bluuebunny/crossref_metadata_2025 huggingface dataset:
Cluster analysis of MNIST data set
Authors: Pei Yuanzhao , Ye Linlin
Published: February 2022

The full name of MNIST is Mixed National Institute of Standards and Technology database. This is a very large database of handwritten digits. The data set is divided into two parts: the first part is 60,000 training set images, the second part is 10,000 test set images, each image is composed of 28×28 pixels, and the value of each pixel between 0 and 1, based on this data set, not only can a judgment method for handwritten numbers be designed, but also the accuracy of the recognition algorithm can be compared through the test set. At present, machine learning experts around the world use different learning methods to test the data set. At present, the mainstream methods with higher accuracy are: support vector machines, convolutional neural networks, and naive Bayes classification. This article tries to use the clustering method to train the MNIST data set. First, the image data of the training set is converted into 60000×785 rows of two-dimensional matrix data, one of which is the real value of the image, and then through K-means the algorithm divides the data into 10 categories, uses the T-SNE algorithm to reduce the dimensionality, and visualizes by randomly selecting 1000 training data. It is found that the clustering effect of the numbers 0, 6, and 8 is the best, while the number 1 is completely invisible, the accuracy of K-means algorithm clustering is 83.33%. In order to further explore the test effects of different clustering methods on the data set, other clustering methods are introduced: MiniBatchKMeans algorithm. When the cluster is set to 10, the clustering of data 6 and 8 in MiniBatchKMeans the effect is good. At this time, the accuracy of the MiniBatchKMeans algorithm clustering is 87.67%. By comparing the test results of other algorithms, it is found that the MiniBatchKMeans algorithm is better than the K-means algorithms and the clustering result of is better than some supervised learning methods.
Intelligent fault diagnosis system design and implementation of diaphragm pump based on artificial intelligence
Authors: Xu Xiaoqing , Guo Zhihao , Liang Xiaowei
Published: February 2022

This article designs and implements a fault diagnosis system for diaphragm pump. The key components of the diaphragm pump are equipped with three-axis vibration intelligent sensor to collect vibration data, the edge side completes the data pre-processing, and then transmits it to the cloud platform through NBIoT. For the non-linear, non-smooth complex system, the time frequency representation is obtained by continuous wavelet transformation, after compressing the time frequency representation as the input of the two-dimensional neural network model, using the two-dimensional convolutional neural network model for training and monitoring, to complete the identification and positioning of diaphragm pump fault.
Research and application of calibrating device for pipeline detector
Authors: Hu C A , Li G , Ouyang H M , Du W B
Published: February 2022

Underground pipeline is an important part of urban infrastructure, known as the “lifeline” of the city. At present, there are many incomplete data of urban ground line pipelines, only part of the data is not high precision or inconsistent with the status quo, which is easy to cause serious accidents in the construction of underground pipelines often cut or damaged, so it is particularly important to establish a reliable underground pipeline database as soon as possible. Pipeline detectors currently occupy tens of thousands of units in the market, and the annual growth rate of 20%∼30%. At present, the positioning error (sounding error) of pipeline detector is faced with the problem of undetermined and untraceable. The relevant calibration device established in this paper can provide reliable data and provide strong guarantee for the data of pipeline detector.
Analysis of fatigue characteristics of dual-drive axial piston motor cylinder block
Authors: Shi W W , Deng H S , Hong D B , Shi X Y
Published: February 2022

To improve the service life of axial piston motor with dual-driving, the cylinder model of axial piston motor with dual-driving is established, the cylinder force is derived and used as the boundary condition, based on the results of finite element analysis, the S-N curve of the cylinder material is modified and fatigue solution is carried out. The results show that: the main stress and strain of the cylinder block are mainly located at the cylinder block hole and the flow distribution window, the stress concentration is generated at the structural mutation, and the stress and strain are the largest; the cylinder block will be repeatedly subjected to high-pressure oil action will produce fatigue damage, fatigue damage mainly occurs at the location of higher stress.
Design of Pipeline Flowmeter Calibration System Based on PLC Control
Authors: Liu Cong , Zhang Xu , Gai Xuhui , Xu Lenian
Published: February 2022

In order to solve the problems of error and data storage and calculation in the calibration process of traditional pipeline flowmeter due to human factors, a calibration system based on PLC control was designed on the basis of a standard method. PLC controls the frequency converter through CAN bus, and then controls the motor to supply water to the calibration system. At the same time, the PLC extended IO modules are used to collect the real-time flow data of the standard meter and the tested meter. PLC and upper computer through Ethernet information exchange, and the use of the Kingview software to achieve the basic control of the PLC and the data display, data storage, data calculation. The test data show that when the errors of the standard table meets ±0.5%, the errors of the tested meter can meet ±1%, and the calibration efficiency is high and the data are accurate. Therefore, compared with the manual calibration method, the calibration system based on PLC control can better control the errors, and is more convenient for data storage and calculation, and has higher practical value.
Research of Intelligent Video Surveillance System based on Artificial Neural Network
Authors: She Chuyun , Zheng Runlan , Yang Qiaoyin , Liang Shaowei
Published: February 2022

In order to improve the video monitoring capabilities, this paper designs an intelligent video surveillance system. Firstly, it analyzes the current problems of video surveillance, and then proposes intelligent requirement in three aspects. In the training process, the model is obtained by searching, gray conversion, and training. Finally, the correctness of this system is verified by the actual application in real station.
Intelligent Electrical Fault Detection and Recognition Based on Gray Wolf Optimization and Support Vector Machine
Authors: Zou Xin , Lv Rongxin , Li Xinyan , Chen Huan , Wang Ziqi , Yang Hanning
Published: February 2022

With the increase of electrical equipment, the hidden danger of its failure also rises. Aiming at the problem that the classification accuracy of the basic traditional classification algorithm is not high when judging whether the electrical failure occurs, this paper proposes a Gray Wolf Optimization Support Vector Machine model to improve the recognition rate of electrical diagnosis, referred to as GWO-SVM. We first collected the most common linear (incandescent lamps) and non-linear (microwave ovens) household electrical appliances in normal working and arc fault waveform signals in real life, and then carried out frequency domain feature extraction. Finally, compared with no-optimized SVM and BP neural network, we employed the gray wolf optimization algorithm to optimize support vector machine, and the accuracy of GWO-SVM reaches 90%.
A Layered Settlement Monitoring Device for Foundation and Application of its Assembly Method
Authors: Qian Bin , Guo Changqi , Li Bingyi , Zhan Xinjie , Fan Mingqiao
Published: February 2022

For the vacuum preloading foundation treatment project, water covering construction is often carried out during vacuum pumping. It is very inconvenient for the monitoring personnel to measure the readings in the water with layered settlement instruments and equipment. This paper introduces an assembly method of foundation layered settlement monitoring device, including the assembly process of the monitoring device itself and the assembly process of embedding the monitoring device in the foundation. It has the advantages of simple structure, simple installation and stable data. It can realize the in-situ monitoring of different foundations, save manpower and material resources, and greatly improve the monitoring efficiency and accuracy.
Design and Cutting Test Analysis of Chinese Cabbage Harvester
Authors: Cao Liwen , Miao Shuaitong , Gu Lizhi
Published: February 2022

Chinese cabbage is a major vegetable widely planted in most areas of my country. With the increase in market demand and the growth of Chinese cabbage planting area, traditional manual harvesting can no longer meet the development needs of the times, and agricultural mechanization has become a trend. In view of the actual production situation of Chinese cabbage in China, the important parts of the Chinese cabbage harvester are designed based on the TRIZ theory, and the working principle of the Chinese cabbage harvester is clarified. The designed Chinese cabbage harvester includes the functions of pulling, transporting and cutting roots, and completes most of the work required for manual harvesting. Carrying out cutting experiments to explore the best cutting parameters in the root cutting process is conducive to the subsequent design and research of the Chinese cabbage harvester.
Experimental Study on Performance and Base Compaction of Cement Stabilized Macadam with Vibration Mixing
Authors: Wang Bingchen
Published: February 2022

