Time-varying Load Research Articles

Energy Consumption Prediction of Electric Construction Machinery Based on Condition Identification

Energy saving and emission reduction have become the consensus of global development. Electric construction machinery has drawn more and more attentions due to its zero emission and high efficiency. However, because of the installed capacity of the battery, the complex working conditions and the time-varying load of construction machinery, the working time of electric construction machinery is hard to estimate. It is important to accurately predict the remaining working time of the whole machine to ensure that the driver can reasonably arrange the operation time. In this paper, the electric loader is studied. To improve the estimation accuracy of the working time of electric loader, the typical working conditions are analyzed. The data of V-type working mode cycles of the actual experimental prototype are analyzed, which provides the basis for the segmentation of working conditions and the extraction of characteristic parameters. The fuzzy C-means clustering algorithm is used, an estimation method of operation energy consumption based on working condition identification is proposed. The results show that the energy consumption estimation method based on the motor average torque proposed in this paper has better estimation accuracy than the traditional estimation method based on the latest unit time energy consumption, which provides an idea for estimating the working time of electric loader and has certain practical significance.

Fracture mechanical investigation of preformed metal sheets using a novel CC-specimen

Joining is used in many areas of manufacturing where components are formed from individual parts or sheets into complex structures. A simple and common method applied in industry to join dissimilar and coated materials is clinching. This joining process does not require additional joining parts, which saves weight to reduce energy requirements and harmful emissions due to moving masses. In addition, the joining process is carried out without pre-punching and is therefore time-efficient. Damage caused by the joining process or by operational loading can lead to cracks near the joint, to crack propagation due to time-varying loading and subsequently to the complete failure of the component. To avoid these damage cases, knowledge about the fracture mechanical behavior of the clinched connection is required.Within the scope of this paper, a novel CC-specimen for fracture mechanical investigation of preformed metal sheets is developed and investigated. The new specimen geometry is taken directly from a clinched joint in order to identify a possible influence of the outer forming area of the joint on the fatigue crack growth rate. The clinched joint is placed at three different positions and is moved from the radius to the center of the C-shape at 3 mm intervals. In order to investigate the crack growth rate of this new specimen, it is necessary to numerically determine the geometry factor function for the stress intensity factor as well as the calibration curve for the crack length measurement with the direct current potential drop method beforehand. Finally, the results of the crack growth rate tests using the CC-specimen with different positions of the clinched joint are compared with the results of the base material.

Fatigue damage evolution using NDT techniques for Health Monitoring of CFRP laminates

In this work, an experimental method based on ultrasonic measurements with piezoelectric transducers (PZTs) was proposed for monitoring the evolution of fatigue damage on a batch of carbon fabric Open Hole specimens. The amplitudes of the recorded ultrasonic sinusoidal waves in packets were evaluated with pitch-catch modality during the different phases of the fatigue life and correlated to the applied loads.The examination of the ultrasonic data showed high sensitivity of the UT signal respect to stiffness decay and to fatigue damage associated with delamination near the hole. Occasional ultrasound measurements with the consolidated pulse-echo Phased Array technique were carried out by the authors at regular time intervals during the tests to evaluate the state of damage in relation to the degradation of the signal detected with the PZT sensors.The results have shown the potential capability of the applied experimental technique for real-time detection of delamination on composite elements subjected to time-varying loads.

