Vibration condition monitoring of planetary gears based on decision level data fusion using Dempster-Shafer theory of evidence

In recent years, due to increasing requirement for reliability of industrial machines, fault diagnosis using data fusion methods has become widely applied. To recognize crucial faults of mechanical systems with high confidence, indubitably decision level fusion techniques are the foremost procedure among other data fusion methods. Therefore, in this paper in order to improve the fault diagnosis accuracy of planetary gearbox, we proposed a representative data fusion approach which exploits Support Vector Machine (SVM) and Artificial Neural Network (ANN) classifiers and Dempster-Shafer (D-S) evidence theory for classifier fusion. We assumed the SVM and ANN classifiers as fault diagnosis subsystems as well. Then output values of the subsystems were regarded as input values of decision fusion level module. First, vibration signals of a planetary gearbox were captured for four different conditions of gear. Obtained signals were transmitted from time domain to time-frequency domain using wavelet transform. In next step, some statistical features of time-frequency domain signals were extracted which were used as classifiers input. The gained results of every fault diagnosis subsystem were considered as basic probability assignment (BPA) of D-S evidence theory. Classification accuracy for the SVM and ANN subsystems was determined as 80.5 % and 74.6 % respectively. Then, by using the D-S theory rules for classifier fusion, ultimate fault diagnosis accuracy was gained as 94.8 %. Results show that proposed method for vibration condition monitoring of planetary gearbox based on D-S theory provided a much better accuracy. Furthermore, an increase of more than 14 % accuracy demonstrates the strength of D-S theory method in decision fusion level fault diagnosis

Online Condition Monitoring of Rotating Machines by Self-Powered Piezoelectric Transducer from Real-Time Experimental Investigations

This paper investigates self-powering online condition monitoring for rotating machines by the piezoelectric transducer as an energy harvester and sensor. The method is devised for real-time working motors and relies on self-powered wireless data transfer where the data comes from the piezoelectric transducer’s output. Energy harvesting by Piezoceramic is studied under real-time motor excitations, followed by power optimization schemes. The maximum power and root mean square power generation from the motor excitation are 13.43 mW/g(2) and 5.9 mW/g(2), which can be enough for providing autonomous wireless data transfer. The piezoelectric transducer sensitivity to the fault is experimentally investigated, showing the considerable fault sensitivity of piezoelectric transducer output to the fault. For instance, the piezoelectric transducer output under a shaft-misalignment fault is more than 200% higher than the healthy working conditions. This outcome indicates that the monitoring of rotating machines can be achieved by using a self-powered system of the piezoelectric harvesters. Finally, a discussion on the feasible self-powered online condition monitoring is presented

AN IMPACT-BASED PIEZOELECTRIC ENERGY HARVESTER UTILIZING SPHERICAL MASS COLLISION PHENOMENON

The base-excitation piezoelectric energy harvesters have been vastly investigated under periodic base excitation as a conventional method. However, the waveforms of environment’s vibrations are mostly non-harmonic low-frequency periodic signals that reduce the efficiency of the harmonic-based resonance harvester. This study presents an alternative piezoelectric energy generation, the impact-based piezoelectric energy harvester concept rather than the typical harmonic-based one. The harvester benefits from impact excitation, leading to higher frequencies around the harvester’s natural frequencies. The impact concept is utilized for energy harvesting based on contact between a piezoelectric patch and a miniatured spherical mass. An experimental study was carried out to evaluate the effects of impact velocity and boundary condition on the dynamic behavior and power generation of the piezoelectric energy harvester. Moreover, a finite element model implemented a feasible framework to investigate the output power of the energy harvester under various impact forces. The results demonstrated μJ-scale energy generation by a single impact, indicating great energy generation possibilities for ultra-low-frequencies. The results also indicated that the boundary condition plays a critical role in energy harvesting, affecting the probability of voltage cancelation phenomenon occurrence. It was shown that the optimal boundary condition decreases the negative effects of voltage cancelation to improve the performance of the impact-based energy harvester

Design and analytical evaluation of an impact-based four-point bending configuration for piezoelectric energy harvesting

Aiming toward improved energy conversion in piezoelectric energy harvesters, this study investigates four-point bending (FPB) energy harvesters (FPB-EH) to explore their prominent features and characteristics. The FPB configuration innovatively extends energy harvesting capabilities relative to conventional cantilever beams. The FPB-EH comprises a composite piezoelectric beam that rests on two supports of a fixed clamp, excited by contact force applied at two contact lines on a moving clamp. A comprehensive analytical electromechanical model for the vibrating energy harvester is presented with unique modeling features, including multi-beam sections and multi-mode-shape functions. Solutions of the analytical model are presented for a wide range of contact force types, including steady-state solutions for harmonic forces, impact forces, periodic and non-periodic arbitrary forces. This comprehensive model progresses the state-of-the-art piezoelectric modeling knowledge and is readily applicable to various energy harvesting configurations. The model is validated against experimental results and finite element analysis. Next, a parametric study was performed to evaluate the effects of various FPB characteristics, including the fixed and moving clamp spans, the waveform, and the period-time of contact force. The results indicate that the FPB configuration can enhance energy conversion efficiency and normalized output energy by factors of over 3 and 6, respectively. Finally, guidance is given for selecting between cantilever and four-point bending configurations

Evaluating The Association Between Serum Hsp27 Antibody and Hypertension in Patients without Underlying Cardiovascular Disease

Introduction: An association between heat shock protein 27 (Hsp27) antigen with cardiovascular risk factors has been shown previously. Furthermore, higher levels of serum anti-HSP27 antibodies are also related to higher cardiovascular morbidity and mortality. In the current study, we looked at the relationship between serum Hsp27 antibodies and hypertension, as an important cardiovascular risk factor, in individuals without evidence of cardiovascular disease (CVD).Methods: A sub-population of hypertensive patients (HTN+) without underlying CVD were recruited from the Mashhad stroke and atherosclerosis heart disease (MASHAD) study to assess the association between serum Hsp27 antibodies and hypertension; independent of other cardiovascular risk factors. A total of 1599 people were studied of whom 288 individuals had hypertension and 1311 were used as controls (HTN-).Results: Mean serum Hsp27 antibody titers were 0.20 (0.27) OD in the whole population sample and was not significantly different in the normotensive (HTN-) compared to HTN+ individuals with different degrees of hypertension.Conclusion: There were no significant associations between serum anti-Hsp27 concentrations and either the presence or severity of hypertension. Future studies are warranted to explore the association of anti-Hsp27 antibody and antigen levels and other cardiovascular risk factors