In order to improve the engineering application prospect of vibration mixing cement stabilized macadam, the performance of vibration mixing cement stabilized macadam and the compaction performance of base course are studied in this paper. The proportioning scheme of cement crushed stone stabilized soil is designed, and the proportioning of cement stabilized crushed stone is established by compaction method and testing compressive strength. Through the indoor test, the 7-day and 28-day unconfined compressive strength of ordinary mixing and vibration mixing are compared. The results show that the 7-day strength is increased by 38.6% and the 28-day strength is increased by 32.5%. The compaction test of ordinary mixing and vibration mixing cement stabilized macadam base is carried out. The research results show that the compactness of vibration mixing cement stabilized macadam after rolling for one time and final rolling is increased by 1.5% and 3.1% respectively. The research shows that the improvement of compaction technology of cement stabilized soil pavement under vibration mixing can improve the performance index of pavement and can be popularized.
“5G+TSN+DT” Solutions for Digital Factory Key Issues of Networking, Precision, Automation and Digitalization
Authors: Wang Han , Li Shaobin
Published: February 2022

With advanced technologies of the Internet of Things (IoT) and Artificial Intelligence (AI) developing, key issues and challenges of networking, precision, automation and digitalization are arising for digital factory (DF) top designing and establishing. Advanced technologies of 5G, Time Sensitive Network (TSN) and Digital Twin (DT) provide new solutions for DT planning and operating. This study explores “5G+TSN +DT” practical solutions for DF designing and building, especially in the aspects of networking, precision, automation and digitalization, which is of great significance to understand the opportunities and challenges of DF industry development.
Intelligent Software Service Configuration Technology Based on Association Mining
Authors: Wang Fei , Zhao Zhengjian , Wang Zhichao , Ma Minchao , Lu Junjie
Published: February 2022

Association relationship and types between software service configuration parameters determine that the configuration items must meet the corresponding rules and constraints in parameter value and setting order. However, the distribution of software services and the architecture based on the loose coupling of heterogeneous components make the association of configuration parameters more concealed. The correlation and constraints of configuration parameters are crucial to ensure system configuration. When deploying, migrating, and updating systems, violating constraints will lead to configuration errors, resulting in system failures. To minimize the loss caused by configuration errors, association rules between configuration items can be mined to avoid potential incorrect settings. This paper proposes an intelligent software service configuration technology based on association mining by analyzing configuration items. The sample data of the configuration file is extracted from the open source code base, and the configuration file is parsed to obtain the configuration item name and value. Then mine the association rule of each configuration item pair based on the configuration item name, value, and type. According to the mined configuration constraints, configuration item error detection, cascade update and value recommendation are performed. Finally, the proposed method is tested and evaluated on six typical open source software, and the experimental results prove the accuracy and effectiveness of the method in this paper.
Target Detection of Marine Ships Based on a Cascade RCNN
Authors: Wu Lei , Chen Shicai , Liang Chengcheng
Published: February 2022

Faster RCNN is a classic algorithm with high accuracy and a wide range of applications in the field of target detection, and Cascade RCNN is improved based on Faster RCNN. The article applies the Cascade RCNN method to the detection of marine ship targets. It improves the traditional Faster RCNN algorithm and extracts areas that may contain pedestrians through RPN. In this paper, a multi-layer cascade detector is used to distinguish and classify the target area, and an algorithm is designed to detect and verify the data set. In the end, it is concluded that the Cascade RCNN algorithm performs better than the traditional algorithm.
The Optimization of Multi-classifier Ensemble Method Based on Dynamic Weighted Voting
Authors: Yang Ping , Fang Jian , Xu Junting , Jin Guanghao , Song Qingzeng
Published: February 2022

Generally, on the same data set, different deep learning classification models will achieve different performances. The existing weighted voting method can combine the results of models, which can improve the performance of classification. On the other side, its classification accuracy is affected by the accuracy of all models. In this paper, we proposed a dynamic weighted voting method. Our method dynamically selects models on different data sets, and integrates them according to their weights, thereby improving the classification accuracy. We evaluated the methods on three data sets of CIFAR10, CIFAR100 and Existing, which increased the accuracy about 0.65%, 0.91%, and 0.78% respectively compared with the existing weighted voting method.
Development of End Beam Obstacle Avoidance Program based on ABB Automatic Painting Programming
Authors: Li Jingyu , Shao Wangsheng , Li Xiaochuang , Sun Yuhang
Published: February 2022

