This PDF file contains the front matter associated with SPIE Proceedings Volume 13079, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The existing tower settlement monitoring technology is difficult to realize the accurate settlement monitoring of multi-tower and large range. Therefore, the online monitoring technology of the uneven settlement of the tower of the DC grounded pole line is designed. The overall scheme of online monitoring of a single tower is optimized, the laser equipment is used as the main tool of settlement monitoring and ranging, a geometric shape is built together with the tower to be measured and the reflection plate, and the settlement changes of the tower support are obtained through calculation. Laser equipment is deployed, laser wave is demodulated, the signal is collected by grating fiber, settlement data is calculated according to the strain of transmission lines of tower and tower, and signal conversion and transmission are completed through a wireless network. Finally, the influence of fiber grating is corrected according to the temperature change, and the non-uniform settlement of the tower and tower of the ground pole line of DC transmission is realized through online monitoring. The technology is applied to a certain line tower for testing, and the results are compared with the results obtained by the BOFDA demodulation instrument. In the case of multiple DC transmission ground pole lines, the error between the results obtained by the designed non-uniform settlement monitoring technology and the theoretical results is less than ±1mm, indicating that the monitoring results obtained by the designed technology are more accurate.

Machining deformation compensation technology based on on-machine measurement (OMM) has been widely applied in the field of thin-walled parts machining. However, few research has been conducted on the calculation method of machining error for thin-walled parts. In this study, based on surface reconstruction technology of non-uniform rational B-spline (NURBS), a quick method for calculating machining error of thin-walled parts is proposed. The value of machining error is equal to the distance from the cutter location on the tool envelope to the corresponding point on the reconstructed surface. To simplify the solution process, a spatial rotation translation transformation is performed firstly on the reconstructed surface. Subsequently, we developed an iterative algorithm to efficiently locate the corresponding points on the reconstructed surface, enabling us to accurately calculate the machining error value.

Pantograph is an important subsystem in the Pantograph-OCS system, and its health condition is related to the smooth running of high-speed train. This article, the structure of high-speed railway pantograph model is first optimized based on finite element analysis. After optimization, the average low-order vibration frequency was reduced by 7.75%, and it was concluded that the optimal pantograph sliding plate consists of four equally symmetrical structures. Then, the weak links in the pantograph structure were obtained by comprehensive static strength analysis, and acceleration sensors were arranged to collect the working status data of the pantograph. Finally, a deep belief network (DBN) is used to detect the health status of key pantograph components. The vibration signals collected by multiple sensors were segmented and extracted, and feature extracted for unsupervised DBN training. By comparing and analyzing the prediction results, an appropriate number of samples was selected to improve the diagnostic accuracy of the model to 97.87%. The experimental results show that the fully trained pantograph DBN network model can achieve high accuracy in identifying and classifying fatigue conditions.

In the current industrial environment, electronic instruments have been widely used, but at the same time, electronic instruments also face many problems, such as zero temperature drift and sensitivity temperature drift caused by temperature changes. This article proposes an algorithm based on software proofreading that combines anomaly detection algorithms with neural networks. It is concluded that this method can indeed proofread instruments and maintain errors within an acceptable range. This method can further improve the accuracy and reliability of the current industry, ensuring process optimization and efficiency improvement.

Traditional γ-ray spectrum processing software uses full-spectrum stabilization, which can make it difficult to correct peak positions of nuclides after significant nonlinear spectral drift occurs. Additionally, the nuclide activity must be calculated through a complex peak searching process after stabilization. To address these challenges and correct spectral line drift caused by environmental changes in γ-ray spectrum measurements, we propose a Local software Processing method based on Multi-Energy Windows. Our method involves fitting the γ-ray spectrum, dividing it into multiple nuclide energy windows and comparing the fitted peaks within each energy window with standard peaks to correct the spectral lines, which brings each local single peak back to its standard position after stabilization. Simulation experiments show that our method has a stabilization error of less than ±1 channel and provides a significant correction effect for severe nonlinear spectral drift. Furthermore, the corrected fitted peaks can be used directly to calculate the peak area without the need for further peak searching, simplifying the process of nuclide analysis.

