SBIR Phase II: Proposal for Research into Low-Cost Distributed Wireless Sensing of Operational Condition in Industrial Electric Motors

This Small Business Innovation Research (SBIR) Phase II project will result in a commercially viable network of low cost wireless sensors that predict electric motor failure before failure occurs. American industries and manufacturers rely heavily on electric motors to power their equipment and processes. To minimize motor downtime costs, many use labor intensive preventative maintenance programs, manually inspecting motors on a fixed schedule. These inspections cost an average of $500 per motor per year, with 80% of that cost wasted. This waste can be eliminated through the use of sensors that monitor motor performance in real time, 24x7. Unfortunately, current systems cost thousands of dollars per motor on average. This is too expensive for most 1-150 HP motor applications, which comprise 98% of the motor market. This research will quantify and refine the performance of a low cost network of sensor nodes, and algorithms used by the nodes to predict motor failures, through controlled laboratory testing and field testing. It will also integrate vibration energy harvesting technology into the nodes. The result will be a network of sensor prototypes that are demonstrated to meet key performance and price metrics, and are commercially viable for use with 1-150 HP motors. The broader impact/commercial potential of this project is that a prototype low cost sensor system will facilitate predictive maintenance of electric motors in US industrial and manufacturing facilities at a fraction of the cost of the current alternatives. As a result, tens of thousands of facilities around the US will be able to afford the initial investment to implement predictive maintenance on their motor systems, maximize up-time, and minimize motor maintenance costs. This will increase the competitiveness of these US industrial and manufacturing firms and ultimately help create and preserve American 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.