A Novel TOPSIS-Based Test Vector Compaction Technique for Analog Fault Detection

نویسندگان

  • Badar-ud-din Ahmed
  • Youren Wang
  • Rizwan Ullah
  • Najam-ud-din Ahmed
چکیده

Technique for Order preference by Similarity to Ideal Solution (TOPSIS) is a Multi Attribute DecisionMaking (MADM) technique employed in diverse disciplines for the prioritization of alternative options/solutions to a problem. Test vector compaction for analog fault detection is a field which is witnessing continuous growth and experimentation. This study suggests a novel TOPSIS-based approach for the compaction of analog test vector to be constituted from test signals achieved by an exhaustive search method. The compacted test vector can help to reduce the test costs while at the same time enabling the test designer to base the compaction methodology on objectively obtained deterministic data.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Efficient test compaction for combinational circuits based on Fault detection count-directed clustering

Test compaction is an effective technique for reducing test data volume and test application time. In this paper, we present a new static test compaction algorithm based on test vector decomposition and clustering. Test vectors are decomposed and clustered in an increasing order of faults detection count. This clustering order gives more degree of freedom and results in better compaction. Exper...

متن کامل

Application of asymmetrical periodic signals as test vectors for analog fault detection: a novel perspective of classical concepts

Analog fault diagnosis is a field of paramount importance, and test signal generation is an important prerequisite for analog fault detection. Several stimuli have been used as input test vectors. This study presents a novel approach for the adoption of classical methods and signals for fault detection. This involves the use of asymmetrical periodic signals and comparison of their effectivity i...

متن کامل

A Novel Intelligent Fault Diagnosis Approach for Critical Rotating Machinery in the Time-frequency Domain

The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...

متن کامل

A static test compaction technique for combinational circuits based on independent fault clustering

Testing system-on-chip involves applying huge amounts of test data, which is stored in the tester memory and then transferred to the circuit under test during test application. Therefore, practical techniques, such as test compression and compaction, are required to reduce the amount of test data in order to reduce both the total testing time and the memory requirements for the tester. In this ...

متن کامل

A Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns

Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is complete...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • J. Electronic Testing

دوره 28  شماره 

صفحات  -

تاریخ انتشار 2012