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Soft Computing Techniques Used In Engineering Fields

846 words - 4 pages

Soft computing techniques are set of nature-inspired computational methodologies which consider the computational utility of architectures and algorithms inspired by nature and their applications for solving mathematical problems. These are basically stochastic search techniques and are computationally efficient as they possess the ability of implementing distributed computing. Unlike traditional hard computing techniques, these set of techniques have the ability to deal with partial and noisy sets of data, tolerance to initial impression and providing a robust solution with the requirement of minimal computing resources. Over last few decades soft computing methods have successfully been applied to solve many complex problems related to engineering fields. Dote and Ovaska [1] provided a comprehensive review on application of soft computing methodologies for solving complex industrial problems including its application to the aerospace industry, communications systems, consumer appliances, electric power systems, manufacturing automation and robotics, power electronics and motion control, process engineering, and transportation planning. Gao and Ovaska [2] made a review on applications of soft computing in motor fault diagnosis, Hajela [3] in multidisciplinary aerospace design, Flintsch and Chen [4] in infrastructure management, Nikravesh [5] in reservoir characterization, Avineri [6] in traffic and transport management systems, Oduguwa et al. [7] in manufacturing industry, Saridakis and Dentsoras [8] in engineering design which addresses issues such as, the design knowledge representation (modeling), the search for optimal solutions and the retrieval of pre-existing design knowledge and the learning of new knowledge, Chandrasekaran et al. [9] in machining performance prediction and optimization respectively. In past two decades there has been much interest for applying soft computing methodology in structural damage assessment problems leading to some successful implementations. The present work is conducted to provide a brief review of all such studies and to provide a better understanding of how to apply soft computing in such problems.
A structure may be damaged by a number of means including long term degradation of the structures as well as extreme events like natural disasters, fire, accidental or intentional overloading, collision or terrorism activities. In order to maintain the safety and reliability of the structure it is necessary to inspect the condition regularly for any defect. Traditionally; methods such as visual inspection, eddy current methods, acoustics or ultrasonic waves, thermal field and magnetic field methods are used for damage detection purposes [10, 11]. All these methods are restricted to local examinations in limited areas in the vicinity of the damage. However, prior information regarding damage identification in aerospace, civil and mechanical structures...

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