Signal Denoising Method Based on Adaptive Redundant Second-Generation Wavelet for Rotating Machinery Fault Diagnosis

Vibration signal of rotating machinery is often submerged in a large amount of noise, leading to the decrease of fault diagnosis accuracy. In order to improve the denoising effect of the vibration signal, an adaptive redundant second-generation wavelet (ARSGW) denoising method is proposed. In this method, a new index for denoising result evaluation (IDRE) is constructed first. Then, the maximum value of IDRE and the genetic algorithm are taken as the optimization objective and the optimization algorithm, respectively, to search for the optimal parameters of the ARSGW. The obtained optimal redundant second-generation wavelet (RSGW) is used for vibration signal denoising. After that, features are extracted from the denoised signal and then input into the support vector machine method for fault recognition. The application result indicates that the proposed ARSGW denoising method can effectively improve the accuracy of rotating machinery fault diagnosis

Data-Driven Distributed Optical Vibration Sensors: A Review

Distributed optical vibration sensors (DOVS) have attracted much attention recently since it can be used to monitor mechanical vibrations or acoustic waves with long reach and high sensitivity. Phase-sensitive optical time domain reflectometry (Φ-OTDR) is one of the most commonly used DOVS schemes. For Φ-OTDR, the whole length of fiber under test (FUT) works as the sensing instrument and continuously generates sensing data during measurement. Researchers have made great efforts to try to extract external intrusions from the redundant data. High signal-to-noise ratio (SNR) is necessary in order to accurately locate and identify external intrusions in Φ-OTDR systems. Improvement in SNR is normally limited by the properties of light source, photodetector and FUT. But this limitation can also be overcome by post-processing of the received optical signals. In this context, detailed methodologies of SNR enhancement post-processing algorithms in Φ-OTDR systems have been described in this paper. Furthermore, after successfully locating the external vibrations, it is also important to identify the types of source of the vibrations. Pattern classification is a powerful tool in recognizing the intrusion types from the vibration signals in practical applications. Recent reports of Φ-OTDR systems employed with pattern classification algorithms are subsequently reviewed and discussed. This thorough review will provide a design pathway for improving the performance of Φ-OTDR while maintaining the cost of the system as no additional hardware is required

Applications of machine learning to reciprocating compressor fault diagnosis: a review

Operating condition detection and fault diagnosis are very important for reliable operation of reciprocating compressors. Machine learning is one of the most powerful tools in this field. However, there are very few comprehensive reviews which summarize the current research of machine learning in monitoring reciprocating compressor operating condition and fault diagnosis. In this paper, the recent application of machine learning techniques in reciprocating compressor fault diagnosis is reviewed. The advantages and challenges in the detection process, based on three main monitoring parameters in practical applications, are discussed. Future research direction and development are proposed

MEMS micromirrors for imaging applications

Strathclyde theses - ask staff. Thesis no. : T13478Optical MEMS (microelectromechanical systems) are widely used in various applications. In this thesis, the design, simulation and characterisation of two optical MEMS devices for imaging applications, a varifocal micromirror and a 2D scanning micromirror, are introduced. Both devices have been fabricated using the commercial Silicon-on-Insulator multi-users MEMS processes (SOIMUMPs), in the 10 m thick Silicon-on-Insulator (SOI) wafer. Optical MEMS device with variable focal length is a critical component for imaging system miniaturisation. In this thesis, a thermally-actuated varifocal micromirror (VFM) with 1-mm-diameter aperture is introduced. The electrothermal actuation through Joule heating of the micromirror suspensions and the optothermal actuation using incident laser power absorption have been demonstrated as well as finite element method (FEM) simulation comparisons. Especially, the optical aberrations produced by this VFM have been statistically quantified to be negligible throughout the actuation range. A compact imaging system incorporating this VFM has been demonstrated with high quality imaging results. MEMS 2D scanners, or scanning micromirrors, are another type of optical MEMS which have been widely investigated for applications such as biomedical microscope imaging, projection, retinal display and optical switches for telecommunication network, etc. For large and fast scanning motions, the actuation scheme to scan a micromirror in two axes, the structural connections and arrangement are fundamental. The microscanner introduced utilises two types of actuators, electrothermal actuators and electrostatic comb-drives, to scan a 1.2-mm-diameter gold coated silicon micromirror in two orthogonal axes. With assistance of FEM software, CoventorWare, the structure optimisation of actuators and flexure connections are presented. The maximum optical scan angles in two axes by each type of actuator individually and by actuating the two at the same time have been characterised experimentally. By programming actuation signals, the microscanner has achieved a rectangular scan pattern with 7° 10° angular-scan-field at a line-scan rate of around 1656 Hz.Optical MEMS (microelectromechanical systems) are widely used in various applications. In this thesis, the design, simulation and characterisation of two optical MEMS devices for imaging applications, a varifocal micromirror and a 2D scanning micromirror, are introduced. Both devices have been fabricated using the commercial Silicon-on-Insulator multi-users MEMS processes (SOIMUMPs), in the 10 m thick Silicon-on-Insulator (SOI) wafer. Optical MEMS device with variable focal length is a critical component for imaging system miniaturisation. In this thesis, a thermally-actuated varifocal micromirror (VFM) with 1-mm-diameter aperture is introduced. The electrothermal actuation through Joule heating of the micromirror suspensions and the optothermal actuation using incident laser power absorption have been demonstrated as well as finite element method (FEM) simulation comparisons. Especially, the optical aberrations produced by this VFM have been statistically quantified to be negligible throughout the actuation range. A compact imaging system incorporating this VFM has been demonstrated with high quality imaging results. MEMS 2D scanners, or scanning micromirrors, are another type of optical MEMS which have been widely investigated for applications such as biomedical microscope imaging, projection, retinal display and optical switches for telecommunication network, etc. For large and fast scanning motions, the actuation scheme to scan a micromirror in two axes, the structural connections and arrangement are fundamental. The microscanner introduced utilises two types of actuators, electrothermal actuators and electrostatic comb-drives, to scan a 1.2-mm-diameter gold coated silicon micromirror in two orthogonal axes. With assistance of FEM software, CoventorWare, the structure optimisation of actuators and flexure connections are presented. The maximum optical scan angles in two axes by each type of actuator individually and by actuating the two at the same time have been characterised experimentally. By programming actuation signals, the microscanner has achieved a rectangular scan pattern with 7° 10° angular-scan-field at a line-scan rate of around 1656 Hz

Wavelet Theory

The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editor’s personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior