Research On Condition Monitoring And Fault Warning System Of Pure Electric-driven Construction Machinery

Facing the continuous emergence of global climate deterioration and energy crisis,as well as the dual guidance of relevant policies and the market,the electrification of construction machinery has become an inevitable trend in the future.With the vigorous development of electric energy storage and pure electric-driven technology,pure electric-driven construction machinery has attracted great attention from universities and manufacturers at home and abroad.Compared with traditional fuel-driven construction machinery,the equipment intelligence of pure electric-driven construction machinery and the complexity of the vehicle system have been significantly improved.Therefore,it is particularly important to establish a state monitoring and fault diagnosis system for pure electric-driven construction machinery.Taking the pure electric-driven loader as an example,the intelligent management is realized by establishing a monitoring and management system for the loader.Firstly,according to the requirements of the monitoring and management system,the overall design of the system is completed.The monitoring system is divided into vehicle terminal,CAN communication network,interactive terminal,monitoring and management platform.Secondly,the software system of vehicle terminal is designed.STM32F767 is taken as the main processor and the UCOSIII embedded real-time operating system is used to complete the design of the underlying driver for data integration,and the human-computer interaction interface is designed based on the STem Win graphics library.Thirdly,the system parameters of the test prototype and the function definition of the vehicle controller are analyzed,the network structure of the fault diagnosis system is constructed based on CAN communication;the fault diagnosis code of the test prototype is formulated,the fault level is divided,and the vehicle fault reminding mechanism is designed based on CZ6 to realize the fault diagnosis.Fourthly,by analyzing the characteristic quantity of the electromechanical transmission system of the test sample,the fault characteristic quantity is extracted.SVR and LS-SVR are used to predict the feature quantity and the cross validation method is used to optimize the relevant parameters of the algorithm.Lastly,the performance of SVR and LS-SVR is compared to verify the feasibility of the prediction algorithm.Finally,based on the analysis of typical working conditions of pure electric-driven loader and the operation data of actual test prototype,an operation energy consumption estimation method based on working condition identification is proposed.The results show that the energy consumption estimation method based on the average torque of the segment motor proposed in this paper has better estimation accuracy than the traditional method.