A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation

The study of the behavior of smart distribution systems under increasingly dynamic operating conditions requires realistic and time-varying load profiles to run comprehensive and accurate simulations of power flow analysis, system state estimation and optimal control strategies. However, due to the limited availability of experimental data, synthetic load profiles with flexible duration and time resolution are often needed to this purpose. In this paper, a top-down stochastic model is proposed to generate an arbitrary amount of synthetic load profiles associated with different kinds of users exhibiting a common average daily pattern. The groups of users are identified through a preliminary Ward’s hierarchical clustering. For each cluster and each season of the year, a time-inhomogeneous Markov chain is built, and its parameters are estimated by using the available data. The states of the chain correspond to equiprobable intervals, which are then mapped to a time-varying power consumption range, depending on the statistical distribution of the load profiles at different times of the day. Such distributions are regarded as Gaussian Mixture Models (GMM). Compared with other top-down approaches reported in the scientific literature, the joint use of GMM models and time-inhomogeneous Markov chains is rather novel. Furthermore, it is flexible enough to be used in different contexts and with different temporal resolution, while keeping the number of states and the computational burden reasonable. The good agreement between synthetic and original load profiles in terms of both time series similarity and consistency of the respective probability density functions was validated by using three different data sets with different characteristics. In most cases, the median values of synthetic profiles’ mean and standard deviation differ from those of the original reference distributions by no more than ±10% both within a typical day of each season and within the population of a given cluster, although with some significant outliers.

Bending-torsional-axial-pendular nonlinear dynamic modeling and frequency response analysis of a marine double-helical gear drive system considering backlash

The double-helical gear system was widely used in ship transmission. In order to study the influence of backlash on the nonlinear frequency response characteristics of marine double-helical gear system, according to the structural characteristics of double-helical gear transmission, considering the time-varying meshing stiffness, backlash, damping, comprehensive transmission error, external load excitation, and other factors, a three-dimensional bending-torsional-axial-pendular coupling nonlinear dynamic modeling and dynamic differential equation of 24-DOF double-helical gear transmission system were established. The Runge–Kutta numerical method was used to analyze the influence of backlash, time-varying meshing stiffness, damping, error and external load excitation on the amplitude frequency characteristics. The results show that the backlash can cause the runout of the double-helical gear system, and the system has first harmonic and second harmonic response. With the increase of backlash, the amplitude of the system increases and the jumping phenomenon remains unchanged. The amplitude frequency response of the system is stimulated by time-varying meshing stiffness and comprehensive transmission error, and restrained by damping and external load excitation. The vibration displacement amplitude of the system increases with the increase of vibration displacement and has little effect on the state change of the system. The vibration test of double-helical gear is carried out. The frequency response components obtained by numerical simulation are basically consistent with the experimental results, which proves the correctness of the theoretical calculation. It provides a technical basis for the study of vibration and noise reduction performance of double-helical gear.

MRAS-based current estimator for DC–DC converters considering time-variant load impedance

MRAS-based current estimator for DC–DC converters considering time-variant load impedance

Coupled consolidation via vertical drains in unsaturated soils induced by time-varying loading based on continuous permeable boundary

Considering continuous permeable boundary and coupled radial-vertical flow in this paper, a generalized semi-analytical solution for the consolidation enhanced by vertical drains (VDs) in unsaturated soils under time-varying loading is proposed. Firstly, the continuous permeable boundary is introduced into the axisymmetric consolidation model. Afterwards, the coupled controlling governing equations of excess pore pressures (EPPs) are solved by mathematical methods such as the decoupling technology, the Laplace transformation and inversion. Then, the validity of the current solution is verified by special cases with double-permeable boundary conditions (BCs) and instantaneous loading. The case analyses eventually were carried out, and the results show that the smear effects slow down the consolidation process but that is not obvious when the smear parameter is great than five. The effect of vertical flow on consolidation becomes insignificant when the ratio of radial to vertical permeability coefficient is greater than five; conversely, when its value is less than five, the above effect increases with the enhancement of the permeability properties at the top (or bottom) boundary. Moreover, the new solution can be applied to time-varying loadings, and different distributions of top and bottom boundary permeability.

