Showing papers on "Fault detection and isolation published in 1997"

Fault detection and isolation on a PWM inverter by knowledge-based model

Abstract: This paper presents an approach based on knowledge models to detect and isolate faults in a pulsewidth modulation inverter supplying a synchronous machine. These faults do not affect the system protection. A diagnosis system which uses only the input variables of the drive is presented. It is based on the analysis of the current-vector trajectory and of the instantaneous frequency in faulty mode. These two methods have been successfully applied to an experimental system.

A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners

Abstract: This paper presents a method for automated detection and diagnosis of faults in vapor compression air conditioners that only requires temperature measurements, and one humidity measurement. The differences between measured thermodynamic states and predicted states obtained from models for normal performance (residuals) are used as performance indices for both fault detection and diagnosis. For fault detection, statistical properties of the residuals for current and normal operation are used to classify the current operation as faulty or normal. A diagnosis is performed by comparing the directional change of each residual with a generic set of rules unique to each fault. This diagnostic technique does not require equipment-specific learning, is capable of detecting about a 5% loss of refrigerant, and can distinguish between refrigerant leaks, condenser fouling, evaporator fouling, liquid line restrictions, and compressor valve leakage.

Proactive network fault detection

Abstract: The increasing role of communication networks in today's society results in a demand for higher levels of network availability and reliability. At the same time, fault management is becoming more difficult due to the dynamic nature and heterogeneity of networks. We propose an intelligent monitoring system using adaptive statistical techniques. The system continually learns the normal behavior of the network and detects deviations from the norm. Within the monitoring system, the measurements are segmented, and features extracted from the segments are used to describe the normal behavior of the measurement variables. This information is combined in the structure of a Bayesian network. The proposed system is thereby able to detect unknown or unseen faults. Experimental results on real network data demonstrate that the proposed system can detect abnormal behavior before a fault actually occurs.

Model-based fault detection system for electric motors

Abstract: The present invention relates to fault detection in a large population of motors of a common motor type. Initially, a plurality of motors of a common motor type is tested to obtain a first residual based on selected measured operating parameters. A second residual is then developed for each individual motor comprising the plurality of motors. If the difference between the first and second residuals exceeds a selected threshold, the motor generating the second residual is defective and removed from the plurality of motors and the threshold is adjusted to reflect the removal of the defective motor from the plurality of motors. The first residual may be used to monitor the operation of motors not included in the original plurality of motors to detect impending failure.

Logic synthesis of multilevel circuits with concurrent error detection

Abstract: This paper presents a procedure for synthesizing multilevel circuits with concurrent error detection. All errors caused by single stuck-at faults are detected using a parity-check code. The synthesis procedure (implemented in Stanford CRCs TOPS synthesis system) fully automates the design process, and reduces the cost of concurrent error detection compared with previous methods. An algorithm for selecting a good parity-check code for encoding the circuit outputs is described. Once the code has been selected, a new procedure called structure-constrained logic optimization is used to minimize the area of the circuit as much as possible while still using a circuit structure that ensures that single stuck-at faults cannot produce undetected errors. It is proven that the resulting implementation is path fault secure, and when augmented by a checker, forms a self-checking circuit. The actual layout areas required for self-checking implementations of benchmark circuits generated with the techniques described in this paper are compared with implementations using Berger codes, single-bit parity, and duplicate-and-compare. Results indicate that the self-checking multilevel circuits generated with the procedure described here are significantly more economical.

A neural-network approach to fault detection and diagnosis in industrial processes

Abstract: Using a multilayered feedforward neural-network approach, the detection and diagnosis of faults in industrial processes that requires observing multiple data simultaneously are studied in this paper. The main feature of our approach is that the detection of the faults occurs during transient periods of operation of the process. A two-stage neural network is proposed as the basic structure of the detection system. The first stage of the network detects the dynamic trend of each measurement, and the second stage of the network detects and diagnoses the faults. The potential of this approach is demonstrated in simulation using a model of a continuously well-stirred tank reactor. The neural-network-based method successfully detects and diagnoses pretrained faults during transient periods and can also generalize properly. Finally, a comparison with a model-based method is presented.