The hydraulic hose assembly consists of hoses, hose fittings and other accessories, and is an important component of the hydraulic system. With the wide application of hydraulic system in various fields, the quality and quality of hydraulic hose assembly are also put forward higher requirements. Based on the analysis of the relevant research, the paper develops the measurement and control system based on LabVIEW software, and develops the hydraulic hose pulse test system. The test results show that the system can perform pulse test with pulse frequency 0.5~1Hz and test pressure up to 70MPa for different types of hoses in the specified temperature range. The pulse waveform includes square wave and water hammer wave. All the test results are in line with the requirements of the test standards, which can meet the testing needs of enterprises for ultra-high pressure, large specifications and high-performance hydraulic hoses, and achieve the expected development goals.

The trajectory detection of composite fiber bundles holds significant importance for mechanical performance analysis and process parameter control. However, during the fiber bundle forming process, its surface presents challenges for existing detection techniques due to being difficult to access, having weak textural features, and exhibiting local high reflectivity characteristics. Addressing these issues, this paper proposes a novel measurement method based on 3D vision reconstruction technology to achieve high-precision measurement of fiber bundle trajectories in a non-contact manner. In this method, a "coarse to fine" stereo-matching strategy is introduced. Leveraging the constraints of binocular views, an initial matching strategy tailored for weak textural features is established. Furthermore, based on the locally obtained subarea images from the initial matches, a multi-directional fusion of feature enhancement and local stereo matching using deformation optical flow is proposed, enabling higher precision in 3D visual measurement. Through experimental verification using the composite shell winding process, the proposed method is demonstrated to efficiently and accurately capture the trajectories and winding angles of fiber bundles.

The residual stress magnetic measurement method is a new non-destructive testing method developed in recent years. This article studies the magnetic properties of ferromagnetic materials and the principle of stress relationship, develops a nine pole residual stress magnetic measurement instrument, and conducts practical engineering testing of residual stress in high-risk and crack prone areas of lifting equipment. A safety evaluation method for lifting equipment that considers both residual stress and working stress is proposed. The engineering application of residual stress detection in lifting equipment shows that the magnetic anisotropy detection method for residual stress is more direct, reasonable, fast, and convenient. The safety evaluation of lifting equipment needs to consider the impact of residual stress, and the safety evaluation of lifting equipment considering the impact of residual stress is more safe and scientific.

When the synonymous terminal of the traction transformer is grounded on the secondary side of the electric locomotive ground detection circuit, the DC bus of the traction converter will be charged abnormally before the traction converter starts, resulting in a hidden danger. Therefore, before the pulse is sent, the circuit principle of the ground detection circuit under this working condition is analyzed, the cause of DC bus abnormal charging is found, and the circuit of the existing ground detection circuit is optimized. The semi-physical simulation platform is built, and the optimized grounding detection loop is verified through the platform to monitor whether there is abnormal charging phenomenon in the DC bus under the fault condition. Simulation results show that the optimized grounding detection circuit can effectively solve the problem of DC bus abnormal charging of electric locomotive, improve the safety and stability of traction converter, and the optimized circuit is simple and easy to implement, and has high application value.

The measurement characteristics of chemiluminescence nitrogen analyser directly affect the measurement results of total nitrogen content. In order to promote the development of petroleum technology, the corresponding calibration method is studied to ensure the accuracy and reliability of the quantity value. On the basis of fully understanding the structure and working principle of the chemiluminescence nitrogen analyzer, the main measurement parameters were analyzed, and the calibration feasibility was analyzed combined with the corresponding standards and measurement technical specifications. The specific calibration method was determined, which was verified by experiments to provide technical basis for the effective traceability of the chemiluminescence nitrogen analyzer.

Oxygen index measuring instrument is used to measure the minimum oxygen concentration required for sample combustion in a mixture of oxygen and nitrogen gas under specified test conditions. However, there is no national calibration specification for the instrument, the metrological traceability system for oxygen index measuring instrument has not been established in China currently, and there is no means to evaluate the metrological performance of the instrument. This article proposes an effective calibration method for oxygen index measuring instrument by determining and studying its key technical parameters, basing on the analysis of the structure and measurement principle of oxygen measuring instrument, and combining with the national standard GB/T 2406.1-2008 Plastics - Determination of burning behavior by oxygen index - Part 1: Guidance. The experimental results show that the proposed calibration method is scientific and feasible. Furthermore, the uncertainty of the calibration results is evaluated, which proves that the calibration method is scientific and practical and provides reliable technical support for the quality insurance of oxygen index measuring instrument.

