Condition monitoring and diagnosis of steam traps with wireless smart sensors

Abstract

An autonomous, wireless and self-powered smart sensor is described, addressing the condition monitoring and diagnosis of steam traps, whose performance degradation impairs energy efficiency in most of the process industries. The diagnostic criteria in the two possible failure modes of steam traps are presented, as well as the structure and technologies of the embedded devices for sensing, communication, and power supply, special attention being paid to the capability to run the system on the thermoelectric energy gathered from local pipes. Also, a platform supporting the integration of 'field' devices in large numbers is presented, which may address the data requirements in the scope of Asset Management.