bluuebunny/crossref_metadata_2025_split huggingface dataset:
A small variable rate underwater CAN-fiber data transmission system
Authors: Chen Zerui , Cheng Yanyan , Zhao Shijie 
Published: December 2024

Abstract
Currently, the primary data transmission methods underwater include optical fibers, radio waves, blue-green light, underwater acoustics, electric fields, and inductive coupling electric fields. Optical fibers are extensively utilized for underwater data transmission due to their benefits, such as long transmission distances, strong anti-interference capabilities, good environmental adaptability, and minimal limitations from navigating carriers. However, optical fibers face challenges in meeting high-speed transmission requirements beyond 10km due to communication distance constraints. As a result, optical fibers are often used as a replacement for the CAN communication system, but they come with drawbacks such as large volume and fixed speed. They lack dynamic testing and release-length experiments, supporting only one-time use. To tackle these issues, this paper presents a comprehensive design of a variable (adaptive) baud rate optoelectronic data transmission system for underwater applications with limited space. Lake trials were conducted under various conditions, demonstrating the system’s excellent performance. It ensures high-speed data transmission without interference and extends communication distances. This system holds significant reference value for the engineering implementation of composite data transmission systems constrained by space.
Design and implementation of wheel speed simulation system for civil aircraft
Authors: Li Xuesong 
Published: December 2024

Abstract
In the ground simulation test of civil aircraft braking systems, a number of functional, performance, and fault tests need to be carried out, and wheel speed is an important input parameter of the brake control box in the test. To meet the demand of the aircraft to provide wheel speed to the brake control box, a wheel speed simulation system was developed in this paper. The system can simulate the wheel speed state of the aircraft when the aircraft is sliding and braking, and transmit the wheel speed signal to the brake control box, which features portability and versatility, and the system is reliable and stable, which well meets the test needs of the brake system.
Pt100 temperature measurement sensors design and transducer simulation
Authors: Li Haoran 
Published: December 2024

Abstract
Temperature measurement (thermometry) is indispensable in industrial operations, aiding engineers in monitoring and evaluating temperatures. This study focuses on the utilization of Platinum Resistance Temperature Detectors (Pt100 RTDs) for precise thermal measurements, operating within an input simulation range of 0-10 V and tailored for measuring temperatures from 10°C to 90°C in chemical processes. Using the Siemens PLC300 simulation system as the power supply, the experiment involved connecting a Pt100 RTD to a DC balance Wheatstone bridge to assess thermal conductivity characteristics. The experiment in this research setup included a simulation of the circuit diagram using Multisim software, comprising a bridge configuration, amplifier circuitry, and voltage display. Results based on the Coefficient of Determination and Mean Squared Error demonstrated the sensor’s high accuracy and reliability. The experiment also underscored the importance of calibration and the impact of ambient conditions on measurement accuracy. The findings affirm the Pt100 RTD’s potential in industrial applications, offering valuable insights into its performance and areas for improvement in circuit design and component selection.
Research on the traceability method of direct current electrical energy value based on quantum voltage
Authors: Xu Xitong , Jia Fuquan , Bai Jingfen 
Published: December 2024

Abstract
After the redefinition of the International System of Units (SI), China has affirmed the establishment of a voltage primary standard based on the Josephson effect and a resistance primary standard based on the quantum Hall effect. Despite this, the derived measure of direct current (DC) energy has yet to fully realize its re-realization in physical constants. As the regulations and systems for DC energy measurement are newly established, the gradual adaptation to quantum changes and the enhancement of DC energy value capabilities are crucial. Integrating natural physical constants into the DC system is essential for establishing a foundation for a more streamlined future. This paper introduces two strategies for developing DC energy standards based on quantum voltage. Through theoretical analysis, the paper substantiates the viability of tracing DC energy to fundamental physical constants.
Design of high-precision multi-channel ice detection system
Authors: Zhou Nianpeng , Song Pan , Zhang Yang , Zhu Chunling 
Published: December 2024

