Microcontroller-based transient signal analysis and distributed system for intelligent process monitoring

摘要

The research presented in this thesis considers the feasibility of utilising dsPICs (digital signal controllers) in the development of effective monitoring systems which have the capability to adapt to changes in operating conditions and can be quickly calibrated to suit a range of applications, thus helping to reduce the development time constraint. The capability of these monitoring solutions to detect and isolate faults occurring in pneumatic processes is investigated and their effectiveness verified. Three applications are considered gas pipe leakage, linear actuator operations and gripper action. In each case, solutions are developed based upon the dsPIC. The solutions utilise the analysis of pressure transients to overcome the limitation in the dsPIC memory. The deployment of minimal sensors and electronics was essential to optimise the cost of the system. Leak detection techniques are developed with application to gas fitting pipes. The speed at which correct decisions are determined was the essence of this work. The solutions are tested, compared and their capability validated using pipes which had been rejected according to industrial standards. In this application a dsPIC digital signal controller and a pressure sensor were deployed, thus ensuring a low cost monitoring solution. Linear actuator "end of stroke" monitoring has, previously, largely been possible using limit switches. A more challenging method based upon the deployment of a pressure sensor is outlined. Monitoring model surfaces were obtained and their capability to determine the health of the process was proved, at various supply pressures. With regard to the gripper monitoring, a performance surface by which the gripper action can be monitored is generated and embedded within the dsPIC. Various faults are simulated and their effect on the gripper performance investigated. Leakage and blockage are also investigated at various places in the pneumatic circuit to allow for an algorithm to be devised. Faults may be detected and isolated, and their locations identified to allow for timely recovery treatment, thus supporting an enhanced process monitoring strategy.