Search Results (533)

Reliable wave prediction plays a significant role in wave energy converter (WEC) research, but there are still prediction errors that would increase the uncertainty for the power grid and reduce the power quality. The efficiency and stability of the power take-off (PTO) system are also important research topics in WEC applications. In order to solve the above-mentioned problems, this paper presents a model predictive control (MPC) method composed of a prediction error compensation controller and a PTO optimization controller. This work aims to address the limitations of existing wave prediction methods and improve the efficiency and stability of hydraulic PTO systems in WECs. By controlling the charging and discharging of the accumulator, the power quality is enhanced by reducing grid frequency fluctuations and voltage flicker through prediction error compensation. In addition, an efficient and stable hydraulic PTO system can be obtained by keeping the operation pressure of the hydraulic motor at the optimal range. Thus, smoother power output minimizes grid-balancing penalties and storage wear, and stable hydraulic pressure extends PTO component lifespan. Finally, comparative numerical simulation studies are provided to show the efficacy of the proposed method. The results validate that the dual-controller MPC framework reduces power deviations by 74.3% and increases average power generation by 31% compared to the traditional method. Full article

Underwater towed systems (UTSs) are widely used in underwater exploration and oceanographic data acquisition. However, the heave motion information of the towing ship is usually affected by the measurement transmitting delay, sensor noise and surface waves, which will result in uncontrolled depth variation of the towed vehicle, so as to adversely affect the monitoring performance and mechanical robustness of the UTS. To resolve this problem, a heave motion prediction approach based on sparse Bayesian learning (SBL) incorporated with empirical mode decomposition (EMD) for the UTS is proposed in this paper. With the proposed approach, a heave motion model of the towing ship with random waves is firstly developed based on strip theory. Meanwhile, the EMD is employed to eliminate the high-frequency noise of the measurement data to restore low-frequency towing ship motion. And then, the SBL is utilized to train the weight parameters in the built model to predict the heave motion, which not only reconstruct the heave motion from non-stationary sensor signals with noise but also prevent overfitting. Furthermore, the depth compensation of the towed vehicle is then performed using the predicted heave motion. Finally, experimental results demonstrate that the proposed EMD-SBL method significantly improves both the prediction accuracy and model adaptability under various sea conditions, and it also guarantees that the maximum prediction depth error of the heave motion does not exceed 1 cm. Full article

Near-field acoustic holography (NAH) provides an effective way to achieve wide-band, high-resolution visualization measurement of the sound insulation performance of building components. However, based on Green’s function, the microphone array’s inherent amplitude and phase mismatch errors will exponentially amplify the sound field inversion process, significantly reducing the measurement accuracy. To systematically evaluate this problem, this study combines numerical simulation with actual measurements in a soundproof room that complies with the ISO 10140 standard, quantitatively analyzes the influence of array system errors on NAH reconstructed sound insulation and acoustic images, and proposes an error correction strategy based on channel transfer function normalization. The research results show that when the array amplitude and phase mismatch mean values are controlled within 5% and 5°, respectively, the deviation of the weighted sound insulation measured by NAH can be controlled within 1 dB, and the error in the key frequency band of building sound insulation (200–1.6k Hz) does not exceed 1.5 dB; when the mismatch mean value increases to 10% and 10°, the deviation of the weighted sound insulation can reach 2 dB, and the error in the high-frequency band (≥1.6k Hz) significantly increases to more than 2.0 dB. The sound image shows noticeable spatial distortion in the frequency band above 250 Hz. After applying the proposed correction method, the NAH measurement results of the domestic microphone array are highly consistent with the weighted sound insulation measured by the standard method, and the measurement difference in the key frequency band is less than 1.0 dB, which significantly improves the reliability and applicability of low-cost equipment in engineering applications. In addition, the study reveals the inherent mechanism of differential amplification of system errors in the propagating wave and evanescent wave channels. It provides quantitative thresholds and operational guidance for instrument selection, array calibration, and error compensation of NAH technology in building sound insulation detection. Full article

