Development of a detection and diagnosis systems for alternator and starter testing

产品质量和可靠性仍然是汽车制造商的首要任务之一，这些必须是

Product quality and reliability continues to be one of the top priorities for auto manufactures, and these must be maintained in spite of the need for lighter parts and lower manufacturing costs. As the Original Equipment Manufacturers (OEMs) move to leaner structures, the demands placed on the equipment suppliers to assure quality and reliability of the products they produce is increasing. Typically the automotive suppliers have fewer internal resources than the OEMs with less capability and expertise to perform the required quality and reliability analysis. In this project we propose to implement a fault detection and diagnostic (FDD) strategy for electric alternators and starters. Current industry standards employ electrical and mechanical tests at the end of the assembly line. These current methods are not able to detect all faults, and thus there is a need for improved FDD strategies. In this project we propose to use acoustic and vibration measurements and introduce these to the end of line production test systems. The use of this type of data is not new, but their FDD implementation in production test environments with high background sounds and vibrations has proved challenging. McMaster has developed a number of unique algorithms that provide a capability to detect faults. These methods have proven effective in isolating the signals generated by faulty part from the background noise. In this project, acoustic and vibration measurements are used in a combined form in conjunction with Principal Components Analysis, Wavelets and a new filtering strategy referred to as the Smooth Variable Structure Filter (SVSF). By comparing against baseline, these algorithms will be used for the isolation and detection of faults in alternators and starters.