Torque Parameters Research Articles

Torque Parameter Characteristics of Non-contact Magnetic Coupling considering Rotor Volume Modeling

Torque Parameter Characteristics of Non-contact Magnetic Coupling considering Rotor Volume Modeling

Novel multifractal-based classification model for the quality grades of surrounding rock within tunnels

Understanding the variation patterns of tunnel boring machine (TBM) operational parameters is crucial for assessing engineering geological conditions and quality grades of surrounding rock within tunnels. Studying the multifractal characteristics of the TBM operational parameters can help identify the patterns, but the relevant research has not yet been explored. This paper proposed a novel classification model for quality grades of surrounding rock in TBM tunnels based on multifractal analysis theory. Initially, the statistical characteristics of eight TBM cycle data with different grades of surrounding rock were explored. Subsequently, the method of calculating and analyzing the multifractal characteristic parameters of the TBM operational data was deduced and summarized. The research results showed that the TBM operational parameters of cutterhead torque, total thrust, advance rate, and cutterhead rotation speed have significant multifractal characteristics. Its multifractal dimension, midpoint slope of the generalized fractal spectrum, and singularity strength range can be used to evaluate the surrounding rock grades of the tunnel. Finally, a novel classification model for the tunnel surrounding rocks based on the multifractal characteristic parameters was proposed using the multiple linear regression method, and the model was verified through four TBM cycle data containing different surrounding rock grades. The results showed that the proposed multifractal-based classification model for tunnel surrounding rocks has high accuracy and applicability. This study not only achieves multifractal feature representation and surrounding rock classification for TBM operational parameters but also holds the potential for adaptive adjustment of TBM operational parameters and automated tunneling applications.

Addendum to: Research on electromagnetic torque and fault parameter identification of pumped storage machine under power generation state based on optimized network parameter method

Addendum to: Research on electromagnetic torque and fault parameter identification of pumped storage machine under power generation state based on optimized network parameter method

Exploring the Effects of Different Torque and Speed Parameters on Smear Layer and Microcrack Formation in Apical Dentin of Root Canals with Single File Instrumentation

Exploring the Effects of Different Torque and Speed Parameters on Smear Layer and Microcrack Formation in Apical Dentin of Root Canals with Single File Instrumentation

Research on electromagnetic torque and fault parameter identification of pumped storage machine under power generation state based on optimized network parameter method

Because of the complex and frequent multi-operation conditions of pumped storage machine and the difficulty of its numerical analysis, an optimized network parameter method (ONPM) is given to identify the second harmonic electromagnetic torque of large salient-pole generators. Different from the former research which only considers the positive and negative sequence components, the second harmonic electromagnetic torque of pumped storage machine under power generation state is identified in neutral point grounded system, which are displayed by the lumped parameters. Then, in order to test the validity of the theoretical analysis among power generation salient-pole generators, the finite element model of 300 MVA pumped storage machine under power generation is established. Through the comparison and analysis of the finite element result data with the actual experimental data in the steady state of no-load test and short-circuit test, the correctness of the finite element model is completely verified. Finally, in the case of small current asymmetry and large current asymmetry, the second harmonic electromagnetic torques obtained by ONPM and finite element method (FEM) are found respectively, and their relative errors are elaborately displayed. The results display that ONPM can accurately identify the electromagnetic torque parameters which indicate the specific operation and fault state of pumped storage machine under power generation state. This fault parameter identification has practical significance for monitoring and improving the operation state and stability of large salient-pole generator.

A Simplified Power Regulation Strategy for Grid-tied PMSG-based Marine Current Turbine System in High-speed Marine Current Conditions

