Condition monitoring - fault detection and diagnosis Literature review

Condition monitoring - fault detection and diagnosis - Literature review Example Hybrids of SVM methods such as combined SVM (CSVM) have been used extensively for process control such as in the Eastman process. Results indicate the superiority of SVM based methods over other methods of control (Tafazzoli & Saif, 2009). SVM methods have been employed extensively in order to classify reciprocating compressor faults. SVM methods were employed in order to classify faults of reciprocating refrigeration compressors through the application of wavelet transform and statistical methods. Significant features were extracted from both raw noise signals and vibration signals. The selection of relevant RBF kernel parameters was carried out through iteration (Yang et al., 2005). In a similar application, SVM methods were applied to reciprocating compressors butterfly valves to classify cavitation faults (Yang et al., 2005). A comparable research was performed on reciprocating compressor valves to classify faults through vibration signals alone. Data for this purpose was gathered from the surface of the valve and the resulting vibration signals were decomposed by applying local wave methods (Ren et al., 2005). One of the larger problems posed by reciprocating compressor valves is the non stationary and non linear characteristics of the extracted vibration signals. In order to deal with the non stationary and non linear nature of such data, information entropy with good fault tolerance potential was utilised as the feature parameter fed to a SVM. This was utilised as being a comprehensive characteristic of the raw vibration signal. The resulting decision function was used to solve the limits of traditional fault classifications. The added strength of the SVM was its ability to be trained with only a few input samples to deal with multiple new faults (Chen & Lian, 2010). The small linear pattern recognition performance and relatively small data sets extracted from reciprocating