Input Force Research Articles

Sequential Bayesian estimation of state and input in dynamical systems using output-only measurements

• A sequential Bayesian method is proposed for estimating the state and input forces. • Covariance matrices of the process and measurement noise are updated sequentially. • Estimations of the state and input have decent accuracy and stability. • Low-frequency drift appearing in estimations of the input and state is eliminated. The problem of joint estimation of the state and input in linear time-invariant dynamical systems is revisited proposing novel sequential Bayesian formulations. An appealing feature of the proposed method is the promise it delivers for updating the covariance matrices of the process and measurement noise in a real-time fashion using asymptotic approximations. The proposed method avoids the direct transmission of the input into predictions of the state using a zero-mean Gaussian distribution for the input. This prior distribution aims to eliminate low-frequency drifts from estimations of the state and input. Moreover, the method is outlined in a computational algorithm offering real-time estimations of the state and input forces. Numerical and experimental examples are used to examine and demonstrate the efficacy of the method. It is observed that the proposed method achieves decent accuracy for estimating the state, input forces, and noise covariance matrices when compared to the actual values. Contrary to the present methods that produce significant low-frequency drifts while using noisy acceleration response-only measurements, the proposed method offers drift-free perfect predictions. This Bayesian filtering-technique proposed for the reconstruction of the state and input forces can next be employed in the emerging fatigue prognosis frameworks.

Continuous scavenging of broadband vibrations via omnipotent tandem triboelectric nanogenerators with cascade impact structure

Ambient vibration energy is highly irregular in force and frequency. Triboelectric nanogenerators (TENG) can convert ambient mechanical energy into useable electricity. In order to effectively convert irregular ambient vibrations into electricity, the TENG should be capable of reliably continuous operation despite variability in input forces and frequencies. In this study, we propose a tandem triboelectric nanogenerator with cascade impact structure (CIT-TENG) for continuously scavenging input vibrations with broadband frequencies. Based on resonance theory, four TENGs were explicitly designed to operate in tandem and cover a targeted frequency range of 0–40 Hz. However, due to the cascade impact structure of CIT-TENG, each TENG could produce output even under non-resonant conditions. We systematically studied the cascade impact dynamics of the CIT-TENG using finite element simulations and experiments to show how it enables continuous scavenging from 0–40 Hz even under low input accelerations of 0.2 G–0.5 G m/s2. Finally, we demonstrated that the CIT-TENG could not only scavenge broadband vibrations from a single source such as a car dashboard, but it could also scavenge very low frequency vibrations from water waves and very high frequency vibrations from air compressor machines. Thus, we showed that the CIT-TENG can be used in multiple applications without any need for redesign validating its use as an omnipotent vibration energy scavenger.

Agricultural Sustainable Development and Economic Stability in Northeast China under Climate Change

At present, a sustainable agricultural development is extremely important for economic backwardness in the northeast of China to stabilize local economy and prevent economic disaster. The paper is constructing an economic climate model of northeast region, the inspection result of this model represents: climate warming, drought, and extreme climate bring significant negative effect towards cereal output in northeast region; and this paper also represents the analysis results that the price, labor force, capital and technology inputs have a positive effect on cereal output. Recognizing these impacts correctly and taking active measures will be favorable to ensure a sustainable development and regional economic stability of the northeast region.

Design of a Novel Piezoelectric Energy Harvester Based on Integrated Multistage Force Amplification Frame

This paper proposes a novel integrated multistage energy harvester to scavenge the mechanical energy from human footstep during walking. The device involves a four-stage force amplification using wedge mechanism, leverage mechanism, half-bridge mechanism, and bridge-type force amplifier. It is devised to magnify the input force exerted on a piezoelectric stack so as to enhance the power output. By fully exploiting the characteristics of the force amplification frame, the harvester also provides the function of position protection, which enables the bearing of large load and thereby protecting the piezoelectric stack. By this, the maximum displacement input is restricted to a certain range to ensure the walking comfort. A static analytical model of the energy harvester is established through the force analysis based on the stiffness matrix method. The main architectural parameters of the device are optimized by adopting a multiobjective genetic algorithm with ANSYS software. Moreover, a prototype is fabricated for experimental investigation. Experimental results show that the harvester exhibits a large force amplification ratio of 17.9 and high-peak power output of 50.8 mW across a matched resistor.