With the rapid advancement of high-precision optical systems, increasingly stringent demands are imposed on the surface figure accuracy of optical components. The magnitude of residual stress in multilayer films directly influences the post-coating surface figure stability of these components, making the control of multilayer film stress a critical factor in enhancing optical surface figure accuracy. In this study, which addresses the process constraints and substrate damage risks associated with conventional annealing-based stress compensation for large-aperture optical components, we introduce an active stress engineering strategy rooted in in situ deposition process optimization. By systematically tailoring film deposition parameters and adjusting the thickness modulation ratio of TiO₂ and SiO₂, we achieve dynamic compensation of residual stress in multilayer structures. This approach demonstrates broad applicability across diverse optical coatings, where it effectively mitigates stress-induced surface distortions. Unlike annealing methods, this intrinsic stress polarity manipulation strategy obviates the need for high-temperature post-processing, eliminating risks of material decomposition or substrate degradation. By enabling precise nanoscale stress regulation in large-aperture films through controlled process parameters, it provides essential technical support for manufacturing ultra-precision optical devices, such as next-generation laser systems and space-based stress wave detection instruments, where minimal stress-induced deformation is paramount to functional performance. Full article

Many novel microwave devices have been developed based on the left-handed (LH) structure. This paper studies three CMOS standing-wave oscillators (SWOs) using an LH LC network. The first SWO is a class-B VCO, and the second SWO is a class-C SWO. The SWOs are implemented with the TSMC 0.18 μm 1P6M CMOS process technology. The SWOs utilize two units of an LH LC resonator, and the LC resonator is shunted with a pair of cross-coupled transistors to compensate for the loss in the LC resonator. The first and second SWOs utilize two O-shaped inductors to form a unit cell with capacitors. The third SWO utilizes an eight-shaped inductor and an orthogonal transformer to conserve the die area and suppress the magnetic coupling noise. The die area of the third oscillator is 0.986 × 0.756 mm². The SWO can generate differential signals in the frequency range of 8.3 GHz–9.3 GHz (10.83%), and its measured figure of merit (FOM) is −188.6 dBc/Hz at a 1 MHz offset frequency. Full article

Light detection and ranging (LiDAR) sensors are essential for applications where high-resolution distance and velocity measurements are required. In particular, frequency-modulated continuous wave (FMCW) LiDAR, compared with other LiDAR implementations, provides superior receiver sensitivity, enhanced range resolution, and the capability to measure velocity. Integrating LiDARs into electronic and photonic semiconductor chips can lower their cost, size, and power consumption, making them affordable for cost-sensitive applications. Additionally, simple designs are required, such as FMCW signal generation by the direct modulation of the current of a semiconductor laser. However, semiconductor lasers are inherently nonlinear, and the driving waveform needs to be optimized to generate linear FMCW signals. In this paper, we employ pre-distortion techniques to compensate for chirp nonlinearity, achieving frequency nonlinearities of 0.0029% for the down-ramp and the up-ramp at 55 kHz. Experimental results demonstrate a highly accurate LiDAR system with a resolution of under 5 cm, operating over a 210-m range through single-mode fiber, which corresponds to approximately 308 m in free space, towards meeting the requirements for long-range autonomous driving. Full article

Offshore cranes equipped with active motion compensation (AMC) systems play a vital role in marine engineering tasks such as offshore wind turbine maintenance, subsea operations, and dynamic load positioning under wave-induced disturbances. These systems rely on complex hydraulic actuators whose strongly nonlinear dynamics—often described by differential-algebraic equations (DAEs)—impose significant computational burdens, particularly in real-time applications like hardware-in-the-loop (HIL) simulation, digital twins, and model predictive control. To address this bottleneck, we propose a neural network-based surrogate model that approximates the actuator dynamics with high accuracy and low computational cost. By approximately reducing the original DAE model, we obtain a lower-dimensional ordinary differential equations (ODEs) representation, which serves as the foundation for training. The surrogate model includes three hidden layers, demonstrating strong fitting capabilities for the highly nonlinear characteristics of hydraulic systems. Bayesian regularization is adopted to train the surrogate model, effectively preventing overfitting. Simulation experiments verify that the surrogate model reduces the solving time by 95.33%, and the absolute pressure errors for chambers $p_1$ and $p_2$ are controlled within 0.1001 MPa and 0.0093 MPa, respectively. This efficient and scalable surrogate modeling framework possesses significant potential for integrating high-fidelity hydraulic actuator models into real-time digital and control systems for offshore applications. Full article

This paper proposes a dual-mode CMOS analog front-end (AFE) circuit for short-wave infrared (SWIR) image sensors, which integrates a hybrid readout circuit (ROIC) and a 12-bit two-step single-slope analog-to-digital converter (TS-SS ADC). The ROIC dynamically switches between buffered-direct-injection (BDI) and direct-injection (DI) modes, thus balancing injection efficiency against power consumption. While the DI structure offers simplicity and low power, it suffers from unstable biasing and reduced injection efficiency under high background currents. Conversely, the BDI structure enhances injection efficiency and bias stability via an input buffer but incurs higher power consumption. To address this trade-off, a dual-mode injection architecture with mode-switching transistors is implemented. Mode selection is executed in-pixel via a low-leakage transmission gate and coordinated by the column timing controller, enabling low-current pixels to operate in low-noise BDI mode, whereas high-current pixels revert to the low-power DI mode. The TS-SS ADC employs a four-terminal comparator and dynamic reference voltage compensation to mitigate charge leakage and offset, which improves signal-to-noise ratio (SNR) and linearity. The prototype occupies 2.1 mm × 2.88 mm in a 0.18 µm CMOS process and serves a 64 × 64 array. The AFE achieves a dynamic range of 75.58 dB, noise of 249.42 μV, and 81.04 mW power consumption. Full article

Bilateral teleoperation systems have been widely used in many fields of robotics, such as industrial manipulation, medical treatment, space exploration, and deep-sea operation. Delays in communication, known as an inevitable issues in practical implementation, especially for long-distance operations and challenging communication situations, can destroy system passivity and potentially lead to system failure. In this work, we address the time-delayed three-channel teleoperation design problem to guarantee system passivity and achieve high transparency simultaneously. To realize this, the three-channel teleoperation structure is first reformulated to form a two-channel-like architecture. Then, the wave variable technique is used to handle the communication delay and guarantee system passivity. Two novel wave variable compensators are proposed to achieve delay-minimized system transparency, and energy reservoirs are employed to monitor and regulate the energy introduced via these compensators to preserve overall system passivity. Numerical studies confirm that the proposed method significantly improves both kinematic and force tracking performance, achieving near-perfect correspondence with only a single-trip delay. Quantitative analyses using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Dynamic Time Warping (DTW) metrics show substantial error reductions compared to conventional wave variable and direct transmission-based three-channel teleoperation approaches. Moreover, statistical validation via the Mann–Whitney U test further confirms the significance of these improvements in system performance. The proposed design guarantees passivity with any passive human operator and environment without requiring restrictive assumptions, offering a robust and generalizable solution for teleoperation tasks with communication time delay. Full article

This study systematically compares the metrological characteristics of single- exposure, double-exposure, and continuous-exposure holographic interferometry for micro-deformation detection. Results demonstrate that the double-exposure method achieves optimal balance across critical performance metrics through its ideal cosine fringe field modulation. This approach (1) eliminates object wave amplitude interference via dual-exposure superposition, establishing submicron linear mapping between fringe displacement and deformation amplitude; (2) introduces a fringe gradient-based direction detection algorithm resolving deformation vector ambiguity; and (3) implements an error-compensated fusion framework integrating theoretical modeling, MATLAB 2015b simulations, and experimental validation. Experiments on drilled glass samples confirm their superior performance in terms of near-ideal fringe contrast (1.0) and noise suppression (0.06). The technique significantly improves real-time capability and anti-interference robustness in micro-deformation monitoring, providing a validated solution for MEMS and material mechanics characterization. Full article

In recent years, the global demand for renewable energy has been steadily increasing, and offshore wind power generation technology has thus developed rapidly, with the optimization of the performance of the pitch control system, as a key technology to ensure the efficient and safe operation of wind turbines, becoming a research hotspot. Offshore wind turbines face complex environmental changes, particularly regarding the load perturbations caused by wind speed, wind direction, waves, and other factors, which have a significant impact on the stability and accuracy of the pitch control system. In order to reduce the impact of load disturbance on pitch accuracy, this paper proposes a pitch control strategy with load disturbance compensation. Firstly, the relationship between hydraulic cylinder displacement and pitch angle is analyzed; then, the mathematical model comparing hydraulic cylinder displacement, servo motor speed, and external load disturbance force is constructed; the hydraulic cylinder position control strategy with load disturbance compensation is proposed; and finally, the effectiveness of the control strategy is verified through simulations and experiments. Full article

