Electrical Signature Analysis provides insight into the quality of incoming power and it’s impact through an operating facility when matching prognostics to local distribution events. In most cases the loss of equipment and production due to these conditions is viewed as undefined or are completely missed as utility standards do not require reporting specific types of instances. In this presentation we will compare incoming power and impacts to internal equipment and production including the identification of ground and neutral conditions. The presentation will include several lessons-learned from power to load monitoring at several facilities and what actions were performed to mitigate the conditions.
Howard W Penrose, Ph.D., CMRP is the president of MotorDoc® LLC, a veteran-owned small business, a past-chair of the Society for Maintenance and Reliability Professionals (SMRP), an Institute of Electrical and Electronics Engineers (IEEE) various Power Engineering Society and Dielectrics and Electrical Insulation Society standards development committees, and Chair American Clean Power (ACP) standards committee and ACP powertrain committee. Dr. Penrose is a leading researcher in Electrical Signature Analysis prognostics and continuous monitoring and electric machinery machine learning and augmented intelligence practical applications. He is a 5-time recipient of the UAW/GM people make quality happen award, as well as being involved in the development of the LVAD heart-pump, low atmosphere flywheel insulation systems, high-temperature electric machine design, GM hybrid vehicle technology, and John Deere hybrid construction machine design and training. He is a past senior research engineer for the UIC Energy Resources Center (industrial/utility programs) and a committee member of US DOE commercial/industrial motor, VFD and pump-systems programs in the 1990s. He is the SMRP government relations chair of smart-grid, infrastructure and cybersecurity subcommittees and similar positions with other professional societies. He has been a Certified Maintenance and Reliability Professional since 2005 and holds professional machine learning and data science/engineering certifications from Stanford University, University of Michigan and IBM.