Marine current turbine systems (MCTSs) play a crucial role in harnessing renewable energy from ocean currents. These systems are designed with specific rated values of marine current speed, dictating their optimal operational parameters. However, the dynamic nature of marine currents can lead to fluctuations, occasionally exceeding the rated values for which these systems are designed. This poses significant challenges to the efficient and safe operation of MCTSs, necessitating the development of effective power regulation strategies. In response to these challenges, this paper presents a simplified power regulation strategy to address the complexities of high-speed marine current conditions. The strategy focuses on constraining the reference torque command, a pivotal parameter governing power generation within MCTS. By precisely managing the reference torque command, the strategy aims to ensure that power output remains within designated limits, thereby safeguarding the MCTS despite high-speed marine current conditions. The proposed strategy leverages a computational approach to determine the generator's reference torque command, utilizing key parameters such as the rated power of the MCT and the mechanical angular rotor speed. It facilitates seamless transition between unconstrained reference torque command (URTC) and constrained reference torque command (CRTC) modes, enabling precise power regulation. This flexibility empowers the MCTS to respond promptly to changes in marine current conditions, facilitating precise and responsive power regulation. To validate the effectiveness of the proposed strategy, the paper conducts a comprehensive analysis of MCTS performance across both URTC and CRTC modes utilizing Typhoon HIL604 real-time simulator. Through detailed examinations of MCT speed responses, generator torque, output power, and grid-side parameters, the study provides valuable insights into the dynamics of MCTS operation. This comprehensive understanding enhances the stability and adaptability of MCTSs across diverse operating conditions, thereby advancing their potential as a sustainable energy solution.

The Effect of Combining Blood Flow Restriction with the Nordic Hamstring Exercise on Hamstring Strength: Randomized Controlled Trial.

(1) Background: It is a matter of curiosity what effect the blood flow restriction (BFR) method, which is usually combined with low-intensity resistance exercises, will have when used with high-intensity eccentric exercises. (2) Methods: The present study examined the effects of combining BFR with nordic hamstring exercises (NHEs) on hamstring muscle strength, bilateral deficit (BLD), and training volume. Thirty young female volleyball players, who trained three times a week, participated voluntarily in the study. These players were stratified into three groups, each comprising ten individuals: a control group (CG), an NHE group, and an NHE + BFR group. Hamstring muscle strength and BLD values were determined using an H-BORD device, while training volume was measured in terms of sets and repetitions. (3) Results: Statistical analysis revealed that there were no statistically significant differences in non-dominant and dominant leg peak torque parameters in the exercise groups (F = 2.65; p = 0.097; ηp2 = 0.17; F = 1.15; p = 0.0334; ηp2 = 0.084), while the total training volume was lower in the NHE + BFR group. (4) Conclusions: As a result, it was seen that adding the BFR method to NHE did not provide additional gains. However, due to the low training volume of BFR + NHE, it may be recommended to apply BFR together with NHE to athlete groups.

Sensorless force estimation of teleoperation system based on multilayer depth Extreme Learning Machine

The force feedback technology has a crucial impact on the precise control of teleoperation system. Robots in fields such as minimally invasive surgery and nuclear waste cannot integrate force sensors to obtain force feedback due to their end size and harsh working environment. In order to obtain end-effector force feedback in sensorless situation, a sensorless force estimation model based on artificial neural network is defined in this paper. For improving the model prediction ability, a new Multi-layer Depth Extreme Learning Machine (MDELM) is proposed. Firstly, the network structure of the extreme learning machine is redesigned, and the smoothing function and Gauss-Laplacian function are constructed as the feature extraction layer and enhancement layer of the MDELM model. Then, to further improve the prediction performance of MDELM, an improved Sooty Tern Optimization Algorithm (STOA) is introduced to optimize the parameters of the model. The results show that the proposed force estimator outperforms the existing model with an MAE of less than 0.205, which is at least 18.65% lower than the existing model. In addition, when the acceleration of the remote operating system is a fixed constant or the information is not available，a sensorless force feedback system can be constructed by combining motor torque, joint position and joint velocity parameter. In general, this study provides an effective force estimation solution for teleoperation system without force sensor.

New Speed Control Scheme for a Three-Phase Induction Machines - (3~IM) Based on Sine Duty Cycle Modulation (SDCM)

This paper proposes a new control scheme for three-phase induction machines based on the sinusoidal duty cycle modulation control strategy combined with V/f control. This technique allows efficient open-loop control of inverter switches. The proposed diagram shows the main characteristics:1 0.1   ,0 50 ,Hzf 21.44 ,base KHzf  2 ,12ref V Vu  . In addition, it guarantees optimum operation of the inverter with the torque and speed parameters of the three-phase induction machine complying with current requirements:10rC Nmmax 6,5A/50Hz/ THD=1,2%

Prediction of cutterhead torque change trend of shield machine based on partial state visible HMM and LSTM

