4,674 research outputs found

    Testing of Level Shifters in Multiple Voltage Designs

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    The use of multiple voltages for different cores is becoming a widely accepted technique for efficient power management. Level shifters are used as interfaces between voltage domains. Through extensive transistor level simulations of resistive open, bridging and resistive short faults, we have classified the testing of level shifters into PASSIVE and ACTIVE modes. We examine if high test coverage can be achieved in the PASSIVE mode. We consider resistive opens and shorts and show that, for testing purposes, consideration of purely digital fault effects is sufficient. Thus conventional digital DfT can be employed to test level shifters. In all cases, we conclude that using sets of single supply voltages for testing is sufficient

    A design for testability study on a high performance automatic gain control circuit.

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    A comprehensive testability study on a commercial automatic gain control circuit is presented which aims to identify design for testability (DfT) modifications to both reduce production test cost and improve test quality. A fault simulation strategy based on layout extracted faults has been used to support the study. The paper proposes a number of DfT modifications at the layout, schematic and system levels together with testability. Guidelines that may well have generic applicability. Proposals for using the modifications to achieve partial self test are made and estimates of achieved fault coverage and quality levels presente

    A low-speed BIST framework for high-performance circuit testing

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    Testing of high performance integrated circuits is becoming increasingly a challenging task owing to high clock frequencies. Often testers are not able to test such devices due to their limited high frequency capabilities. In this article we outline a design-for-test methodology such that high performance devices can be tested on relatively low performance testers. In addition, a BIST framework is discussed based on this methodology. Various implementation aspects of this technique are also addresse

    Testing microelectronic biofluidic systems

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    According to the 2005 International Technology Roadmap for Semiconductors, the integration of emerging nondigital CMOS technologies will require radically different test methods, posing a major challenge for designers and test engineers. One such technology is microelectronic fluidic (MEF) arrays, which have rapidly gained importance in many biological, pharmaceutical, and industrial applications. The advantages of these systems, such as operation speed, use of very small amounts of liquid, on-board droplet detection, signal conditioning, and vast digital signal processing, make them very promising. However, testable design of these devices in a mass-production environment is still in its infancy, hampering their low-cost introduction to the market. This article describes analog and digital MEF design and testing method

    Reliable Low-Latency and Low-Complexity Viterbi Architectures Benchmarked on ASIC and FPGA

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    The Viterbi algorithm is commonly applied in a number of sensitive usage models including decoding convolutional codes used in communications such as satellite communication, cellular relay, and wireless local area networks. Moreover, the algorithm has been applied to automatic speech recognition and storage devices. In this thesis, efficient error detection schemes for architectures based on low-latency, low-complexity Viterbi decoders are presented. The merit of the proposed schemes is that reliability requirements, overhead tolerance, and performance degradation limits are embedded in the structures and can be adapted accordingly. We also present three variants of recomputing with encoded operands and its modifications to detect both transient and permanent faults, coupled with signature-based schemes. The instrumented decoder architecture has been subjected to extensive error detection assessments through simulations, and application-specific integrated circuit (ASIC) [32nm library] and field-programmable gate array (FPGA) [Xilinx Virtex-6 family] implementations for benchmark. The proposed fine-grained approaches can be utilized based on reliability objectives and performance/implementation metrics degradation tolerance

    Construction of an Expert System Based on Fuzzy Logic for Diagnosis of Analog Electronic Circuits

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    The paper presents construction of the fuzzy logic system to analog circuits soft fault diagnosis. The classical dictionary construction is replaced by fuzzy rule system. The first part refers to analog fault diagnosis, its techniques, approaches and goals. It clarifies common strategy and define differences between detecting, locating and identifying a fault in analog electronic circuit. The second part is focused on a creation of fuzzy rule expert system with use of sensitivity functions and known circuit topology. To detect, locate and identify a faulty element in a circuit the sensitivity matrix is used. The advantage of the method is its utilization in all, AC, DC and time domain. The fuzzy system, like the classical fault dictionary, can detect and locate single catastrophic faults and, on the contrary to the classical one, it also detects and locates parametric faults. Moreover, it allows identification of these faults, such that sign of the faulty parameter deviation is designated. The method has deterministic character as well as  it can be applied on the verification and production stage

    Machine learning and its applications in reliability analysis systems

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    In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA
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