Input Force Research Articles

Coupling input and output intensity to explore the sustainable agriculture intensification path in mainland China

Sustainable intensification (SI) of agriculture is widely regarded as an important way to alleviate the contradiction between the food gap and ecosystem health. Correlate input intensity and output intensity have been regarded as an important dimension in most estimation frameworks of SI. But in practice, this correlation is generally expressed in terms of efficiency metrics and calculated as the ratio of output intensity to input intensity, which cannot quantitatively explain the impact of input intensity on output intensity and provide a threshold value for estimating the suitability of SI. This study's goals are to propose an input—output coupled method to explain the impact of input intensity on output intensity and thereby estimate the suitability of provincial SI. Provincial annual input intensity and output intensity were estimated from an emergy-based perspective by taking China as a case study. The K-means algorithm was used to identify the structural pattern of arable land input intensity. A sliding window-based partial correlation index method was proposed and applied to reveal the interaction process between input intensity and output intensity. The results show that there are two main change paths in the pattern of input intensity: one path in the western irrigation regions and the other path in the eastern northeast China Plain and middle-lower Yangtze Plain. The former path can be expressed as a small increase in fertilizer and agro-machinery input intensity with a decrease in labour force input intensity. The latter path shows a larger increase in fertilizer and pesticide input intensity. For each type of input intensity except mulching film, its correlation to output intensity has experienced a similar coupling—decoupling—recoupling process in both plain provinces and mountainous or plateau provinces. According to Landau's theory of phase transition, the complex coupling of input and output undergoes a phase transition process from order to disorder and then to order, depicted by the sliding window-based partial correlation coefficient as the order parameter from a holistic perspective. The inflection points of coupling relation changes show that the phenomenon of fertilizer and pesticide overuse has steadily occupied most provinces in eastern China and is spreading westwards. Although the “zero growth action for fertilizers and pesticides” has made considerable achievements in reducing the input intensity of fertilizer and pesticides since 2015, the situation of superfluous fertilizer and pesticide input has not changed substantially. The input intensity of fertilizer and pesticides still needs to be further reduced. This study can contribute to the estimation method system of SI. The input—output coupled method is applicable for other spatial scales and regions (or countries) to estimate the suitability of SI.

Design and analysis of magnetostrictive two-dimensional kinetic energy harvester

Conventional energy harvesters often require high ambient vibration frequencies and can only capture vibration energy in a single direction. To address these issues, this paper designs a magnetostrictive two-dimensional kinetic energy harvester placed under the floor and capable of capturing energy in both vertical and horizontal directions. In order to achieve higher electrical power output at low-frequency input forces, a two-stage force amplification mechanism is designed to amplify the walking kinetic energy of pedestrians and the main parameters of this structure are analyzed and optimized. On the other hand, by constructing different forms of bias magnetic field, the influence of bias magnetic field on the deflection and motion of the internal magnetic domain of Terfenol-D is systematically studied, and the best bias form that can make the material shows the strongest magnetization characteristics is determined. Next, a prototype harvester was built, and an experimental vibration system was set up to test and analyze the output characteristics of the harvester comprehensively. The experimental results show that the harvester produces 21.2 mW of peak output power under sinusoidal excitation at an operating frequency of 4 Hz. Under random excitation, a peak output voltage of 2.64 V and 170 mW peak power was obtained. Under actual pedestrian walking tests, 17.62 mW peak output power is obtained to power low-power devices. The study’s results provide preliminary evidence that the designed magnetostrictive energy harvester can stably harvest kinetic energy from pedestrian walking.

Development of a hybrid intelligent switching hydraulically interconnected suspension system under a multi-objective optimized mode selection strategy with real-world condition

Reduction in vertical acceleration is crucial for car manufacturers. This parameter evaluates the comfort index. Moreover, the handling index is another feature that must be under investigation. The suspension system has an essential impact on these two indices. A hybrid intelligent switching hydraulically interconnected suspension (HISHIS) is proposed. The parallel configuration is combined with the diagonal configuration in the suspension system. A mode selection strategy is discussed to select the layout between diagonal and parallel configurations. The only mode of parallel configuration is called Anti-pitch configuration. The diagonal configuration has three modes, including Anti-roll, Anti-oversteering, and Anti-vibration configuration. According to the mode selection strategy, one of these three diagonal configuration modes might be selected. The origin of roll and pitch generation is inertia force and road inputs. Hopfield neural network can recognize the origin of roll and pitch generation. Therefore, the performance of valves will change according to Hopfield neural network recognition. The results of different maneuvers show the improvement at each targeted parameter in various tasks independently. The data logger gathered the acceleration of the vehicle in real-world conditions. However, the margins of the selection strategy block are multi-objective optimized with a genetic algorithm to reach better responses in real-world conditions. The roll angle, yaw rate, allowable exposure time, and pitch angle are improved by 63%, 5%, 40%, and 99% on average. Also, optimizing the selection strategy improves the allowable exposure time by 9%. Obviously, by combining two layouts, it is possible to have a flexible situation to improve ride comfort and handling situations. In addition, there is a conditional strategy to select different layouts and modes to reach a better response.

Multibody dynamic modeling of the behavior of flexible instruments used in cervical cancer brachytherapy.

The steep radiation dose gradients in cervical cancer brachytherapy (BT) necessitate a thorough understanding of the behavior of afterloader source cables or needles in the curved channels of (patient-tailored) applicators. The purpose of this study is to develop and validate computer models to simulate: (1) BT source positions, and (2) insertion forces of needles in curved applicator channels. The methodology presented can be used to improve the knowledge of instrument behavior in current applicators and aid the development of novel (3D-printed) BT applicators. For the computer models, BT instruments were discretized in finite elements. Simulations were performed in SPACAR by formulating nodal contact force and motion input models and specifying the instruments' kinematic and dynamic properties. To evaluate the source cable model, simulated source paths in ring applicators were compared with manufacturer-measured source paths. The impact of discrepancies on the dosimetry was estimated for standard plans. To validate needle models, simulated needle insertion forces in curved channels with varying curvature, torsion, and clearance, were compared with force measurements in dedicated 3D-printed templates. Comparison of simulated with manufacturer-measured source positions showed 0.5-1.2mm median and<2.0mm maximum differences, in all but one applicator geometry. The resulting maximum relative dose differences at the lateral surface and at 5mm depth were 5.5% and 4.7%, respectively. Simulated insertion forces for BT needles in curved channels accurately resembled the forces experimentally obtained by including experimental uncertainties in the simulation. The models developed can accurately predict source positions and insertion forces in BT applicators. Insights from these models can aid novel applicator design with improved motion and force transmission of BT instruments, and contribute to the estimation of overall treatment precision. The methodology presented can be extended to study other applicator geometries, flexible instruments, and afterloading systems.

Data-driven model reduction approach for active vibration control of cable-strut structures

The cable-strut structures have the features of low stiffness and weak damping, resulting in large vibration response under dynamic excitation. The vibration response of the cable-strut structures can be reduced by active control methods. However, many traditional active control methods need to build a state-space model (SSM) based on finite element model (FEM), and solving the active control force for the high-dimensional SSM is time-consuming. In this paper, the dynamic mode decomposition with control (DMDc) method is proposed to achieve a data-driven reduced-order SSM for active vibration control of cable-strut structures. This proposed method only uses the data of structural response and control force input to build reduced-order SSM and does not rely on the FEM. Linear quadratic regulator (LQR) design using the DMDc-based reduced-order SSM (DMDc-LQR) is more computationally efficient than that using the FEM-based SSM (FEM-LQR). The relationship between the design parameters of the DMDc-LQR controller and the FEM-LQR controller is established, which ensures that the control performance indexes of the DMDc-LQR controller and the FEM-LQR controller are equal. The effectiveness of the proposed DMDc-LQR method is validated using numerical Kiewitt cable dome and tensegrity grid under wind and seismic loads. The results show that the DMDc-LQR controller maintains similar control effect to that of the FEM-LQR controller and has advantage of high computing efficiency as well. In addition, the influence of critical parameters (i.e., data noise and model order) on vibration control effect is comprehensively explored. It is found that increasing the model order is effective to mitigate the noise influence on the DMDc-based reduced-order SSM and ensures the effectiveness of the DMDc-LQR controller.

Triboelectric nanogenerator as next generation traffic monitoring system: Concept and modelling

Rapid development of intelligent transportation demands accurate methods for monitoring vehicle overload information. This paper reports a detail analysis on the viability of triboelectric nanogenerator (TENG) as a smart traffic monitoring system. PVDF and silk film were exploited for TENG fabrication for their strong penchant of gaining and loosing electrons. The objective of this paper is two fold. Initially the electrical performance of the fabricated prototype was measured and reported. The prototype exhibited a maximum open circuit voltage of 648 V and an instantaneous power density of 24 mW/mm2. It was also capable to light up 75 commercial green LEDs. Furthermore, a TENG based traffic monitoring system was introduced for monitoring the traffic overload information and for counting the number of vehicles rolled on it. The TENG was used to convert the mechanical energy from the rolling of vehicles into electric pulses. The pulses that were generated by the TENG was incorporated into an interfacing circuit to anticipate the number of vehicles passed by it. The amplitude of those pulses also give a valuable information regarding the weight of vehicles as the generated voltage is proportional to the input force. Different output voltages of 207 V, 367 V and 558 V were produced for different types of vehicles like bicycle, motorbike and four wheeler passenger vehicle respectively depending on their mass. Output voltage was also varied depending on the load carried by vehicles and showed an increasing trend with load. In consequence, the proposed system can substantially be implemented at various automotive toll plazas to corroborate the paid tax and the actual tax that is supposed to be paid on the basis of laden weight of the vehicle.

A data-driven suspension kinematics and compliance model considering multi-axis coupling effects

The kinematics and compliance characteristics (K&amp;C) significantly impact a vehicle’s dynamic response. While a comprehensive multibody suspension model can accurately express desired suspension K&amp;C characteristics, the complexity of the model limits its use in real-time applications. The K&amp;C characteristics are usually obtained through decoupled bench tests, whereby it is assumed that the suspension K&amp;C characteristics can be orthogonally decomposed and that the function outputs can be added up to restore the original characteristics, which may not be accurate. Therefore, in this research, a novel suspension K&amp;C simulation/test method is proposed to demonstrate the suspension characteristics under coupled force inputs. A multibody dynamic model of an air suspension is constructed and calibrated through bench tests. Then, a series of coupled tire forces with shapes of space spiral curves are applied to the multibody model to produce the coupled K&amp;C data. A novel data-driven model based on Long Short-Term Memory (LSTM) network is proposed to predict suspension K&amp;C. Finally, the proposed data-driven K&amp;C model and the decoupled K&amp;C model are compared under full vehicle simulations. The results suggest that the proposed method is more accurate than the decoupled K&amp;C model and can express the suspension hysteresis characteristics without further modification.

A novel bridge-type compliant displacement amplification mechanism under compound loads based on the topology optimisation of flexure hinge and its application in micro-force sensing

The design and modelling of bridge-type compliant displacement amplification mechanisms (CDAMs) are key components in precision engineering. In this study, a bridge-type CDAM under compound loads with an optimum flexure hinge configuration is designed, analysed, and tested. For the case when the flexure hinge configuration is unknown, the internal force distribution for a bridge-type CDAM under compound loads is analysed, and the topology of the flexure hinge is optimised. By applying different volume constraints, the optimised flexure hinge configurations are all V-shaped. Subsequently, a static model of the V-shaped flexure hinge is established. For a bridge-type CDAM with V-shaped flexure hinges, the compliance matrix of the flexure hinge is combined with the relationship among the local compliance matrices in a serial mechanism; consequently, the analytical relationship between the output displacement, output force, and input force is derived. The CDAM is parametrically optimised to further improve the output performance. Simulations and experiments verify the topology optimisation result, static model, and parametric optimisation result. Finally, the CDAM and its static model are applied to the tensile manipulation and micro-force sensing in a microfiber tensile test.