Cutterhead torque is a key parameter to determine the normal operation of shield machine. Accurately predicting the change trend of cutterhead torque can provide decision support for shield operators to control operating parameters. Therefore, a prediction method of cutterhead torque change trend based on partial state visible Hidden Markov Model (HMM) and Long Short-Term Memory (LSTM) network is proposed in this paper. First, the Spearman correlation coefficient is introduced to analyze the correlation of the tunneling parameters, and the historical tunneling data of the cutter torque, pitch angle and related parameters are obtained to establish a database. Secondly, the pitch angle prediction model is established based on LSTM network, and the predicted pitch angle is used as the observation sequence, and the implicit relationship between cutterhead torque and pitch angle is mined through HMM to obtain the probability matrix. Finally, the cutterhead torque prediction model is established, and the pitch angle sequence is used as input to output the corresponding cutterhead torque change trend. The results show that the method can accurately predict the dynamic change trend of the cutterhead torque in the case of less known parameter states, and the effectiveness of the method are verified in this paper.

State Estimation of Drive-by-Wire Chassis Vehicle Based on Dual Unscented Particle Filter Algorithm

Accurate vehicle dynamic information plays an important role in vehicle driving safety. However, due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles, the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation. This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm, which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle. In the dual unscented particle filter algorithm, two unscented particle filter transfer information to each other, observe the vehicle state information and the tire force parameter information of the four wheels respectively, which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving. The performance with the dual unscented particle filter algorithm, which is analyzed in terms of the time-average square error, is superior of the unscented Kalman filter algorithm. The effectiveness of the algorithm is further verified by driving simulator test. In this paper, a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.

Study on the Load Cell Utilization for Dynamic Torque Measurement in 3-Blade Savonius Wind Turbine Design

This paper presents the design and analysis of a Savonius wind turbine. Wind turbines harness wind energy to generate electricity, presenting a renewable and clean alternative to traditional power sources. This savonius wind turbine is a type of wind turbine that can rotate even at relatively low wind speeds, so it is necessary to develop a measuring instrument that has high accuracy and is affordable to evaluate the performance of this turbine. In this research, a load cell with an affordable price with a percentage error of approximately 15%, is used as a dynamic torque measurement tool on wind turbines, this torque parameter can be used as an important performance determinant of the wind turbine in generating power. This research was conducted in the Agricultural Machinery Workshop and Integrated Laboratoryy, University of Sumatera Utara, Medan from March to August 2022. The research is performed in several phases, which are 3D design, simulation, schematic design, prototype making, collecting actual data, analyzing actual data, and simulation data. The simulation results are compared with the actual data from the loadcell that has been tested, from the results of the comparison the accuracy value and deviation value of the instrument will be obtained.

An optimized particle swarm optimization algorithm for turbine torque and generator load parameter identification

Hydraulic turbine control system is a complex system with strong nonlinearity and multiple variables. Therefore, in order to better control the turbine system, it is necessary to obtain the parameters of key components. Aiming at the limitation of the traditional particle swarm optimization algorithm in global search ability, mutation operator and dynamic inertia weight coefficient are introduced to enhance the search ability of the algorithm. In addition, in order to further improve the global search performance of the algorithm, this paper combines the optimized particle swarm optimization algorithm with genetic algorithm to form a hybrid parameter identification algorithm. The hybrid algorithm not only uses the fast convergence of particle swarm optimization (PSO), but also uses the global search advantage of genetic algorithm (GA) to realize efficient and accurate identification of turbine torque and load parameters. Through MATLAB2021a/Simulink simulation experiments, the application effect of the algorithm in the identification of turbine torque and generator load parameters is verified. The simulation results show that the optimized particle swarm optimization algorithm has significant advantages in the accuracy and robustness of parameter identification, and the identified parameters have a high degree of fitting with the actual measured torque and speed. This study not only provides a new optimization strategy for the parameter identification of turbine regulation system, but also provides an effective intelligent algorithm solution for the parameter identification of nonlinear system.

