BACKLASH-FREE POWER DRIVE OF MACHINES

2021 ◽  
pp. 25-28
Author(s):  
V. M. Zyablikov
Keyword(s):  
Rolling Bearing ◽  
Single Stage ◽  
Free Rotation ◽  
Reliable Operation ◽  
Planetary Gearbox ◽  
Torsion Spring ◽  
Power Drive

Thebacklash-freepower drive of the machines ensures that the working shaft does not move freely when changing the direction of rotation. As a backlash-freegapless power drive, a single-stage planetary gearbox is proposed, containing two Central wheels, a carrier, and satellites, which are blocks of two gears, each of which is mounted on the carrierʼs axis by means of a rolling bearing and a freerunning Cam clutch. At the same time, the couplings are placed so as to ensure free rotation of the wheels in different directions. The gears are connected to each other by a pre-twisted cylindrical torsion spring. The proposed design will ensure reliable operation of the drive when the specified requirements are met.

scholarly journals A Novel Domain Adaptation-Based Intelligent Fault Diagnosis Model to Handle Sample Class Imbalanced Problem

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3382
Author(s):  
Zhongwei Zhang ◽  
Mingyu Shao ◽  
Liping Wang ◽  
Sujuan Shao ◽  
Chicheng Ma
Keyword(s):  
Fault Diagnosis ◽  
Domain Adaptation ◽  
Class Imbalance ◽  
Rolling Bearing ◽  
Industrial Applications ◽  
Mechanical Equipment ◽  
Reliable Operation ◽  
Cross Domain ◽  
Geometric Difference ◽  
Model Generalization

As the key component to transmit power and torque, the fault diagnosis of rotating machinery is crucial to guarantee the reliable operation of mechanical equipment. Regrettably, sample class imbalance is a common phenomenon in industrial applications, which causes large cross-domain distribution discrepancies for domain adaptation (DA) and results in performance degradation for most of the existing mechanical fault diagnosis approaches. To address this issue, a novel DA approach that simultaneously reduces the cross-domain distribution difference and the geometric difference is proposed, which is defined as MRMI. This work contains three parts to improve the sample class imbalance issue: (1) A novel distance metric method (MVD) is proposed and applied to improve the performance of marginal distribution adaptation. (2) Manifold regularization is combined with instance reweighting to simultaneously explore the intrinsic manifold structure and remove irrelevant source-domain samples adaptively. (3) The ℓ2-norm regularization is applied as the data preprocessing tool to improve the model generalization performance. The gear and rolling bearing datasets with class imbalanced samples are applied to validate the reliability of MRMI. According to the fault diagnosis results, MRMI can significantly outperform competitive approaches under the condition of sample class imbalance.

scholarly journals Fault Diagnosis for Rotating Machinery Using Multiscale Permutation Entropy and Convolutional Neural Networks

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 851 ◽  
Author(s):  
Hongmei Li ◽  
Jinying Huang ◽  
Xiwang Yang ◽  
Jia Luo ◽  
Lidong Zhang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Convolutional Neural Networks ◽  
Spatial Information ◽  
Single Channel ◽  
Rolling Bearing ◽  
Permutation Entropy ◽  
Planetary Gearbox ◽  
Rotating Machine ◽  
Fusion Methods

In view of the limitations of existing rotating machine fault diagnosis methods in single-scale signal analysis, a fault diagnosis method based on multi-scale permutation entropy (MPE) and multi-channel fusion convolutional neural networks (MCFCNN) is proposed. First, MPE quantitatively analyzes the vibration signals of rotating machine at different scales, and obtains permutation entropy (PE) to construct feature vector sets. Then, considering the structure and spatial information between different sensor measurement points, MCFCNN constructs multiple channels in the input layer according to the number of sensors, and each channel corresponds to the MPE feature sets of different monitored points. MCFCNN uses convolutional kernels to learn the features of each channel in an unsupervised way, and fuses the features of each channel into a new feature map. At last, multi-layer perceptron is applied to fuse multi-channel features and identify faults. Through the health monitoring experiment of planetary gearbox and rolling bearing, and compared with single channel convolutional neural networks (CNN) and existing CNN based fusion methods, the proposed method based on MPE and MCFCNN model can diagnose faults with high accuracy, stability, and speed.

scholarly journals Optimal Design of a Multibrid Permanent Magnet Generator for a Tidal Stream Turbine

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 487
Author(s):  
Khalil Touimi ◽  
Mohamed Benbouzid ◽  
Zhe Chen
Keyword(s):  
Permanent Magnet ◽  
System Optimization ◽  
Gear Ratio ◽  
Single Stage ◽  
Direct Drive ◽  
Planetary Gearbox ◽  
Tidal Stream ◽  
Optimization Methodology ◽  
Tidal Stream Turbine ◽  
Permanent Magnet Generator

Tidal stream energy is acquiring more attention as a future potential renewable energy source. Considering the harsh submarine environment, the main challenges that face the tidal stream turbine (TST) industry are cost and reliability. Hence, simple and reliable technologies, especially considering the drivetrain, are preferred. The multibrid drivetrain configuration with only a single stage gearbox is one of the promising concepts for TST systems. In this context, this paper proposes the design optimization of a multibrid permanent magnet generator (PMG), the design of a planetary gearbox, and afterwards analyzes the multibrid concept cost-effectiveness for TST applications. Firstly, the system analytical model, which consists of a single-stage gearbox and a medium speed PMG, is presented. The optimization methodology is afterwards highlighted. Lastly, the multibrid system optimization results for different gear ratios including the direct-drive topology are discussed and compared where the suitable gear ratio (topology) is investigated. The achieved results show that the multibrid concept in TST applications seems more attractive than the direct-drive one especially for high power ratings.

33: Synchronous Urethral Strictures: Prevalence and 10-Year Experience with Single Stage Reconstruction Via Systematic Retrograde Surgical Approach

2007 ◽  
Vol 177 (4S) ◽  
pp. 12-12
Author(s):  
L. Andrew Evans ◽  
Benjamin Moses ◽  
Kevin Rice ◽  
Craig Robson ◽  
Allen F. Morey
Keyword(s):  
Surgical Approach ◽  
Single Stage ◽  
Urethral Strictures
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