Shear stress-induced nuclear shrinkage through activation of Piezo1 channels in epithelial cells.

The cell nucleus responds to mechanical cues with changes in size, morphology and motility. Previous work has shown that external forces couple to nuclei through the cytoskeleton network, but we show here that changes in nuclear shape can be driven solely by calcium levels. Fluid shear stress applied to MDCK cells caused the nuclei to shrink through a Ca2+-dependent signaling pathway. Inhibiting mechanosensitive Piezo1 channels through treatment with GsMTx4 prevented nuclear shrinkage. Piezo1 knockdown also significantly reduced the nuclear shrinkage. Activation of Piezo1 with the agonist Yoda1 caused similar nucleus shrinkage in cells not exposed to shear stress. These results demonstrate that the Piezo1 channel is a key element for transmitting shear force input to nuclei. To ascertain the relative contribution of Ca2+ to cytoskeleton perturbation, we examined F-actin reorganization under shear stress and static conditions, and showed that reorganization of the cytoskeleton is not necessary for nuclear shrinkage. These results emphasize the role of the mechanosensitive channels as primary transducers in force transmission to the nucleus.

Contact-implicit trajectory optimization using variational integrators

Contact constraints arise naturally in many robot planning problems. In recent years, a variety of contact-implicit trajectory optimization algorithms have been developed that avoid the pitfalls of mode pre-specification by simultaneously optimizing state, input, and contact force trajectories. However, their reliance on first-order integrators leads to a linear tradeoff between optimization problem size and plan accuracy. To address this limitation, we propose a new family of trajectory optimization algorithms that leverage ideas from discrete variational mechanics to derive higher-order generalizations of the classic time-stepping method of Stewart and Trinkle. By using these dynamics formulations as constraints in direct trajectory optimization algorithms, it is possible to perform contact-implicit trajectory optimization with significantly higher accuracy. For concreteness, we derive a second-order method and evaluate it using several simulated rigid-body systems, including an underactuated biped and a quadruped. In addition, we use this second-order method to plan locomotion trajectories for a complex quadrupedal microrobot. The planned trajectories are evaluated on the physical platform and result in a number of performance improvements.

Modeling, online identification, and compensation control of single tendon sheath system with time-varying configuration

• The transmission models of single TSS with arbitrary route configurations are developed. • A tendon-sheath-based bending sensor is proposed for online parameter identification. • Two compensation strategies are developed to enhance the control accuracy of TSS without distal feedback. • The effectiveness is validated by trajectory tracking and frequency response experiments. Tendon sheath system (TSS) has been widely used in many applications with strict spatial limitations due to its flexibility, dexterity, and remote transmission ability. However, the inherent configuration-dependent nonlinearities between tendon and sheath seriously degrade the transmission performance and result in inaccurate force and position control. In this paper, the force and position transmission models of single TSS with arbitrary route configurations and terminal loads are developed based on the analysis of system friction and deformation. A tendon-sheath-based bending sensor is proposed for the online identification of accumulated bending angle. To enhance the accuracies of force control and position control with time-varying configuration, two control strategies are developed for the friction and deformation compensation without sensory feedback from distal end. An experimental setup of tendon sheath actuation is established to gain insights into the force and position transmission processes and evaluate the effectiveness of the developed transmission models and compensation controllers. The results of model validation experiments with sinusoidal force input show that the modeling errors of force and position transmission are less than 5% and 2.5%, respectively. Moreover, the trajectory tracking experiments and frequency response experiments are carried out, and the results demonstrate the feasibility of the proposed identification strategy and compensation controllers in improving control accuracy and ensuring control bandwidth of single TSS with time-varying bending angle.