Engine Start‐Up Torque Coordinated Control for Multimode Hybrid Electric Vehicle Equipped With a Two‐Speed Dedicated Hybrid Transmission

A multimode hybrid electric vehicle (HEV) equipped with a dedicated hybrid transmission (DHT) can be generally divided into pure electric mode with engine shutdown and hybrid mode with engine operation. Engine start‐stop control is the key to achieving a transition between these two modes. To address the issues of engine start‐up torque coordination control and torque interference, first, the start‐up requirements of DHT‐HEV engines in different driving scenarios are summarized, a multistage dynamic model for DHT‐HEV engine start‐up is established, and the key issues of engine start‐up torque coordination control are analyzed. Second, an engine start‐up torque coordinated control strategy with torque interference and parameter uncertainty is proposed, a robust model predictive controller (RMPC) is designed to adjust clutch pressure, a finite time disturbance observer (FTDO) is designed to obtain torque interference during the engine start‐up process, and a sliding mode observer (SMO) is designed to obtain vehicle driving resistance torque. Finally, a simulation and hardware‐in‐the‐loop (HIL) test are conducted to verify the performance of the relevant observers, torque coordination control, and interference compensation control during the engine start‐up process.

Effect of Diethyl Ether on Performance and Exhaust Gas Emissions of Heavy-Duty Diesel Engines Fueled with Biodiesel-Diesel Blend (B35)

To accelerate the energy transition, starting February 1, 2023, the Indonesian government has made it mandatory to use biodiesel (B35). Biodiesel has different characteristics from diesel oil, especially its greater viscosity and density, lower heating value, and high NOx emission. Therefore, this research has been carried out by adding the additive diethyl ether (DEE) to B35 to reduce the viscosity and density, increase the cetane number, and reduce emissions. The effects of diethyl ether on engine performances have been evaluated, including parameters of torque, power, brake thermal efficiency, brake-specific fuel consumption, exhaust emissions, and lubricants. The fuels used are B35 (35% FAME palm oil + 65% diesel oil), and B35 + DEE, with a DEE volume percentage of 3% to 6%. Diesel fuel (B0) was used as a comparison. Tests were carried out in the engine performance test laboratory using the heavy-duty diesel engine Komatsu SAA12V140E-3 at various engine speeds. The test results showed that adding diethyl ether slightly increases the average maximum power, increases brake thermal efficiency, and reduces brake-specific fuel consumption and emissions compared to B35. Very significant effects were seen in NOx and SO2 exhaust emissions. At maximum load, the mixture with 4% diethyl ether gave the greatest brake thermal efficiency, the lowest brake-specific fuel consumption, and the greatest reduction in NOx and SO2 emissions, respectively 7.69%, 6.30%, 53.48%, and 40.89% compared to B35, and 2.24%, (-0.90%), 48.88% and 71.17% compared to B0, respectively. Evaluation of lubricating oil during the performance test did not show a significant difference for all types of fuel used.

Designing tools for assessing the reliability of electric motor torque measurements by using identifiers of anomalous deviations in a noisy signal system

The problem of the reliability of measurements of rotational parameters of electric motors was solved, which was focused on the development of an algorithm for evaluating measurements under conditions of additional noise. An analysis of methodological approaches and mathematical tools used to process and interpret the uncertainty of measurement results was carried out. Cases where they may not be effective due to high noise levels were considered. To detect anomalies in the signal, an algorithm for assessing the reliability of measurements using fuzzy logic was proposed. A structural diagram of the model for measuring the torque of an electric motor under the conditions of a noisy signal was developed, where transfer functions were used to model the angular velocity and torque parameters. A method for detecting anomalies in noisy signals is presented, which identifies the amplitude and time characteristics of spiking pulses. The method includes the application of a wide range of analytical tools for deep analysis of signals and is particularly effective for detecting anomalies that may be hidden in background noise. A prototype of a measuring bench was developed, which uses neural networks to detect anomalies when measuring the rotational parameters of electric motors, which made it possible to obtain a training sample using a sample electric motor and apply it to evaluate the parameters of another electric motor. In a practical aspect, the developed methods and technological solutions for improving the reliability of measurements of rotational parameters of electric motors could be used to make corrections in existing systems. In particular, they could be used in industry, electric transport, as well as in the aerospace and military sectors where the reliability of measuring systems is important

Study of the Relationships among the Reverse Torque, Vibration, and Input Parameters of Mud Pumps in Riserless Mud Recovery Drilling