A complete physical 3D model from first principles of vibrational-powered electromagnetic generators

The dynamic behavior of a vibrational electromagnetic generator using a magnetic levitation architecture was theoretically and experimentally studied in great detail, when operating under a wide range of three-dimensional excitations. We developed a complete rigorous physical model from first principles based on the theory of electrodynamics of continua, centered on the laws of electrodynamics and balance of mass, linear momentum, angular momentum, energy and entropy. Local electromagnetic and gravitational body forces, couples and powers were considered, and the surface tractions were divided into constraint and friction components, as well as those due to external mechanical energy sources. The balance of linear momentum, angular momentum and circuit equations resulted in up to 13 non-linear differential equations describing the dynamics of the levitating-magnet and container, relating input forces and torques with output displacement, constraint forces and voltage. The balance of energy yielded a consistent equivalence between the time rate of change of the internal kinetic and potential energies of the generator and the output power, associated with the external circuit, Ohmic losses and friction losses, as well as the input mechanical power being supplied to the system by the environment. Both the input and output powers were proven to tend to increase equally when operating the generator under resonant conditions. The levitating generator was shown to be sensitive to axial translational and centrifugal inertial forces, each one effectively resulting in a uni-stable or bi-stable system. The dynamical response yielded multiple initial conditions dependent steady-states, hysteretic frequency output and chaotic characteristics. Relevant guidelines to optimize the energy conversion efficiency of energy harvesters are provided. This model was validated by experimental tests, including general 3D motions combining translations and rotations: cross-correlations exceeding 90% were achieved. Such Newtonian and Langrangian modelling approaches hold great potential to be easily adapted to a wide range of other electromagnetic generators, with multiple degrees-of-freedom and operating under various environments, such that significant advances in energy technologies can be supported.

Strategies for Reducing Booming Noise Generated by the Tailgate of an Electric Sport Utility Vehicle

This article investigates the source of booming noise emanating from the tailgate of an electric sport utility vehicle (SUV), along with proposed strategies to mitigate it. This annoying low-frequency booming noise, which significantly impacts interior sound quality, is less perceptible in conventional internal combustion engine vehicles. However, this noise is more readily detected in electric SUVs, highlighting the necessity for focused measures to reduce it. This study involved the measurement of booming noises during on-road vehicle tests to pinpoint their origins. Additionally, ODSs were extracted from the tailgate vibration signals to gain insight into its dynamic behavior. Modal tests were conducted on the tailgate to determine its dynamic characteristics and compared with driving test results to reveal the mechanism responsible for tailgate-induced booming noise. It was established that such noise is primarily due to the tailgate modes, resulting from a combination of rigid body motion in the fore-aft direction and deformation in the central section of the panel. An analytical model of the tailgate was developed using commercial finite-element analysis software to propose measures for reducing booming noise. Experimental findings validated this model’s accuracy. Structural enhancements were implemented to enhance the panel stiffness and improve the connection between the vehicle and tailgate via bushings to reduce the booming noise resulting from tailgate motion. Under random force inputs, the analytical results demonstrated a 13.8% reduction in maximum deformation in the tailgate model in the improved structural configuration with increased panel stiffness. This study identifies the mechanism generating booming noise, establishes a practical and simple dynamic model, and proposes improvement measures aimed at reducing the booming noise.

