automobile engine disclosed by the present invention, comprises the following steps:

[0034] (1) Determine engine failure characteristic parameter set, failure type set, described failure characteristic parameter set comprises a plurality of failure characteristic parameters, and described failure type set comprises a plurality of failure types;

[0035] (2) According to the failure characteristic parameter set and the failure type set, a structural risk minimization machine learning model based on kernel function is established;

[0036] (3) Using the sample set, train and optimize the machine learning model based on kernel function for structural risk minimization;

[0037] (4) Detect multiple failure characteristic parameters of the engine, and use the multiple failure characteristic parameters as the data source for failure detection;

[0038] (5) Input the data source into the machin...

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Abstract

The invention discloses an automobile engine failure detection method including the following steps: determining a failure characteristic parameter set and a failure type set of an engine, wherein the failure characteristic parameter set contains multiple failure characteristic parameters, and the failure type set contains multiple failure types; building a structural risk minimization machine learning model based on a kernel function according to the failure characteristic parameter set and the failure type set; using a sample set to train and optimize the structural risk minimization machine learning model based on a kernel function; detecting multiple failure characteristic parameters of the engine, and taking the multiple failure characteristic parameters as a data source of failure detection; and inputting the data source to the structural risk minimization machine learning model based on a kernel function to get a failure detection result. According to the method, by combining a structural risk minimization machine learning algorithm based on a kernel function and principal component feature extraction, rapid and accurate engine failure detection is realized. Moreover, the method has the advantages of strong failure detection capability, high rate of definite diagnosis, and low misjudgment rate.

Description

technical field [0001] The invention relates to the technical field of automobile failure detection, in particular to a failure detection method of an automobile engine. Background technique [0002] The engine is the heart of a car, and its faults account for the highest proportion of the whole car. The consumption of accessories per car per unit mileage and the consumption of maintenance man-hours, the engine also takes the first place. If the engine fails and fails to be detected and eliminated in time, the result will not only cause damage to the engine itself, but may even cause serious consequences of car crashes and deaths. Therefore, using a shorter time and lower maintenance costs, making accurate judgments on engine stoppage or abnormal operation in a timely manner, finding out the cause of failure and troubleshooting methods, can greatly reduce the blindness of maintenance, and it is very important for improving the power of the car. Performance, economy, reliabi...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/214
Inventor 万毅黄海隆
Owner WENZHOU UNIVERSITY
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