Received: 2013.11.22 Accepted: 2014.01.24 Published: 2014.03.05 DETECTION OF CHANGES OF THE SYSTEM TECHNICAL STATE USING STOCHASTIC SUBSPACE OBSERVATION METHOD (original) (raw)

Detection of Changes of the System Technical State Using Stochastic Subspace Observation Method

2014

System diagnostics based on vibroacoustics signals, carried out by means of stochastic subspace methods was undertaken in the hereby paper. Subspace methods are the ones based on numerical linear algebra tools. The considered solutions belong to diagnostic methods according to data, leading to the generation of residuals allowing failure recognition of elements and assemblies in machines and devices. The algorithm of diagnostics according to the subspace observation method was applied – in the paper – for the estimation of the valve system of the spark ignition engine. Keyworda: system diagnostic, subspace method, vibroacoustic.

Estimation of combustion engine technical state by multidimensional analysis using SVD method

Int. J. of Vehicle Systems Modeling and Testing, 2013

The changes of vibration estimators as a result of engine maladjustment, waste, damage or failure are the main idea of vibrodiagnostic investigation. Diagnostic investigations that use vibration to determine the technical state of combustion engines are very difficult. A limited set of proposed methods could have use in diagnostics. This paper presents a validation of research results of the use of the singular value decomposition (SVD) method. The research object is a combustion engine with power 55 kW at 830 rpm, which is feasible to obtain signals generated by vibration, as well as investigate the influence of the engine in the variation of the vibroacoustic data. Using the SVD method is possible to decide which symptom in the observation matrix is the best to recognise the technical state of combustion engines.

Part failure diagnosis for internal combustion engine using noise and vibration analysis

Periodica Polytechnica Transportation Engineering

Former practice proves that the vibration and noise caused by rotating or alternately moving parts together with the physical and chemical processes inside an internal combustion engine contain a great amount of information about what happens in-side the machine. The art of extracting useful information from time based vibro-acoustic signals is especially difficult in the case of an operating internal combustion engine because there are many vibration and noise sources and the rotation speed is not constant. The other problem is that the rotational speed is not constant in the case of an internal combustion engine during a single working cycle and in the course of continuous opera-tion. we developed a method to follow the fine details of angular speed fluctuations e. g. because of the activity of single piston. Our purpose was to develop a flexible and improvable measure-ment system which is usable both for experiments and final tests of several engines. Using the measuring set-up w...

Application of a subspace-based fault detection method to industrial structures

1999

Early detection and localization of damage allow increased expectations of reliability, safety and reduction of the maintenance cost. This paper deals with the industrial validation of a technique to monitor the health of a structure in operating conditions (e.g. rotating machinery, civil constructions subject to ambient excitations, etc.) and to detect slight deviations in a modal model derived from in-operation measured data. In this paper, a statistical local approach based on covariance-driven stochastic subspace identi"cation is proposed. The capabilities and limitations of the method with respect to health monitoring and damage detection are discussed and it is explained how the method can be practically used in industrial environments. After the successful validation of the proposed method on a few laboratory structures, its application to a sports car is discussed. The example illustrates that the method allows the early detection of a vibration-induced fatigue problem of a sports car. 1999 Academic Press R This work has been carried out within the framework of the Eureka project no. 1562 SINOPSYS (Model based Structural monitoring using in-operation system identi"cation) coordinated by LMS, Leuven, Belgium. The data analyses were performed when L. Mevel was at LMS, Leuven.

On-line diagnosis of mechanical defects of the combustion engine with principal components analysis

2015

Vibroacoustic diagnostics of combustion engines might be a complementary tool to OBD systems especially in mechanical defects detection. The presented method allows preliminary diagnosing of the mechanical defects on-line during driving without resampling the signal. The diagnosis is based on statistical features of the vibration signal. Principal components analysis (PCA) offers an approach for linear transformation of the problem variables so that the redundant information is reduced and the diagnostic model is more easily extracted. The product chosen for the investigation presented in this paper is a spark ignition engine. Performing analytical model, which is time consuming and costly, can supplement described method only in chosen cases. It is possible to diagnose of engine from the objective parameters of the specially prepared vibration signal without performing simulation models.

Subspace-based fault detection algorithms for vibration monitoring

Automatica, 2000

We address the problem of detecting faults modeled as changes in the eigenstructure of a linear dynamical system. This problem is of primary interest for structural vibration monitoring. The purpose of the paper is to describe and analyze new fault detection algorithms, based on recent stochastic subspace-based identi"cation methods and the statistical local approach to the design of detection algorithms. A conceptual comparison is made with another detection algorithm based on the instrumental variables identi"cation method, and previously proposed by two of the authors.

Application of vibration signal Kalman filtering to fault diagnostics of engine exhaust valve

Journal of Vibroengineering

A vibration signal of an internal combustion engine contains several diagnostic information, which are for the most part not utilised since they require complex processing methods in order to separate useful data and noise elimination. The method of diagnostics of leakages in a system: exhaust valve - cylinder, on the basis of reference model of the vibration signal is presented in the paper. It is proposed the statistical autoregressive model of signal with abstractive parameters. The recursive time-varing parameters estimation in the model is performed by the Kalman filtering. The model presented in the paper is illustrated with the signal of the spark ignition combustion engine Fiat Punto. The results of the analysis of the engine vibration signal under conditions of a defected exhaust valve and an increased valve clearance are presented. During road tests the vibrations acceleration signal was recorded as well as certain auxiliary signals used for a synchronisation and identific...

Detection of engine valve faults by vibration signals measured on the cylinder head

Proceedings of The Institution of Mechanical Engineers Part D-journal of Automobile Engineering, 2006

This technical note proposes a simple technique for the detection of incipient engine valve faults by vibration signals measured on the cylinder head. The characteristics of the vibration signal are analysed, indicating that its time domain and frequency domain characteristics are both useful for engine diagnosis while the cycle-by-cycle variation seems a disadvantage. A simple diagnostic technique named partial sampling and feature averaging (PSFA) has been presented. Only a specific part of the vibration signal corresponding to a particular impact force within each operating cycle is sampled and analysed, and then the diagnostic features are extracted from each part but averaged among many cycles. Identification of abnormal valve clearance just requires a partial sampling of the vibration signal extracted during the period of valve closing, and detection of gas leakage from valves needs a partial sampling signal corresponding to the period of in-cylinder combustion. The experimental results show that the proposed technique is feasible, effective and simple in implementation. exhaust valve closing, and the in-cylinder combustion JAUTO90