Bruno Fazenda

This paper presents the use of the induction motor current to identify and quantify common faults within a two-stage reciprocating compressor. The theoretical basis is studied to understand current signal characteristics when the motor undertakes a varying load under faulty conditions. Although conventional bispectrum representation of current signal allows the inclusion of phase information and the elimination of Gaussian noise, it produces unstable results due to random phase variation of the sideband components in the current signal. A modified bispectrum based on the amplitude modulation feature of the current signal is thus proposed to combine both lower sidebands and higher sidebands simultaneously and hence describe the current signal more accurately. Based on this new bispectrum a more effective diagnostic feature namely normalised bispectral peak is developed for fault classification. In association with the kurtosis of the raw current signal, the bispectrum feature gives rise to reliable fault classification results. In particular, the low feature values can differentiate the belt looseness from other fault cases and discharge valve leakage and intercooler leakage can be separated easily using two linear classifiers. This work provides a novel approach to the analysis of stator current for the diagnosis of motor drive faults from downstream driving equipment.

This paper reviews analytical models and software for sound propagation modelling and prediction, including room acoustics and outdoor sound propagation, and current instrumentation for sound measurement. Based on the review of the state-of-the-art for acoustic modelling and sound measurement instrumentation, emerging challenges are discussed. Finally, the paper proposes new instrument development using 3D sound-field sensor arrays and 1D/2D acoustic sensor arrays incorporated with sensor networks for soundscape investigation and further applications.

This paper introduces a new method for the estimation of sound source distance and direction using at least three microphone sensors in indoor environments. Unlike the other methods that normally use approximations in obtaining the time difference between sensors, this method exploits the existed geometrical relationships of the sensors to form an exact solution to estimating the source position. To overcome reverberation, an enhancing pre-process has been used for different sound sources with different spectra, e.g., single frequency, multiple frequencies and different noise shapes. Source direction and distances are estimated from time of sound wave travel and distances of acoustic sensors. Using the method described in this paper a level of 1° accuracy is obtained. Several experimental tests have been undertaken that verify the results. Conclusions and future work are also described.

This paper introduces a new method for the estimation of sound source distance and direction using at least three microphone sensors in indoor environments. Unlike the other methods that normally use approximations in obtaining the time difference between sensors, this method exploits the existed geometrical relationships of the sensors to form an exact solution to estimating the source position. To overcome reverberation, an enhancing pre-process has been used for different sound sources with different spectra, e.g., single frequency, multiple frequencies and different noise shapes. Source direction and distances are estimated from time of sound wave travel and distances of acoustic sensors. Using the method described in this paper a level of 1° accuracy is obtained. Several experimental tests have been undertaken that verify the results. Conclusions and future work are also described.

A system has been investigated for the detection of incoming direction of an emergency vehicle. Acoustic detection methods based on a cross microphone array have been implemented. It is shown that source detection based on time delay estimation outperforms sound intensity techniques, although both techniques perform well for the application. The relaying of information to the driver as a warning signal has been investigated through the use of ambisonic technology and a 4 speaker array which is ubiquitous in most modern vehicles. Simulations show that accurate warning information may be relayed to the driver and afford correct action.

This paper presents an investigation into the diagnosis of transmission belt condition through acoustic monitoring. A relevant belt model and laser interferometry measurements are used to guide the design and analysis of the acoustic monitoring system. The fault under scrutiny is the development of a loss of tension in the belt which may occur due to degradation of belt material. Results show that it is possible to diagnose this kind of fault using acoustic diagnostic techniques. Analysis of acoustic signals reveals changes in the natural frequencies of the belt which are matched by results for laser interferometry.