A numerical simulation study of Venturi overreading characteristics is carried out with Mixture model and Realizable k-e model, and a prediction model of Venturi overreading under low pressure conditions is proposed. Compared with the existing experimental data, it demonstrates that the numerical simulation results have high accuracy, the results indicate that the quality is the main factor affecting the Venturi overreading Meanwhile, the model in this paper is compared with ten classical overreading prediction models such as homogeneous model. It shows that the average prediction deviation of the model in this paper is 3.2%, ranking second, and the maximum prediction deviation is 7.3%. This study can provide reference for the study of Venturi wet gas flowmetering overreading model, and also provide a theoretical basis and options for flowmetering technology.

In recent years, the global oil price fluctuated greatly, offshore oil storage in the VLCC has risen gradually in foreign countries, the case of VLCC offshore oil storage has not appeared in China. In order to improve China's oil reserve system, improve effectively the profit of the old VLCC, the actual VLCC was taken as the research object, relevant research were carried out in the paper. In consideration of the actual situation of the aging equipment in the old VLCC, high potential risk of offshore oil storage and the importance of the multi-parameter monitoring so on, the design requirements of the multi-parameter monitoring system in the old VLCC for offshore oil storage were analyzed, the multi-parameter monitoring system in the old VLCC was structured by use of the software Python, the error of the monitoring system data was tested. The results shown that the errors of oxygen content and gas pressure in the multi-parameter monitoring system in the old VLCC developed were less than 2%, and the accuracy rate was more than 98%. So the multi-parameter monitoring system in the old VLCC for offshore oil storage is feasible and can provide a good guarantee for the offshore oil storage in the old VLCC.

The content of six impurity elements of cadmium, copper, lead, platinum, antimony and tellurium in high content silver was detected by laser ablation inductively coupled plasma mass spectrometry, which had the advantages of green, micro-loss, high efficiency and accuracy. In this paper, the key parameters of the energy density, the ablation spot, and the laser frequency are optimized. The optimal test conditions are: the energy density is 19.4 J/cm², the laser spot is 60μm,and the laser frequency is 10 Hz. The external standard method and the relative sensitivity factor method were used to test the content of the six elements, and the results of the two methods were consistent. The results showed that the t values were less than 2.57, indicating that the two methods had good consistency. Therefore, in the absence of a suitable series of standard samples, the relative sensitivity method of single standard sample can be considered to test the content of cadmium, copper, lead, platinum, antimony and tellurium in high content silver.

To address the problem of false positives and false negatives caused by complex scenes and large scale differences in optical remote sensing image detection technology, a detection algorithm based on improved YOLOv5s is proposed. This algorithm achieves accurate detection of targets without sacrificing detection speed. The algorithm incorporates the ECA attention mechanism into the main feature extraction network to improve the algorithm's ability to extract target features. Experiments were conducted on publicly available domestic datasets. The results show that the improved algorithm's average precision mean has increased by 4.9%. The average precision for airplanes, oil barrels, and overpasses has increased by 0.4 percentage points, 0.4 percentage points, and 19.3 percentage points respectively. This effectively improves detection accuracy while maintaining a similar detection speed.

In order to achieve automated strawberry harvesting and facilitate deployment on mobile devices, this paper proposes an improved model based on YOLOv5s. The main improvements are as follows: the lightweight MobileNetV3-Small is used to replace the original CSPDarkNet53 backbone, and the network structure is further pruned to enhance the model's efficiency and adaptability for mobile devices; the CBAM attention mechanism is incorporated into different levels of the network structure to enhance the model's sensitivity to feature channels and improve the feature extraction capabilities at different levels, thereby optimizing the model's performance; to enhance the detection accuracy of small objects, a dedicated small object detection layer is added to better capture the feature information of small objects; EIOU is used instead of the traditional CIOU loss function to avoid hindering model optimization due to unclear object boundaries, further enhancing regression accuracy. The experimental results show that the mAP@0.5 and fps of the improved YOLOv5s-MNSX-C-D model in this paper are 94.3% and 48.2f/s, respectively. Compared with the YOLOv5s, Faster R-CNN, SSD and RetinaNet model, the scores of mAP@0.5 and fps have improved. The effectiveness of the improved model is verified by the ablation experiments, and a good equilibrium is obtained.

