Fault Detection Technology Research Articles

Automated fault detection and diagnosis methods for supermarket equipment (RP-1615)

Many automated fault detection and diagnostics methods have been developed for application to building mechanical systems over the past 20 years because they have the potential to reduce operating costs and energy consumption by providing early warning of performance degradation faults. Supermarkets could be a very beneficial setting to deploy automated fault detection and diagnostics, particularly in the refrigeration systems, which are major energy users and are known to commonly suffer from significant refrigerant leakage problems. The current article provides an overview of the common mechanical systems deployed in supermarkets, and then describes a comprehensive review of the literature on automated fault detection and diagnostics methods from other systems that could potentially be applied in supermarket settings. A collection of supermarket field data is analyzed in the context of its potential use in automated fault detection and diagnostics methods from other systems. The review includes methods to categorize and assess the automated fault detection and diagnostics approaches, from the perspective of a potential adopter of automated fault detection and diagnostics technology for a supermarket setting. The article concludes that supermarket automated fault detection and diagnostics is still in the early stages of development and that there is a need to further develop automated fault detection and diagnostics methods for supermarket applications. To facilitate the development of supermarket-specific automated fault detection and diagnostics approaches, additional data sets from refrigeration equipment are needed.

Fault detection of aircraft based on support vector domain description

To realize intelligent fault detection of aircraft lacking fault samples, a novel fault detection algorithm for aircraft based on Support Vector Domain Description (SVDD) is proposed. The Genetic Algorithm (GA), threshold scaling factor, rapid anomaly detection, modifying kernel function and SVDD model boundary based on equal loss are introduced to the fault detection algorithm. The empirical analyses show that the method has good fault detection ability. The classification accuracy is improved by 5.52% after using the GA. The fault detection time of the SVDD algorithm is improved by 0.4 seconds on average when compared to the red line shutdown system. The accurate classification rate is enhanced by 0.0225, and the number of support vectors is reduced by 1 after adopting the modified kernel function. The fault detection algorithm in this paper provides novel intelligent fault detection technology for aircraft.

Advanced Primary–Backup Platform with Container-Based Automatic Deployment for Fault-Tolerant Systems

Within mission-critical systems, the primary–backup scheme is a desirable approach for improving reliability and fault tolerance. It can be used to ensure a high mission success rate despite unexpected errors. However, it must cope with the need to maintain consistency between a primary and a backup whenever the primary encounters unexpected errors. We overcome this issue by introducing a platform that uses container-based light virtualization and an automatic build system to isolate an application so that it may then be deployed on different devices without manual intervention. We believe an advanced deployment procedure can retain the consistency of the primary–backup systems with low implementation complexity. Integrated with a cloud application, it can also manage mission-critical systems effectively, communicate with the redundant systems, and detect unexpected errors by using sophisticated fault-detection technologies. We demonstrate that the platform can improve the reliability of mission-critical systems through realistic experiment using a model electronic vehicle and can reduce hardware dependencies.

Adaptive Fault Detection Technology Research Based on Distributed Database Disaster

Distributed storage systems demonstrate superior performance in terms of capacity, I/O throughput and scalability, but the reliability of inexpensive components is not high, and it is easy to cause catastrophic consequences of data loss. Fault detection is a key technology to provide high availability for distributed system, the new adaptive fault detection system architecture is proposed in this paper, which considered availability and disaster recovery ability, is divided into four levels: 1) Client layer: in this layer, customers can keep in touch with local network or outside network disaster recovery/backup center; 2) Server layer: in this layer, the high availability is guaranteed by its backup scheme; 3) Local recovery layer: in this layer, data backup and recovery are realized through local real-time replication; 4)Remote recovery layer: in this layer, data backup and recovery are realized (delayed) through remote backup database. And we evaluated and tested this method in our lab network environment.

A Comprehensive Review of Catastrophic Faults in PV Arrays: Types, Detection, and Mitigation Techniques

Three major catastrophic failures in photovoltaic (PV) arrays are ground faults, line-to-line faults, and arc faults. Although there have not been many such failures, recent fire events on April 5, 2009, in Bakersfield, CA, USA, and on April 16, 2011, in Mount Holly, NC, USA, suggest the need for improvements in present fault detection and mitigation techniques, as well as amendments to existing codes and standards to avoid such accidents. This review investigates the effect of faults on the operation of PV arrays and identifies limitations to existing detection and mitigation methods. A survey of state-of-the-art fault detection and mitigation technologies and commercially available products is also presented.

