Nagabhushan Mahadevan

A Robust Method for Hybrid Diagnosis of Complex Systems

Abstract The AI model-based diagnosis community has developed qualitative reasoning mechanisms for fault isolation in dynamic systems. Their emphasis has been on the fault isolation algorithms, and little attention has been paid to robust online detection and symbol generation that are essential components of a complete diagnostic solution. This paper discusses a robust diagnosis methodology for hybrid systems that combines fault detection with a combined qualitative and quantitative fault isolation scheme. We focus on fault detection, symbol generation, and parameter estimation, and illustrate the effectiveness of this method by running experiments on the fuel transfer system of aircraft

Practical Implementation of Diagnosis Systems Using Timed Failure Propagation Graph Models

Timed failure propagation graphs (TFPGs) are causal models that capture the temporal aspects of failure propagation in typical engineering systems. In this paper, we present several practical modeling and reasoning considerations that have been addressed based on experience with complex real-time vehicle subsystems. These include handling intermittent faults, reasoning over dynamically commanded test sequences, dealing with the constraints of limited computational resources, and providing automated model verification. We finally present a vehicle subsystem case study.

A component model for hard real-time systems: CCM with ARINC-653

The size and complexity of software in safety‐critical systems is increasing at a rapid pace. One technology that can be used to mitigate this complexity is component‐based software development. However, in spite of the apparent benefits of a component‐based approach to development, little work has been done in applying these concepts to hard real‐time systems. This paper improves the state of the art by making three contributions: (1) we present a component model for hard real‐time systems and define the semantics of different types of component interactions; (2) we present an implementation of a middleware that supports this component model. This middleware combines an open‐source CORBA Component Model (CCM) implementation (MICO) with ARINC‐653: a state‐of‐the‐art real‐time operating systems (RTOS) standard, (3) finally; we describe a modeling environment that enables design, analysis, and deployment of component assemblies. We conclude with a discussion of the lessons learned during this exercise. Our experiences point toward extending both the CCM as well as revising the ARINC‐653. Copyright

Component-oriented modeling of hybrid dynamic systems using the generic modeling environment

This paper presents a component oriented modeling environment for building hybrid dynamic models of physical system. The modeling environment is created using the generic modeling environment (GME), a meta programmable visual modeling application developed at the Institute for Software Integrated Systems (ISIS). The core of the modeling language itself is a hybrid extension of the bond graph modeling language. The advantages of an object-oriented approach to physical system modeling combined with the advanced features of GME for managing model complexity are illustrated by building a library of hydraulic system components. A simulation model can be automatically generated from the physical system model using a model translator. As an example application we use the component library to build the model of a coupled multi-tank system with controlled and autonomous hybrid behaviors, and illustrate this with a simulation example

Model-based software health management for real-time systems

Complexity of software systems has reached the point where we need run-time mechanisms that can be used to provide fault management services. Testing and verification may not cover all possible scenarios that a system will encounter, hence a simpler, yet formally specified run-time monitoring, diagnosis, and fault mitigation architecture is needed to increase the software systems dependability. The approach described in this paper borrows concepts and principles from the field of “Systems Health Management” for complex systems and implements a two level health management strategy that can be applied through a model-based software development process. The Component-level Health Manager (CLHM) for software components provides a localized and limited functionality for managing the health of a component locally. It also reports to the higher-level System Health Manager (SHM) which manages the health of the overall system. SHM consists of a diagnosis engine that uses the timed fault propagation (TFPG) model based on the component assembly. It reasons about the anomalies reported by CLHM and hypothesizes about the possible fault sources. Thereafter, necessary system level mitigation action can be taken. System-level mitigation approaches are subject of on-going investigations and have not been included in this paper. We conclude the paper with case study and discussion.

A Real-Time Component Framework: Experience with CCM and ARINC-653

The complexity of software in systems like aerospace vehicles has reached the point where new techniques are needed to ensure system dependability while improving the productivity of developers. One possible approach is to use precisely defined software execution platforms that (1) enable the system to be composed from separate components, (2) restrict component interactions and prevent fault propagation, and (3) whose compositional properties are well-known. In this paper we describe the initial steps towards building a platform that combines component-based software construction with hard real-time operating system services. Specifically, the paper discusses how the CORBA Component Model (CCM) could be combined with the ARINC-653 platform services and the lessons learned from this experiment. The results point towards both extending the CCM as well as revising the ARINC-653.

A model-based approach to designing QoS adaptive applications

In this paper we present a model-based approach for designing quality of service adaptive applications. We have developed a prototype distributed QoS modeling environment (DQME) that captures important elements of dynamic QoS adaptation at the model level. This modeling environment is designed independent of and can be integrated with, specific application domains to capture their QoS features and adaptation strategies. It combines the domain-specific modeling capability of the generic modeling environment with the QoS adaptation mechanisms of the quality objects middleware framework. DQME captures both the QoS and the functional concerns of distributed real-time embedded systems, and provides clear separation of these two. Integrated code-synthesis tools facilitate code generation and model refinement. We present a signal analyzer case study to demonstrate the use of the DQME modeling tool in real world applications.

Distributed diagnosis of complex systems using timed failure propagation graph models

Timed failure propagation graph (TFPG) is a directed graph model that represents temporal progression of failure effects in physical systems. In this paper, a distributed diagnosis approach for complex systems is introduced based on the TFPG model settings. In this approach, the system is partitioned into a set of local subsystems each represented by a subgraph of the global system TFPG model. Information flow between subsystems is achieved through special input and output nodes. A high level diagnoser integrates the diagnosis results of the local subsystems using an abstract high level model to obtain a globally consistent diagnosis of the system.

Model-based fault-adaptive control of complex dynamic systems

Complex control applications require capabilities for accommodating faults in the controlled plant. Fault accommoda- tion involves the detection and isolation of faults, and then taking appropriate control actions to mitigate the fault effects and main- tain control. This requires the integration of fault diagnostics with control in a feedback loop. This paper discusses a generic frame- work for building fault-adaptive control systems using a model- based approach, with special emphasis on the modeling schemes that describe different aspects of the system at different levels of abstraction and granularity. The concepts are illustrated by a fault adaptive notional fuel system control example.

Range-Finding Sensor Degradation in Gamma Radiation Environments

The effects of gamma radiation on common sensors used in robots intended for nuclear remediation scenarios are examined. Commercial rangefinders are chosen as an exemplar of the impact of gamma radiation on sensors and systems. This paper illustrates sensor radiation degradation not only in operational failure, but also in changes in the sensor transfer function. Three types of commercial range-finding sensors are considered [infrared (IR) triangulation using a position sensitive detector, sonar using time of flight, and laser rangefinder using triangulation and a CMOS camera]. Experimental results show significant changes in the IR sensors static sensitivity with dose, abrupt failure of the laser range finder at low dose, and degradation and abrupt failure for the sonar detector. The input-output relationship of the IR sensor showed further variation after a period of room-temperature annealing. Significant part-to-part variation in radiation response is shown for both the sonar and IR sensor. System level impacts due to sensor input-output relationship degradation and a technique to diagnose the degradation extendable to more complex sensor assemblies are presented.