Research on Fuel Injector Fault Diagnosis Based on Grid Search and Voting Classification Model
In order to improve the efficiency of injector maintenance for high-pressure common rail test benches,an automated di-agnosis method for injector faults was proposed based on grid search and voting classification models.Due to the difficulty in collecting fault data of piezoelectric injectors,AMESim software was used to simulate various fault conditions that may occurred in piezoelectric in-jectors under different rail pressures and pulse width states.Subsequently,the collected 1 760 sets of data were trained using a voting classification model composed of random forest,support vector machine,and GBM,and the hyperparameters of each classifier were opti-mized using grid search method.The experimental results show that the accuracy,precision,recall,and F1-score of this model in diagno-sing the 5 fault states and normal state of piezoelectric injectors are 98.86％,99.13％,98.56％and 98.83％,respectively,demonstra-ting high accuracy and stability.This method can be used to locate injector faults rapidly and efficiently.
万方数据
维普
