Performance investigation of twisted blade inline Savonius turbine at variable load condition using numerical method

The torque stability and shutdown control of electric learner-driven vehicle (ELV) in the condition of motor load suddenly changing make the ELV has the same clutch handling characteristics with the traditional vehicle, and this makes the ELV popularization possible. A special control method is put forward in this article to achieve the consistency with the mechanical properties of engine. A multiparameter control model to identify the real condition of clutch handling by driver is builded with fuzzy control law. The torque stability and shutdown control of the motor with the load raising rapidly condition are approached by the adjusting of armature voltage with PWM control law. Keywords: Electric Learner-driven Vehicle;Torque Stability;Fuzzy Control

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A Model-Based Method for Leakage Detection of Piston Pump Under Variable Load Condition

IEEE Access ◽

10.1109/access.2019.2930816 ◽

2019 ◽

Vol 7 ◽

pp. 99771-99781 ◽

Cited By ~ 2

Author(s):

Hongbin Tang ◽

Wenxian Yang ◽

Zichao Wang

Keyword(s):

Load Condition ◽

Piston Pump ◽

Variable Load ◽

Leakage Detection ◽

Model Based

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Study on Coordinated Control Theory of Shield Thrust Hydraulic System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.619.399 ◽

2012 ◽

Vol 619 ◽

pp. 399-405

Author(s):

Huan Huan Feng ◽

Kui Chen ◽

Xiang Dong Wu ◽

Feng Yuan Li ◽

Zhu Feng Wang

Keyword(s):

Control Theory ◽

Load Condition ◽

Coordinated Control ◽

Joint Modeling ◽

Control Technique ◽

External Loading ◽

Variable Load ◽

Fuzzy Pid Control ◽

Compound Control ◽

Thrust System

In order to improve the dynamic coordinated control performance of shield thrust hydraulic cylinder during the shield construction process, we used the shield electro-hydraulic control synthetic experimental platform as research object. The simulation models of thrust system and external loading were built in AMESim. The result of PID closed-loop simulation indicated that thrust system can enable the compound control of thrust pressure and velocity by using the compound control technique of pressure and flow. In view of the complex and varied external load condition of shield thrust system, we simulated the fuzzy and fuzzy-PID control strategy of thrust system in passive automatic adjustment mode, based on the Joint Modeling and Simulation Environment (JMASE) of AMESim and Matlab/Simulink. The multi-external loads of thrust system mainly contained unequal-fixed load, equal-variable load and unequal-variable load. Finally, a coordinated control theory of shield thrust system was put forward. Such theory could provide some theoretical guidance for the design of shield machine and control of shield construction.

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Research on the wheel wear of metro vehicles based on the time-varying passenger flow

Industrial Lubrication and Tribology ◽

10.1108/ilt-01-2019-0014 ◽

2019 ◽

Vol 71 (9) ◽

pp. 1038-1046

Author(s):

AiHua Zhu ◽

Caozheng Fu ◽

JianWei Yang ◽

Qiang Li ◽

Jiao Zhang ◽

...

Keyword(s):

Load Condition ◽

Constant Load ◽

Variable Load ◽

Time Varying ◽

Wheel Wear ◽

Wear Prediction ◽

Content Type ◽

Passenger Flow ◽

Wheel Profile ◽

Simulation Results

Purpose This study aims to investigate the effect of time-varying passenger flow on the wheel wear of metro vehicles to provide a more accurate model for predicting wheel wear and a new idea for reducing wheel wear. Design/methodology/approach Sectional passage flow data were collected from an operational metro line. A wheel wear simulation based on time-varying passenger flow was performed via the SIMPACK software to obtain the worn wheel profile and wear distribution. The simulation involves the following models: vehicle system dynamics model, wheel-track rolling contact model, wheel wear model and variable load application model. Later, the simulation results were compared with those obtained under the traditional constant load condition and the measured wear data. Findings For different distances traveled by the metro vehicle, the simulated wheel profile and wear distribution under the variable load remained closer to the measurements than those obtained under the constant load. As the distance traveled increased, the depth and position of maximum wear and wear growth rate under the variable load tended to approach the corresponding measured values. In contrast, the simulation results under the constant load differed greatly from the measured values. This suggests that the model accuracy under the variable load was significantly improved and the simulation results can offer a more accurate basis for wear prediction. Practical implications These results will help to predict wheel wear more accurately and provide a new idea for simulating wheel wear of metro vehicles. At the same time, measures for reducing wheel wear were discussed from the perspective of passenger flow changes. Originality/value Existing research on the wheel wear of metro vehicles is mainly based on the constant load condition, which is quite different from the variable load condition where the passenger flow in real vehicles varies over time. A method of simulating wheel wear based on time-varying load is proposed in this paper. The proposed method shows a great improvement in simulation accuracy compared to traditional methods and can provide a more accurate basis for wear prediction and wheel repair.