On an equivalent model of multi-layer piezoelectric actuators for facilitating finite element simulations

Multi-layer piezoelectric actuators (MPA) are widely used precision actuators. For design and optimization of MPA-based applications with a complex structure, finite element method, which can achieve a high computation accuracy, is widely applied in finite element analysis software for computation and analysis. However, MPA are commonly made of hundreds of thin piezo layers and the piezoelectric material involves electro-mechanical coupled fields, which makes it cumbersome to directly implement them in finite element analysis software and hard to solve. In this paper, it is shown that the multi-layer and electro-mechanical coupled-field MPA can be simply considered as a homogeneous mechanical solid with a pair of equivalent forces acting on the two ends. This equivalent model can greatly facilitate the implementation of MPA in finite element analysis software and cut down computational cost for design and optimization of MPA-based applications. The rationale behind the equivalent model is unveiled and the equivalent force input is derived with respect to voltage input in terms of the standard 3D piezoelectric coefficients. The effectiveness of the equivalent model is further verified by conventional model of MPA via FE simulations in ANSYS.

Remote acoustic detection of cuts in a vibrating plate with stochastic input forcing in a reverberant environment.

A mechanical structure subject to vibratory forcing will often radiate sound. When remotely recorded, this sound depends on the vibratory forcing, the structure's frequency response function, and the structure-to-receiver acoustic propagation. Thus, successful remote acoustic detection of changes in a structure's vibration response between baseline and subsequent test recordings may require compensation for possible baseline-to-test changes in vibratory forcing and acoustic propagation. Compensation schemes for unknown structural forcing in an unknown reverberant environment that allow such remote detection are described here and found to be successful when the random forcing has a consistent power spectrum and the structure-radiated sound is recorded with an array of receivers. In particular, experimental results are presented for remote acoustic detection of 13-76 mm cuts in a vibrating 0.30-m-square by 3-mm-thick edge-clamped aluminum plate subject to 0.1-2 kHz base excitation in a reverberant laboratory. Radiated sound from the plate is recorded remotely with a 15-element microphone array and processed with the synthetic time reversal blind deconvolution algorithm to compensate for unknown reverberation. Cut detection success is compared for frequency-sweep and random-input forcing when this forcing is known and unknown, and when there are plate-to-array geometric changes between the baseline and test measurements.

An Automatic MEMS Gyroscope Mode Matching Circuit Based on Noise Observation

The performance of microelectromechanical system (MEMS) gyroscopes can be significantly enhanced by matching the resonance frequencies of the drive and sense mechanical resonators. However, the precise control of the resonance frequency in a closed loop readout circuit is challenging. This brief presents an automatic detection and control circuit, which performs a background tuning of the MEMS element. The tuning method is based on the observation of noise at the output of a continuous time ${\Delta \Sigma }$ modulator readout circuit, so that no modification of the sense loop, such as additional input force generation is required. Parasitic modulation of the sensor’s zero rate output due to the mode matching loop is canceled by an additional offset compensation circuit. The system is validated on an FPGA connected to a MEMS gyroscope and an ASIC readout circuit. The digital mode matching circuit would consume a power of ${21}~{\mu }\text{W}$ on an area of 0.17 mm2 in a ${0.35}~{\mu } \text {m}$ CMOS technology.

