Performance identifications of equipments used in the steam heating systems by acoustic analyses

The total system efficiency decreases due to the various losses in the systems where the steam is used as the purpose of processes in both industrial plants and large scale heating systems. Important losses occur because of the false work of the systems either during the steam production or during its transferring. These kinds of losses are most of the time bigger than the isolation losses. Fundamentally, it is possible to give the losses in two main groups as fitting losses and boiler losses. Vibration analysis depending on performance maintenances and trouble analyses has an important area for a long time. In this study, acoustic analysis techniques have been used to examine the steam traps which are used on the steam pipe fittings and to detect the working performances of the steam boilers. Because of the sound is a type of a signal, sound data was evaluated as a source of the digital signal. Signals were obtained by microphones which reflect the best of the acoustic data. This recorded data is accepted as time series and the spectral densities were obtained by doing Fourier transformation. Depending on the types of steam traps, recorded signals were correlated with the amounts of steam losses of steam traps and it was determined if they were in the maintains and change limits. The range of losses throughout the system were also calculated. Assessing the performance of the boiler, determination of coefficient of excess air and bearing failures in steam boilers were made by the acoustic analysis. Fourier Transformation and AR methods are utilized to obtain graphical data calculating the power spectral densities with the use of acoustic data from steam boiler combustion both for excess and lack of air. Excess air factor was determined by the method Yule-Walker. On the other hand, the frequencies of both on normal and defective bearings in an other steam boiler at the primer air fan were calculated by using Fourier transformation. The frequency of the defect was identified by applying FIR filter design.