Abstract
Effectively detecting aircraft icing caused by supercooled water is essential for ensuring safe flight. This paper utilizes ultrasonic pulse-echo technology to measure ice thickness. Unlike traditional ultrasonic detection devices, which are widely used for flaw detection but are bulky, inconvenient, and have low detection accuracy, this study develops a multichannel, high-resolution pulse-echo wireless detection system with a field-programmable gate array (FPGA) as the central processing unit. The system primarily involves the design of ultrasonic pulse-echo hardware, high-speed data processing, and wireless transmission. Ice detection experiments were conducted on an ice-aluminum double-layer structure. The test results indicate that this system can effectively detect the thickness of ice layers with a resolution of 1 mm.
Reliability and maintainability design of the micro ammeter
Authors: Chen Hongliang , Han Lin , Guo Jiaxin , Wen Xingxi 
Published: December 2024

Abstract
The reliability design and maintainability design of the micro ammeter were made in the paper. Firstly, reliability and maintainability models for the micro ammeter were established, and corresponding predictions and allocations were made. Secondly, this paper developed an analysis tool to improve the efficiency of reliability calculations greatly. Then, three micro ammeters participated in the 612-hour reliability test, and all successfully passed the reliability assessment.
Effect of multiple scattering on ultrasonic imaging detection for titanium alloy
Authors: Zhao Yang , Zhang Xinyue , Huang Yufeng , Yang Pinghua 
Published: December 2024

Abstract
Ultrasonic imaging for the micro-pores can evaluate the performance state of the parts. Wave multiple scattering caused by the micro-pores is significant for ultrasonic imaging. This paper provides an ultrasonic imaging method combined with a total focusing method (TFM) to inspect the micro-pores in additive manufacturing titanium alloys. Initially, a geometric model of the titanium alloy containing micro-pores was created using k-wave software for Phased Array Ultrasonic Testing (PAUT) detection simulations. Subsequently, the time-domain TFM algorithms were developed to generate defect images based on the simulation data. Finally, the influence of wave multiple scattering on TFM imaging has been analyzed.
Research on calibration method for flange-type apparatus to Measure Water Permeability of Concrete
Authors: Deng Xiaodong , Fu Yanxiang , Yuan Jing , Xu Yang , Ren Tingting 
Published: December 2024

Abstract
The water permeability of concrete is a crucial indicator to evaluate its ability to resist the infiltration of water or other liquids under pressure, which is vital for ensuring the stability and durability of building structures. The flange-type apparatuses are commonly used for detecting concrete’s impermeability and determining its impermeability rating. This article proposes a novel calibration method specifically designed for the flange-type apparatus to measure the water permeability of concrete, according to which the standard pressure measuring device is connected to the calibrated apparatus by a connection device designed and presented in this article in order to ensure sealing performance and operational safety during the experiment. Additionally, a host computer software is presented in this article for data recording and analysis to realize real-time recording and saving of experimental data, as well as generating pressure curves. The flange-type apparatus is calibrated mainly through the measurement of two metrological parameters, which are indication error and set pressure retention error. Experimental verification has confirmed that this method can simultaneously calibrate both parameters, which can significantly improve the accuracy and efficiency of on-site calibration of flange-type apparatus to measure the water permeability of concrete.
Research on static calibration method of wind tunnel balance based on CNN
Authors: Fu Huawei , Jin Feng , Xu Yue , Tao Aihua , Qiao Liyan , Liu Wang 
Published: December 2024

