Abstract
In this paper, a detailed offline multiple fault diagnosis has been presented in conjunction with a detection technique for cross-referencing digital microfluidic biochips. Because of the fundamental mixed expertise, biochips demonstrate distinctive mechanisms of failure and defects. Therefore, for certifying the dependability of a system, both online and offline test procedures are needed. Due to the technological advancements, designs of the DMFBs are getting upgraded day by day. Thus, cross-referencing type of architecture where pin count has been reduced drastically is also receiving attention. Hence, finding multiple faulty electrodes in this type of architecture has become a great challenge. Here, the proposed algorithm can detect multiple faults anywhere within a cross-referencing chip that satisfies the electrode interference challenge as well as dynamic fluidic constraints. The result analysis shows a significant improvement in the fault diagnosis time.
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Chowdhury, S., Kabir, K.A., Dhal, D., Pal, R.K., Saha, G. (2021). Multiple Fault Identification and Diagnosis in Cross-Referencing Digital Microfluidic Biochips. In: Chaki, R., Chaki, N., Cortesi, A., Saeed, K. (eds) Advanced Computing and Systems for Security: Volume 14. Lecture Notes in Networks and Systems, vol 242. Springer, Singapore. https://doi.org/10.1007/978-981-16-4294-4_11
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DOI: https://doi.org/10.1007/978-981-16-4294-4_11
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