Runtime Diagnosis Research Articles

Решение обратной задачи теплопередачи в конденсаторе турбоустановки со встроенным теплофикационным пучком

For power plants reduction of heat losses is one of the main ways to save energy. Energy saving issue is one of the priority areas of the development of science, engineering, and technology in the Russian Federation. Efficiency upgrading of the equipment operation are associated with the condensers of turbine units, since more than 50 percent of the fuel energy is released into the environment with cooling water. The operating efficiency of a condenser with built-in heating beams significantly affects the vacuum in the condenser and, thus, the operating efficiency of the entire unit. Diagnostics of the condition and improvement of operating modes of the condenser of a turbine unit with a built-in heating unit is an urgent scientific and practical issue. To develop a model of a condenser with a built-in heating beam, the methodology of matrix formalization of the description of heat and mass transfer processes has been used. To solve the problem of diagnosing the condition of equipment, methods of least squares and mathematical programming have been used. Within the framework of the matrix formalization methodology, the authors have developed an approach to solve inverse problems of diagnosing and designing multi-flow heat exchange equipment considering the phase transition in coolants. The authors have obtained and analyzed solutions of the inverse problem from the point of view of diagnosing the state of heat exchange equipment using the example of a turbine unit condenser with a built-in heating beam. Analysis of the calculated results has shown an adequate description by the model of the standard data for the analyzed condenser. Analysis results have shown the possibility to use the model for runtime diagnosis of the condition of power equipment and the efficient use of energy resources due to preventing ineffective modes. The proposed approach allows us to formulate and solve inverse problems of diagnosing the state of equipment of condensing units for various purposes.

A Comprehensive Approach to On-board Autonomy Verification and Validation

Deep space missions are characterized by severely constrained communication links. To meet the needs of future missions and increase their scientific return, future space systems will require an increased level of autonomy on-board. In this work, we propose a comprehensive approach to on-board autonomy. We rely on model-based reasoning, and we consider many important (on-line and off-line) reasoning capabilities such as plan generation, validation, execution and monitoring, runtime diagnosis, and fault detection, identification, and recovery. The controlled platform is represented symbolically, and the reasoning capabilities are seen as symbolic manipulation of such formal model. We have developed a prototype of our framework, and we have integrated it within an on-board Autonomous Reasoning Engine. Finally, we have evaluated our approach on three case-studies inspired by real-world projects and characterized it in terms of reliability, availability, and performance.

Timed analysis and model mapping to enhance run-time diagnosis in industrial automation systems

The paper presents an evolution of a new diagnostic approach, based on the TiDiaM (Timed Diagnostic Model), which can be applied in the discrete production systems area. The aim of this innovative diagnostic model and algorithm is a fast isolation and a successive identification of faults that can occur in a generic automatic device only observing measures and commands exchanged between plant and controller, modeled as observable events. In this paper a number of improvements, which allow TiDiaM application in real cases, will be discussed. The main presented progresses are the explicit modeling of time-out, the well defined separation between the nominal behavior, given by the control engineer, and the failure behavior, automatically inserted in the control model and the timed analysis on the fault estimates which starts after the expiration of a timeout. A set of software tools has been developed in order to support the dissemination and the application of the new diagnostic methodology in real industrial scenario.

Implementation and Experiment Verification of a Metro Power Traction Simulator System

A metro power traction simulator system is designed and implemented. Designation method of the flywheels which simulate the metro vehicle moment inertia is given. A train runtime diagnosis system is completed by adopting MVB protocol. The dynamic simulation of metro power traction system is realized under the control of train runtime diagnosis system. The feasibility and utility are proved by the experiment results.

Performance study of combined test rig for metro train traction

This paper deals with a combined test rig for a traction system in the laboratory environment. An experimental system was designed and implemented to verify the performance of the traction system for a metro train. For a highly accurate control of the system, a hybrid control algorithm combining vector control and slip frequency control was applied to control the traction inverter. The design method of the flywheels, which represent the equivalent model of the train moment inertia, was elaborated. A train runtime diagnosis system was completed by adopting the multi-function vehicle bus (MVB) protocol. The dynamic performance of the metro power traction system was emulated under the control of the train runtime diagnosis system. Using the combined test rig, the performances of the traction system in traction, braking, temperature rise, etc., were verified through traction and breaking experiments.

Building Accountability Middleware to Support Dependable SOA

The Intelligent Accountability Middleware Architecture (Llama) project supports dependable service-oriented architecture (SOA) monitoring, runtime diagnosis, and reconfiguration. At its core, Llama implements an accountability service bus that users can install on existing service-deployment infrastructures. It collects and monitors service execution data from a key subset of services; enables Llama users to incorporate others' advanced diagnosis models and algorithms into the framework; and provides enterprise service bus extensions for collecting service profiling data, thus making process problems transparent to diagnose. Finally, experimental results indicate that using Llama contributes a modest amount of system overhead.

Simulation self-diagnoses

After an initial simulation model is created for a construction process, it still involves a time-consuming and difficult debugging process to identify and correct errors in the model until a valid experiment is obtained. Both comprehensive knowledge and hands-on experience are essential in achieving efficiency in this labor-intensive process. This research presents the simulation self-diagnosis methods based on the general role that simulation entities play in advancing a simulation, in which entities dynamically flow in the model and activate activities to operate as the simulation time advances. A valid simulation requires that all entities must flow in correct patterns and all activities must be correctly executed in the experiment. The presented self-diagnosis methodology consists of two separate stages: model compilation and runtime diagnosis. Compiling a model intends to examine the matching relations between modeling elements in the model. Diagnosing an experiment at runtime explores any abnormally executed activities and then to search for corresponding causes. Both stages can pinpoint errors in the model and suggest corresponding corrective measures. An example is used to illustrate the improved debugging process with the enhanced self-diagnosis function.