Abstract
A wind tunnel balance is an important device for force measurement experiments in vehicle wind tunnel experiments and is used to measure the aerodynamic loads acting on the model. The static calibration of the balance is a critical step to ensure measurement accuracy. The traditional calibration method uses a fitting method based on the least squares method, which could be better for dealing with the nonlinear errors of the balance. In order to further improve the calibration performance of wind tunnel balance, this paper proposes a fitting method based on the Convolutional Neural Network (CNN). The mapping relationship between input and output is established for a six-component balance. The optimal parameters of the network model are explored. Through the analysis of the prediction results of the network model, it is found that the CNN balance calibration method is generally better than the traditional least squares fitting method in suppressing the error caused by system nonlinearity. The prediction accuracy of its components reaches the advanced index of the national military standard, which improves the fitting accuracy of the balance formula.
Experimental study of ARtag-based indoor localization techniques
Authors: Chen Chaoda , Chen Ziyang , Li Kangxing , Guo Junrong , Huang Zhixing , Lu Xuan 
Published: December 2024

Abstract
To address the limitations of traditional indoor localization techniques in indoor environments, the ARtag indoor localization technique is proposed to determine the optimal recognition distance to optimize the robot’s localization performance in indoor environments. The performance of the robot at different distances is evaluated by setting up an ARtag at different distances in an indoor environment, testing and comparing the robot’s recognition accuracy and response time at these distances. The experimental results show that at a distance of 25 cm, the robot has the fastest response speed and the highest stability, with a recognition accuracy of 100% and a response time of only 0.39 ms. The ARtag indoor localization technique can significantly improve the robot’s localization performance at specific distances, which can provide a basis for optimizing the performance of indoor robotic applications.
Research on dynamic swing experiment of atomic gravimeter based on the inertially stabilized platform
Authors: Che Hao , Li An , Ma Jinxiu , Han Yu , Qin Fangjun 
Published: December 2024

Abstract
Based on the principle of quantum interference, with excellent accuracy, sensitivity, and stability, miniaturized and portable atomic gravimeters are gradually exploring the possibility of applying them to mobile platforms such as ships. However, the vibration noise brought by the dynamic environment has a great influence on it. To explore the stability and reliability of the atomic gravimeter in the mobile platform, we built a dynamic measurement system of the atomic gravimeter in the laboratory. With the help of the swing test bench, the swing of the roll and pitch directions was added to the system to simulate the wave environment, and the dynamic swing experiment was carried out. By changing different swing levels, the system can work in different vibration environments and measure the gravity value. The experimental results show that the atomic gravimeter can work normally in various swing environments, and the internal coincidence accuracy of 1.861 mGal is achieved. The measurement standard deviation of 2.194 mGal and the resolution of 1.160 mGal@48 s are obtained under static conditions. The measurement standard deviation of 34.200 mGal and the resolution of 9.538 mGal@48s are obtained under mixed swing conditions. Under the condition of mixed rolling, the standard deviation of the interference phase noise of the atomic gravimeter and its contribution to the resolution of gravity measurement reach 23.121 π mrad and 2.045×10−6 g/shot, respectively. Our work provides a new reference for the research of high-precision atomic gravimeters based on quantum sensing technology in the field of gravity measurement in ship-borne environments.
Detection of concrete reinforcement condition based on Decay Time Constant
Authors: Ren Xiao , Wu Haitao , Li Yong , Wu Zhaoguo , Bao Jiankang , Zhou Xiaolong , Zhou Qing 
Published: December 2024

Abstract
Reinforced concrete (RC) is widely used in all kinds of building facilities and electric power infrastructure. When its internal reinforcement structure is unreasonable or the quality of reinforcement is not up to standard, the performance of RC will be greatly reduced, resulting in a huge safety hazard. In this paper, a non-destructive testing method based on pulsed eddy current (PEC) for the state of internal reinforcement in concrete is proposed with concrete poles as the research object. The relationship between PEC response and the multiple parameters of the reinforcement has been analyzed, the decay time constant (DTC) is obtained, and a simulation model is built to demonstrate the connection between the DTC and the electrical conductivity, relative magnetic permeability, and thickness. Finally, a simulation model is constructed to verify the effectiveness of the proposed method for rebar condition detection.
Real-time 3D human pose estimation system based on multi-views
Authors: Cai Huiqi , Han Peng 
Published: December 2024