To enable real-time detection of falls among elderly individuals, this paper presents a fall detection system based on the dynamic changes in human body posture. This system employs inertial sensors to collect posture data from elderly individuals. After preprocessing and feature extraction, the system utilizes the ReliefF algorithm to determine feature weights. Based on this, it establishes a fall risk index. Subsequently, four Support Vector Machine (SVM) models with different kernel functions are trained. The predictions from these models are then combined using a voting mechanism and integrated with genetic algorithms, resulting in a multi-kernel SVM ensemble model. Finally, a comprehensive algorithmic model for fall detection is established. Through experimental testing, this comprehensive algorithmic model achieves an accuracy rate of 99.3%, thereby confirming the feasibility of the system.

With the proposal of the "double carbon" goal, the traditional power system has gradually developed into a new power system with scenery as the main body, and with the change of energy structure and system form, the "renewable energy + energy storage" model will play an increasingly important role in the regulation and protection of the power system. However, with the increase of the installed scale of energy storage, it also brings safety problems. In recent years, the frequent fire accidents of energy storage power stations have brought resistance to the development of the industry. Aiming at the safety problem of energy storage power station, this paper analyzed the accident causes and fire development of energy storage power station, selected SOC(state of battery charge), discharge current, ambient temperature and other characteristic parameters as input parameters, combined with GA-Elman neural network algorithm, built a rapid prediction model of battery temperature, and verified the model. The simulation results show that this method can improve the prediction accuracy and shorten the prediction time. The system monitors the internal environment of the energy storage power station, identifies and judges the fire situation of the battery, and realizes a refined fire warning and management system of the energy storage power station.

A method for locating the damage in buoyancy materials of manned submersibles based on polyvinylidene fluoride (PVDF) spherical transducer is proposed to address the problem of difficulty in real-time monitoring and positioning the damaged buoyancy materials during manned submersible operations. A PVDF spherical transducer array based on the optimal quaternion matrix principle was designed to determine the precise location of the damaged buoyancy material in the damaged area. The sound source localization model was established using the time-delay difference method to obtain the exact coordinates of the fracture site of the buoyancy material. To extract effective sound signals from the fracturing of buoyancy materials, a wavelet threshold-based signal denoising method was designed. Based on the localization principle, a software and hardware system for buoyancy material damage location was intended, and the feasibility of the process was verified by constructing an experimental platform. The experimental results show that under a laboratory simulated deep-sea noise environment, the wavelet threshold-based sound signal denoising method can effectively extract the target signal of buoyancy material fracture, and the spherical transducer with the denoised sound signal can accurately locate the damage position.

Stray current corrosion is an important factor affecting the safe operation of buried steel pipelines. Aiming at the problems such as single function, low accuracy and poor usability of configuration software of existing stray current detection equipment, a stray current detection system based on STM32 and Labview for buried steel pipelines is designed, which can simultaneously measure a variety of stray current interference evaluation indexes. The system consists of two parts: acquisition system and host computer. The hardware circuit of acquisition system is designed in modular way, and the host computer is built by joint programming of Labview software and MATLAB software. The experimental results show that the measurement error of the system is less than 0.1%, which meets the standard requirements. The system has the feasibility of field application and popularization.

River crossing pipeline is an important part of China's oil and gas pipeline network system. For river crossing pipelines, the traditional technology of location, depth and corrosion protection layer damage detection is not suitable. Based on the investigation of the current typical river crossing pipeline inspection technology and equipment at home and abroad, this paper introduces a typical river crossing pipeline inspection equipment equipped with ROV, which is independently developed, and carries out inspection application on a domestic underwater pipeline crossing the Yangtze River. The field application results show that the ROV based detection technology of river crossing pipeline buried depth, negative protection potential and anti-corrosion layer quality is feasible, and the accuracy meets the requirements of field detection, which provides technical support and guidance for the field detection of typical river crossing pipelines in China.

It is necessary to study the aerodynamic force and the surrounding flow field state of the detector in the natural gas pipeline in the discharge process. Based on CFD（Computational Fluid Dynamics）methods, the ANSYS-ICEM and CFX software are applied to generate the three-dimensional compressible steady-state physical model, Flow field of the detector and the upstream and downstream pipelines was simulated. The k-ɛ turbulence model and the real gas state equation are simulated calculation. The aerodynamic force of the detector increases with the relative velocity of the medium. The aerodynamic force increases with the decrease of the discharge cross-sectional area, and the smaller the discharge area, the faster the growth rate. The pressure and velocity distributions of the flow field around the detector are analyzed. It shows that the method can provide data support and technical support for the design of detector speed control structure and the research of control scheme.

