Fault coverage

About: Fault coverage is a research topic. Over the lifetime, 10153 publications have been published within this topic receiving 161933 citations. The topic is also known as: test coverage.

Fault model-driven test derivation from finite state models: annotated bibliography

Abstract: The annotated bibliography highlights work in the area of algorithmic test generation from formal specifications with guaranteed fault coverage, i.e., fault model-driven test derivation. A fault model is understood as a triple, comprising a finite state specification, conformance relation and fault domain that is the set of possible implementations. The fault model can be specialized to Input/Output FSM, Labeled Transition System, or Input/Output Automaton and to a number of conformance relations such as FSM equivalence, reduction or quasi-equivalence, trace inclusion or trace equivalence and others. The fault domain usually reflects test assumptions, as an example, it can be the universe of all possible I/O FSMs with a given number of states, a classical fault domain in FSM-based testing. A test suite is complete with respect to a given fault model when each implementation from the fault domain passes it if and only if the postulated conformance relation holds between the implementation and its specification. A complete test suite is said to provide fault coverage guarantee for a given fault model.

Circular BIST with partial scan

Abstract: A BIST (built-in self test) methodology that uses the circular BIST technique to perform a random test of sequential logic circuits is presented. The fault coverage obtained using this technique is supplemented by deterministic tests that are presented to the CUT (circuit under test) by configuring the circular path as a partial scan chain. A CAD (computer-aided-design) tool for automating this methodology is described, a variety of heuristics for picking which flip-flops should be included in the circular path are evaluated, and experimental results are presented. >

Fault-Tolerant Control for an Internet-Based Three-Tank System: Accommodation to Sensor Bias Faults

Abstract: This paper focuses on the fault-tolerant control problem for an Internet-based three-tank system in the presence of possible sensor bias faults. The Internet-based three-tank system is an experimental setup that can be regarded as a typical networked system for evaluating networked fault-diagnosis and fault-tolerant control methods. Packet dropout phenomenon in the sensor-to-controller link is considered in this paper, and the fault type we deal with is chosen as the sensor bias fault. Fault-diagnosis unit is designed toward an auxiliary system. Sensor bias faults can be detected by comparing the residual signal generated by the fault detection filter and a prescribed threshold. After that, the fault can be isolated by using the residual analysis approach. Once the fault is isolated, it can be estimated iteratively in the least-squares sense. A fault accommodation method is proposed, and a fault-tolerant control strategy is achieved based on the fault information provided by the fault-diagnosis unit. The approach brought forward in this paper is demonstrated via an experimental study on the practical Internet-based three-tank system. Results show the effectiveness and the applicability of the proposed techniques.

A Fault Diagnosis Method for Industrial Gas Turbines Using Bayesian Data Analysis

Abstract: This paper presents an offline fault diagnosis method for industrial gas turbines in a steady-state. Fault diagnosis plays an important role in the efforts for gas turbine owners to shift from preventive maintenance to predictive maintenance, and consequently to reduce the maintenance cost. Ever since its birth, numerous techniques have been researched in this field, yet none of them is completely better than the others and perfectly solves the problem. Fault diagnosis is a challenging problem because there are numerous fault situations that can possibly happen to a gas turbine, and multiple faults may occur in multiple components of the gas turbine simultaneously. An algorithm tailored to one fault situation may not perform well in other fault situations. A general algorithm that performs well in overall fault situations tends to compromise its accuracy in the individual fault situation. In addition to the issue of generality versus accuracy, another challenging aspect of fault diagnosis is that, data used in diagnosis contain errors. The data is comprised of measurements obtained from gas turbines. Measurements contain random errors and often systematic errors like sensor biases as well. In this paper, to maintain the generality and the accuracy together, multiple Bayesian models tailored to various fault situations are implemented in one hierarchical model. The fault situations include single faults occurring in a component, and multiple faults occurring in more than one component. In addition to faults occurring in the components of a gas turbine, sensor biases are explicitly included in the multiple models so that the magnitude of a bias, if any, can be estimated as well. Results from these multiple Bayesian models are averaged according to how much each model is supported by data. Gibbs sampling is used for the calculation of the Bayesian models. The presented method is applied to fault diagnosis of a gas turbine that is equipped with a faulty compressor and a biased fuel flow sensor. The presented method successfully diagnoses the magnitudes of the compressor fault and the fuel flow sensor bias with limited amount of data. It is also shown that averaging multiple models gives rise to more accurate and less uncertain results than using a single general model. By averaging multiple models, based on various fault situations, fault diagnosis can be general yet accurate. DOI: 10.1115/1.3204508

Generation of low power dissipation and high fault coverage patterns for scan-based BIST

Abstract: This paper presents a low hardware overhead test pattern generator (TPG) for scan-based BIST that can reduce switching activity in CUTs during BIST and also achieve very high fault coverage with a reasonable length of test sequence. Since the correlation between consecutive vectors applied to a circuit during BIST is significantly lower, switching activity in the circuit can be significantly higher during BIST than that during its normal operation. Excessive switching activity during test application can damage CUTs during BIST. The proposed BIST decreases the number of transitions that occur at scan inputs during scan shift operations and hence decreases switching activity during BIST. The proposed BIST is comprised of two TPGs: LT-RTPG and 3-weight WRBIST TPG, both of which are proposed in previous publications. This paper shows that the 3-weight WRBIST TPG, which is used to detect random pattern resistant faults, can also be used to reduce switching activity in CUTs during BIST. Experimental results also show that the proposed BIST can be implemented with very low area overhead.