Spatiotemporal snow water storage uncertainty in the midlatitude American Cordillera

Abstract. This work quantifies the uncertainty of accumulation-season peak snow water storage in the portions of the midlatitude American Cordillera where snow is a dominant driver of hydrology. This is accomplished through intercomparison of commonly used global and regional products over the Western United States (WUS) and Andes domains, which have similar hydrometeorology but are disparate with respect to the amount of available in situ information. The recently developed WUS Snow Reanalysis (WUS-SR) and Andes Snow Reanalysis (Andes-SR) datasets, which have been extensively verified against in situ measurements, are used as baseline reference datasets in the intercomparison. Relative to WUS-SR climatological peak snow water equivalent (SWE) storage (269 km3), high- and moderate-resolution products (i.e., those with resolutions less than ∼10 km) are in much better agreement (284±14 km3; overestimated by 6 %) compared to low-resolution products (127±54 km3; underestimated by 53 %). In comparison to the Andes-SR peak snow storage (29 km3), all other products show large uncertainty and bias (19±16 km3; underestimated by 34 %). Examination of spatial patterns related to orographic effects showed that only the high- to moderate-resolution Snow Data Assimilation System (SNODAS) and University of Arizona (UA) products show comparable estimates of windward–leeward SWE patterns over a subdomain (Sierra Nevada) of the WUS. Coarser products distribute too much snow on the leeward side in both the Sierra Nevada and Andes, missing orographic and rain shadow patterns that have important hydrological implications. The uncertainty of peak seasonal snow storage is primarily explained by precipitation uncertainty in both the WUS (R2=0.55) and Andes (R2=0.84). Despite using similar forcing inputs, snow storage diverges significantly within the ECMWF Reanalysis v5 (ERA5) (i.e., ERA5 vs. ERA5-Land) products and the Global Land Data Assimilation System (GLDAS) (modeled with Noah, Variable Infiltration Capacity (VIC), and Catchment model) products due to resolution-induced elevation differences and/or differing model process representation related to rain–snow partitioning and accumulation-season snowmelt generation. The availability and use of in situ precipitation and snow measurements (i.e., in WUS) in some products adds value by reducing snow storage uncertainty; however, where such data are limited, i.e., in the Andes, significant biases and uncertainty exist.

DESIGN And IMPLEMENTATION Of HYDRIC CONTROLLER For TWOWHEELED ROBOT

The two-wheeled robotic machine (TWRM) with five degrees of freedom (DOF) is a type of mobile robot that consists of two wheels and a body that can rotate and move in different directions. The proposed architecture of the TWRM in this paper features five DOFs, which allows for greater flexibility and range of motion. However, this also makes controlling the system more challenging, as thecenter of mass (COM) changes while performing tasks in multiple directions. To address this issue, the study utilizes a state-space model created by linearizing the non-linear modeling equations at the equilibrium point using the Lagrangian modeling. To stabilize the TWRM, several controllers were evaluated, including PID, LQR, and LQR with PID methods. The PID controller is a popular feedbackcontrol strategy that adjusts the control output based on the error between the desired and actual values of the systemoutput. LQR is a state-space control technique that aims to minimize a cost function that expresses the system's performance criteria. The PID with LQR technique combines the strengths of both strategies, with PID used as a feed-forward to control the intermediate body (IB) and end-effector and LQR used as state feedback to regulate all states. The controllers were evaluated under variouscircumstances, including disturbance signals, trackingpathways, and moving actuators. Simulation results showedthat the LQR with LQR controller performed better thanthe other two control systems in terms of least overshoot,rising time, and applied input forces. This suggests that thePID with LQR technique is a robust and effective controlstrategy for stabilizing the TWRM and improving itsperformance for various tasks.

Design, Simulations and Tests of a Novel Force and Moments Sensor for Instrumented Knee Implants.

Early identification of mechanical complications of total knee arthroplasties is of great importance to minimize the complexity and iatrogenicity of revision surgeries. There is therefore a critical need to use smart knee implants during intra or postoperative phases. Nevertheless, these devices are absent from commercialized orthopaedic implants, mainly due to their manufacturing complexity. We report the design, simulations and tests of a force and moments sensor integrated inside the tibial tray of a knee implant. By means of a "tray-pillar-membrane" arrangement, strain gauges and metal additive technology, our device facilitates the manufacturing and assembly steps of the complete system. We used finite element simulations to optimize the sensor and we compared the simulation results to mechanical measurements performed on a real instrumented tibial tray. With a low power acquisition electronics, the measurements corroborate with simulations for low vertical input forces. Additionally, we performed ISO fatigue testings and high force measurements, with a good agreement compared to simulations but high non-linearities for positions far from the tray centre. In order to estimate the center of pressure coordinates and the normal force applied on the tray, we also implemented a small-size artificial neural network. This work shows that relevant mechanical components acting on a tibial tray of a knee implant can be measured in an easy to assemble, leak-proof and mechanically robust design while offering relevant data usable by clinicians during the surgical or rehabilitation procedures. This work contributes to increase the technological readiness of smart orthopaedic implants.

