Online and nonintrusive continuous motor energy and condition monitoring in process industries

Abstract

Maintaining electrical and mechanical systems within the industrial process environment continues to present a daunting challenge. With electrical motors at the center of most processes, prognostics are best accomplished during motor operation. However, since disruption of the process is rarely possible, often systems must be de-energized during scheduled outages before they can be maintained. Predictive maintenance techniques offer a viable solution to this dilemma. As a result, predictive maintenance has been the subject of many recent technical papers. Nonintrusive continuous monitoring of critical systems is emerging as the best method to maximize reliability and uptime with minimal impact on the plant process operation. This paper discusses the importance of predictive maintenance for industrial process applications and investigates a number of emerging technologies that enable this approach, including online energy efficiency evaluation and continuous condition monitoring. The paper gives an overview of existing and future technologies that can be used in these areas. Two methods for bearing fault detection and energy efficiency estimation are discussed. The paper concludes with focus on one pilot installation at Weyerhaeuserpsilas Containerboard Packaging Plant in Manitowoc, Wisconsin USA, where the site is realizing benefits from a new and novel approach.