Vibro-acoustic condition monitoring of Internal Combustion Engines: A critical review of existing techniques

The article describes a concept of a non-invasive method for diagnosing the size of valve clearance in internal combustion engines, based on the analysis of engine surface vibration signals using artificial neural networks. The applicability of the method was tested on a single-cylinder compression-ignition engine with a low power rating, which had an OHV timing gear, acting indirectly on the valves, and manual adjustment of valve clearance. The method uses as diagnostic signals the readings of vibration sensors, which record the acceleration of engine head movement as a function of the angle of rotation of the crankshaft, with pre-set valve clearance values measured in a cold condition. From among the signals recorded, components corresponding to the impact of rocker arms against valve stems were identified and low-pass filtered in order to eliminate measurement interference. A classifier of selected features of the signals processed was constructed using artificial neural networks. This classifier recognizes signals generated by engines with correct valve clearance as well as those with too much and too little valve clearance.

/pdf/application-of-vibration-signal-in-the-diagnosis-of-ic-2tmcubg0o8.pdf

Application of vibration signal in the diagnosis of IC engine valve clearance

A fault diagnostics system of three-phase induction motors was implemented. The implemented system was based on acoustic signals of three-phase induction motors. A feature extraction step was performed using SMOFS-20-EXPANDED (shortened method of frequencies selection-20-Expanded). A classification step was performed using 3 classifiers: LDA (Linear Discriminant Analysis), NBC (Naive Bayes Classifier), CT (Classification Tree). An analysis was carried out for incipient states of three-phase induction motors measured under laboratory conditions. The author measured and analysed the following states of motors: healthy motor, motor with one faulty rotor bar, motor with two faulty rotor bars, motor with faulty ring of squirrel-cage. Measured and analysed states were caused by natural degradation of parts of the machine. The efficiency of recognition of the analysed states was good. The proposed method of fault diagnostics can find application in protection of three-phase induction motors.

/pdf/diagnostics-of-rotor-damages-of-three-phase-induction-motors-1p37tlotsw.pdf

Diagnostics of Rotor Damages of Three-Phase Induction Motors Using Acoustic Signals and SMOFS-20-EXPANDED

The vibration signals acquired on machines usually have complex spectral structure. As the signal of interest (SOI) is weak (especially at an early stage of damage) and covers some frequency range (around structural resonance), it requires its extraction from a raw observation. Until now, most of the techniques assumed the presence of Gaussian noise. Unfortunately, there are cases when the non-informative part of the signal (considered as the noise) is non-Gaussian due to the random disturbances or nature of the process executed by the machine. Thus, the problem can be formulated as the extraction of the SOI from the non-Gaussian noise. Recently this problem has been recognized by several authors and some new ideas have been developed. In this paper, we would like to compare these techniques for benchmark signals (Gaussian noise, cyclic impulsive signals, non-cyclic impulsive signals with random amplitudes and locations of impulses and a mixture of all of them). Our analysis will cover spectral kurtosis, kurtogram, stability index (Alpha selector), conditional variance-based selector, spectral Gini index, spectral smoothness index and infogram. Finally, a discussion on the efficiency of each method is provided.

https://www.mdpi.com/2076-3417/10/8/2657/pdf

Selection of the Informative Frequency Band in a Bearing Fault Diagnosis in the Presence of Non-Gaussian Noise—Comparison of Recently Developed Methods

Extraction of fault component from abnormal sound in diesel engines using acoustic signals

A change in the technical condition of mechanical components of internal combustion engines may not be detected by on-board diagnostic systems installed in vehicles. In similar cases, measurements and analyses of vibroacoustic signals being recorded prove useful. Since there are certain limitations to vibration measurements, including those related to the vibration transmission and the engine’s high temperature at measurement points, the authors of this paper have proposed that measurements and analyses of acoustic signals should be applied for the sake of assessment of the internal combustion engine technical condition. However, such an assessment requires new acoustic signal processing methods to be developed, and so this subject has been elaborated in the paper. The article provides a discussion on the option of applying a wavelet packet decomposition while filtering the internal combustion engine’s acoustic signal in order to diagnose an excessive valve clearance. The authors prepared an algorithm enabling selection of the chosen details and approximation of the wavelet analysis to low-frequency components, which constitute the noise, as well as high-frequency components comprising information on the possible enlarged engine valve clearance. Next, based on the selected high-frequency acoustic signal components, a method for automatic detection of enlarged clearance valves was developed, assuming that energy participations of the acoustic signal being emitted were to be determined while opening and closing individual valves. Under the study discussed, identification tests were conducted using two 4-cylinder internal combustion engines featuring valves of different clearances to consequently confirm the efficiency of the algorithm developed for the acoustic signal filtration and automatic detection of enlarged clearance valves.

Condition monitoring of engine timing system by using wavelet packet decomposition of a acoustic signal

Timing gear systems of motorcycle engines are equipped with chain tensioners, which are subject to premature damage in certain engine models. Early detection of such damage is essential, as it may protect the user from unexpected engine failure while the motorcycle is running. This paper presents the results of research whose purpose was to use the measurements and analyses of vibration signals for the diagnosing of damage to the hydraulic tensioner in the timing gear system. Stand tests were conducted of the motorcycle engine in which new, used or damaged tensioners were installed. The research results allow to conclude that a change in the technical condition of the tensioner caused by wear contributes to an increased level of engine vibrations and that it is possible to detect damage to the timing gear system tensioner by means of measurement, processing and analysis of vibration signals.

/pdf/condition-monitoring-of-the-cam-chain-tensioner-in-the-3tm5mubgy8.pdf

Štefan Liščák

Papers

Condition monitoring of engine timing system by using wavelet packet decomposition of a acoustic signal

Condition monitoring of the cam chain tensioner in the motorcycle engine