The available cutting time of the tool directly affects the machining efficiency and quality of the workpiece, and research and analysis should be carried out to improve the monitoring accuracy of the available cutting time of the tool. Therefore, this paper studies the improvement methods for the above problems, and proposes a production scheduling decision-making method and system for multiple CNC machining centers that includes the constraints of available cutting time of tools. The visual interface is used to realize the production scheduling management of multiple CNC machining centers. Verify the feasibility of the development system. The test results show that the system developed in this paper can optimize the production scheduling scheme through the allocation of workpiece processing tasks and the selection of processing equipment under the constraint of the available cutting time of the tool, which can effectively improve the utilization efficiency of tools and processing equipment, and improve the quality of the workshop while ensuring the processing quality.

In order to improve the adaptability and maintainability of a certain type of servo controller in the space environment, BM3803 has three-mode redundancy, EDAC and parity check fault tolerance design, which can meet the requirements of radiation resistance, long life and high reliability in harsh space environment applications. Therefore, an on-orbit reconstruction method of on-board CPU software based on BM3803 processor is proposed based on this project. In this method, the up-coding program block sent by the integrated processor is received through RS485 bus, and the up-coding program is stored and run by partitioning EEPROM and SRAM. Multiple verification of the receiving process, improve the reliability of the file upload process; The packet serial number, packet check and total check are transmitted down by telemetry to realize effective monitoring of the up-filling process. The load switching between the original program and the reconfigured program is realized by the combination of recharging load and sending instruction. Through testing, the correctness, rationality and reliability of the scheme are verified. At present, the scheme has been applied in orbit.

With the rapid development of computer technology and intelligent instrumentation in China, data acquisition and data processing technology have become one of the preliminary work for digital signal processing, which is widely used in many fields of production and life. LabVIEW through the virtual system front panel and system block diagram to establish virtual instrument graphic programming system, has been regarded as the standard data acquisition instrument control software, widely used in academia, industry and research room. Based on LabVIEW development platform, a set of data acquisition and processing system is designed, and serial communication, data acquisition, processing, storage, display and other functions are realized through simulation.

The development of intelligent detection system makes the running state of cigarette equipment continuously known, which provides a basis for fault detection and maintenance of cigarette enterprises. In order to improve production and reduce fault consumption, it is urgent to be able to detect the fault of the smoke machine in time or even to detect the fault of the smoke machine in advance, and to give the corresponding reliable solution in time, as well as the fault type, fault equipment and other information, reduce the time for workers to retrieve the source of equipment failure and think about the solution, and greatly reduce the huge loss caused by the failure of the smoke machine. Therefore, a method of fault diagnosis and pre-maintenance of tobacco machine is proposed, which is based on fault tree support vector machine state evaluation method for pre-maintenance and normal operation and maintenance of tobacco machine. This method can detect the machine fault in time and prevent the possible machine fault. According to the results, the fault type, solution and other information can be fed back to realize the pre-maintenance and normal operation and maintenance of the cigarette machine, which has guiding significance and reference value for the production and maintenance of cigarettes.

To solve the effect of micro-vibration on remote sensing satellite, a kind of integrated vibration suppression design technology of platform and payload is studied. According to the force path, satellite configuration and vibration suppression, a small satellite is integrated and the finite element model of the integrated vibration suppression structure is established. The results show that the vibration isolation efficiency of the integrated design structure for platform and payload is more than 80%. The max standard value of vibration response is less than 6 mg. The micro-vibration test of the integrated structure shows that the vibration isolation efficiency is more than 81%, and the max standard value of the vibration response is 5.5 mg, which is consistent with the FEM theory results. The integrated structure has passed the ground vibration test and flight verification with the satellite. The integrated design process and results can provide a reference for the integrated design of similar satellites to suppress vibration.

In this paper, a protocol conversion method is proposed for converting the PCI communication bus to the VME communication bus. This proposal includes a detailed description of the FPGA-based PCI bus IP core protocol analysis and the algorithm for designing a finite state machine for PCI-VME bus protocol conversion. To test the system-level interconnection, an eight-axis electric locomotive network control system test platform is used. The test results confirm that the bus bridge is capable of performing reliable PCI protocol analysis and VME data bus communication. The development of this equipment provides essential technical support for advancing the autonomous process of China's VME bus-based locomotive control system.

