A fault simulation methodology for MEMS

Rosing, R.; Richardson, A.; Dorey, A.P.

doi:10.1109/date.2000.840828

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…As described in paper [14] the quiescent current (IDDQ) testing can identify many defects that escape other test methods and is also useful in fault diagnosis, but the future of IDDQ testing is uncertain.…”

Section: Current Based Measurement Techniquesmentioning

confidence: 99%

Low cost environment for teaching and experimenting current based testing

Stroia

Moga

Dumitrean

et al. 2008

2008 IEEE International Conference on Automation, Quality and Testing, Robotics

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This paper presents a low cost environment for teaching and experimenting current based testing techniques. An original hardware platform built around and USB communication capable microcontroller together with a set of software applications were developed. This environment allows construction of IDDQ signature collections and experimenting of testing methods based on analysis of IDDQ signature. It also permits to study the setups appropriate for built-in current sensor based techniques for analog or digital circuits. Real-time data exchange with MATLAB is provided for experimenting methods of fault detection and diagnosis based on the analysis of IDDT waveform (wavelet based analysis, spectrum, etc.)

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Section: Current Based Measurement Techniquesmentioning

confidence: 99%

Low cost environment for teaching and experimenting current based testing

Stroia

Moga

Dumitrean

et al. 2008

2008 IEEE International Conference on Automation, Quality and Testing, Robotics

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“…Techniques have been developed to reuse existing test techniques to cope with the non-electrical interfaces [3] [4]. Fault models, fault simulation strategies [6] [7] and test solutions for microelectromechanical transducers [8] are currently under development, but additional research in smart sensor test engineering is required. The requirements for test will depend heavily upon the manufacturing procedures and the application.…”

Section: Introductionmentioning

confidence: 99%

Applications of mixed-signal test strategies to next-generation microsystems

2000

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Improvements in test technology for next generation microsystems is now becoming essential, especially in sensing applications as in most cases, each sensor has a unique set of characteristics causing inevitable difficulties associated with calibration and validation. Ideally, a microsystem should generate a calibrated output and a reliability indicator. IEEE1451.2 has been developed to provide a standard interface yet research into methods of providing these features through Built-In Self-Test (BIST) and On-line monitoring (OLM) techniques is still needed. One of the current industrial techniques uses multiple sensors to determine faults allowing systems to be temporarily reconfigured until the problems are resolved. This technique is only economical if multiple sensors with a strong functional correlation are present within the original system. In case only one sensor is present, using redundancies within this sensor would be more economical than adding extra sensors for test purposes.The aim of this paper is to review generic properties of sensor systems to identify areas where mixed signal testing techniques could be adapted for sensor test and to identify areas for further research.

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“…This kernel can be used in Fault Detection (FD) of MEMS [16][17][18][19][20][21]. FD in MEMS is quite difficult, since faults can originate from various sources such as the electronic and the "mechanical" sections.…”

Section: Introductionmentioning

confidence: 99%

Application of set membership identification for fault detection of MEMS

Reppa

Tzes

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.

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In this article, a set membership (SM) identification technique is tailored to detect faults in microelectromechanical systems. The SM-identifier estimates an orthotope which contains the system's parameter vector. Based on this orthotope, the system's output interval is predicted. If the actual output is outside of this interval, then a fault is detected. Utilization of this scheme can discriminate mechanicalcomponent faults from electronic component variations frequently encountered in MEMS. For testing the suggested algorithm's performance in simulation studies, an interface between classical control-software (MATLAB) and circuit emulation (HSPICE) is developed.

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A fault simulation methodology for MEMS

Cited by 6 publications

References 12 publications

Low cost environment for teaching and experimenting current based testing

Low cost environment for teaching and experimenting current based testing

Applications of mixed-signal test strategies to next-generation microsystems

Application of set membership identification for fault detection of MEMS

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