ОПРЕДЕЛЕНИЕ ПАРАМЕТРОВ ЖИВУЧЕСТИ ЗАЩИЩЕННЫХ ОТВЕТСТВЕННЫХ СТРОИТЕЛЬНЫХ КОНСТРУКЦИЙ ПРИ УДАРНО-ВОЛНОВОМ НАГРУЖЕНИИ

Актуальность работы связана с тенденцией возникновения чрезвычайных ситуаций аварийного характера на предприятиях нефтегазовой промышленности. В связи с чем необходимо проектировать железобетонные конструкций, на которые возможно воздействие интенсивных кратковременных динамических нагрузок аварийного типа, носящих ударно-волновой характер. Учет реакции распора при проектировании позволяет выявить скрытые запасы несущей способности в изгибаемых железобетонных конструкциях, а также снизить трещинообразование, за счет увеличения жесткости. Эффективным способом снижения величины динамического воздействия является применение податливых опор в виде сминаемых вставок кольцевого сечения. Таким образом, совместное применение податливых опор и учет реакции распора дает возможность предотвратить повреждения, полное или частичное разрушение конструкций. Кроме того, повреждения строительных конструкций ответственных зданий и сооружений нефтегазового комплекса приводят к остановке технологического процесса, что в ряде случаев не только экономически не выгодно, но и недопустимо, а также может привести к значительному материальному ущербу и гибели людей. Цель: разработать методику и алгоритм построения энергетической диаграммы, выполнить числовую оценку применения податливых опор на живучесть защищенных строительных конструкций при интенсивном нагружении Методы: экспериментальные исследования: реакция входного силового воздействия, реакция выходного силового воздействия, ускорения, перемещения методами тензометрии, численное интегрирование методом Симпсона. Результаты. Разработана методика и алгоритм построения усредненной энергетической диаграммы. Выполнена числовая оценка применения податливых опор на живучесть защищенных строительных конструкций сооружений нефтегазового комплекса при кратковременном динамическом нагружении.

High precision laser macrodrilling of carbon fiber reinforced plastics with a new nanosecond pulsed laser—Optimized toward industrial needs

Due to their outstanding strength-to-weight ratio, carbon fiber reinforced plastics (CFRP) are of high interest for lightweight construction. Within industrial fields requiring lightweight design and energy efficiency, the demand for CFRP increases continuously. Until now, machining of CFRP, as a crucial step in the production chain of composite parts, is mainly performed by conventional techniques such as drilling, milling, and abrasive water jet cutting. These techniques come with known drawbacks, including force input, handling of auxiliaries, and tool wear. The laser cutting of CFRP has already shown its high potential to be a practical alternative due to wear-free and contactless processing. However, if sufficient cutting rates are required, laser cutting has to overcome the challenge of either nonorthogonal cutting edges when using short pulsed high power lasers or heat input into the material when using continuously emitting (continuous wave) high power singlemode laser sources, as shown by Staehr et al. [J. Laser Appl. 28, 022203 (2016)]. Within this investigation, the machining with a novel short pulsed high power laser source by Trumpf Laser GmbH emitting at λ = 1030 nm will be examined. The lab-state laser source provides nanosecond pulses at tp = 20 ns, at a maximum pulse energy of Ep = 100 mJ, and a maximum average power of Pavg = 1.5 kW, while maintaining a very good beam quality allowing for small focus diameters down to df = 84 μm with the focusing optics used. It was shown that processing with small focus diameters results in narrow cutting kerfs contributing to the cutting edge angle. In addition, the investigations revealed a minimized thermal load resulting from the short pulses. At the same time, challenges resulting from shielding effects when specific parameters are used will be displayed and discussed. Different processing strategies for adjusting the cutting edge angle toward orthogonality will be presented in this paper. This optimization procedure aims at the drilling of macroscopic holes with a diameter of Ø > 4 mm in CFRP laminates with a thickness of s ≥ 2 mm at very high precision.

A Gaussian process latent force model for joint input-state estimation in linear structural systems

The problem of combined state and input estimation of linear structural systems based on measured responses and a priori knowledge of structural model is considered. A novel methodology using Gaussian process latent force models is proposed to tackle the problem in a stochastic setting. Gaussian process latent force models (GPLFMs) are hybrid models that combine differential equations representing a physical system with data-driven non-parametric Gaussian process models. In this work, the unknown input forces acting on a structure are modelled as Gaussian processes with some chosen covariance functions which are combined with the mechanistic differential equation representing the structure to construct a GPLFM. The GPLFM is then conveniently formulated as an augmented stochastic state-space model with additional states representing the latent force components, and the joint input and state inference of the resulting model is implemented using Kalman filter. The augmented state-space model of GPLFM is shown as a generalization of the class of input-augmented state-space models, is proven observable, and is robust compared to conventional augmented formulations in terms of numerical stability. The hyperparameters governing the covariance functions are estimated using maximum likelihood optimization based on the observed data, thus overcoming the need for manual tuning of the hyperparameters by trial-and-error. To assess the performance of the proposed GPLFM method, several cases of state and input estimation are demonstrated using numerical simulations on a 10-dof shear building and a 76-storey ASCE benchmark office tower. Results obtained indicate the superior performance of the proposed approach over conventional Kalman filter based approaches.

