The Condition Monitoring Of Hydraulic System Based On DSP

The technique of hydraulic system condition monitoring and measuring is an effective method, which can guarantee the hydraulic equipment to run quite efficiently under the safe reliable condition. Now, intelligence diagnoses system such as specialty system, neural network, and information mixing have been used in the condition monitoring and failure diagnose of hydraulic system. Integrated application of the lots of diagnose technique can decrease the difficulty of diagnoses, reduce the time of diagnose, improve work efficiency bring much economic effect to enterprise.This text putting forward a scheme of hydraulic system condition monitoring and measuring on-line based on DSP, which based on aim at the shortage of current monitoring method, i.e.: As the technological core of the monitoring system with the monitoring technology of hydraulic system condition based on electric current signal, taking DSP as the core hydraulic system condition monitor as hardware platform, regard computer as the expansion platform of monitoring system to monitor the condition of hydraulic system. Through designing the software and hardware of the hydraulic system condition monitor, the sample of this monitor is developed, and which function is verified through a large number of experiments.Proved through theory analysis and experimental result, the hydraulic system condition monitor has realized the basic function that monitoring system require. Such as filter and commutate the electromechanical signal, sampling and recovery the signal, display the state data, respond the input of the key, to communicate with computer through the COM port, monitor the virtual value of voltage and current, monitor the power and power factor of electromotor, monitor the power of hydraulic system, obtain the envelope and curve of the power and so on. It can complete the hydraulic system condition monitoring independently and exactly, and supply the hardware support for the hydraulic system condition monitoring.