bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of typhoon disaster loss based on the factor analysis-random forest model
Authors: Liu Xu , Liang Yingqi , Fu Xiang , Wang Zheng , Cai Wenbo , Zhao Dajun 
Published: March 2024

Abstract
Typhoon disasters in China’s coastal areas pose significant challenges for disaster prevention and mitigation, urban planning and national economic construction. This study aims to address the problem of incomparable disaster assessment indicators and low prediction accuracy of machine learning for small sample data. It establishes an index system based on the practical disaster investigation classification standards, which ensures data sources and uniformity. It also proposes a combination algorithm of factor analysis-random forest regression for direct economic loss prediction, which improves the typhoon disaster losses prediction. The results show that the optimized model has higher accuracy than single decision tree model, random forest model and factor analysis-decision tree model. The factor analysis method verifies the importance of influencing factors, which indicates that China faces great risks of coastal floods caused by super typhoons. The combination regression model can predict disaster losses reasonably, providing effective technical support for typhoon disaster assessment and management.
Research on numerical simulation method for 3D marine direct current resistivity
Authors: Ling Jiaxuan , Deng Wei , Liu Siqin , Chen Qingrui , Wei Shiwei , Li Mengmeng , Wei Shuliu 
Published: March 2024

Abstract
As one of the most important methods in marine electromagnetic exploration, the marine direct current (DC) resistivity method has been widely used in the exploration of marine minerals, oil and gas, as well as in large-scale engineered geological exploration and other fields. Efficient and high-precision forward algorithms are the foundation for an accurate quantitative interpretation of the marine DC resistivity method. We have implemented an efficient and high-precision forward modeling approach for 3D marine DC resistivity. First, the wave number domain anomalous potential control equations are obtained by performing a 2D Fourier transform along the horizontal direction based on the differential control equations satisfied by the marine DC anomalous potential. Instead of directly solving the 3D numerical simulation problem, we transform the 3D numerical simulation problem into multiple 1D numerical simulation problems in the wavenumber domain by dimensionality reduction for computational efficiency. Second, the boundary conditions of the governing equations are given to obtain the corresponding boundary value problems, and the anomalous potential is solved using the 1D finite element method in the wavenumber domain. Next, we perform a 2D inverse Fourier transform on the wave-number domain anomalous potential to obtain the spatial domain anomalous potential. Furthermore, compact operators are used to iteratively modify the potential and obtain high-precision numerical solutions. Finally, we demonstrate the correctness of the proposed algorithm’s solution strategy by using a hierarchical ocean model, and the efficiency of the proposed algorithm by using a spherical model.
Sea ice detection network for icebreakers in polar environments with attention-based deeplabv3+ architecture
Authors: Li Sheng , Wang Min , Wu Jia , Sun Shuo , Shi Minghang , Ma Rui 
Published: March 2024

Abstract
Shipborne sea ice detection aboard icebreakers plays a paramount role in polar navigation. The continuous evolution of deep learning semantic segmentation networks has promoted the advancement of sea ice detection tasks. At this stage, there are relatively few studies on shipboard sea ice detection, and the accuracy of polar sea ice detection will be reduced due to problems such as blurred sea fog and indistinct boundaries. In this study, a shipboard sea ice detection dataset is constructed, and a sea ice detection method that combines multi-branch attention feature alignment and multi-scale feature extraction is proposed. The heterogeneous receptive field enhancement atrous spatial convolution pooling pyramid module is designed, and the feature alignment module based on the attention mechanism is constructed, which strengthens the model’s extraction of sea ice features and elevates representation performance. Experimental results underscore the heightened precision of our approach in sea ice detection, to some extent alleviating the issue of missed detections in new ice. It constitutes a positive contribution towards advancing shipborne sea ice detection in polar environments.
Noise Generation Mechanisms of Marine Composite Pipelines Excited by the Internal and External Flows
Authors: Lin Yukun , Feng Baoming , Kang Rongjun , Liu Yongwei 
Published: March 2024

