Reference number : GC-2017-Q3-00666, amendment number : , agreement type : G, recipient legal name : Habibi, Saeid (McMaster University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Idea to Innovation, program name french : De l'idée à l'innovation, program purpose english : Product quality and reliability continues to be one of the top priorities for manufacturers, 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 suppliers have fewer internal resources than the OEMs with less capability and expertise to perform the required quality and reliability analysis. At McMaster, we have developed and implemented a Fault Detection and Diagnostic (FDD) strategy for a range of applications including electric motor and internal combustion engine testing. In the applications considered, our FDD algorithm has achieved a fault detection rate of 100% and a diagnosis rate of 96%. In these applications, acoustic and vibration measurements were used in a combined form in conjunction with Principal Components Analysis, Wavelets and digital filtering. This is a considerable improvement compared to current industry standards; these employ electrical and mechanical tests against thresholds that are not able to detect all faults and have limited capability in fault diagnosis._x000D_
Our Advanced FDD system consists of two parts: 1) the FDD algorithm and software; and 2) a novel WIreless Sensory and Computing (WISC) platform that has been designed in a generic form for rotating machinery. The future applications of our FDD algorithms can include all systems exhibiting a periodic behavior. This may include biological systems such as the heart. A market assessment of our FDD system was performed and identified considerable opportunities for our technology for its application to automotive systems as well as wind turbines. This proposal pertains to the customisation of our Advanced FDD system for its application in these two specific sectors. This custom prototype is a critical step in the commercialization of this technology and will form the basis for a start-up venture._x000D_, program purpose french : Product quality and reliability continues to be one of the top priorities for manufacturers, 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 suppliers have fewer internal resources than the OEMs with less capability and expertise to perform the required quality and reliability analysis. At McMaster, we have developed and implemented a Fault Detection and Diagnostic (FDD) strategy for a range of applications including electric motor and internal combustion engine testing. In the applications considered, our FDD algorithm has achieved a fault detection rate of 100% and a diagnosis rate of 96%. In these applications, acoustic and vibration measurements were used in a combined form in conjunction with Principal Components Analysis, Wavelets and digital filtering. This is a considerable improvement compared to current industry standards; these employ electrical and mechanical tests against thresholds that are not able to detect all faults and have limited capability in fault diagnosis._x000D_
Our Advanced FDD system consists of two parts: 1) the FDD algorithm and software; and 2) a novel WIreless Sensory and Computing (WISC) platform that has been designed in a generic form for rotating machinery. The future applications of our FDD algorithms can include all systems exhibiting a periodic behavior. This may include biological systems such as the heart. A market assessment of our FDD system was performed and identified considerable opportunities for our technology for its application to automotive systems as well as wind turbines. This proposal pertains to the customisation of our Advanced FDD system for its application in these two specific sectors. This custom prototype is a critical step in the commercialization of this technology and will form the basis for a start-up venture._x000D_, agreement title english : Advanced fault detection and diagnosis system, agreement title french : Advanced fault detection and diagnosis system, agreement number : I2IPJ, agreement value : 125000.0, agreement start date : 2017-10-18, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada