Performance Analysis of Stiction Detection Methods
S.Abirami1, S. Sivagamasundari2

1S. Abirami, Research Scholar, Department of Electronics and Instrumentation Engineering, Annamalai University, Chidambaram – 608002, India.
2S. Sivagamasundari, Department of Electronics and Instrumentation Engineering, Annamalai University, Chidambaram – 608002, India.

Manuscript received on 22 August 2019. | Revised Manuscript received on 19 September 2019. | Manuscript published on 30 September 2019. | PP: 1369-1374 | Volume-8 Issue-11, September 2019. | Retrieval Number: J96790881019/2019©BEIESP | DOI: 10.35940/ijitee.J9679.0981119
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Abstract: Industrial studies stated that, nearly 30% of badly performing process control loops are produced by nonlinearities in the pneumatic control valves, one among the main cause is stiction. The influence of this stiction nonlinearity is commonly detected as the process variable oscillations. As industrial plants contain several loops that are interacting, these oscillations will be spread to the whole system. Overhauling the defective valves will be the one among the top solution to this problem, which is probable only during the period of shut down process. But, this solution of process shut down to separate the defective valve is not cost-effective solution and hence it is taken into account as the prime one. So, there is a necessity for a technique to identify the effect of the control valve stiction. Detection algorithms available in literature are numerous and these techniques create either a quantitative or a qualitative statement about the occurrence of stiction in the control valve. While using available data, a detection method is considered to be effective only when its concluding result is relatively reliable. The main drawback while detecting stiction is that the stem position (MV) of the valve is not available in most of the situations. Quantifying the actual position of the control valve stem is always not probable. Commonly, process output and controller output are taken as the available data from most of the processes. The methods which use these data sets (PV and OP) are more appreciable by the control engineers. In this work, modified bispectral analysis technique is used as control valve stiction detection method and to prove its efficiency four different existing detection techniques available in literature are considered in this study and the performance of each method is reported. Here, eleven different data sets, seven from different laboratory processes and four from process industries are used to make the comparative analysis of performance.
Keywords: Detection, stiction, stem position, process output, controller output, Modified Bispectral analysis.
Scope of the Article: Probabilistic Models and Methods