Abstract
The marine pipeline is an important energy transportation platform today. It can cause underwater noise pollution due to sound radiation caused by pipeline vibration during oil and gas transportation. This study focuses on the noise-generation mechanisms of marine composite pipelines under internal and external flow excitation. We investigated the impact of different materials, diameters, and wall thicknesses on the sound radiation characteristics of the pipeline under internal flow excitation. The relationship between radiated sound power and flow velocity was analysed. Additionally, we discussed the radiated sound field of marine composite pipelines under external flow excitation. Our results show that the radiated sound power under internal flow excitation is over 20 dB higher than that under external flow excitation in the 10 Hz to 2000 Hz frequency range. We conducted an experimental test near Zhoushan city, China, where the internal flow was driven by a pump and the external flow represented ocean currents. The results confirmed that the main noise-generating mechanism of marine composite pipelines is internal flow excitation. The numerical findings were validated by the experimental test. Overall, this paper provides a foundation for future investigations into the sound radiation of marine composite pipelines.
Acoustic scattering characteristics of underwater buried oil pipeline
Authors: Yin Jiancheng , You Xiangyu , Yao Yu 
Published: March 2024

Abstract
With the development of offshore oil resources, subsea oil pipelines have emerged. As a fast, economical, and safe way to transport oil resources, subsea pipelines are known as the “lifeline” of offshore oil projects. However, the detection of submarine pipelines is very difficult due to the complex underwater environment. One of the mainstream methods to detect submarine pipelines is the employment of sonar. Hence, the acoustic scattering characteristics of submarine pipelines play an important role in detecting themselves. In this study, the acoustic scattering model of the buried pipeline is established using the finite element method, and the scattering mechanism of the buried pipeline is analyzed. The effects of different frequencies, grazing angles, burial depth, and other factors on the acoustic scattering characteristics of the buried pipeline are investigated, providing the reference significance for detecting submarine pipelines.
An interpretation experiment on eddies’ role in sound propagation in the ocean using ray model
Authors: Kuang Xiaodi , Zhang Zhiyuan , Li Jingshi , Yuan chengyi 
Published: March 2024

Abstract
The relationship between mesoscale eddies and ambient acoustic propagation under different conditions were studied using high resolution ocean reanalysis products in South China Sea, which was summarized by a linear-equation representing the convergence zone change with respect to eddy signatures and source positions. Beyond the experiments scales, warm eddies “dragged” the sound propagation and cold eddies “squeezed” that in contrast, and the acoustic amplifying mechanism can be summarized as stronger(eddies), nearer(eddies) and deeper(source).
Random medium modeling and underwater acoustic field simulation
Authors: Zheng Guangxue , Piao Shengchun , Gong Lijia , Sun Yu 
Published: March 2024

Abstract
The von Karman random medium model is established based on the small scale random medium theory in this paper. Combined with the finite element theory, the numerical simulation of the sound field under this model is realized by using the spectral-element method, and the characteristics of the sound field are compared with those under the uniform medium underwater environment. The results show that the correlation length reflects the variation of the heterogeneous size, and the scattering wave generated by random disturbance may provide a more reasonable explanation for the amplitude and energy anomalies in some trial data.
High resolution spectrum estimation of virtual array based on FIM
Authors: Cai Yu , Liu Benqi , Pan Xiefan 
Published: March 2024

Abstract
Underwater small aperture sonar spectral estimation methods are limited by physical dimensions, resulting in insufficient azimuthal resolving power. In this paper, we propose that based on the Fourier Integral Method(FIM) equivalent to a virtual array of extended aperture, after using subarray smoothing, combined with the spectral estimation method, we get the improved FIM-CBF, FIM-Capon and FIM-MUSIC, and give the applicable conditions of these three improved methods, and use the virtual aperture expansion and noise averaging suppression, to achieve the improvement of the azimuthal resolving power of the spectral estimation method under the low SNR.
The Average Sound Energy Spectrum Produced by a Single Raindrop
Authors: Liu Shu , Wang Jian , Chen Yu , Wang Jiru , Zhu Jing , Chen Wei , Bian Yujie 
Published: March 2024