Predominant airborne transmission and insignificant fomite transmission of SARS-CoV-2 in a two-bus COVID-19 outbreak originating from the same pre-symptomatic index case

The number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to increase worldwide, but despite extensive research, there remains significant uncertainty about the predominant routes of SARS-CoV-2 transmission. We conducted a mechanistic modeling and calculated the exposure dose and infection risk of each passenger in a two-bus COVID-19 outbreak in Hunan province, China. This outbreak originated from a single pre-symptomatic index case. Some human behavioral data related to exposure including boarding and alighting time of some passengers and seating position and mask wearing of all passengers were obtained from the available closed-circuit television images/clips and/or questionnaire survey. Least-squares fitting was performed to explore the effect of effective viral load on transmission risk, and the most likely quanta generation rate was also estimated. This study reveals the leading role of airborne SARS-CoV-2 transmission and negligible role of fomite transmission in a poorly ventilated indoor environment, highlighting the need for more targeted interventions in such environments. The quanta generation rate of the index case differed by a factor of 1.8 on the two buses and transmission occurred in the afternoon of the same day, indicating a time-varying effective viral load within a short period of five hours.

DeepCC: Multi-Agent Deep Reinforcement Learning Congestion Control for Multi-Path TCP Based on Self-Attention

With the development of the Internet of Things (IoT) and 5G, there are ubiquitous smart devices and network functions providing emerging network services efficiently and optimally through building many network connections based on WiFi, LTE/5G, Ethernet, and etc. The Multipath TCP (MPTCP) protocol that enables these devices to establish multiple paths for simultaneous data transmission, has been a widely used extension of standard TCP in smart devices and network functions. On the other hand, more heavy and time-varying traffic loads are generated in an MPTCP network, so that an efficient congestion control mechanism that schedules the traffic between multiple subflows and avoids congestion is highly required. In this paper, we propose a decentralized learning approach, DeepCC, to adapt to the volatile environments and realize the efficient congestion control. The Multi-Agent Deep Reinforcement Learning (MADRL) is used to learn a policy of congestion control for each subflow according to the real-time network states. To deal with the problem of the fixed state space and slow convergence, we adopt two self-attention mechanisms to receive the states and train the policy, respectively. Due to the asynchronous design of DeepCC, the learning process will not introduce extra delay and overhead on the decision-making process. Experiment results show that DeepCC consistently outperforms the well-known heuristic method and DRL-based MPTCP congestion control method in terms of goodput and jitter. Besides, DeepCC with the attention mechanism reduces convergence time by about 50% and increase goodput by about 80% compared with the commonly used structures of neural networks.

Adaptive finite-time control for quadrotor UAV with time-varying load based on disturbance observer

Adaptive finite-time control for quadrotor UAV with time-varying load based on disturbance observer

The competitions of time-varying and constant loadings in asset pricing models: empirical evidence and agent-based simulations

The competitions of time-varying and constant loadings in asset pricing models: empirical evidence and agent-based simulations

Review on Reactive Power and Voltage Optimization of Active Distribution Network with Renewable Distributed Generation and Time-Varying Loads

With a high proportion of renewable distributed generation and time-varying load connected to the distribution network, great challenges have appeared in the reactive power optimization control of the active distribution networks. This paper first introduces the characteristics of active distribution networks, the mechanism and research status of wind power, photovoltaic, and other renewable distributed generators, and time-varying loads participating in reactive power and voltage optimization. Then, the paper summarizes the methods of reactive power optimization and voltage regulation of active distribution network, including multi-timescale voltage optimization, coordinated optimization of network reconfiguration and reactive power optimization, coordinated optimization of active and reactive power optimization based on model predictive control, hierarchical and zoning control of reactive power, and voltage and power electronic switch voltage regulation. The pros and cons of the reactive power optimization algorithms mentioned above are summarized. Finally, combined with the development trend of the energy Internet, the future directions of reactive power and voltage control technology in the active distribution network are discussed.

