An On-line BIST RAM Architecture with Self Repair Capabilities

The emerging field of self-repair computing is expected to have a major impact on deployable systems for space missions and defense applications, where high reliability, availability, and serviceability are needed. In this context, RAM (random access memories) are among the most critical components. This paper proposes a built-in self-repair (BISR) approach for RAM cores. The proposed design, introducing minimal and technology-dependent overheads, can detect and repair a wide range of memory faults including: stuck-at, coupling, and address faults. The test and repair capabilities are used on-line, and are completely transparent to the external user, who can use the memory without any change in the memory-access protocol. Using a fault-injection environment that can emulate the occurrence of faults inside the module, the effectiveness of the proposed architecture in terms of both fault detection and repairing capability was verified. Memories of various sizes have been considered to evaluate the area-overhead introduced by this proposed architectur

Graph-based real-time fault diagnostics

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components

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

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

ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems

ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems

Dependable reconfigurable multi-sensor poles for security

Wireless sensor network poles for security monitoring under harsh environments require a very high dependability as they are safety-critical [1]. An example of a multi-sensor pole is shown. Crucial attribute in these systems for security, especially in harsh environment, is a high robustness and guaranteed availability during lifetime. This environment could include molest. In this paper, two approaches are used which are applied simultaneously but are developed in different projects. \u

A Hierachical Infrastrucutre for SOC Test Management

HD2BIST - a complete hierarchical framework for BIST scheduling, data-patterns delivery, and diagnosis of complex systems - maximizes and simplifies the reuse of built-in test architectures. HD2BIST optimizes the flexibility for chip designers in planning an overall SoC test strategy by defining a test access method that provides direct virtual access to each core of the system

Robot graphic simulation testbed

The objective of this research was twofold. First, the basic capabilities of ROBOSIM (graphical simulation system) were improved and extended by taking advantage of advanced graphic workstation technology and artificial intelligence programming techniques. Second, the scope of the graphic simulation testbed was extended to include general problems of Space Station automation. Hardware support for 3-D graphics and high processing performance make high resolution solid modeling, collision detection, and simulation of structural dynamics computationally feasible. The Space Station is a complex system with many interacting subsystems. Design and testing of automation concepts demand modeling of the affected processes, their interactions, and that of the proposed control systems. The automation testbed was designed to facilitate studies in Space Station automation concepts

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

A two-level structure for advanced space power system automation

The tasks to be carried out during the three-year project period are: (1) performing extensive simulation using existing mathematical models to build a specific knowledge base of the operating characteristics of space power systems; (2) carrying out the necessary basic research on hierarchical control structures, real-time quantitative algorithms, and decision-theoretic procedures; (3) developing a two-level automation scheme for fault detection and diagnosis, maintenance and restoration scheduling, and load management; and (4) testing and demonstration. The outlines of the proposed system structure that served as a master plan for this project, work accomplished, concluding remarks, and ideas for future work are also addressed