Abstract
The characteristics of underwater acoustic radiation generated by a single raindrop impacting the water surface play a fundamental role in the study of rainfall noise. However, the underwater sound signal generated by a single raindrop has great randomness in the amplitude of sound pressure, frequency range and energy size, so that the uncertainty of the sound energy spectrum curve of a single raindrop is relatively large. In this paper, by generating artificial rainfall containing only one size of raindrop, the acoustic radiation generated by artificial rainfall composed of about 136,000 raindrops with an equivalent diameter of 0.9 mm was measured by reverberation method. A smooth, continuous sound energy spectrum of single raindrop covering the full frequency band is obtained.
Error analysis of IMU pipeline bending strain detection based on full-scale test
Authors: Shi Tong , Liu Xiaoben , Lu Yanan , Zhang Haoning , Li Rui , Fu Kuan , Feng Qingshan , Huang Qiyu 
Published: March 2024

Abstract
The strain identification technology based on inertial mapping unit (IMU) internal detectors is currently a widely used internal detection technology for identifying pipeline bending strain both domestically and internationally. It calculates the bending strain of the entire pipeline through the detected centerline coordinate data. However, there are issues such as abnormal vibration and noise during the actual operation of the inertial navigation internal detector, as well as trajectory deviation during the detector’s operation. This issue leads to a certain deviation between the strain detected by IMU and the actual strain of the pipeline. This article utilizes a self-designed full size pipeline bending strain loading device to conduct full size pipeline bending strain tensile tests. Compare the internal detection data obtained from the experiment with the actual bending strain data of the pipeline and conduct error analysis. The research conclusion indicates that as the bending strain increases, the error between the IMU detection strain and the actual strain of the pipeline increases. When there is vibration noise, the maximum error is 0.077% for 0.33% true strain, and the maximum error rate for larger strain segments is 27.1%. The comparison between noise reduction detection data and true strain shows that when the true strain is 0.12%, 0.21%, and 0.33%, the average error is 0.0285%, 0.0315%, and 0.0555%, respectively. The research conclusion provides technical support and guidance for obtaining true strain of pipelines based on IMU internal detection in the future.
Design of ammonia leakage online monitoring system based on tunable diode laser absorption spectroscopy
Authors: Jia Ribo , Gao Junbo , Yang Shenhao , Cheng Junna 
Published: March 2024

Abstract
A real-time online ammonia volume fraction monitoring system based on tunable diode laser absorption spectroscopy (TDLAS) is designed to meet the demand for ammonia gas leakage monitoring in ammonia-fueled ships. The system uses a 1, 512 nm distributed-feedback (DFB) laser as the light source and a 5 m high-temperature Boss-Gas-Cell as the absorption cell. By applying a 4 Hz scan signal and a 31.4 kHz modulation signal to the laser current, the effective absorption signal of the gas is transferred to the high-frequency band, then the second harmonic (2f) signal about gas volume fraction is extracted by a digital lock-in amplifier from the gas absorption signal, and ammonia volume fraction can be calculated from the amplitude of 2f signal. The test results show that the ammonia detection accuracy in the range of 0-500 ppm can reach ±1% FS, the response time is less than 30 s, and the system measurement repeatability is less than 1%, which meets the needs of ammonia leakage monitoring in ammonia-fueled vessels.
Design of power supply system for portable aviation inspection equipment
Authors: Yang Yang , Ai Hao , Li Shibo , Xiao Guokai 
Published: March 2024

