Search

The fault diagnosis and prognosis of low speed machines remains a difficult problem despite remarkable advances in the conditional monitoring domain. The Rolling-element bearing is a vital part of these machines and its failure is one of the main causes of machine breakdown. In order to have an efficient maintenance strategy, fault diagnosis of a bearing and time estimation of its remaining useful life is needed. However, conventional vibration analysis at very low speeds generally fails to detect vibrations issued from a faulty bearing due to its low energy, high and variable loading conditions and to the noisy environment generated by other mechanical components of low speed machines such as gearing systems. In this work, instantaneous angular speed (IAS)-based fault diagnosis is introduced in order to compensate for the shortcoming of conventional monitoring techniques since it is strictly synchronized to shaft rotation and much less dependent on the transfer path between the defect and the sensor contrary to vibration and acoustic emission analysis. At very low speeds and in the case of a seeded spall on the bearing’s race, the shaft IAS reveals the shaft dynamical behavior when the rolling element passes into the spall. It is proven that this behavior is different when entering the spall than when exiting. The determination of entrance and exit moments allows a precise fault size estimation which is a critical step for bearing prognosis. The proposed fault size estimation method is tested on different seeded spall widths at different low speeds. The results gave a satisfactory fault width estimation and show that IAS measurement is a promising tool for the health monitoring of very low speed machines. [ABSTRACT FROM AUTHOR]

This paper takes part of a research contract in which the objective is to provide a monitoring process by vibration analysis of bearings on the transfer shaft, within automotive field. Presses have a specialty to work at low speed and to generate a shock type signal with very important amplitude, as a consequence of the stamp that hides the vibration signature of different mechanical components of the machine. A methodology is introduced for the acquisition and the signals treatment, outcoming from a press, with the objective to diagnose the bearings of the transfer shaft. However, the signals resulting from accelerometer sensors are the results of a mixture of sources of vibrations, sources being able to be allotted to one or more defects and are generally polluted by noise. This work presents the three principal methods of denoising and the study of their influence on the scalar parameters (kurtosis, crest factor) within the framework of the detection of defects of the chipping types of bearings on a form press. [ABSTRACT FROM AUTHOR]

Vibratory analysis allows us to interpret the fundamental conditions of rotating machines. This interpretation is useful in the diagnosis of faults. In practice, the vibratory measurements made by sensors come from a mixture of vibratory sources corresponding to different machine components. Thus, it becomes hard to conduct state interpretation for each individual component. This fact leads us to consider the inverse problem, reconstruction of the vibratory sources based on measurements. However, the inversion is unfortunately unstable. To limit the instability, previous studies proposed use of a large number of sensors and the processing of measurements using regularization methods. However, regularization requires estimation of the regularization parameter, which is a hard task. In addition, regularization can remove some vibratory sources. Moreover, the sensor positions are "random", but the stability is significantly influenced by the sensor positions and by the mixture properties described by modal analysis. This article proposes to link modal analysis and stability. This link allows us to reduce the number of sensors and to avoid regularization methods. Thus, two complementary approaches are developed to determine optimal sensor positions: A numerical approach with a numerical updated model and an experimental approach using modal analysis. Thanks to the use of these optimal positions, stability is improved and vibratory sources are correctly reconstructed. [ABSTRACT FROM AUTHOR]

The monitoring of rotating machinery is increasingly important for industry. Partly, it is made from indicators given by vibration analysis. These indicators give only the overall state of operation of the studied machine. Indeed, the piezoelectric sensors, which are used for vibration analysis, record the vibrations generated by the various components of the machine. Numerous studies have developed techniques for locating and quantifying the vibration sources from the recorded signals. Thus, it is legitimate to believe that these sources can give us an indicator which should be characteristic of the damage of each critical component and which should allow to follow the severity of a defect. This paper studies the feasibility (i) firstly, to restore an indicator (RMS value) for each component, (ii) secondly, to monitor the evolution of this indicator through the severity of the defect. [Copyright &y& Elsevier]

Among the methods which make it possible to establish a diagnosis on the operating condition of a mechanism, the vibratory techniques seem very promising and are booming. The signals collected by accelerometers are the result of a mixture of various sources each of which corresponds to operation of a component. The diagnosis and monitoring of each component require the determination of the contribution of each source in the signal collected. The objective of this work is to use and optimize the techniques applied to the inverse problems with the aim of quantifying the contribution of each source in the obtained mixture, more particularly, the sources which are characteristic of a damaged element. However, the inverse problems are generally unstable. These instabilities are often related to the errors of measurement or the parasites contained in the signals and require methods of stabilization. This paper proposes a methodology, based on the restitution of the sources. Thus, the methodology ensures the detection and the localization of a defect of a component by the optimization of the position of a limited number of sensors. Two approaches are then proposed: the numerical approach which employs an updated numerical model of the studied structure and the experimental approach based on the correlation between the position of the sensors and the modal parameters of this same structure. The experimental validation of this methodology is carried out on a casing made up of two bearings. [Copyright &y& Elsevier]