Design of a variable-gain adjacent cross-coupled controller for coordinated motion of multiple permanent magnet linear synchronous motors

Coordination position control of multi-motors systems is widely applied in agricultural and industrial fields that require high precision and synchronization among motors. Current adjacent cross-coupled control is unable to change the control gains as motor states are time-variant. The invariant gain compensation will inevitably weaken the coordinated control performance, especially in the presence of load disturbances. To solve this issue, this paper proposes a variable-gain adjacent cross-coupled controller. A sliding mode controller is adopted to cope with the disturbances and uncertainties for each single permanent magnet linear synchronous motor (PMLSM). The motor state of each PMLSM can be detected through system identification in real time. According to the motor states of the PMLSMs based on the system identification technique, a fuzzy position control algorithm is implemented for regulating the gain compensation. A consistent steady-state performance is subsequently maintained even with the existence of system uncertainties and load disturbances. It is proved from the experimental results that, compared with fixed-gain adjacent cross-coupled control scheme, the proposed controller has a better synchronization, a higher tracking accuracy and synergistic accuracy, under both no load and time-varying load conditions. For the variable-gain adjacent cross-coupled control, a position tracking error and a synergistic error within 7 μm and 8 μm can be achieved, respectively.

Robust output regulation for voltage control in DC networks with time-varying loads

In this paper, we propose novel control schemes for regulating the voltage in Direct Current (DC) power networks, where the loads are the superposition of time-varying signals and uncertain constants. More precisely, the proposed control schemes are based on the robust output regulation methodology and, differently from the results in the literature, where the loads are assumed to be constant, we consider time-varying loads whose dynamics are described by a class of differential equations with parametric uncertainty. The proposed control schemes achieve voltage regulation and guarantee the local robust stability of the overall network in case of impedance (Z), current (I), and power (P) load types and the global robust stability in case of ZI loads. The simulation results illustrate excellent performance of the proposed control schemes in different scenarios, where real load data are considered.

Bridge Resistance Updating Based on the General Particle Simulation Algorithms of Complex Bayesian Formulas

The existing bridges are subjected to time-variant loading and resistance degradation processes. How to update resistance probability distribution functions with resistance degradation model and proof load effects has become one of the research hotspots in bridge engineering field. To solve with the above issue, this paper proposed the general particle simulation algorithms of complex Bayesian formulas for bridge resistance updating. Firstly, the complex Bayesian formulas for updating resistance probability model are built. For overcoming the difficulty for the analytic calculation of complex Bayesian formulas, the general particle simulation methods are provided to obtain the particles of complex Bayesian formulas; then, with the improved expectation maximization optimization algorithm obtained with the combination of K-MEANS algorithm and Expectation Maximization (EM) algorithm, the above simulated particles can be used to estimate the posteriori probability density functions of resistance probability model; finally, a numerical example is provided to illustrate the feasibility and application of the proposed algorithms.

Effect of variable axial load on seismic behaviour of reinforced concrete columns

This study investigated the effect of variable axial loads (time-varying axial loads) on the seismic performance and failure mechanism of reinforced concrete (RC) columns with different constraints at the top. The contribution of horizontal and vertical ground motions to the variation in the axial force was revealed by evaluating the axial forces on the RC frame columns and bridge piers under the action of near-fault ground motions. The variation law of the axial force was arrived at using the fast Fourier transform (FFT). Based on previous experiments, 30 cases were designed to discuss the effect of various parameters, namely amplitude, frequency and phase of the variable axial load on the seismic performance of the column. The hysteresis behaviour of specimens under different variable axial loads in terms of hysteresis loops, skeleton curves, stiffness degradations, and energy dissipations were analysed. The results indicated that the frequencies of the variable axial load and lateral displacement of the RC column were constants related to the characteristics of the structure. In addition, variable axial loads were detrimental to the seismic performance of the RC columns, especially those with a large amplitude variation, high frequency, and an identical phase as the lateral drift. It is unsafe to design or evaluate the column based on a constant axial load. Furthermore, constraints at the top of the column strengthened the effect of the variable axial load on the seismic performance of the column, and this resulted in an opposite influence rule of the variable axial load.

