Papers by Author: Feng Shou Gu

Abstract: Conventional condition monitoring techniques such as vibration, acoustic, ultrasonic and thermal techniques require additional equipment such as sensors, data acquisition and data processing systems which are expensive and complicated. In the meantime modern sensorless flux vector controlled drives can provide many different data accessible for machine control which has not been explored fully for the purpose of condition monitoring. In this paper polynomial models are employed to describe nonlinear relationships of variables available from such drives and to generate residuals for real time fault detection and performance comparisons. Both transient and steady state system behaviours have been investigated for optimal detection performance. Amongst 27 variables available from the drive, the torque related variables including motor current, I_d, I_q currents and torque signals show changes due to mechanical misalignments. So only these variables are explored for developing and optimising detection schemes. Preliminary results obtained based on a motor gearbox system show that the torque feedback signal, in both the steady and transient operation, has the highest detection capability whereas the field current signal shows the least sensitivity to such faults.

Abstract: This paper presents the use of the MUSIC algorithm improved by higher order statistics (HOS) to extract key features from the noisy acoustic emission (AE) signals. The low signal-to-noise ratio of AE signals has been identified as a main barrier to the successful condition monitoring of pump mechanical seals. Since HOS methods can effectively eliminate Gaussian noise, it is possible in theory to identify a change in seal conditions from AE measurements even with low signal-to-noise ratios. Tests conducted on a test rig show that the developed algorithm can successfully detect the AE signal generated from the friction of seal faces under noisy conditions.

Abstract: The induction motor is the most common driver in industry and has been previously proposed as a means of inferring the condition of an entire equipment train, predominantly through the measurement and processing of power supply parameters. This has obvious advantages in terms of being non-intrusive or remote, less costly to apply and improved safety. This paper describes the use of the induction motor current to identify and quantify a number of common faults seeded on a two-stage reciprocating compressor. An analysis of the compressor working cycle leads to current signal the components that are sensitive to the common faults seeded to compressor system, and second- and third-order signal processing tools are used to analyse the current signals. It is shown that the developed diagnostic features: the bispectral peak value from the amplitude modulation bispectrum and the kurtosis from the current gives rise to reliable fault classification results. The low feature values can differentiate the belt looseness from other fault cases and valve leakage and inter-cooler leakage can be separated easily using two linear classifiers. This work provides a novel approach to the analysis stator current data for the diagnosis of motor drive faults.

Abstract: Various research groups across the globe have developed models for engine condition monitoring and fault diagnosis based on the data from steady state performance measurements over the last two decade. However, these performance data are not amenable for easy collection in some situations and some of the data may show little performance deviation at the steady state conditions of operation. The aim of this study is to identify engine operating conditions and parameters that can be used to develop a diagnostic tool for internal combustion (CI) engine running on biodiesel blends fuel. Ricardo Wave Software was used to stimulate healthy and degraded engine. The degraded condition of operation was created by forcing one injector to work with 90%, 80% and 70% of the normal fuel flow efficiency. The measurable performance parameters such as brake power, brake torque and exhaust temperature and CO emission have been used to compare the deviations during steady and transient condition. From the comparison of the data obtained from transient and steady state simulation of the engine with and without injector fault, it can be concluded that the transient parameters show higher deviations and hence are better suited for condition monitoring and diagnostic modelling in engine working speed.

Abstract: In many cases, it is impractical to measure the vibrations directly at or close to their source. It is a common practice to measure the vibration at a location far from the source for condition monitoring purposes. The vibration measured in this way inevitably has high distortions from the vibrations due to the effect of the attenuation of signal paths and the interference from other sources. The suppression of the distortions is a key issue for the remote measurements based condition monitoring. In this paper, the influences of transducer locations are investigated on a typical gearbox transmission system for the detection of the faults induced to the gearbox. Several signal processing techniques’ analysis results show that the attenuation and interference cause high influences on the gear transmission signals. However, time synchronous average (TSA) is very effective to detect the local faults induced to the gear system.

Abstract: The free vibration of a fluid/structure system consisting of a cylindrical blockage submerged in a liquid enclosed by a cylindrical shell is investigated for the purpose of pipe line transportation monitoring. The wavenumbers are obtained and the reflection and transmission characteristics of these waves at the blockage interfaces are investigated theoretically. Reflection and transmission ratios are obtained in the axisymmetric mode, as functions of frequency. High order modes play an important role in the near field of the discontinuity and are taken into account.