The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
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,...
Fault diagnosis of incipient crack failure in rotating shafts allows the detection and identification of performance degradation as early as possible in industrial plants, such as downtime and potential injury to personnel. The present work studies the performance and effectiveness of crack fault detection by means of applying wavelet packet decomposition (WPD) and empirical mode decomposition (EMD)...
A new MATLAB toolbox DB-KIT was recently developed for the design and implementation of fault diagnosis systems. For the purpose of key performance indicator (KPI) oriented fault detection, over the past few years, a series of test statistics and the corresponding thresholds were derived based on the modified data structures originating from the existing multivariate statistical analysis tools. These...
The fault diagnosis of gear transmission system is a complex process because of it's various influencing factors and variable performance. Further more, the gear transmission system often runs under variable load dynamic transient conditions. In order to extract the fault features from the complex running state accurately and improve the reliability and effectiveness of fault diagnosis, a novel approach...
Permanent magnet synchronous motor with its high torque density, high efficiency and high reliability, has become the mainstream of the drive system for electric vehicles, elevators, etc. The existing method of fault diagnosis based on the motor model has not considered the fractional characteristics of motor. it is difficult to effectively diagnose minor faults of the current. With the permanent...
Considering that the information uploaded by fault indicator devices is often lost or wrong in actual operation, a fault diagnosis method for distribution networks based on multi-source information is developed in this paper. The multi-source information includes information from distribution automation terminals and the customer electric information acquisition system (CEIAS). Firstly, using the...
DC-DC converters face an exponential growth in the context of the ever-increasing use of DC grids, namely at the home and business levels. In this domain, efficiency and reliability are of major concern. Solutions already available in the literature concerning fault-tolerant DC-DC converters do not consider the application of such converters in household environments and their constraints. To solve...
Fault diagnosis of roller bearings in rotating machinery is of great significance to identify latent abnormalities and failures in industrial plants. This paper presents a new self-adaptive fault diagnosis system for different conditions of roller bearings using InfraRed Thermography (IRT). In the first stage of the proposed system, 2-Dimensional Discrete Wavelet Transform (2D-DWT) and Shannon entropy...
The modular multilevel converter with series and parallel connectivity was shown to provide advantages in several industrial applications. Its reliability largely depends on the absence of failures in the power semiconductors. We propose and analyze a fault-diagnosis technique to identify shorted switches based on features generated through wavelet transform of the converter output and subsequent...
In order to extend the life of the Solid Oxide Fuel Cell system and maximize the performance of the stack, it is very important to study the fault diagnosis method of SOFC system. At First, this paper analyzes the phenomenon and mechanism of the blower fault and leakage fault for the SOFC system. At last, this paper introduce a method which uses the fault tree method to diagnose the external system...
In this paper, a reinforcement learning approach is proposed to detect unexpected faults, where the noise-to-signal ratio of the data series is minimized for achieving robustness. The model parameter is taken as a special action of the reinforcement learning, and the policy valuation and policy improvement are utilized to find the parameters, which can make the estimated model consistent to the real-time...
Accurate fault diagnosis, with immediate fault identification and isolation, is of paramount importance for power converters of switched reluctance motor drives, as it allows early adoption of fault tolerant procedures that eliminate the adverse effects of faults on machine operation. This paper presents an online fault diagnostic algorithm for power converter faults in SRM drives based on high frequency...
This paper presents the design, analysis, and experimental validation of a fault detection and identification (FDI) scheme for dc-dc power electronic converters. The FDI scheme includes two new classes of fault filters: (1) a linear-switched fault detection (FD) filter and (2) a bank of linear-switched fault identification (FI) filters. Both the FD filter and the bank of FI filters have a structure...
The paper proposes a novel method for health monitoring and early stage fault diagnosis of IGBT by analyzing the electromagnetic radiation (EMR) pattern. The main cause behind IGBT failure is the evolving stress due to thermal cycle. The change in the operating characteristic of IGBT affects the EMR signature. The paper establishes the relation between different IGBT characteristic with EMR pattern...
This paper proposes a method for fault diagnosis of high-resistance connection (HRC) in vector-controlled permanent magnet synchronous machine (PMSM) drive system, which is based on a signal injection strategy applied to the PMSM control system during its normal operation. Two kinds of the signal injection methods are proposed to diagnose the HRC. In the proposed method, not only HRC fault can be...
Series arc fault is an important incentive for electrical fires. Wavelet transform is a widely used series arc fault identification method. However, it is difficult to distinguish the normal condition and arc fault when only using wavelet transform, and a large amount of redundant data will be generated. To solve this problem, this paper presents a new series arc fault identification method which...
Model predictive control (MPC) is a promising alternative for power electronics and electric drives. Research on fault diagnosis and fault-tolerant control for power converters with MPC is insufficient. Accurate fault diagnosis and fault-tolerant control solutions with easy implementation are very desirable. In this work we propose a novel current based fault diagnosis method of one-and two-phase...
The realization of early detection of incipient faults makes great sense for the guarantee of system performance and security operation. Therefore, It is necessary to estimate the fault amplitude especially when the system security assessment is the main goal. Regarding the incipient fault with low Fault-Noise-ratio (FNR), in this paper, a practical online fault estimation method is presented for...
In the practical engineering of cement vertical mill, many faults occur in the bearings, including the driving end and the fan end. This paper introduces the structure of common bearing, and analyzes the potential fault position and the characteristic frequency when fault occurs. Furthermore, an improved empirical mode decomposition algorithm is adopted to study the fault characteristic of bearings...
The fault detection and estimation problems are investigated for a class of Markov jump linear systems (MJLS) with state delays based on the particle filter. For MJLS subjected to the actuator fault, we use particle filter to estimate the Markov parameter, then the states are estimated depended on the Kalman filter. According to the estimation result, a residual is designed by using the sliding-time...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.