With the development complexity of civil aircraft, the development cycle and cost are also increasing. Model-Based Systems Engineering(MBSE) plays a significant role in the design of aircraft. In this paper, an architecture design approach based on MBSE applied in aircraft provide guidance system is introduced. Top-level requirements and stakeholder’s needs captured through scenario analysis are inputs to functional analysis. Functional architecture produced by functional analysis which includes functional definition and decomposition. Capturing requirements through functional architecture. Physical architecture which is implementation of functional architecture to ensure that the final solution meets stakeholder needs.

Due to magnetic flux concentrator (MFC) can cluster and aggregate magnetic field flux, so it can improve the GMR biosensor sensitivity, and the uniformity of the magnetic field in GMR biosensor detection area plays a great significance on GMR biosensor performance. Therefore, this paper employs the COMSOL software to study the characteristics of magnetic field generated by the magnetic flux concentrator. The influence of various parameters (length, thickness, etc.) of the magnetic flux concentrator on the uniformity of the magnetic field in GMR biosensor detection area had been investigated. The simulation results have certain theoretical guidance for high sensitivity GMR biosensors design.

To strengthen the application of digital twin technology in the power grid, the application of digital twin technology to substation grounding networks is studied. The corrosion state of the substation grounding network will affect the stable operation of the power system to a certain extent, so this paper proposes a non-destructive testing based on electrochemical corrosion detection technology to realize the corrosion process, and maps the detection results to the virtual model through digital twin technology. The results of engineering practice show that the method can be used to evaluate the corrosion tendency and corrosion rate of the substation grounding network and realize the long-term monitoring and automatic inspection of the grounding network operation and maintenance.

A device that can imitate human breathing movement is vital to evaluate the performance of flexible sensors and wearable equipment. It can be used to implement millions of fatigue tests with continuous movement at controllable conditions that is better than tests on human bodies. To imitate the breathing movement of humans, the pneumatic thoracic cavity has been employed in previous research. However, it has low position accuracy and large hysteresis of the driven module. To address these issues, a new humanoid thoracic cavity based on a multi-link parallel mechanism is proposed. Its morphology based on human anatomy is achieved by using the region-splicing method. The rib of the device is enhanced to promote its structural strength based on a support mechanism. The kinematics of the proposed mechanism is established and analyzed, and the kinematic model is evaluated by experiments. The tensile test of the flexible stretchable sensors and the repeated positioning accuracy test of the platform were conducted. The experimental results demonstrate that the proposed device possesses stability, reliability, and high control accuracy.

This paper presents a novel approach to address the lateral control issue in trajectory tracking for autonomous cars. Traditional model-free adaptive control algorithms have some limitations, prompting the development of an enhanced data-driven model-free adaptive control scheme. More precisely, inside a specified trajectory, the vehicle's issue of lateral control is converted into a problem of tracking the preview-deviation-angle. A dynamic linearized data model is developed for the lateral control of autonomous cars, taking into account the input and output data. To enhance the steering angle control rate, a time-varying proportional control term is incorporated. An enhanced trajectory tracking control technique for the MFAC system is proposed, followed by a demonstration of its convergence. The simulation findings demonstrate that the IMFAC scheme exhibits a superior output response compared to both MFAC and PID in both low-speed and highspeed scenarios. Furthermore, the IMFAC system is capable of achieving autonomous vehicle path tracking.

In order to meet the demand of high precision remote traceability, a remote traceability system based on optical fiber was designed and implemented. The system traced the time of the local time to the remote high-benchmark time source based on the high precision and high stability of two-way time transfer via optical fiber, and adopted the dual backup mechanism of primary and standby circuits to ensure its reliability. Experiment showed that the system can achieve the traceability effect with the time difference less than 2 ns and the daily frequency stability within 7×10^-15.

To enable stroke patients to achieve accurate, real-time, and stable rehabilitation outcomes in human-machine interaction, this study proposes a human-machine interaction system based on 7 degrees of freedom (7-DOF) collaborative robotic arm motion intent recognition. The patient's motion intent is achieved through the degree and direction of interaction between their palm and the end-effector of the robotic arm. The control system then uses the parsed motion intent to set and drive the direction and speed of the robotic arm's end-effector. Motion intent is primarily expressed through two indicators: motion direction and motion speed. The former is determined by the direction in which the patient applies force to the end-effector of the robotic arm. The latter is jointly determined by the magnitude of the applied force and the angle between the direction of the applied force and the tangent direction at the trajectory point. When the applied force is greater, and its direction is more aligned with the prescribed trajectory tangent direction, the speed of the robotic arm's end-effector increases. This, in turn, guides the patient to continually strengthen and improve their control ability in terms of the prescribed trajectory's direction and force intensity.

