Skip to Main Content
Generally industrial plants are anticipated to run constantly with full capacity with the aim of to meet the production needs. Abnormalities in the machinery or equipment must be detected and analyzed at the early stage to avoid major problems and cost consumption. Control valves are vital components of process control loops and the condition must be monitored on a regular basis to ensure that the performance does not turn beyond specified tolerance bands. A scheduled shutdown for inspection and diagnosis is usually implemented. Consequently, by monitoring the condition of control valves and the associated accessories, the maintenance strategy can be predicted for these critical components. This paper aims to study the effectiveness of Acoustic Emission (AE) technique as a fault detection monitoring system on control valves. The paper discusses a method based on different types of statistical analysis parameters such as kurtosis, standard deviation, max amplitude and RMS on time domain analysis of AE signals to distinguish between healthy and unhealthy control valves. A real time AE measurement system is developed and tested. The acquired AE signatures are processed and analyzed using MATLAB.