Abstract
Multi-view-based real-time 3D human pose estimation systems have seen widespread application across various domains, including sports, virtual reality, film production, and video surveillance. Despite significant advancements at the algorithmic level, the challenge of real-time performance remains a critical factor that restricts the full application potential of these systems. The synchronization and fusion of data from multiple cameras, high computational complexity, and the rigidity of system architecture contribute to the difficulty in balancing speed and accuracy within existing systems. In response to these challenges, a real-time 3D human pose estimation system based on multiple views has been proposed. This system achieves synchronization of data from multi-views, incorporates a lightweight model design, and implements parallel processing within its architecture. As a result, it is capable of outputting high-precision 3D human poses at a real-time speed of 25.56 FPS.
Innovation in nitrogen concentration measurement method based on TRIZ
Authors: Zhu Huibo , Song Wei , Xing Chunhua , Wang Lixin 
Published: December 2024

Abstract
The current UV curing (Ultra-Violet Ray Curing) process necessitates the absence of oxygen, and the industrial standard often achieves this by replacing air with nitrogen to attain a nitrogen concentration of 99.97%, thereby fulfilling process requirements. However, the existing nitrogen concentration measuring instruments with a response time of 30 s are incapable of directly ascertaining whether the nitrogen concentration within the chamber has already reached 99.97% prior to those 30 s. This paper systematically analyzes the issues in the current measurement system through the application of the Theory of Inventive Problem Solving (TRIZ), encompassing Function Analysis, Cause -Effect Chain Analysis, Engineering Contradiction and Inventive Principles [1, 2]. Furthermore, a novel nitrogen measurement scheme is proposed to clarify the temporal profile of nitrogen concentration during the displacement process, thereby providing a basis for accurately setting the nitrogen displacement time. This approach can lead to a reduction in nitrogen wastage and shorten production cycles.
Intelligent recognition of atomic saturated absorption spectra based on 1D Convolution Neural Network
Authors: Zhu Yuchen , Liang Changwen , Huang Yihang , Zhu Lingxiao 
Published: December 2024

Abstract
Laser frequency locking technology is widely used in quantum precision measurement, quantum simulation, quantum information, etc. The conventional frequency locking process based on the saturated absorption spectrum needs to find the target peak corresponding to a specific frequency manually. However, due to the complexity of atomic energy level structure and drifts caused by the parameters of semiconductor lasers in different environments, it is usually time-consuming and related to the experience of operators. To solve the above problems, a new approach based on machine learning has been proposed. Using the one-dimensional convolution neural network combined with the gradient analysis method, the recognition accuracy of 0.9784 and high precision of feature extraction have been achieved. The approach presented in this paper combines laser frequency locking in the quantum field with AI and addresses the bottleneck issue in intelligent frequency locking of semiconductor lasers, which holds significant reference value.
GRU-based anomaly monitoring method for injection molding equipment
Authors: Xie Xiaobo , Zhang Zilin , Hu Mingxue , Liao Jige , Zheng Gengzhe 
Published: December 2024

Abstract
For the prediction of abnormal states in the overall injection molding equipment, this paper proposes a novel idea of GRU-based anomaly monitoring for injection molding equipment, thereby enriching research in this field. Firstly, the existing multimodal data of injection molding equipment is mined, and a prediction model is trained using GRU as the benchmark model for simulating the prediction of abnormal states. Finally, practical examples are used for verification. Experimental results show that this method can effectively monitor the abnormal states of injection molding equipment. Currently, there are relatively few studies on the prediction of abnormal states in the overall injection molding equipment. The method proposed in this paper enriches research in this area and has practical significance.
Research on multi-scale defect detection methods based on image segmentation and multi-model parallel inference
Authors: Liu Xiali , Wu Guangdong , Wei Long , Cao Jialun , Deng Yaohua 
Published: December 2024