This article presents a novel design of integrated human vital signs simulator, whose function includes the simulation of blood oxygen, blood pressure and ECG. According to the light transmission model basing on the optical properties of biological tissues, the pulse oximetry simulation module is designed, including its overall structure, a analog finger, a light source driving circuit, etc. The non-invasive blood pressure simulation module is designed basing on oscillographic method, and a piston rod type variable air chamber pulse waveform generation mechanism is included, using PWM constant current control and ultra small subdivision technology to control the linear motor to achieve stable and accurate displacement, and the pulse wave is simulated according to the blood pressure envelope. ECG verification waveform is generated by STM32F407 chip basing on ARM. The experimental verification results show that the designed simulator can meet the requirements of JJF 1470-2014 Calibration Specification for Multiparameter Physiological Simulators, and can complete the measurements efficiently and accurately.

This design is based on a flexible wire transmission drive system in order to achieve a more supple, flexible, lightweight, and cost-effective functionality for the exoskeleton robotic hand. The entire hand is equipped with ten drive wires, and power is exclusively sourced from a single motor (a single-drive configuration). The control of motion output from this singular power source to the drive wires of the five fingers is efficiently achieved through the operation of a transmission structure and the on-off control of electromagnetic coils, facilitating the start-stop function. Furthermore, real-time control is maintained over two drive wires on each finger, enabling the generation of stroke movements in accordance with specific requirements. This innovative design results in a reduction in both the volume and weight of the exoskeleton hand's power device, leading to decreased production costs.

The Stacking-RF model is proposed to improve the low accuracy of a single classifier in bearing fault diagnosis tasks by using a stacking ensemble learning strategy. The model utilizes KNN, LR, SVM, BP, and RF as base classifiers, with RF employed as meta classifiers. Subsequently, we evaluate the performance between the single and stacking models, while investigating the most effective stacking combination to identify various failure modes of rolling bearings accurately. The experimental results of the XJTU-SY bearing dataset show that the diagnosis accuracy of stacking models (98.10%-99.55%) is significantly improved, compared with each member classifier (94.60%-98.98%). It can be demonstrated that the proposed Stacking-RF model can effectively integrate the valuable information of different classifiers, which ultimately leads to a higher accuracy (99.55%). This study shows that the stacking ensemble learning method has a good application prospect in rolling bearing fault diagnosis.

A feature extraction method called MWBF, based on the fusion of multiple wavelet bases, is proposed to address the issue of insufficient feature representation when applying a single wavelet base for wavelet packet transform on non-stationary rolling bearing signals. We constructed an initial feature vector by performing a multi-wavelet packet decomposition on the signal and extracting statistical characteristics. Subsequently, we optimized the feature selection using the Linear Discriminant Analysis (LDA) method. Finally, different machine learning models are employed for the classification of multiple fault modes in rolling bearings such as k-nearest neighbor (kNN) and logistic regression (LR). Experimental results on the XJTU-SY bearing dataset show that the diagnostic accuracy of the model using the MWBF method (99.75% ~ 99.83%) is significantly higher than that of the wavelet packet feature extraction method based on a single wavelet basis (95.22% ~ 97.46%). The MWBF-LR model achieved a classification accuracy of 99.83% when using LR as the subsequent classifier.

This paper introduces the necessity of aerospace cryogenic tank application, expounds the technical characteristics and composition of aerospace cryogenic tank, analyzes the technical difficulties of cryogenic fluid management, and combs the key technology matrix and main key technologies. According to the different service mission cycles of aerospace cryogenic tanks, four technical schemes of cryogenic tanks are introduced. The above four technical schemes are compared, analyzed and discussed, and the key contents of aerospace pressure vessel technology inheritance, development standards and key technology research are explained. Finally, the technical content is summarized and the development trend is introduced.

