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Arabian Journal for Science and Engineering

, Volume 43, Issue 9, pp 4501–4515 | Cite as

Application of Parallel Multi-model Simulation Method for Condition Monitoring of a Power Hydraulic System

  • Santosh Kr. Mishra
  • Jay Prakash Tripathi
  • J. Das
  • Sanjoy K. Ghoshal
Research Article - Mechanical Engineering

Abstract

In hydraulic system, the occurrence of fault is a common phenomenon which mainly results due to abnormal behavior of its decisive components leading to sudden alarming rise in some of its critical parameters, and hence, the need for condition monitoring techniques arises. Residuals which happen to be an indicator of faulty signal are equivalent to the number of sensors set up in the plant. Hence, the need is to place in considerable number of sensors throughout the plant to create residuals, a prime requisite required for isolating fault. But it appears a tedious task and seems technically improbable to isolate all potential faults with the instruments at our disposal, and it can turn out to be an expensive affair to put inexact number of sensors in order to evaluate individually every physical state. To tackle with such problem, an already-developed methodology has been implemented on the test setup, i.e., a closed-loop hydrostatic transmission system consisting of a variable-displacement pump and a fixed displacement motor. In this way, an experimental exposure is added to the revisited methodology which was lacking. Moreover, the parameter estimation technique in the revisited methodology is modified to tackle with the situations where the generation of symbolic expression for estimating the suspected parameters is not trivial due to nonlinearity in equation. Therefore, the estimation problem is resolved numerically in Simulink. Due to same reason of the absence of symbolic expression, the observer-based residual is generated instead of ARR-based residual.

Keywords

Hydrostatic transmission system Parameter estimation Condition monitoring Residual Fault signature matrix 

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Copyright information

© King Fahd University of Petroleum & Minerals 2017

Authors and Affiliations

  • Santosh Kr. Mishra
    • 1
  • Jay Prakash Tripathi
    • 2
  • J. Das
    • 1
  • Sanjoy K. Ghoshal
    • 2
  1. 1.Department of Mining Machinery EngineeringIndian Institute of Technology (ISM)DhanbadIndia
  2. 2.Department of Mechanical EngineeringIndian Institute of Technology (ISM)DhanbadIndia

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