Path-Following Based on Fuzzy Line-of-Sight Guidance for a Bionic Snake Robot With Unknowns

To improve the convergence rate of path-following errors of a bionic snake robot and reduce the overshoot of kinematic errors, a path-following control method based on fuzzy line-of-sight (LOS) guidance for a bionic snake robot with unknowns is developed. This method designs the time-varying LOS forward distance and sliding mode switching gain according to fuzzy rules, offsets the external interferences, weakens the damage of chattering to robot joints, and reduces the negative impact of external interferences on the robot path-following. In addition, the uncertain friction coefficients are predicted by using the adaptive estimation, which compensates for joints’ rotating force inputs and improves environmental adaptability of the body. By establishing the appropriate Lyapunov function, the stability of the gait angle, motion position, and whole system are verified. Simulation and experiment results show the feasibility and superiority of the proposed method.

Groundwater Vulnerability in a Megacity Under Climate and Economic Changes: A Coupled Sociohydrological Analysis

AbstractGroundwater depletion has become increasingly challenging, and many cities worldwide have adopted drastic policies to relieve water stress due to socioeconomic growth. Located on the declining aquifer of the North China Plain, Beijing, for example, has developed plans to limit the size of the city’s population. However, the effect of population displacement under uncertain macroeconomic and climate change remains ambiguous. We adopt a sociohydrological model, with explicit consideration of the dynamics of human‐water interactions, to explore the groundwater vulnerability of Beijing. We investigate how human response might shape the development trajectories of the groundwater‐population‐economy system under different macroscale economic and climate scenarios. Furthermore, we use a machine learning algorithm to identify the decisive factors to be considered for reducing groundwater vulnerability. Our results show that while rapid external economic development or larger annual average precipitation would enable recovery of the groundwater table in the short term, they may slacken human water shortage awareness and result in more acute groundwater depletion in the long run. Strengthening policymaker perceptions of groundwater depletion would prompt timely response policies for controlling population size. Improving the quantity and quality of labor force input to economic development would avoid downturns in the economy due to labor shortages. The outcomes of this study suggest that these strategies would effectively reduce groundwater vulnerability in the long run without causing severe socioeconomic recession. These findings highlight the importance of endogenizing human behavioral dynamics in sustainable urban water management.

On the relationship between the vibration characteristics of the automobile wheel and generated road noise in the vehicle cabin

The relationship between vibration characteristics of an automobile wheel and the generated road noise in the vehicle cabin was investigated experimentally and numerically because it is one of the vibration transmission paths caused by the input force from roads. Experiments were conducted using 15-inch wheels in two different vibration characteristics, and the results were discussed based on the measurements of the noise in the cabin and vibrational acceleration of the sub-frame of the vehicle when driving on smooth and rough roads at a speed of 30 km/h. Further, transient analysis using FEM was also performed using a tire-wheel assembly model. The results showed that large differences were observed in the generated noise of 49, 90, and 167 Hz in the case of the smooth road, and these differences were due to the difference in the magnitude of vibrational accelerations of the wheel at these frequencies.