Abstract
Given that airborne electronic equipment may have a variety of wiring methods and may encounter a set of systems using multiple power supplies, it is necessary to take some measures on the circuit to ensure the normal work of the power supply and the post-circuit. A portable aviation detection equipment power supply system is designed in this paper. The system supports simultaneous access of two power supplies to identify and judge the input power supply and switch between the battery and the external power supply, effectively avoiding the security risks caused by battery backflow current. The battery power is monitored in real-time through the battery power detection circuit and will be reminded when the battery power is too low. Since the circuit uses a MOS tube to control the switching of the power supply, there is almost no voltage drop loss. In addition, the EMC protection circuit is set up at the power supply side to further improve the safety and reliability of the system.
Structure design and deformation analysis of double hydraulic cylinder deep-sea pressure simulator
Authors: Wu Jianmei , Li Yang 
Published: March 2024

Abstract
Because of the particularity of the deep-sea environment and the difficulty of on-site observation and research, it is particularly important to establish a deep-sea simulation system for research. Based on the high measurement accuracy requirement of deep-sea simulation equipment, a design scheme of a deep-sea pressure simulation device with a double hydraulic cylinder that can measure small water pressure changes is proposed. Firstly, the working parameters and pressure principle of the design are introduced, and then the deformation of the deep-sea pressure simulation device is analyzed. The mathematical model of piston feed and pressure without considering the deformation of the sealed pressure cylinder and the mathematical model of piston feed and pressure considering the deformation of the sealed pressure cylinder are established respectively. Finally, the relationship curve is analyzed by using origin software. The results show that when the deep-sea pressure simulator is used to simulate the underwater environment, it is necessary to consider not only the influence of liquid compression on the pressure but also the influence of deformation on the pressure.
Global sensitivity analysis of fatigue life based on structural health monitoring
Authors: Liu Shiyu 
Published: March 2024

Abstract
Fatigue cracks are one of the most common causes of structure failure. Structural health monitoring (SHM) has shown important practical significance in ensuring the safety of civil infrastructures by providing continuous, accurate, and reliable monitoring at low cost. Given that data provided by SHM involves various types of uncertainty, this study presents the interval-random hybrid model for fatigue life based on fatigue crack growth theory. By introducing global sensitivity indices, the influences of different variables on the variance of structural fatigue life are analyzed. To enhance computational efficiency, the method is proposed by combining the space partition with unscented transformation (SP-UT).
Stress detection method of pipeline based on vibration characteristics
Authors: Li Jinzhou , Liu Xiaoben , Shi Tong , Zhang Hong , Wang Hao , Sha Shengyi , Bu Mingzhe 
Published: March 2024

Abstract
Stress concentration during the operation of long-distance transmission pipelines is an inevitable problem. In this paper, a pipeline stress detection method based on vibration characteristics is proposed. We establish a finite element model for knock detection and determine the law of vibration frequency and pipeline stress. The reliability of the model is verified by the knock detection experiments. It is found that the natural frequency stress of the vibration of the sample shows a close correlation under the knocking effect. The study results provide an innovative process for pipeline stress detection.
Application of calibration-free wavelength modulated spectral absorption technique in temperature measurement under ultra-short optical path
Authors: Ren Yunhao , Gao Feng , Duan Xiaoming , Cai Yu , Li Yachao , Zhou Yihui 
Published: March 2024

Abstract
The measurement of gas temperature parameters is of great significance in scientific research and industrial production. Wavelength modulation technology, as a non-contact optical detection means, has the characteristics of strong anti-interference ability and is widely used in various complex and harsh environments. The accuracy of temperature measurement is affected by short optical paths and weak absorption. In this paper, a calibration-free wavelength modulated ultra-short optical path measurement system is established, and the selection rules of spectral lines under the ultra-short optical path and weak absorption are proposed. The measurement results of wavelength modulation without calibration are in good agreement with those of thermocouple temperature measurement, and the relative error is less than 10%.
Noise reduction analysis of deformation data based on CEEMD-PE-SVD modeling
Authors: Duan Qingda , Xia Hua , Huang Ya 
Published: March 2024