Application benefits of Distribution Automation and AMI systems convergence methodology for distribution power restoration analysis

Abstract Self healing mechanisms to minimize the impact of faults and outages on distribution grid are being considered as one of the critical requirements for smart distribution grid. Many automation technologies were being developed and proposed in order to meet these requirements. Power restoration techniques based on Distribution Automation’s Fault Detection, Isolation and Restoration (FDIR) technology at feeder level and Advanced Metering Infrastructure’s Outage Management System (OMS) at the LV distribution level are two such complementary technologies evolved over the past few years in order to locate, isolate the faults and restore the power quickly to as many loads as possible, which are not affected by the faults or outages. With the evolution of new system level paradigm, Distribution Automation (DA) and Advanced Metering Infrastructure (AMI) System’s convergence, it is possible to improve the effectiveness and efficiency of power restoration schemes with AMI acting as a feedback system to the DA system supporting required communication latency, bandwidth and protocols. This paper illustrates the benefits of the distribution power restoration method based on DA–AMI convergence approach.

On the Fault Detection Technology of the Cable Based on the Empirical Mode Decomposition Filter

Once malfunctions of power cables occur, rapid and accurate determination of the fault location not only reduces the cost of repairing and the outage loss, but also improves the reliability of power supply. The detection signal of cable fault is susceptible to the noise of test fleld, so it is of di‐culty to identify the characteristic points of the re∞ected pulse from the fault location, thus fails to meet the requirements of fault location. This paper makes an analysis of the law of the time-frequency distribution of the disturbed pulse signal with the Empirical Mode Decomposition (EMD) method, and also realizes how to determine the cut-ofi point of the components dominated by the noise and the useful signal in the component of eigenmode with the method based on autocorrelation function. Since this method is able to eliminate the useful signals in the dominant components in the noise, which has negative efiect on the accuracy of the reconstructed signal, a method of wavelet fllter is proposed to extract the useful signal from the component of eigenmode dominated by the noise. Finally, the results from numerical simulation validate this method in improving the performance of flltering.

Numerical and Experimental Study on the Effect of Signal Bandwidth on Pipe Assessment Using Fluid Transients

AbstractA non-intrusive fault detection technology for real time condition assessment of pipelines is highly desirable for pipeline operators and the use of artificially induced fluid transients for this purpose has been the topic of many studies in the past. Fluid transients are stress waves in the fluid that can propagate through pipelines at high speeds and can collect information on the pipe condition during its travel. Whilst many transient-based fault detection methods have been proposed in the literature, little work was done on the characteristics of the transient signal that is best suited for fault detection. Such a study is critical for the development of this technology as the generation of controlled pressure waves is a challenging key step of the procedure. This paper presents analytical, numerical and experimental results to illustrate the effect of signal bandwidth (frequency content) of the induced transient signals has on the spatial resolution, accuracy and range of transient based faul...

Effective model based fault detection scheme for rudder servo system

The inherent nonlinearities of the rudder servo system (RSS) and the unknown external disturbances bring great challenges to the practical application of fault detection technology. Modeling of whole rudder system is a challenging and difficult task. Quite often, models are too inaccurate, especially in transient stages. In model based fault detection, these inaccuracies might cause wrong actions. An effective approach, which combines nonlinear unknown input observer (NUIO) with an adaptive threshold, is proposed. NUIO can estimate the states of RSS asymptotically without any knowledge of external disturbance. An adaptive threshold is used for decision making which helps to reduce the influence of model uncertainty. Actuator and sensor faults that occur in RSS are considered both by simulation and experimental tests. The observer performance, robustness and fault detection capability are verified. Simulation and experimental results show that the proposed fault detection scheme is efficient and can be used for on-line fault detection.

Overview of Fault Detection and State Diagnosis Technology in Wind Turbine Blades

The blade is an important component in wind turbines, and the detection and diagnosis of its defects has become an important subject in wind power industry. This paper introduces the principles of the existing methods for state detection and fault diagnosis in wind blades, and then discusses the deficiency of each method. The existing difficulties and some key problems to be solved are also pointed out in this paper. Finally, the trend of its future development has been discussed.

LATEST PROGRESS OF FAULT DETECTION AND LOCALIZATION IN COMPLEX ELECTRICAL ENGINEERING

Abstract In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

Qualitative Simulation Theory and its Applications

Describes the background and qualitative simulation theory development, then describes the qualitative simulation and application of fault detection, fault detection Finally, qualitative simulation development are discussed. In order to deal with this kind of challenge, appear a series of system fault detection and diagnosis technology, including qualitative simulation technology is one of the important technical one. Through the Qualitative Simulation theory QSIM (Qualitative Simulation) related theory analysis and of the technology in fault detection field operation of the process of research, analysis found that the technology in the field of FDD advantages and disadvantages, in view of the existing shortage, it gives a fuzzy set theory and similarity principle on the make, theoretically perfect this model, and the detection and diagnosis research form an effective guidance.