Methodologies of Using Neural Network and Fuzzy Logic Technologies for Motor Incipient Fault Detection

Abstract: From the Publisher: This book will introduce the necessary concepts of neural network and fuzzy logic, describe the advantages and challenges of using these technologies to solve motor fault detection problems, and discuss several design considerations and methodologies in applying these techniques to motor incipient fault detection.

Automatic fault detection, isolation, and recovery in transparent all-optical networks

Abstract: Network fault identification is an important network management function, which is closely related to fault management and has an impact on other network management functions such as configuration management, and performance management. This paper investigates fault surveillance and fault identification mechanisms for a transparent optical network in which data travels optically from the source node to the destination node without going through any optical-to-electrical (O/E) or electrical-to-optical (E/O) conversion. Mechanisms and algorithms are proposed to detect and isolate faults such as fiber cuts, laser, receiver, or router failures. These mechanisms allow nonintrusive device monitoring without requiring any prior knowledge of the actual protocols being used in the data transmission.

Operation of fault tolerant machines with winding failures

Abstract: This paper examines winding faults in a demonstrator drive, based on a specification for an aircraft fuel pump. This drive has been designed with a degree of inherent fault tolerance and is capable of continued operation in the presence of a variety of faults. Some of the most severe faults arise from winding insulation failure within a phase of the machine. A method of detecting turn to turn short circuits which can result from winding insulation breakdown is presented, along with a strategy for continued post fault operation of the drive. The detection method operates in real time, requires no additional sensors and is sufficiently sensitive to detect even a single shorted turn.

Fault isolation filter design for linear time-invariant systems

Abstract: This paper is concerned with the problem of detecting and isolating multiple faults by a full-order observer of the plant state. We first obtain the fault isolability condition from the dual concept, namely static-state feedback decoupling. A new full-state observer design method is then developed to isolate simultaneous multiple faults. The method can isolate m simultaneous faults with m output measurements (such that the isolability condition is satisfied) under zero initial error of state estimation. Asymptotic fault isolation results can also be obtained using the same observer design if the number of invariant eigenvalues is (n-m), and if they are stable, where n represents the system order, m is the number of faults in the system. In both cases m can be up to the system order n.

Adaptive recovery for mobile environments

Abstract: Mobile computing allows ubiquitous and continuous access to computing resources while the users travel or work at a client’s site. The flexibility introduced by mobile computing brings new challenges to the area of fault tolerance. Failures that were rare with fixed hosts become common, and host disconnection makes fault detection and message coordination difficult. This paper describes a new checkpoint protocol that is well adapted to mobile environments. The protocol uses time to indirectly coordinate the creation of new global states, avoiding all message exchanges. The protocol uses two different types of checkpoints to adapt to the current network characteristics, and to trade off performance with recovery time.

Unreliable intrusion detection in distributed computations

Abstract: Distributed coordination is difficult, especially when the system may suffer intrusions that corrupt some component processes. We introduce the abstraction of a failure detector that a process can use to (imperfectly) detect the corruption (Byzantine failure) of another process. In general, our failure detectors can be unreliable, both by reporting a correct process to be faulty or by reporting a faulty process to be correct. However, we show that if these detectors satisfy certain plausible properties, then the well known distributed consensus problem can be solved. We also present a randomized protocol using failure detectors that solves the consensus problem if either the requisite properties of failure detectors hold or if certain highly probable events eventually occur. This work can be viewed as a generalization of benign failure detectors popular in the distributed computing literature.