Micro-Electro-Mechanical Systems (MEMS) loudspeakers are attracting growing interest as alternatives to conventional miniature transducers for in-ear audio applications. However, their practical deployment is often hindered by pronounced resonances in their frequency response, caused by the mechanical and acoustic characteristics of the device structure. To mitigate these limitations, we present a model-based digital signal equalization approach that leverages a circuit equivalent model of the considered MEMS loudspeaker. The method relies on constructing an inverse circuital model based on the nullor, which is implemented in the discrete-time domain using Wave Digital Filters (WDFs). This inverse system is employed to pre-process the input voltage signal, effectively compensating for the transducer frequency response. The experimental results demonstrate that the proposed method significantly flattens the Sound Pressure Level (SPL) over the 100 Hz-10 kHz frequency range, with a maximum deviation from the target flat frequency response of below 5 dB. Full article

Bow-tie cavity configurations have gained significant attention due to their efficacy in facilitating stable resonator operation for applications requiring short pulse operation and high repetition rate pulses, offering versatility and reliability. While there is an extensive body of literature addressing the theoretical aspects and applications of this laser configuration, there exists a gap in practical insights and systematic approaches guidance pertaining to the development and precision alignment of this laser type. The paper achieves this by compiling a range of analytical and optimization techniques for the bow-tie cavity configuration and delineating the necessary steps for the optimization required for continuous wave operation. This ultimately leads to the attainment of the pulsed regime through the Kerr Lens Mode-locking technique, offering a detailed account of the development, optimization, and performance evaluation of a Ti:Sapphire femtosecond laser cavity, using dispersion-compensating mirrors to produce a low-energy pulse of 1 nJ, a high repetition rate of 1 GHz, and a short pulse duration of 61 fs. This work can be useful for researchers and engineers seeking to embark on the development of compact and high-performance femtosecond lasers for a spectrum of applications, encompassing biomedical imaging, laser-assisted surgery, spectroscopy, and optical frequency combs. Full article

When ships conduct offshore operations in the ocean, they are subject to disturbances from natural factors such as sea breezes and waves. These disturbances lead to movements detrimental to the ship’s stability, especially heave movement in the vertical direction, which profoundly impacts the safety of shipboard facilities and staff. To counter this, the active wave compensation device is widely used on ships to maintain the stability of the working environment. However, the system’s efficiency and accuracy are compromised by the significant delay incurred while obtaining real-time motion signals and driving the actuator for motion compensation. To solve the time delay problem of shipborne wave compensation equipment in motion compensation under complex sea conditions, it is necessary to improve the ship heave motion prediction accuracy in an active wave compensation system. This paper presents a prediction method of ship heave motion based on the particle swarm optimization (PSO) and convolutional neural network–long short-term memory (CNN-LSTM) hybrid prediction model. The paper begins by establishing the ship heave motion model based on the P–M spectrum and slice theory, simulating the ship heave motion curve under different sea conditions on MATLAB. This simulation provides crucial data for the subsequent prediction model. The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. The experiments demonstrate that the proposed PSO-CNN-LSTM hybrid model effectively addresses the problem of predicting drift and boasts significantly higher prediction accuracy, making it suitable for predicting the short-term heave motion of ships. The data show that the optimized root mean square error (RMSE) value under level 5 sea conditions is 0.01265 compared to 0.01673 before optimization, and the optimized RMSE value under level 6 sea conditions is 0.01140 compared to 0.01479 before optimization, which demonstrates that the error between the predicted value and the actual value of the model decreases. This improved accuracy provides reassurance in the model’s predictive capabilities and lays the foundation for improving the accuracy of the motion compensation system in the future. Full article

The direct porting of the Range Migration Algorithm to GPUs for three-dimensional (3D) cylindrical synthetic aperture radar (CSAR) imaging faces difficulties in achieving real-time performance while the architecture and programming models of GPUs significantly differ from CPUs. This paper proposes a GPU-optimized implementation for accelerating CSAR imaging. The proposed method first exploits the concentric-square-grid (CSG) interpolation to reduce the computational complexity for reconstructing a uniform 2D wave-number domain. Although the CSG method transforms the 2D traversal interpolation into two independent 1D interpolations, the interval search to determine the position intervals for interpolation results in a substantial computational burden. Therefore, binary search is applied to avoid traditional point-to-point matching for efficiency improvement. Additionally, leveraging the partition independence of the grid distribution of CSG, the 360° data are divided into four streams along the diagonal for parallel processing. Furthermore, high-speed shared memory is utilized instead of high-latency global memory in the Hadamard product for the phase compensation stage. The experimental results demonstrate that the proposed method achieves CSAR imaging on a $1440\times 100\times 128$ dataset in 0.794 s, with an acceleration ratio of 35.09 compared to the CPU implementation and 5.97 compared to the conventional GPU implementation. Full article