Nonlinearity and amplification in cochlear responses to single and multi-tone stimuli

Mechanical displacements of the basilar membrane (BM) and the electrophysiological responses of the auditory outer hair cells (OHCs) are key components of the frequency tuning and cochlear amplification in the mammalian cochlea. In the work presented here, we measured the responses of (1) the extracellular voltage generated by OHCs (VOHC) and (2) displacements within the organ of Corti complex (OCC) to a multi-tone stimulus, and to single tones. Using optical coherence tomography (OCT), we were able to measure displacements of different layers in the OCC simultaneously, in the base of the gerbil cochlea. We explored the effect of the two types of sound stimuli to the nonlinear behavior of voltage and displacement in two frequency regions: a frequency region below the BM nonlinearity (sub-BF region: f < ∼0.7 BF), and in the best frequency (BF) region. In the sub-BF region, BM motion (XBM) had linear growth for both stimulus types, and the motion in the OHC region (XOHC) was mildly nonlinear for single tones, and relatively strongly nonlinear for multi-tones. Sub-BF, the nonlinear character of VOHC was similar to that of XOHC. In the BF region XBM, VOHC and XOHC all possessed the now-classic nonlinearity of the BF peak. Coupling these observations with previous findings on phasing between OHC force and traveling wave motions, we propose the following framework for cochlear nonlinearity: The BF-region nonlinearity is an amplifying nonlinearity, in which OHC forces input power into the traveling wave, allowing it to travel further apical to the region where it peaks. The sub-BF nonlinearity is a non-amplifying nonlinearity; it represents OHC electromotility, and saturates due to OHC current saturation, but the OHC forces do not possess the proper phasing to feed power into the traveling wave.

A Motion Transmission Model for a Class of Tendon-Based Mechanisms With Application to Position Tracking of the da Vinci Instrument

Tendon-based motion/force transmission is a conventional approach in the design of surgical robots. However, due to compliance in the tendons and significant frictions between the tendons, the pulleys, and the sheath, tendon-based systems exhibit highly nonlinear behavior that, in particular, includes hysteresis. In this paper, based on the concepts of creep theory in belt drive mechanics, a novel motion transmission model is developed for tendon-pulley mechanisms. The developed model is of pseudokinematic type; specifically, it relates the output displacement to both the input displacement and the input force. The model parameters are identified for a da Vinci instrument, and the model performance is experimentally evaluated. The experimental results demonstrate greater than 50% improvement in terms of root-mean-square position error as compared to a more conventional friction/compliance-free kinematic model. The model is subsequently used for position control of the tip of the instrument, resulting in elimination of the hysteresis and in accurate trajectory tracking.

The effect of CO2 emissions and economic performance on hydrogen-based renewable production in 35 European Countries

This study applies the OLS and panel data approach to estimate the influence of variables such as greenhouse gas emissions, per capita income, the scale of labor force input, the portion of added value in manufacturing industry and government mechanism on hydrogen-based renewable production in 35 European countries. The empirical results show that the nation's economic input and its income level have a positive effect on hydrogen-based renewable energy, which indicated that the economic growth has promoted living standards, inspired environmental awareness, and influenced the use of alternative energy and renewable energy. Moreover, the empirical results also show that deepening democracy (government mechanism) has a positive impact on hydrogen-based renewable energy in OECD countries, but the impact on non-OECD countries is not clear.

Derivation of road noise improvement factor within a suspension system using the inverse substructuring method

This research aims to develop a method to efficiently reduce the body input force from the chassis due to road-induced excitation. To this end, the frequency response function–based substructuring method is employed to model the vehicle cross member and coupling points. Using this model, the dynamic stiffness modification factor of elastic bushing at the effective path is predicted for reducing road noise. Because of the difficulties in directly obtaining dynamic properties of body mount bushings pressured into the sub-frame, the frequency response function–based substructuring model and inverse formulation method are used to indirectly estimate the bushing’s dynamic properties. Therefore, the primary focus of this study is to validate the feasibility of using the inverse formulation method for deriving road noise improvement factor on a simple cross member application. In this feasibility validation, road excitation is simply substituted with a shaker excitation in vertical direction. The previously developed suspension rig that enables a direct measurement of the body input force at the coupling points and the specially developed cross member jig are used for the validation test.