The NVH (Noise, Vibration, Harshness) of electric vehicles greatly affects driving comfort, and the NVH has become a key indicator for verifying the quality of their products, strengthening the research on noise testing technology can greatly promote the high-quality development of reducers. Given the problem that the noise data acquisition environment of the noise test stand is highly disturbed and difficult to eliminate, this paper proposes a whale optimization algorithm (WOA) with envelope entropy as the fitness function to carry out the improved variational modal decomposition (VMD) to decompose the noise signal of the speed reducer to obtain the IMF component, and to use the signal inter-correlation analysis of the IMF background noise to identify and filter out the noise reduction, and to complete the separation of the noise from the background noise of the speed reducer. The method is based on the iterative optimization of the number of decomposition layers and penalty factor of the VMD by WOA to find out the optimal combination of decomposition parameters and identify and reduce the background noise components based on the signal correlation analysis. Firstly, it is verified that the method has more effective decomposition performance than the traditional VMD algorithm by simulation signal test. Then the method is used for the background noise separation of electric vehicle gearbox, and the results show that the WOA-VMD proposed in this paper correctly separates the background noise signals in the mixed signals, and can effectively carry out the noise separation, and the decomposition filters out the background noise with an average reduction of the sound pressure level of 2.99 dB(A), and the average error of the sound pressure level with the baseline condition is 0.45 dB(A). Also, the noise reduction method using WOA-VMD reduces the sound pressure level by an average of 1.47 dB(A) than that obtained by the VMD algorithm, which has a better noise separation effect. The above conclusion proves that the present method improves the accuracy of noise testing of electric vehicle reducers.

Typhoon is a common natural disaster in coastal areas of China, which is characterized by high speed and strong destructive power. For the analysis of wind turbine under typhoon condition, it is necessary to measure and survey the wind load characteristics during typhoon passing by. Based on this, a reliable automatic unmanned wind measurement system was designed, and the typhoon Muifa was measured during the whole process with the system. The test results verified the feasibility of the wind measurement system, the results showed that: (1) Under the influence of typhoon movement and Coriolis force, the horizontal angle at the measurement point changed significantly, and there was a averaged vertical angle of about 9.1°; (2) The cross-wind turbulence is more significant, the turbulence intensity was the largest, and the integral scale of the turbulent vortex was small; (3) The probability density function of fluctuating wind speed obeyed the Gaussian distribution law, and in the high frequency range above 1 Hz, the spectral density energy of typhoon was larger than that of benign wind, and appropriate correction should be made when von Karman was used for simulation. The research methods and conclusions can provide reference for typhoon simulation and safety analysis of nearshore wind farms.

Bearing failure is one of the common faults in rotating mechanical systems, significantly impacting the reliability and performance of the machinery. However, due to variations in operating conditions and environmental factors, bearing failure data exhibits a multi-source domain issue, posing challenges for traditional fault diagnosis methods to be effectively applied. In this paper, a new multi-source weighted domain adaptive (MSWDA) framework is proposed, which is implemented by feature weighted and multi-layer feature extraction structure. To achieve feature-level distribution alignment, the minimum slice Wasserstein distance is used as a measure to measure the difference in feature distribution. Extensive experiments are conducted on the CWRU bearing datasets to validate the effectiveness of the proposed model.

This article focuses on the development needs of hydroponic cultivation technology in soilless cultivation environment, starting from the actual growth needs of hydroponic crops, and designs a complete intelligent monitoring system for hydroponic crop growth environment. It realizes remote real-time monitoring of environmental factors such as temperature and humidity, light, pH, CO₂, etc. in the hydroponic growth environment of crops. The system uses the CC2530 chip and ZigBee technology for data transmission as the core. Before the sensor data is forwarded by the aggregation node, the collected data is first fused to remove redundant information, and then uploaded to the cloud server through the RTL8720 module. At the same time, the entire system has universality and can be used for monitoring and regulating other environments.

In this paper, under the existing processing and testing technology conditions. The tooth profile data points of the gear are detected by a three-coordinate measuring machine. In order to improve the detection accuracy, the outlier data points are eliminated by using the distance formula based on the point to the straight line and the Pauta criterion. After completing the data point preprocessing, using B-spline curve fitting algorithm, realize the fitting of the involute of the gear. According to the fitting curve results and the involute error range of the standard gear, the involute cluster is calculated. Then use the equidistant curve formula to locate the involute closest to the measured data point. According to the radius of the base circle of the nearest involute from the data point and the coordinate value of the intersection point of the involute and the gear dividing circle, the cumulative pitch deviation ΔF_p of the gear and the radial runout tolerance of the ring gear ΔF_r are calculated, realize the error evaluation of gear. In order to optimize the processing technology of gear shaper, improve the accuracy of gear cutting, accurate data are provided.