The exploitation of cyclostationarity properties of vibratory signals is now more widely used for monitoring rotating machinery and especially for diagnosing bearing defects. The acoustic emission (AE) technology has also emerged as a reliable tool for preventive maintenance of rotating machines. In this study, we propose an experimental study that characterizes the cyclostationary aspect of acoustic emission (AE) signals recorded from a defective bearing (40 μm on the outer race) to see its efficiency to detect a defect at its very early stage of degradation. An industrial sensor (UE10 000) is used. An electrical circuit converts the high frequency signal into an audible signal by heterodyning. The cyclic spectral density, which is a tool dedicated that put into evidence the presence of cyclostationarity, is used for characterizing the cyclostationary. Two new indicators based on this cyclostationary technique are proposed and compared for early detection of defective bearings.

This work deals with the application of the fuzzy logic to automate diagnosis of bearing defects in rotating machines based on vibration signals. The classification tool used is a fuzzy inference system (FIS) of Mamdani type. The vector form of input contains parameters extracted from the signals collected from the test bench studied. The output vector contains the classes for the different operating modes of the experimental study. The results show that; pretreatment data (filtering, decimation,...), the choice of parameters of fuzzy inference system (input variables and output, types and parameters of membership functions associated with different input and output variables of the system, the generation of fuzzy inference rules,...) are of major importance for the performance of fuzzy inference system used as a tool for fault diagnosis of rotating machinery.

The early detection of gear faults remains a major problem, especially when the gears are subjected to non stationary phenomena due to defects. In industrial applications, the crack of tooth is a default very difficult to detect whether using the time descriptors or the frequency analysis. In this work and based on a numerical model, we prove that the crack default affects directly the phase of the frequency component of the defective wheel (frequency modulation). To properly estimate the phases, we suggest two high-resolution techniques (Estimation of Signal Parameters via Rotational Invariance Techniques ESPRIT with a sliding window and Weighted Least Squares Estimator WLSE). The results of both methods are compared to the phase obtained by Hilbert transform. The three techniques are then applied on a multiplicative signal with a frequency modulation to show the influence of the amplitude modulation on the quality of phase estimation. We note that the ESPRIT method is much better in the estimation of frequencies while WLSE shows much efficiency in the estimation of phases if we keep the frequencies almost stables.

This work is interested to the analysis of the vibratory signals coming from a milling operation. The objective is the detection of cutting tool breakage using the cyclostationary tools. Initially, we will show that the vibration signals captured from the milling operation are cyclostationary. The proposed cyclostationary methods are the first and second order synchronous statistics and the spectral correlation. A test rig, composed of a milling machine (cutter with 5 teeth) and a workpiece, is used to extract the vibration signals that are angular sampled in the free fault case and one broken tooth case. This test rig is instrumented with three accelerometers, installed in the three directions, and an optical encoder that allows the angular sampling. Then we will see that the angular sampling of the signals captured from a milling operation is essential to preserve the cyclostationary properties destroyed, in the case of the temporal sampling, by speed fluctuations. The proposed method capacity to detect the broken tooth is shown. The synchronous statistics of order 1 and order 2 detect the broken tooth presence and its emplacement. The spectral correlation analysis distinguishes the broken tooth presence, but is not practical for the diagnosis. For that, an indicator based on the spectral correlation is proposed.

This study presents a NDT method using infrared thermography associated with a microwave excitation. The advantages of such stimulation lie in the volumic absorption of incoming waves which lead to a greater sounded depth. This method is applied to two types of samples. The first is a concrete slab reinforced with CFRP on which a bonding failure is inserted and the second is a wooden plate on which a metallic insert is placed on the back face. The device generating the microwaves is made of a commercial magnetron associated with a pyramidal horn antenna. An infrared camera is placed on the same side as the stimulated surface and thermograms are recorded at regular intervals. The whole assembly is placed in a protective room against high frequencies. The incident power density leads to heating of less than 1 °C of the surface of the samples. The thermograms show a higher temperature rise in front of the defect area. The non-uniformity of the beam, leads us to treat the thermograms with an algorithm of contrast. These first results show the interest of the microwave excitation to detect defects deeper than in the case of surface excitation.

Vibration analysis is the most widely used tool in industrial application for machine’s health condition assessment. Bearings, however, are very sensitive and require special attention. Vibration analysis employs various signal processing methods such as spectral analysis, time-scale, time frequency analysis, etc. these methods are used to analyze bearings’ vibratory behavior by monitoring the evolution of statistical indicators.However, diagnosing the bearing depending on traditional features only isn’t sufficient to assure effective or reliable assessment of the component’ health condition. This paper proposes a multi-features online dynamic classification as a new method for fault detection and health condition monitoring for bearings; this technique uses multiple features, including traditional features extracted from the raw signal, two special features extracted by wavelet analysis, the spectral kurtosis, coupled with a nonlinear principal component analysis and a dynamic classification to capitalize on the hidden information in the time evolution of the features.Through this article, we introduce different measures and techniques used to characterize the health state of rolling, then we deploy a methodology using dynamic classification to detect early defect. To ensure an almost continuous surveillance, this methodology is based on a real-time analysis, and uses specific statistical indicators adapted to the experimental bench. Then, the monitoring of the degradation is achieved through the resulting class of the state of degradation. New parameters such as the speed of the class, the position of the class, the shape of the class will be discussed to inform the state of damage. The suggested methodology is validated by analyzing several fatigue tests from a fatigue bench bearing thrust ball referenced SNR51207.