Non-linear evolution of the resonant drag instability in magnetized gas

Abstract We investigate, for the first time, the non-linear evolution of the magnetized ‘resonant drag instabilities’ (RDIs). We explore magnetohydrodynamic simulations of gas mixed with (uniform) dust grains subject to Lorentz and drag forces, using the gizmo code. The magnetized RDIs exhibit fundamentally different behaviour than purely acoustic RDIs. The dust organizes into coherent structures and the system exhibits strong dust–gas separation. In the linear and early non-linear regime, the growth rates agree with linear theory and the dust self-organizes into 2D planes or ‘sheets.’ Eventually the gas develops fully non-linear, saturated Alfvénic, and compressible fast-mode turbulence, which fills the underdense regions with a small amount of dust, and drives a dynamo that saturates at equipartition of kinetic and magnetic energy. The dust density fluctuations exhibit significant non-Gaussianity, and the power spectrum is strongly weighted towards the largest (box scale) modes. The saturation level can be understood via quasi-linear theory, as the forcing and energy input via the instabilities become comparable to saturated tension forces and dissipation in turbulence. The magnetized simulation presented here is just one case; it is likely that the magnetic RDIs can take many forms in different parts of parameter space.

Mapless Motion Planning System for an Autonomous Underwater Vehicle Using Policy Gradient-based Deep Reinforcement Learning

This research is concerned with the motion planning problem encountered by underactuated autonomous underwater vehicles (AUVs) in a mapless environment. A motion planning system based on deep reinforcement learning is proposed. This system, which directly optimizes the policy, is an end-to-end motion planning system. It uses sensor information as input and continuous surge force and yaw moment as output. It can reach multiple target points in a sequence while simultaneously avoiding obstacles. In addition, this study proposes a reward curriculum training method to solve the problem in which the number of samples required for random exploration increases exponentially with the number of steps needed to obtain a reward. At the same time, the negative impact of intermediate rewards can be avoided. The proposed system demonstrates good planning ability for a mapless environment and excellent ability to migrate to other unknown environments. The system also has resistance to current disturbances. The simulation results show that the proposed mapless motion planning system can guide an underactuated AUV in navigating to its desired targets without colliding with any obstacles.

Parametric optimization and process capability analysis for machining of nickel-based superalloy

The manufacturing of parts from nickel-based superalloy, such as Inconel-800 alloy, represents a challenging task for industrial sites. Their performances can be enhanced by using a smart cutting fluid approach considered a sustainable alternative. Further, to innovate the cooling strategy, the researchers proposed an improved strategy based on the minimum quantity lubrication (MQL). It has an advantage over flood cooling because it allows better control of its parameters (i.e., compressed air, cutting fluid). In this study, the machinability of superalloy Inconel-800 has been investigated by performing different turning tests under MQL conditions, where no previous data are available. To reduce the numerous numbers of tests, a target objective was applied. This was used in combination with the response surface methodology (RSM) while assuming the cutting force input (Fc), potential of tool wear (VBmax), surface roughness (Ra), and the length of tool–chip contact (L) as responses. Thereafter, the analysis of variance (ANOVA) strategy was embedded to detect the significance of the proposed model and to understand the influence of each process parameter. To optimize other input parameters (i.e., cutting speed of machining, feed rate, and the side cutting edge angle (cutting tool angle)), two advanced optimization algorithms were introduced (i.e., particle swarm optimization (PSO) along with the teaching learning-based optimization (TLBO) approach). Both algorithms proved to be highly effective for predicting the machining responses, with the PSO being concluded as the best amongst the two. Also, a comparison amongst the cooling methods was made, and MQL was found to be a better cooling technique when compared to the dry and the flood cooling.