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Multibranch and Multiscale CNN for Fault Diagnosis of Wheelset Bearings Under Strong Noise and Variable Load Condition

IEEE Transactions on Industrial Informatics ◽

10.1109/tii.2020.2967557 ◽

2020 ◽

Vol 16 (7) ◽

pp. 4949-4960 ◽

Cited By ~ 8

Author(s):

Dandan Peng ◽

Huan Wang ◽

Zhiliang Liu ◽

Wei Zhang ◽

Ming J. Zuo ◽

...

Keyword(s):

Fault Diagnosis ◽

Load Condition ◽

Variable Load

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Research on the Embedded Coefficient in Compressive Stress

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.468-471.1463 ◽

2012 ◽

Vol 468-471 ◽

pp. 1463-1466

Author(s):

Da Shan Dong ◽

Mao Chun Gan ◽

Yuan Yuan Teng

Keyword(s):

Numerical Method ◽

Compressive Stress ◽

Load Condition ◽

Steel Plates ◽

Elastic Buckling ◽

Pure Bending ◽

Design Rules ◽

Buckling Failure ◽

The Web

Steel plates connected together are mutually constrained when the member gets elastic buckling failure. A factor χ, embedded coefficient, is used to illustrate the degree of restriction of the flange on the web in GB/T3811-2008’Design Rules for Cranes’. In this standard, the value of the embedded coefficient has been preset in pure bending and pure shearing, while not clearly in compressive stress. In this paper, numerical method is adopted to discuss χ in such load condition.

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Analysis of One Bay Residential Building with Combined RCC Frame and Load Bearing Wall Structures

Journal of the Institute of Engineering ◽

10.3126/jie.v13i1.20356 ◽

2018 ◽

Vol 13 (1) ◽

pp. 117-124

Author(s):

Rajib Maharjan ◽

Vivek Shrestha

Keyword(s):

Cost Minimization ◽

Load Condition ◽

Hybrid Structure ◽

Frame Structure ◽

Variable Load ◽

Actual Behavior ◽

Structural Components ◽

Major Purpose ◽

Load Bearing ◽

Transfer Pattern

The major purpose of this study is to justify construction method of a hybrid structure in core area with construction complexity due unsafe excavation conditions and tries to define its rigidity and strength. Both RCC and Frame structure transfer same load to ground through foundation but the transfer mechanism varies. In some practical condition, building construction should be carried out in compact areas with unsafe adjoining building where adequate excavation for foundation cannot be carried out. In such cases, one bay hybrid structure is proposed for construction with combined RCC frame structure and load bearing walls. In these combined cases, both structures works as same unit to transfer building load but the transfer pattern varies. The variable load transfer pattern is due to discontinuity in structural system which also effect on seismic response of the building. The placement of a masonry load bearing structure in RCC frame structure varies design of all structural components of the building. To study actual behavior of hybrid structure in various load condition and introducing cost minimization techniques of buildings structural analysis was carried using ETABS 2016 with composite structural arrangement and with induction of load bearing wall as structural component. By which seismic behavior of building in both cases was obtained as well as reduction in rebar percentage and dimensional reduction of structural components can be achieved.Journal of the Institute of Engineering, 2017, 13(1): 117-124

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Multiscale inverted residual convolutional neural network for intelligent diagnosis of bearings under variable load condition

Measurement ◽

10.1016/j.measurement.2021.110511 ◽

2022 ◽

Vol 188 ◽

pp. 110511

Author(s):

Wenlei Zhao ◽

Zhijian Wang ◽

Wenan Cai ◽

Qianqian Zhang ◽

Junyuan Wang ◽

...

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Load Condition ◽

Variable Load ◽

Intelligent Diagnosis

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An Unsupervised Bearing Fault Diagnosis Based on Deep Subdomain Adaptation Under Noise and Variable Load Condition

Measurement Science and Technology ◽

10.1088/1361-6501/ac3a31 ◽

2021 ◽

Author(s):

mohammadreza ghorvei ◽

mohammadreza kavianpor ◽

mohammad taghi beheshti ◽

Amin Ramezani

Keyword(s):

Fault Diagnosis ◽

Real World ◽

Load Condition ◽

Local Maximum ◽

Industrial Applications ◽

Variable Load ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Proper Training ◽

The Difference

Abstract Deep learning-based approaches for diagnosing bearing faults have attracted considerable attention in the last years. However, in real-world applications, these methods face challenges. For proper training of these models, a considerable amount of labeled data are necessary, and due to limitations in industry, obtaining this amount of data may not be possible. Because of load variations, the distribution of training and test data may vary, which reduces the accuracy of the trained model for various working conditions. Furthermore, noise has a signiﬁcant impact on bearing fault diagnosis performance in real-world industrial applications. This study introduced the deep subdomain adaptation convolutional neural network (DSACNN) method to overcome these challenges in real scenarios. The local maximum mean discrepancy (LMMD) method reduces the difference between each class distribution in the source and target domains. We validated our proposed method by CWRU bearing dataset under various loads and noise with different SNRs. The results show that DSACNN outperforms other comparative methods in anti-noise performance and reduction of domain’s distribution discrepancies.

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