Abstract
To address the problem of insufficient extraction of tiny chipping features and low detection accuracy due to large-scale differences in photovoltaic (PV) silicon wafers defect detection, this paper proposes a detection strategy based on image segmentation and multi-model parallel inference. By segmenting the image and independently detecting the sub-images, we enhance the capture of local features and enlarge the receptive field. Furthermore, we utilize differentiated models for parallel inference, employing separate models for edge-chipping sub-images and full broken wafer images. With 10 parallel threads processing concurrently, this approach not only accelerates the detection process but also effectively improves the detection rate of small edge-chipping defects. The experimental results show that the proposed method in this paper is able to detect both broken wafer and edge-chipping defects, and the detection rate of edge-chipping defects is dramatically improved compared to the single model detection. The mAP of the YOLOv8m and YOLOv8m-p2 models are 0.704 and 0.771, respectively, which are improved by 30% compared to that before the unsegmentation.
Research on multi-sensor data fusion fault diagnosis method for rotating parts of injection molding machine
Authors: Liao Jige , Xie Xiaobo , Deng Yaohua 
Published: December 2024

Abstract
In the field of fault diagnosis of rotating parts of injection molding machines, traditional methods often rely on single sensor data, which makes it difficult to comprehensively capture the complex dynamic characteristics of the system operation, limiting the accuracy and reliability of diagnosis. To overcome this challenge, this paper proposes a multi-sensor data fusion fault diagnosis method combining graph convolution and Transformer neural network. A constraint-based Bayesian network structure learning algorithm is adopted to fuse vibration and current multi-sensor data, and a graph structure reflecting the basic dependency relationship between sensor data is constructed; a multi-head self-attention mechanism for weight allocation of the basic dependency relationship between multi-sensor data is investigated; and a model architecture taking into account the global and local features of multi-sensor data is constructed by combining graph convolution and Transformer neural network. Experiments show that the fault diagnosis accuracy of the method proposed in this paper reaches 99.20%, which is 5.4% higher than that of single sensor data, proving the effectiveness and accuracy of the method proposed in this paper. Finally, it is applied in the actual scenario of an injection molding machine, and the experimental effect is good.
Intrusion sound and light alarm method for radiation detection operation site based on infrared induction radar
Authors: Fan Yi , Hua Xiongfei , Ji Hui , Zeng Zhikun 
Published: December 2024

Abstract
A method based on infrared induction radar is proposed for intrusion sound and light alarms in radiation detection operation sites. We will use infrared sensors to sense the thermal radiation of human bodies or objects within the work site, and monitor specific areas through the constructed infrared light “wall”. When someone or an object enters the preset alert area and blocks the infrared beam, the sensor will quickly detect changes in thermal radiation and monitor and track potential intruders in real time, then trigger the alarm system. The alarm system emits strong sound and light signals through sound and light alarms to deter intruders and notify relevant personnel, ensuring the safety of the work site. The experimental results show that this method has the characteristics of high efficiency, sensitivity, and reliability, and is suitable for radiation detection operation sites and other places that require high safety requirements, effectively improving the level of safety protection.
Fault diagnosis of pneumatic control valve based on Bat Optimization algorithm and BP neural network
Authors: Xu Bing , Fei Dongyi 
Published: December 2024

Abstract
This article proposes a fault diagnosis model for pneumatic control valves based on a bat optimization (BA) algorithm and backpropagation (BP) neural network. The DAMADICS platform simulates the pneumatic industrial process control valve failures, and the fault signals are collected to construct the data set. A fault diagnosis model combining the Bat Optimization algorithm and Back Propagation neural network (BA-BP) is built, and four common faults are injected for experiments. The method is compared with Support Vector Machine (SVM), BP, and Bayesian optimized BP (BO-BP). Experimental results indicate that BA-BP has high diagnostic precision in the diagnosis of malfunctions in pneumatic valves.