1,720,997 research outputs found
Time-varying metrics of cyclostationarity for bearing diagnostic
No full textBall bearings represent the most adopted solution to support rotating elements. Separated by the cage, the rolling elements are induced by the kinematics of the system to roll and accidentally slip on the rings. In working conditions the continuous contact of the elements leads to a wearing of the bearing surfaces. As a consequence, the early detection of faults represents an issue for modern diagnostic systems. The mathematical model of faulted rolling bearings has been extensively investigated in the last decades and it is widely accepted that a faulted bearing is subject to an unwanted slippery leading to a cyclostationary vibration signal. This paper presents a novel approach to the diagnosis of rolling bearings based on the statistical definition of cyclostationarity. In particular, various metrics have been devised to track the “cyclostationary signature” of the vibration signal and the performance of the proposed algorithms has been assessed through both experimental measurements and synthetic data. Numerical results have shown that the new approach to fault detection is comparable to conventional techniques based on spectral kurtosis, demodulation and spectral correlation, and it can outperform them in some cases; furthermore the simplicity of the proposed algorithms leads to an intrinsic robustness against the mechanical noise typical of practical scenarios
Harmonic-percussive source separation for fault detection in ball bearings characterized by cyclic polynomial motion law
No full textBearings are one of the most investigated components leading to failures in rotating machines. Much attention has been paid to the condition monitoring of machines in non-stationary conditions, nevertheless several working conditions have not been adequately studied yet. For instance, the brushless motors used as electric cams are characterized by cyclic polynomial motion laws and motion inversion of the shaft. This paper presents a new approach based on the harmonic-percussive source separation (HPSS) which separate vibration signal into three components, namely harmonic component, percussive component and residual component. The spectral entropy (SE) of the harmonic and percussive signals is devised as a measure of the informative content carried by each component. A prevalence of the SE in the percussive component is attributable to a faulty condition of the bearing, whereas a prevalence in the SE of the harmonic component suggests a healthy condition of the bearing
On the performance comparison of diagnostic techniques in machine monitoring
No full textPredictive maintenance can save a lot of efforts in modern industry and condition monitoring is attracting a lot of attention accordingly. New algorithms for fault detection appear frequently in the technical literature, however an objective, quantitative and widely accepted approach to performance comparison is still lacking. In this paper, we propose a new method leading to a fair and reproducible performance assessment. The proposed solution is based on vibrational analysis and consists of searching and detecting the theoretical cyclic frequencies that appear as a specific "signature" of a fault. Each algorithm for condition monitoring relies on a metric, then the main idea is to quantitatively characterize the peaks of the metric emerging from the machine noise. We think that the wide adoption of the proposed approach could significantly foster the research in the fields of condition monitoring and predictive maintenance
Space-Time Block Coding for Noncoherently Detected CPFSK
No full textPublication in the conference proceedings of EUSIPCO, Florence, Italy, 200
Modelling and simulation of a vibrating membrane for the acquisition of lung sounds
No full textThe lack of general doctors and physicians represents the main problem for most of the modern national health systems. The high operating and maintenance costs of hospitals and clinics complete the critical picture. The development of new diagnostic tools can play a fundamental role in tackling these challenges. Recent studies have shown that electronic stethoscopes can raise the diagnostic suspicion of several pulmonary diseases, for instance interstitial lung diseases. The vibrating membrane, or diaphragm, is a fundamental component of the stethoscope that significantly affects its performance. Despite several theoretical and experimental studies are available about membrane vibration, the exact role of the diaphragm in a stethoscope for the acoustic coupling is still mostly unclear. In this paper we investigate the effect of the diaphragm on the sensibility and bandwidth of electronic stethoscopes. We setup a 1D numerical simulation of the system composed by the lung, human body, vibrating membrane and microphone. The parameters are devised from breathing mechanics and from the datasheets of a commercial diaphragm and microphone. The performance predicted by numerical simulations have been compared to experimental measurements on our prototype of electronic stethoscope. In particular, the predicted pressure at the input of the microphone is very close to that experimentally measured during outpatient visits at the University Hospital of Modena (Italy)
A simple multiparametric analysis to guide, compare and optimize the design of 'lensless' LED illuminators
No full textLED lighting is becoming increasingly pervasive in many areas ranging from ambient lighting, up to applications such as microscope illumination, UV-LED curing and, UV disinfection for air, surfaces, and water. Irradiance uniformity is often a fundamental parameter for guiding the design, comparison, and optimization of the illuminator. To this end, many methods and procedures have been proposed to guide the arrangement of the LED sources, as well as to guide the design of ad-hoc lenses. Nevertheless, there are many applications in which it is important to be able to consider other aspects as well as the uniformity of the irradiance. For this purpose, we propose both a method that allows calculating the irradiance generated by the used LED sources and, performance indicators for guiding the design and comparing different optical layouts
A statistical approach for modeling individual vertical walking forces
Full text linkThis paper proposes a statistical approach for modeling vertical walking forces induced by single pedestrians. To account for the random nature of human walking, the individual vertical walking force is modeled as a series of steps and the gait parameters are assumed to vary at each step. Walking parameters are statistically calibrated with respect to the results of experimental tests performed with a force plate system. Results showed that the walking parameters change during walking and are correlated with each other. The force model proposed in this paper is a step-by-step model based on the description of the multivariate distribution of the walking features through a Gaussian Mixture model. The performance of the proposed model is compared to that of a simplified load model and of two force models proposed in the literature in a numerical case study. Results demonstrate the importance of an accurate modeling of both the single step force and the variability of the individual walking force
Impact of noise model on the performance of algorithms for fault diagnosis in rolling bearings
No full textCondition monitoring of rolling bearings is attracting much interest since most of the production slowdowns depends on the damaging of these components. Several algorithms for fault detection have appeared in the technical literature in the last decade. In most cases, performance is assessed over both synthetic and experimental data. Unfortunately, the computer simulations adopt signal models that are trivial and are not able to predict the actual performance on the field. In this work we propose a framework suitable to fairly, quantitatively and objectively compare different algorithms for fault detection in rolling bearings. The vibration signal is obtained through computer simulations. The signal entailed by the damage is generated through the model at "impact-delay-line" already available in the technical literature. The machine noise is generated as a wideband component with the possible superposition of narrowband components. The wideband component has been modeled as additive white Gaussian noise, additive white noise drawn from an alpha-stable distribution and additive noise stemming from an autoregressive process. Narrowband components are modeled through trains of Gaussian pulses. The performance of three well known algorithms for fault detection are compared in terms of capability in identifying the theoretical cyclic frequencies related to a damage. In these scenarios the behavior of fault detectors are definitely far from that predicted by classical wideband noise models like, for instance, additive white Gaussian noise
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