Efficient Pattern Generation and Observation Point Insertion for Transition Fault Diagnosis

  • 王 奕達

Student thesis: Master's Thesis

Abstract

Two major techniques are proposed to increase diagnosisability of circuits: 1 Diagnostic pattern generation (DPG) generates high quality diagnostic patterns to distinguish transition fault pairs and identifies equivalent fault pairs 2 Observation point insertion inserts observation points into circuit to distinguish the fault pairs The first technique mainly consists of two methods: 1 Fault Inactivation Method (FIM) generates diagnostic patterns to distinguish fault pairs by inactivating one fault and detecting the other 2 Fault Propagation Method (FPM) generates diagnostic patterns to distinguish fault pairs by initializing both faults at the same time and creating different faulty responses of two faults on outputs Experimental results show that the diagnosis resolutions in ISCAS89 (ITC99) benchmarks can reach 99 999999% (99 999995%) But few fault pairs cannot be distinguished or identified as equivalent fault pairs We use the second technique to insert observation points to distinguish these fault pairs Experimental results show that only 2 (109) observation points are needed for ISCAS89 (ITC99) benchmarks and hence the diagnosis resolutions for all circuits are 100% with area overhead less than 1% In addition for the indistinguished fault pairs with large distance between two faults in a pair we also adopt our second technique Experimental results show that most of fault pairs can be distinguished by inserting few observation points
Date of Award2014 Aug 8
Original languageEnglish
SupervisorKuen-Jong Lee (Supervisor)

Cite this

Efficient Pattern Generation and Observation Point Insertion for Transition Fault Diagnosis
奕達, 王. (Author). 2014 Aug 8

Student thesis: Master's Thesis