Abstract
In the field of high slope deformation monitoring, the deformation data obtained are often characterized by high volatility, strong nonlinearity, and noise content, due to the influence of factors such as the surrounding environment, human operation, and the complexity of the project. To overcome these problems, this paper proposes deformation data based on the coupling of complementary ensemble empirical modal decomposition (CEEMD), permutation entropy (PE), and singular value decomposition (SVD). Firstly, CEEMD decomposition is performed on the deformation data. Secondly, a randomness test is performed on the obtained modal components, and if the entropy value of the component arrangement entropy is greater than 0.5, SVD decomposition will be used for noise reduction. Finally, the components that meet the conditions are reconstructed to realize the noise reduction of the deformation data. The results show that the algorithm model has an excellent noise elimination effect, which can reflect the internal detail information of deformation data and provide a well-established method for future research on the processing of deformation monitoring data.
Multi-View consistency-based point cloud registration method with low overlap rate
Authors: Cui Zhiqiang , Liao Zhaoyang , Lin Xubin , Sun Kezheng , Cheng Taobo , Zhou Xuefeng 
Published: March 2024

Abstract
Accurate and efficient workpiece measurement is crucial for workpiece processing and quality monitoring. Non-contact optical measurement methods have gained more attention due to their simplicity, efficiency, and flexibility compared to complicated and inefficient contact measurement methods. Multi-view registration of measurement data is a key issue in workpiece measurement, as it relies on the system’s geometric accuracy and motion stability, presenting challenges such as the insufficient overlap of multi-viewpoint cloud data and cumulative error. To address these challenges, this paper proposes a multi-view planning and registration algorithm with a low overlap rate. The multi-view planning algorithm employs a greedy method to plan the scanning viewpoints of the workpiece to obtain complete point cloud data efficiently. The multi-view registration algorithm extracts features using a multi-scale geometric feature extraction network, matches the features based on the Hungarian algorithm, builds a graph, and optimizes workpiece positions based on the G2O algorithm for multi-view registration, effectively reducing cumulative error. Measurement experiments on blade workpieces confirm the feasibility of the proposed algorithms.
Temperature compensation for piezoresistive pressure sensor based on deep learning on graphs
Authors: Xue Mingyao , Fang Ting , Hu Chenghe , Dong Chong , Han Jiaming 
Published: March 2024

Abstract
With the escalating demand for precision in piezoresistive pressure sensors to cater to a wide spectrum of applications, a significant challenge emerges due to the material properties of these sensors, which induce a substantial temperature coefficient. This limitation restricts the operational temperature range and is further exacerbated by ambient temperature variations, resulting in pronounced nonlinearity in sensor responses. To address these challenges, A new method using Graph Neural Networks (GNNs) is introduced to address nonlinearity and temperature drift in piezoresistive pressure sensors. GNNs improve the sensors’ accuracy and reliability across different temperatures, expanding their applicability. Test results show a notable accuracy enhancement, with a maximum full-scale error below 0.05% and even lower in specific ranges (under 0.04%). This precision makes the method ideal for industrial pressure sensor applications and production, offering significant benefits.
Research on low power consumption of wireless MEMS methane sensor
Authors: Zhang Haiqing 
Published: March 2024

Abstract
Aiming at the problem that the high power consumption of traditional methane sensors does not realize the comprehensive detection of coal mines underground, based on MEMS methane detection technology, wireless methane sensing low-power research is proposed. First of all, based on the analysis of power correlation, we select the modularized design with low power, which includes power supply, sensing element driver, acquisition, and processing modules. We study the change of sensitive resistance, response time, and power consumption of the MEMS methane sensing element and sensor in different operating modes. Meanwhile, experimental tests are carried out. The experimental result shows that under the premise of ensuring the timeliness and stability of methane gas detection, the power consumption of the wireless MEMS methane sensor in one minute is only 2.4% of the traditional catalytic methane sensing element.