“…Barasu et al, in [62], propose a microwave sensor (handheld ultra-wide band (UWB) radar) to non-invasively achieve vibrations for the CM of bearings in an induction motor, by projecting the microwave on the squirrel cage induction motor (SCIM) and by capturing the reflected signal. A new conception of piezoelectric accelerometer (the most frequently used type in industry) is presented by Ghemari et al in [63], with the aim of obtaining more accurate results. The use of vibrations signals obtained with sensors conceived with the microelectromechanical system (MEMS) technology is discussed by Prashant et al in [61] and Feldman et al in [64], due to their size, cost, portability, and flexibility.…”
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal functioning states are related to specific patterns that can be extracted from vibration signals. Extensively studied issues concern the different methodologies used for carrying out the main phases (signal measurements, pre-processing and processing, feature selection, and fault diagnosis) of a malfunction automatic diagnosis. In addition, vibration-based condition monitoring has been applied to a number of different mechanical systems or components. In this review, a systematic study of the works related to the topic was carried out. A preliminary phase involved the analysis of the publication distribution, to understand what was the interest in studying the application of the method to the various rotating machineries, to identify the interest in the investigation of the main phases of the diagnostic process, and to identify the techniques mainly used for each single phase of the process. Subsequently, the different techniques of signal processing, feature selection, and diagnosis are analyzed in detail, highlighting their effectiveness as a function of the investigated aspects and of the results obtained in the various studies. The most significant research trends, as well as the main innovations related to the various phases of vibration-based condition monitoring, emerge from the review, and the conclusions provide hints for future ideas.
“…Barasu et al, in [62], propose a microwave sensor (handheld ultra-wide band (UWB) radar) to non-invasively achieve vibrations for the CM of bearings in an induction motor, by projecting the microwave on the squirrel cage induction motor (SCIM) and by capturing the reflected signal. A new conception of piezoelectric accelerometer (the most frequently used type in industry) is presented by Ghemari et al in [63], with the aim of obtaining more accurate results. The use of vibrations signals obtained with sensors conceived with the microelectromechanical system (MEMS) technology is discussed by Prashant et al in [61] and Feldman et al in [64], due to their size, cost, portability, and flexibility.…”
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal functioning states are related to specific patterns that can be extracted from vibration signals. Extensively studied issues concern the different methodologies used for carrying out the main phases (signal measurements, pre-processing and processing, feature selection, and fault diagnosis) of a malfunction automatic diagnosis. In addition, vibration-based condition monitoring has been applied to a number of different mechanical systems or components. In this review, a systematic study of the works related to the topic was carried out. A preliminary phase involved the analysis of the publication distribution, to understand what was the interest in studying the application of the method to the various rotating machineries, to identify the interest in the investigation of the main phases of the diagnostic process, and to identify the techniques mainly used for each single phase of the process. Subsequently, the different techniques of signal processing, feature selection, and diagnosis are analyzed in detail, highlighting their effectiveness as a function of the investigated aspects and of the results obtained in the various studies. The most significant research trends, as well as the main innovations related to the various phases of vibration-based condition monitoring, emerge from the review, and the conclusions provide hints for future ideas.
“…In this circuit, R30 and R34 sum the external control resistance RG, 100 differs nearly 2000 times from 49. 4 , so RG can be considered infinite compared to the internal block. The output voltage is equal to the A D620 differential input voltage.…”
Section: Adc Conversionmentioning
confidence: 99%
“…Among these measurement techniques are the contact type and the non-contact type, but for the vibration measurement of the moving parts, the wire contact type measurement mode appears helpless. In this case, non-contact sensors are required [1][2][3][4][5][6][7][8] , Wang [9] et al used an electrostatic induction sensor to measure the vibration of the rotating shaft. This principle is based on the induced charge output signal amplitude on the metal shaft surface, but this method has defects such as uneven induction charge distribution and unknown charge quantity.…”
In view of the problems such as difficulty in and high cost of vibration signal collection of rotating mechanical rotating shaft, this paper proposes a low-cost, fast, stable and reliable hydraulic turbine rotating wheel vibration signal online monitoring scheme specially designed to the imbalance and dynamic balance counterweight of hydraulic turbine rotating shaft. Three high-frequency wireless acceleration sensors are installed on the rotating shaft to monitor the vibration signals of the three directions in real time. Vibration signals are sent to the cloud platform to facilitate data storage. The acceleration signal is decomposed by WOA-VMD. The time domain signal shows the running track of the shaft to guide the dynamic balance counterweight of the rotor. The frequency domain signal is used to analyze the machine vibration in the shaft frequency domain and predict the health status of the shaft according to the frequency change. According to this system, completed the experiment of a hydraulic turbine experiment, proved the feasibility and rationality of the system, and has good application prospect and practical value.
Piezoelectric elements (PEMs) are used in a variety of applications. In this paper, we developed a full analytical model and a simple system identification (SI) method of a piezoelectric actuator, which includes piezostack elements and a three-stage amplification mechanism. The model was derived separately for each unit of the system. Next, the units were combined, while taking into account their coupling. The hysteresis phenomenon, which is significant in piezoelectric materials, is described extensively. The theoretical model was verified in a laboratory setup. This setup includes a piezoelectric actuator, measuring devices and an acquisition system. The measured results were compared to the theoretical results. Some of the most well-known forms of system identification are shown briefly, while a new and simple algorithm is described systematically and verified by the model. The main advantage of this work is to provide a solid background and domain knowledge of modelling and system identification methods for further investigations in the field of piezoelectric actuators. Due to their simplicity, both the model and the system identification method can be easily modified in order to be applied to other PEMs or other amplification mechanism methods. The main novelty of this work lies in applying a simple system identification algorithm while using the system-level approach for piezoelectric actuators. Lastly, this review work is concluded and some recommendations for researchers working in this area are presented.
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