It is difficult to develop the corresponding fault diagnosis system and the software reusability is bad because the engineering equipment types are so many and their performance is diverse. This paper discussed the so...It is difficult to develop the corresponding fault diagnosis system and the software reusability is bad because the engineering equipment types are so many and their performance is diverse. This paper discussed the solution to engineering equipment integrated fault diagnosis system based on component technology, put forward the sys- tem model and gave the system frame design process and working principle. The software was designed based on the three-layer hierarchy. It is easy to rease and maintain, and the operation of the software is simple. A kind of new theory and method to develop the engineering equipment fault diagnosis system for the future was provided.展开更多
Because of poor lubrication, the abrasion of the engineering equipment＇s key connection position （the hinge joint and so on） has become the major factor that affects the mechanical benefit. The excavator WY60 is ta...Because of poor lubrication, the abrasion of the engineering equipment＇s key connection position （the hinge joint and so on） has become the major factor that affects the mechanical benefit. The excavator WY60 is taken as an example in this paper. The automatic grease-pouring, the working state test, and the alarm for fault of every lubricating point on the machine is accomplished by the control sub-system, the lubricating system and other correlated components. The principle and functions of the system are described. The work condition is analyzed. Finally, we present the plan of the software and the hardware of the system, and set up the fuzzy assessment model of reliability of the system.展开更多
The maintenance and forecast expert system of equipment based on Artificial Neural Network is composed of control, measure, failure forecast, execution, data processing module and database. The data processing module ...The maintenance and forecast expert system of equipment based on Artificial Neural Network is composed of control, measure, failure forecast, execution, data processing module and database. The data processing module obtains the change of the controlled objects＇ structure and parameters, then takes correspondent measures according to the examination and diagnosis information. The failure forecast module finds the control system fault, separates the fault symptom location, tells the fault kind, estimates the magnitude and time of the fault, and finally makes evaluation and decision.展开更多
文摘It is difficult to develop the corresponding fault diagnosis system and the software reusability is bad because the engineering equipment types are so many and their performance is diverse. This paper discussed the solution to engineering equipment integrated fault diagnosis system based on component technology, put forward the sys- tem model and gave the system frame design process and working principle. The software was designed based on the three-layer hierarchy. It is easy to rease and maintain, and the operation of the software is simple. A kind of new theory and method to develop the engineering equipment fault diagnosis system for the future was provided.
基金This paper is supported by Scientific Research Foundation of PLAGeneral Equipment Departmentunder Contract No.20060210
文摘Because of poor lubrication, the abrasion of the engineering equipment＇s key connection position （the hinge joint and so on） has become the major factor that affects the mechanical benefit. The excavator WY60 is taken as an example in this paper. The automatic grease-pouring, the working state test, and the alarm for fault of every lubricating point on the machine is accomplished by the control sub-system, the lubricating system and other correlated components. The principle and functions of the system are described. The work condition is analyzed. Finally, we present the plan of the software and the hardware of the system, and set up the fuzzy assessment model of reliability of the system.
文摘The maintenance and forecast expert system of equipment based on Artificial Neural Network is composed of control, measure, failure forecast, execution, data processing module and database. The data processing module obtains the change of the controlled objects＇ structure and parameters, then takes correspondent measures according to the examination and diagnosis information. The failure forecast module finds the control system fault, separates the fault symptom location, tells the fault kind, estimates the magnitude and time of the fault, and finally makes evaluation and decision.
