This SBIR Phase I research proposal proposes research to develop an ultra-compact, low cost system for wirelessly monitoring motors that will cost manufacturers less than $300/ motor to implement. The research will leverage existing patent-pending energy-efficient algorithms for determining motor condition based on vibration and temperature data to develop wireless nodes capable of autonomously determining the condition of any motor to which they are attached. The research will result in a prototype system of wireless nodes implemented at an industrial partner, which will provide the necessary incentive for future investment in the company and technology.
The broader impact of this research will be to enable a wireless system to facilitate condition-based maintenance of electric motors in industrial facilities at a cost of less than $300 per motor to manufacturers, which is about 10% of the cost of current systems. At this price point, tens of thousands of facilities around the United States will be able to afford the initial investment to implement condition-based maintenance on their motor systems. Since condition-based maintenance has been shown to maximize up-time and minimize yearly maintenance costs, this will increase the competitiveness of American manufacturing and ultimately help create more manufacturing sector jobs. Additionally, the prototype system produced as a result of the research will provide an important proof-of-concept for low-cost, low-power wireless sensor nodes that should help spur future development and investment in this field, which is in turn instrumental for the development of "smart grids", "smart cities", and other intelligent infrastructure.
The research performed by Energizing Solutions under this NSF SBIR Phase I Project has facilitated the development of a low-cost wireless system for monitoring industrial electric motors. More specifically, the end-goal of the research started under this project is to facilitate condition-based maintenance of electric motors in industrial facilities at a cost of less than $300 per motor to manufacturers, which is about 10% of the cost of current systems. At this price point, tens of thousands of facilities around the United States will be able to afford the initial investment to implement condition-based maintenance on their motor systems. Three significant project outcomes characterize the research performed under this project. 1) A prototype wireless sensor node (pictured in Figures One - Six) was designed and manufactured. The node consists of a 32-bit low-power microprocessor, a Wireless HART radio, sensor attachments which include accelerometers and temperature sensors, and peripheral housings and electronics. The sensor attachments magnetically couple to the motor housing near the motor bearings and feed information to the microprocessor, which runs patent-pending algorithms to determine the motor condition based on sensor data. The wireless radio then transmits this data through a network manager (Figure Six) back to the computer of a plant manager, where he/she can access the condition of the plant's motors. 2) The operation of the wireless node was validated in both laboratory and real-world conditions. A range of >200m was achieved even in industrial environments with significant electromagnetic interference and multi-path fading. 3) Prototype multi-node wireless networks for motor monitoring were demonstrated at two separate industrial partners, covering 12 motors in total. The network implements self-organizing wireless mesh technology, allowing the network to cope with the challenging conditions at the industrial partner facilities, which included a power plant and an aerospace manufacturing company. This network proves the viability of low-cost low-power wireless technology for industrial motor monitoring applications. Ultimately, Energizing Solutions' motor monitoring technology as developed under this grant will be used by plant managers to continuously monitor motor condition and thus facilitate condition-based maintenance. Since condition-based maintenance has been shown to maximize up-time and minimize yearly maintenance costs, this will increase the competitiveness of American manufacturing and ultimately help create more manufacturing sector jobs. Additionally, the prototype system produced as a result of the research will provide an important proof-of-concept for low-cost, low-power wireless sensor nodes that should help spur future development and investment in this field,which is in turn instrumental for the development of "smart grids", "smart cities", and other intelligent infrastructure.