Input force contribution separation method for utilizing blocked force and operational TPA

In recent years, various transfer path analysis (TPA) methods have been proposed to separate contribution from multiple input points to the response point. In general, TPA methods require transfer function from input to the response points by hammering tests. However, obtaining accurate contribution becomes difficult in case the transfer function varies according to the operating condition or the complexity of the transfer path. In this study, we then considered input force contribution separation method for the difficult condition by combining operational TPA and blocked force used in component TPA. In the method, blocked force in the operational condition is obtained by component TPA at first, and operational TPA is applied between the obtained blocked force and the response point acceleration signals to obtain the transfer function without hammering tests. The contribution is calculated by multiplying the blocked force and the transfer function at the condition. As the verification, the proposed method was applied to a simple vehicle model equipped with a motor. And the response point vibration could be decreased well by measuring the high contributing part according to the contribution separation result. Through the verification test, the effectiveness of the proposed procedure was confirmed.

Dynamic behavior of one-dimensional foam disk chains during low-velocity impact

This study experimentally analyses the deformation and energy retention behavior of ten closed-cell PVC foam disks constituting a one-dimensional granular chain subjected to low-velocity impacts. A pressure-driven impactor loads disk chains of two densities, each at 1 and 10 m/s. The deformations of the disks are captured using high-speed cameras, and the chain's input and output forces are recorded during the impact. Energy retained by the chain and the disks is calculated using the deformations of the disks, input, output, and contact forces. The results show that the energy retained by the chain of H130 foam is 3 times greater than that of the H35 foam at 1 m/s and is about twice as high at 10 m/s. Normalized with respect to input energy, the relative energy retained by the chains of H35 foam is more than that of the H130 foam for the same impact velocity and is higher at lower impact velocities for both foams. In addition, the energy the disk chain retains decays along the chain, and the decay rate is higher for lower impact speeds, implying that the disk chain should be longer for higher impact speeds to mitigate the energy fully.

Output-only structural damage identification based on Q-learning hybrid evolutionary algorithm and response reconstruction technique

Various structural damage identification methods have been developed and employed, while the absence of input excitation measurements may pose a huge challenge in their application since the input forces such as seismic load, traffic load, wind load, are not directly measurable. To address this issue, in the present paper, a novel output-only structural damage detection approach based on Q-learning hybrid evolutionary algorithm (QHEA) and response reconstruction technique is presented. On the one hand, the external excitation and structural acceleration responses are reconstructed with the aid of response reconstruction and Tikhonov regularization techniques in time domain. Structural damage identification can be formulated as an optimization-based inverse problem. On the other hand, a new optimization framework QHEA integrating Jaya algorithm, differential evolution, Q-learning algorithm is developed as search tool. The unknown structural parameters and unmeasured input force are iteratively updated by using two different measurement sets until the reconstructed acceleration responses agree well with the measured responses. Numerical examples involving a cantilever beam structure under single excitation and a simply-supported 51-bar truss structure under multiple excitations, as well as an experimental five-floor steel frame structure in the laboratory are carried out to validate the effectiveness of the proposed method. The final results demonstrate that the proposed method can accurately detect damage locations and quantify damage extents without the information of input excitation. In addition, the superiority of QHEA over other heuristic algorithms, the uncertainties of measurement noise and modeling errors on damage identification results are further examined.

Servo kontrollü maliyet etkin bir aktif kuvvet duyargası tasarımı ve denenmesi

In this work, the computerized control of a hydraulic system with analog characteristics is examined, and within this scope, a novel force sensor is designed. The system consists of two main structures: an analog subsystem comprising a four-way servo valve, hydraulic piston, servo amplifier, and the designed force sensor, and a digitizing subsystem responsible for comparison and control, composed of a desktop computer. Throughout this work, a cost-effective force sensor was designed by integrating a compression spring, guides, a support frame and a linear variable differential transformer (LVDT). In this integrated system, the force applied at a specific magnitude and frequency from an external force measurement and feedback unit is converted into electrical signals by horizontal motion of the LVDT core. These electrical signals from the force sensor are digitized and fed back to the computer and data acquisition card. The digitized data transferred to the software developed in this study continuously compare with the reference data, enabling position-dependent force control. Experiments conducted with the force sensor placed between two hydraulic pistons controlled by a servo valve revealed that it caused the pistons to move right and left, providing the desired control of the system with the reference force input. The system was observed to operate much more stably, especially for high-frequency signal inputs.