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This paper proposes a novel approach for machine fault diagnosis using industrial wireless sensor networks (IWSNs) and on-sensor calculation. In this paper, the induction motor and vibration signal are taken as an example of the monitored industrial equipment and signal due to their wide use. The discrete wavelet transform and wavelet energy-moment are used for on-sensor machine fault feature extraction,...
Condition monitoring of machinery has entered the big data era, while the existence of dirty data reduces the quality of the whole data. In order to recognize the dirty data included in machinery monitoring data, a new method is proposed in this paper. First, a feature named sampled power index (SPI) is designed to transform the dirty data recognition issue into the outlier recognition. Then the windowing...
The operation of bearings usually results in a dynamic behavior generating stationary and non-stationary vibration signals mixed with an amount of background noise. Therefore, the condition monitoring of bearings becomes difficult since the purpose is to extract health indicators able to detect the appearance of faults, track their evolution and predict the bearings' remaining useful life. The aim...
The Prognostics and Health Management (PHM) can be considered as a key process to deploy a predictive maintenance program. Since its inception as an engineering discipline, a lot of diagnostics and prognostics algorithms were developed and furthermore methodologies for health management and PHM development established. These solutions were applied in a lot of industrial cases aiming a maintenance...
Industrial manufacturing plants often suffer from reliability problems during their day-to-day operations which have the potential for causing a great impact on the effectiveness and performance of the overall process and the sub-processes involved. Time-series forecasting of critical industrial signals presents itself as a way to reduce this impact by extracting knowledge regarding the internal dynamics...
With ever-increasing awareness on quality and reliable power distribution, the research in the area of automation of distribution system has great relevance from the practical point of view. Electric power utilities throughout the world are more and more adopting computer aided control, monitoring and management of electric power distribution system to offer improved services to the consumers of electricity...
Power transformer is one of key equipment in power system and its normal operation guarantees reliability and safety of power transmission. In order to keep power transformer in good condition, regular inspection and maintenance is needed after equipment put into service. Various preventive test, on-line monitoring and portable test are must, but condition evaluation and fault diagnosis for power...
Since the last years, there is an increasing interest from the industrial sector to provide the electromechanical systems with diagnosis capabilities. In this context, this work presents a novel monitoring scheme applied to diagnose faults in the main rotatory element of an industrial packaging machine, the camshaft. The developed diagnosis method considers a coherent procedure to process the acquired...
Condition-based predictive maintenance can significantly improve overall equipment effectiveness provided that appropriate monitoring methods are used. Online condition monitoring systems are customized to each type of machine and need to be reconfigured when conditions change, which is costly and requires expert knowledge. Basic feature extraction methods limited to signal distribution functions...
An Industrial Wireless Sensor Network system is described for condition monitoring of electric machines. On-sensor data processing is used to reduce the amount of information that needs to be transmitted, thus saving communications energy. Based on a condition monitoring interval of 3 seconds, and using 2 AAA batteries for power, the system lifetime is measured for four different operating modes....
This paper will study condition monitoring signals of a distributed generation (DG) system not only due to the mechanical and electrical faults inside the wind turbines but also due to the grid system fluctuations. A novel feature extraction and characterisation method based on singularity detection of the monitoring data will be presented, aiming to identify the abnormal events and fault conditions...
In this work a novel wavelet-fuzzy logic approach to structural health monitoring is proposed based on wavelet transform theory and fuzzy logic technology. The proposed method combines the effectiveness of the Wavelet Packet Transform (WPT) as a tool for feature extraction and the capabilities of fuzzy sets to model vagueness and uncertainty. Two stages of operation are considered: pattern training...
Structural Health Monitoring (SHM) is the process of continuous and autonomous monitoring of the physical condition of a structure by means of sensors. It is a mean of Non-Destructive-Inspection for monitoring and ensuring the structural integrity of aircraft. SHM techniques have been explored to reduce air vehicle maintenance and repair costs while maintaining safety and reliability. This research...
An algorithm based on ant colony algorithm for health condition monitoring of aero-engine was put forward. The algorithm conversed the health status classification of aero-engine into solving the clustering-based optimization problem with constrain. Ant colony algorithm based on colony collaboration and learning could solve this clustering problem. The proposed algorithm was applied to monitor health...
Multifractal analysis is applied to extract nonlinear features from complex systems for condition recognition. Abnormal condition is hazardous for process industry complex system which may lead to accidents. Comparing with traditional techniques of condition recognition without concerning nonlinearity of complex system, multifractal spectrum elaborately reveals scale-invariance or self-similarity...
Modern engineering systems are becoming increasingly complex, sophisticated, demanding and globally distributed. Maintaining and sustaining such systems healthy, reliably, safely wherever and whenever needed efficiently and economically is a challenging task facing the 21st century. It is gratifying to note that significant advances are being made by researchers from academia, public and private R...
There has been increasing application of on-line partial discharge (PD) based cable insulation condition monitoring among utilities worldwide due to the ability of on-line PD monitoring to allow incipient insulation faults to be detected and aged cable replacement program to be prioritised. However the application is also accompanied with a number of challenges. Data from on-line PD monitoring systems...
Detection and diagnosis of partial discharge (PD) activity has been widely adopted in electrical plant condition monitoring. For many years incipient partial discharge faults in power cables have been identified through off-line investigation techniques. With the development of measurement technology, more recently, continuous on-line monitoring systems are being installed, because in comparison with...
As rotating machines perform an important role in industrial applications, many researchers have developed various condition monitoring system and fault diagnosis system by applying various techniques such as signal processing and pattern recognition. Recently, fault diagnosis systems using artificial neural network have been proposed. This paper proposes the neural-network-based fault diagnosis system...
This paper describes the application of an active structural health monitoring technique for a composite plate bonded with a distributed piezoceramic patches array. To maximize the performance of a structural health monitoring (SHM) system, an optimal placement of these patches has been proposed using grammians of controllability and observability and the H∞ modal norm. The proposed approach was established...
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