Test set size minimization and fault detection effectiveness: a case study in a space application

Abstract: An important question in software testing is whether it is reasonable to apply coverage based criteria as a filter to reduce the size of a test set. An empirical study was conducted using a test set minimization technique to explore the effect of reducing the size of a test set, while keeping block coverage constant, on the fault detection strength of the resulting minimized test set. Two types of test sets were examined. For those with respect to a fixed size, no test case screening was conducted during the generation, whereas for those with respect to a fixed coverage, each subsequent test case had to improve the overall coverage in order to be included. The study reveals that no matter how a test set is generated (with or without any test case screening) block minimized test sets have a size/effectiveness advantage, in terms of a significant reduction in test set size but with almost the same fault detection effectiveness, over the original non-minimized test sets.

Operation of a fault tolerant PM drive for an aerospace fuel pump application

Abstract: In many applications the failure of a drive has a serious impact on the operation of a system. In some cases the failure results in lost production, whilst in others it may jeopardize human safety. In such applications it is advantageous to use a drive capable of continuing to operate in the presence of any single point failure. Such a drive is termed fault tolerant and the development of a fault tolerant drive is the aim of the research presented. Previous work by B.C. Mecrow et al. (see Seventh International Conference on Electric Machines and Drives, Durham, UK, IEE, p.443-7, 1995) has introduced the concept of a fault tolerant permanent magnet (PM) machine drive for safety critical applications. This drive was based on a novel design of PM machine with a high per unit reactance to limit fault currents. It is shown by A.G. Jack et al. (see IEEE Trans. Ind. Appls., vol.32, no.4, p.889-95, 1996) that the torque and power densities of this PM drive exceed those possible with an SRM drive. This previous work was undertaken on a small prototype machine without a power electronic converter. A new drive has now been built and extensively tested. It uses a similar topology to the prototype machine and is designed to an aircraft fuel pump specification, requiring 16 kW at 13000 rpm. This paper reports the key design attributes and provides detailed measured parameters. The machine is controlled by a power electronic converter using a separate "H bridge" to drive each phase. The controller, implemented via a DSP, uses the measured machine flux linkage to provide robust current control with high dynamic performance.

Vector restoration based static compaction of test sequences for synchronous sequential circuits

Abstract: The authors propose a new procedure for static compaction that belongs to the class of procedures that omit test vectors from a given test sequence in order to reduce its size without reducing the fault coverage. The previous procedures that achieved high levels of compaction using this technique attempted to omit test vectors from a given test sequence one at a time or in consecutive subsequences. Consequently, the omission of each vector or subsequence required extensive simulation to determine the effects of each vector omission on the fault coverage. The proposed procedure first omits (almost) all the test vectors from the sequence, and then restores some of them as necessary to achieve the required fault coverage. The decision to restore a vector requires simulation of a single fault. Thus, the overall computational effort of this procedure is significantly lower. The loss of compaction compared to the scheme that omits the vectors one at a time or in subsequences is small in most cases. Experimental results are presented to support these claims.

Application of a model-based fault detection system to nuclear plant signals

Abstract: To assure the continued safe and reliable operation of a nuclear power station, it is essential that accurate online information on the current state of the entire system be available to the operators. Such information is needed to determine the operability of safety and control systems, the condition of active components, the necessity of preventative maintenance, and the status of sensory systems. To this end, ANL has developed a new Multivariate State Estimation Technique (MSET) which utilizes advanced pattern recognition methods to enhance sensor and component operational validation for commercial nuclear reactors. Operational data from the Crystal River-3 (CR-3) nuclear power plant are used to illustrate the high sensitivity, accuracy, and the rapid response time of MSET for annunciation of a variety of signal disturbances.

A self-validating thermocouple

Abstract: Traditionally the sensor has been the system component neglected by control engineers, yet it has long been recognized that accurate and reliable sensor readings are vital for good controller performance. Self-validating sensors can improve reliability through self-diagnosis and by the provision of on-line metrics (measurement accuracy and its trustworthiness). One benefit of validation is the potential to sustain satisfactory loop performance even in the presence of sensor faults. This paper describes a self-validating thermocouple that can discover several types of internal fault, including the practically important aspect of loss-of-contact with the process environment, and shows how the associated uncertainties can be calculated. The operation of the device is demonstrated through a series of experiments.