A Novel Health Monitoring Approach for Hydraulic Pumps and Motors

In this proposal, Intelligent Automation, Incorporated (IAI) proposes a novel and robust approach to detect hydraulic pump and motor failures. The algorithm was recently developed by Dr. Chiman Kwan, the principal investigator of this proposal, and hiscollaborators. It consists of three major steps. First, based on normal raw sensor measurements, a residual model is built off-line for a given hydraulic pump or motor system. The technique is called Minor Component Analysis (MCA). The residual modeloutputs are non-zero when there is fault. Our approach is direct, accurate, and based on only normal measurement data. Second, based on the residual model outputs, we define a fault detection index, which gives fast and accurate detection of failures.Third, we will determine the nature of the failures by reconstructing the fault magnitude. Furthermore, from the fault magnitude information, we can predict the remaining life of a component. The proposed method works for both static and dynamic systems.The new algorithm is highly relevant to this subtopic since it specifically asks for advanced techniques to monitor hydraulic pumps and motors. Our idea of identifying component failures will give accurate and early warning of failures and hence exactlyfulfills the goals of this subtopic. Health monitoring technology has many applications such as hydraulic pumps, motors, helicopter gearbox systems, jet and automotive engine diagnostics, and many of DOD's flight critical systems. The jet and automobileindustries are multibillion dollar industries that are commercial grounds for this technology. The proposed FDI method can be used in many systems mentioned above.