Although condition monitoring of centrifugal pump bearings to infer faults is common practice, the relationship between a pump’s vibration level and the unsteady flow within has not been extensively researched. The latter, however potentially provides the foundations for further developments in, pump design to increase performance, advanced predictive maintenance programs and, vibration monitoring techniques that can permit inference of pump efficiency states. This paper investigates the correlation between pump vibration and unsteady flow at different motor speeds. A test rig and a numerical CFD model were employed. It was found that flow-induced vibration in general increases with pump speed and was clearly linked to pump efficiency. It therefore seems possible to construct a model to deduce a pump’s efficiency from its pressure and vibration levels, if the efficiency curve is known a priori. However, as the vibration levels are also dependent on the system’s structural natural frequencies and modes, it seems that knowledge of these may also be needed in some instances. The work confirms that utilising a variable speed pump at lower pump speeds allows greater deviations from the design BEP without jeopardising the safety of the pump and should be considered for industrial use.

The vibrations undergone by men are a well-known and widely studied risk factor in the industrial world. They are transmitted to the whole body or the upper limbs and they are measured, and limited, according to international standards. Disorders resulting from exposure to vibration are varied in nature: osteoarticular, muscular, vascular, and neurological. In this context, an European Directive 2002/44/EC to the protection of workers exposed to vibration, precises thresholds for vibration exposures and defines the procedure for risk prevention. Nevertheless, the effect of vibration is little studied in sports despite the ubiquity of these. Vibration can induce discomfort, degrading performance or causing musculoskeletal disorders. This paper makes an overview of the studies involving the vibrations during cycling. At first, this paper will summarize the different standards and guidelines relating vibration in humans, which present a guide for the measurement and evaluation of the vibration and exposure limits. Secondly, this paper presents a state of the art vibration effects: (i) the physiological and pathological disorders in athletes, (ii) and the performance. A third part will be devoted to the synthesis of numerical studies that represent the biodynamic response and help to predict the effects of human body vibration. Finally, new research and innovations will be discussed based on studies in other sports.

This study presents a finite element (FE) model of the human hand-arm system to derive natural frequencies and mode shapes. The FE model is calibrated by considering modal parameters obtained from experimental vibration analyzed by using operational modal analysis (OMA) and transmissibility. Modal and harmonic analyses of the FE model are performed for two boundary conditions. The first one considers fixed shoulder condition while the second one introduces the trunk in order to permit motion of the shoulder. The results show that the natural frequencies of the second model that permits shoulder motion are comparable with those determined from measurements. Especially, the natural frequency about 12 Hz, which is corresponding to the frequency of maximum weight in ISO-5349-1 (2001), is not present in the model with fixed shoulder condition, while it appears in the second model. The results of the present study suggest that improved finite element models of the human hand-arm system may reveal hand-arm injury mechanism, the understanding of which may assist in deriving appropriate frequency weightings for the assessment of different components of the hand-arm vibration syndrome.

The efficiency of passive methods for noise reduction decreases at low frequency. In this frequency range active structural acoustic control (ASAC) can reduce sound radiation of structures by controlling their vibration usually using piezoelectric or electrodynamic transducers. Besides its global effect on the structure, a bending nearfield is observed, depending on the actuator type. In some ASAC strategies as in the virtual impedance approach, actuators and sensors are collocated. Although it does not affect the radiation of the structure, the local bending strongly modifies the transfer function between transducers. A method is proposed in order to identify and compensate it. The global part of the vibratory field is extracted by cancelling the contribution of higher order modes approximated as a stiffness. After compensation, the signal from the sensor is much more representative of the radiation and nearly independent of the nature and the size of the actuator.

The main objective of this article is to study the effect of 2D coupled mode free convection with surface radiation on the fluid flow behavior in an air filled partitioned and shallow cavity subjected to isothermal or insulated boundary conditions. The dimensionless governing equations under Boussinesq approximation are coupled with a radiative model through the boundaries conditions and solved by the finite volume method. The numerical results are discussed in terms of streamlines, isotherms, convective and radiative Nusselt numbers along the cover plate for various aspect ratios (a, b and c), emissivities and Rayleigh number. These results highlighted the condition of the enclosure performance and revealed among other that isothermal boundaries induce better convective heat exchange compared to adiabatic cases. Also, it is noticed that varying aspect ratio (a) causes strong influence on both Nusselt numbers compared to the aspect ratios (b) and (c). The increase of (ϵo) raises Nuconv and decreases Nurad slightly. Whereas, an increase of (ϵC) leads to minor changes in Nurad when (b) or (c) vary, this effect becomes appreciable with increasing (a).