Compared with traditional deepwater drilling, riserless mud recovery (RMR) drilling technology has the advantages of improving drilling efficiency, reducing risks, and minimizing environmental effects. Therefore, RMR drilling technology has been widely applied in recent years. This study primarily investigates the relationships among reverse torque, vibration, and input parameters of mud pumps in riserless mud recovery drilling. Firstly, the operating principle and the structure of the mud pump module are analyzed, and an analytical model for the reverse torque and the vibration of the mud pump is established. Secondly, relevant data are derived from theoretical calculations and experiments, and the relationships among the reverse torque, vibration, and input parameters of the mud pump are analyzed using ANSYS (Version 2020 R1) software. Furthermore, the SVR (support vector regression) algorithm is employed to predict and analyze the amplitude of the mud pump’s vibration. Finally, the conclusions are drawn based on the findings of the relationships among the reverse torque, vibration, and input parameters of the mud pump. The findings show that the reverse torque of the mud pump increases approximately linearly with an increase in rotational speed, and the vibration of the mud pump increases and then decreases with an increase in rotational speed. The predicted values obtained through the prediction algorithm closely match the actual values. The findings provide a valuable reference for the application of RMR technology.

Predictive Torque Control of the Vehicle’s Permanent-Magnet Synchronous-Motor Model Based on Multi-Objective Sorting

The permanent-magnet synchronous motor (PMSM), with the advantages of low energy consumption and stable operation, is considered a green power source to replace gasoline engines. Motor control is the core problem of the electric-drive system, so it is important to study the high-performance motor control algorithm. The traditional PMSM control strategy has problems such as torque pulsation, large overshoot, and parameters which are not easy to adjust. This work proposes a new model-predictive torque control (MPTC) based on multi-objective ranking for these issues. The Romberg observer was utilized to accurately estimate motor flux and torque across a wide range of speeds and ensure optimal performance of the MPTC. The optional voltage vectors were classified using graph theory. The model’s cost function was optimized and the control delay caused by hardware processing was compensated by a modified Euler method. A multi-objective ranking method was used to avoid the offline selection of MPTC weight coefficients. Additionally, one ranking method was used to reduce the complexity of the algorithm for multiple objectives. Based on the simulation results, the newly proposed MPTC method, when compared with traditional approaches, reduced the total harmonic distortion from 2.78% to 2.26%. Torque ripple decreased by approximately 58.4%, and the switching frequency was reduced by 3.05%, lowering the inverter’s switching losses. Therefore, the newly proposed MPTC had faster torque response, reduced computation time, and less torque pulsation, which further improved the dynamic performance of the permanent-magnet synchronous motor.

Resistance training at different intensities promotes different adaptations on the parameters of torque–duration relationship in postmenopausal women

Resistance training at different intensities promotes different adaptations on the parameters of torque–duration relationship in postmenopausal women

Optimal design and control of permanent magnet assisted dual rotor motor

As high-performance motors, permanent magnet motors are widely used in a wide range of applications. It has become a consensus to mine reluctance torque in permanent magnet motors. The combination of permanent magnet motors and reluctance motors to generate higher output torque is one of the hotspots in motor research. A dual-rotor motor can be formed by connecting a coaxial connector or a concentric end disk, which can make the motor generate higher torque. However, although the motor torque has been improved, the cogging torque still affects the output torque of the motor. This paper describes a method to reduce the cogging torque of the permanent magnet rotor of the permanent magnet-assisted double rotor motor. By analyzing the motor power equation, it is concluded that the pole arc coefficient, the thickness of the magnetic steel, the length of the air gap, and the slot width of the stator have four influences on the teeth. For the parameters of the slot torque, the upper and lower limits of the parameter value are obtained according to the size of the motor. A certain parameter is taken as a fixed value, and the remaining parameters are uniformly valued. Use parametric scanning to determine the optimal value range of the parameter, and use Maxwell for parameterization. Simulation and analysis show that the cogging torque of the motor is reduced by 90% and the torque ripple is reduced by 50%. In order to simplify the motor control system, this paper designs a fuzzy controller based on granular functions, and the fuzzy rules of the fuzzy controller are to perform feature sampling and fit the response function, eliminating fuzzification and defuzzification, improving the response speed of fuzzy control, and simplifying the control system.