Adaptive altitude flight control of quadcopter under ground effect and time-varying load: theory and experiments

In recent years, the boom of the quadcopter industry resulted in a broad range of real-world applications which highlighted the urgent need to improve quadcopter control quality. Typically, external disturbances, such as wind, parameter uncertainties caused by payload variations, or the ground effect, can severely degrade the quadcopter’s altitude control performance. Meanwhile, widely used controllers like the proportional-integral-derivative control cannot guarantee control performance when the system is critically affected by factors that exhibit a high degree of variability with time. In this paper, an adaptive control algorithm is proposed to improve quadcopter altitude tracking performance in the presence of both the ground effect and a time-varying payload. First, we derive an adaptive altitude control algorithm using the sliding mode control technique to account for these uncertainties in the quadcopter dynamics model. Second, we apply Lyapunov theory to analyze the stability of the closed-loop system. Finally, we conduct several numerical simulations and experiments to validate the effectiveness of the proposed method.

Track Model with Nonlinear Elastic Characteristic of the Rubber Rail Pad

This paper presents a new basic nonlinear track model consisting of an infinite Euler-Bernoulli beam (rail) resting on continuous foundation with two elastic layers (rail pad and ballast bed) and intermediate inertial layer (sleepers). The two elastic layers have bilinear elastic characteristic obtained from the load-displacement characteristic of the rail pad and ballast. A time-varying load with two components - time-constant one and harmonic other, representing the wheel/rail contact force is considered as the track model input. Rail deflection due to the time-constant component of the load is obtained solving the nonlinear equations of the balance position. Subsequently, the structure of the nonhomogeneous foundation is determined. Dynamic rail response in terms of receptance due to the harmonic component of the load is calculated using the linearised track model with nonhomogeneous elastic characteristic. Influence of the time-constant component and the reflected waves due to the nonhomogeneous foundation are presented.

Dynamic analysis and vibration reduction of mechanical-hydraulic coupled tunnel boring machine (TBM) main drive system

Tunnel Boring Machine always works in the changeable geologies with multiple drivers, which leads to severe vibration of the TBM main drive system and key component failures. The vibration characteristics of TBM under different working conditions and the vibration reduction analysis have important meanings. First of all, by considering the time-varying random loads of the cutters, the contact force of the gears, the stiffness of the main bearing, and the stiffness of the cylinders, a mechanical-hydraulic coupling nonlinear dynamic model of the TBM main drive system was built according to the assembly relationship and load transmission path of the main drive system. Secondly, the dynamic model of the TBM main drive system is verified by comparing the theoretical vibration with the real vibration of the TBM main drive system. The error of the vibration acceleration is 10% to 30%. Three typical loads are defined under typical working conditions, and the vibrations of the TBM main drive system under three typical loads were analyzed. Finally, the sensitivity analysis of the cylinder damping shows that the damping at the position of the propulsion cylinder has a great influence on the vibration of the TBM main drive system. The results show that when the damping coefficient is 2.5 × 106 N·s/m, the maximum reduction of axial acceleration of cutterhead is 0.64 g, and that of the main beam front section is 0.55 g. The variable damping coefficient vibration reduction strategies under three typical loads are verified.

Dynamic Modeling and Vibration Characteristics Analysis of Deep-Groove Ball Bearing, Considering Sliding Effect

To study the vibration characteristics of deep-groove ball bearing, considering the influence of sliding, the dynamic model of the DGB 6205 system is established in this paper. The DGB 6205 system model includes the movement of the bearing inner ring in the X and Y directions, the rotation of the cage, the rotation movement of each ball, the revolution movement of each ball and the movement along the radial direction of each ball. Based on the system model, the differential equations of motion of the system are established, and the correctness of the model is verified by experiment. The slip characteristics of the DGB 6205 system are studied by numerical simulation. At the same time, the influence of time-varying load on the vibration characteristics of the system is studied. Then, the sensitivity of system parameters is analyzed. The results show that the sliding speed between the ball and the inner raceway is greater than that between the ball and the outer raceway. The radial vibration response of DGB 6205 system under time-varying load is less than that under constant load. The increase of radial clearance will increase the vibration response of DGB 6205 system.