Reconfiguration and optimization of flight control system based on multi-model adaptive method

For the reconstruction problem of the flight control law when aircraft actuator was damaged or in failure cases,a new reconfiguration scheme of flight control system was proposed based on the linear quadratic optimal control theory and multi-model adaptive method.Based on fault diagnosis and detection technology,the reference model was obtained by the Linear Quadratic Regulator(LQR).Lyapunov stability theory was applied to ensure the strictly positive real parts and global asymptotic stability of the closed-loop control system.According to the vehicle dynamics control law for fault identification and model switching,the reconfiguration and optimization of vehicle control law based on the multi-model adaption was designed.Against the typical fault conditions,the reconfiguration simulation of the flight control system was made to verify the method,and the corresponding verification results were given,which can ensure that the aircraft effective operation.

Fault Detection and Diagnosis Based on Qualitative Simulation

Engineering technology system's complexity cause a series of system problems, this is without a doubt the contemporary control engineering field important challenges. In order to deal with this kind of challenge, appear a series of system fault detection and diagnosis technology, including qualitative simulation technology is one of the important technical one. Through the Qualitative Simulation theory QSIM (Qualitative Simulation) related theory analysis and of the technology in fault detection field operation of the process of research, analysis found that the technology in the field of FDD advantages and disadvantages, in view of the existing shortage, it gives a fuzzy set theory and similarity principle on the make, theoretically perfect this model, and the detection and diagnosis research form an effective guidance.

A Case Study of Distributed Network Fault Detection Technology in Distance Education

The intrusion detection under the environment of IPv6 is an important security technology along with firewall in system security defense system, which can be used for real-time detection and monitoring of the system in the whole process of system invasion. This paper puts forward an intrusion detection system under IPv6 platform based on intrusion detection feature attribute reduction by using pattern matching, so as to expand the range of application and user group of the security products. By the analysis and comparison of various pattern matching algorithms, the new algorithm realizes the intrusion feature module matching under IPv6, and make detection system be of high efficiency. Later experiments have proved this view.

A Remote Educational Video Dynamic Image Sharp Processing Algorithm

In distance education network transmission process, because transmission distance is too long, transmission network will be affected by complicated external environment factors, which leads to network failure and failure in remote education video image formation, and finally causes unsmooth transmission. This paper puts forward a distributed network fault detection technology to perform fault detection for remote education transmission network nodes and characteristic analysis of the use of network fault by using genetic neural network, accurately locate fault node area so as to realize the remote education networks fault detection. Experiments show that this method can avoid distance education network fault resulted from long transmission distance and improve the transmission efficiency of remote education video image.

Research on Hybrid Renewable Energy Systems with Fault Detection Technology

Research on Hybrid Renewable Energy Systems with Fault Detection Technology

Fault Tolerant Control in Redundant Inertial Navigation System

Conventional fault detection and isolation technology cannot fully ensure system redundancy features when sensors experience drift in a redundant inertial navigation system. A new fault tolerant control method employs state estimation and state feedback techniques to compensate the sensor drift. However, the method is sensitive to measurement noise characteristics, and the performance of the method nearly depends on the feedback gain. This paper proposes an improved fault tolerant control algorithm, which employs an adaptive extended Kalman particle filter (AEKPF) to deal with unknown noise characteristics and model inaccuracies. In addition, a drift factor is introduced in the improved fault tolerant controlin order to reduce the dependence of compensation system on the feedback gain. Simulation results show that the improved fault tolerant control algorithm can effectively correct the faulty sensor even when the multiple erroneous sensors are producing faulty outputs simultaneously. Meanwhile, the AEKPF is able to solve the problem of unknown non-Gaussian noise characteristics. Moreover, the feedback gain is significantly improved by the drift factor.

A Practical Method for 10kV Overhead Line Fault Detection and Location Based on Real-Time Online Wave-Recording Devices

The fault detection and location technology for the neutral non-effectively grounded system is one of the power-system research areas over the years. This paper describes a practical method for 10kV overhead line fault detection and location by using a real-time online wave recording device. By the proposed method, the run-time health state of the distribution overhead lines can also be monitored easily.

A Redundancy Design Schema of Distributed Real-Time Database Applied in ISCS

Reliability is one of the most important properties of integrated supervisory and control system (ISCS) in metro. Redundancy technology, a fault tolerant mechanism, can significantly improve ISCS reliability. This paper introduces a redundancy design schema and its implementation in distributed real-time database, which is the kernel part of ISCS, Including upstream and downstream data redundancy processing technology, fault detection and redundancy switch technology. The result shows that this schema is feasible and reasonable.