A Parallel Approach to Fault Simulation on the Connection Machine
نویسنده
چکیده
A fast algorithm for the fault simulation using data level parallelism is implemented on the Connection Machine. The algorithm employed is the PPSFP (Paralle l Pattern Single Fault Propagation) type. The input of the algorithm is the PI (Primary Input) test patterns obtained from a cellular automata pseudo-random pattern generator. The output of this system is a fault simulation table that describes the necessary test input patterns to detect both sa0 (stuck-at-0) and sa1 (stuck-at-1) faults of the particular link in a given circuit. The output also includes fault-free, sa0, and sa1 output pattern, fault coverage and fault simulation time. The algorithm has been implemented using a combination of C* and PARIS environment. Indexing terms: fault simulation, parallel processing
منابع مشابه
Fault diagnosis in a distillation column using a support vector machine based classifier
Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...
متن کاملA Fault Diagnosis Method for Automaton based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition
In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...
متن کاملA Fault Diagnosis Method for Automaton Based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition
In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...
متن کاملForward kinematic analysis of planar parallel robots using a neural network-based approach optimized by machine learning
The forward kinematic problem of parallel robots is always considered as a challenge in the field of parallel robots due to the obtained nonlinear system of equations. In this paper, the forward kinematic problem of planar parallel robots in their workspace is investigated using a neural network based approach. In order to increase the accuracy of this method, the workspace of the parallel robo...
متن کاملApplication of Thau Observer for Fault Detection of Micro Parallel Plate Capacitor Subjected to Nonlinear Electrostatic Force
This paper investigates the fault detection of a micro parallel plate capacitor subjected to nonlinear electrostatic force. For this end Thau observer, which has good ability in fault detection of nonlinear system has been presented and governing nonlinear dynamic equation of the capacitor has been presented. Upper and lower threshold for fault detection have been obtained. The robustness of th...
متن کامل