In order to improve the company’s production efficiency, in response to the call of the country to accelerate the industrial automation, the company’s developers have independently developed a painting line parametric automatic programming system based on ABB robot using C++ language, the automatic spraying of the main beams of the crane is realized. The automatic programming system can only spray the main beam of the end beam without end. The end beams obstacle avoidance program is optimized based on the automatic programming system, which aims to control the robot to avoid the end beam of the main beam, so that the system can spray the main beam of the crane with the end beam normally.
The Risk Analysis Model Design of the Emergency-Food Supply under Blizzard Conditions
Authors: Liu Yan , Dong Xinpeng
Published: February 2022

This work aims to improve the risk analysis system of the preparation and the transportation of emergency food and to improve the safety, efficiency, and speed of the emergency-food supply in China. We combined the fuzzy analysis and the convolutional neural network to identify the main risk factors of the emergency-food supply. The identification of the risk factors by the fuzzy analysis improved the food-safety risk analysis system. On the other hand, the use of the convolutional neural network to determine the early-warning threshold and to optimize the transportation plan of emergency food effectively improved the safety, efficiency, and speed of the emergency-food supply.
Convolution Neural Network for Renal Function Assessment Based on Glomerular Filtration Rate
Authors: Wu Congzhong , Wang Lulu , Yang Zhen , Wang Jing , Han Li , Li Fei
Published: February 2022

Absract

✓Objective: To develop a Convolution Neural Network (CNN) and discuss its performance in the estimation of Glomerular Fifiltration Rate (GFR) for patients with chronic kidney disease (CKD). Methods: A total of 112 patients with chronic kidney disease were enrolled in this study. The GFR is measured by 99mTc-DTPA renal dynamic and used as standard GFR after normalization by body surface area imaging. We established a CNN model and verified the performance of the model by comparing the GFR predicted by the model with the standard GFR. It turned out that the CNN could better evaluate the GFR of patients which is superior to the CG formula, MDRD formula, CKD-EPI formula and GRNN model. Conclusions: The CNN significantly evaluated GFR for patients with CKD, and it showed better performance than traditional methods and GRNN model and closer to the results of 99mTc-DTPA. The experimental results demonstrated that CNN could be used to estimate GFR.
Design of Intelligent Drip Infusion Control System Based on Huawei Internet of Things Platform
Authors: Hu Yingkun , Chen Guangfeng , Lan Maokun , Zhou Jingfeng
Published: February 2022

In order to solve the problems of heavy labor burden, cumbersome work, patients can not get comfortable care and low medical efficiency, an intelligent drip infusion control system based on Huawei Internet of things platform is designed. The system first describes the system implementation technical principle, hardware design idea, Huawei cloud platform upper management application solution idea, using NB-IoT to communicate with Huawei cloud platform, Huawei cloud server design, web back-end, web front-end and mobile app design process. The test results show that the system has the functions of web page and mobile app remote centralized monitoring, remote speed regulation and remote run out alarm, which reduces the burden of nurses, reduces the contact time between nurses and patients, and improves the medical efficiency.
Driving Capability, a Unified Driver Model for ADAS
Authors: Sun Bohua , Zhai Yang , Li Yaxin , Deng Weiwen , Zhao Shuai
Published: February 2022

To allocate driving privilege in a reasonable way in shared control for intelligent vehicle, the study on driving capability, the unified driver model for ADAS in the longitudinal and lateral scenarios was proposed, which can improve the safety and comfort for intelligent vehicles as well. Driving capability is defined and analyzed and car-following stimulate in longitudinal scenario and moving double lane change stimulate in lateral scenario were designed. Data collection was conducted in Driver-In-the-Loop Intelligent Simulation Platform (DILISP). Driving capability identification model was established basing on Hammerstein process and Principal Component Analysis (PCA) was used to decouple and reduce the dimension for the key parameters in Hammerstein identification model. The classification is done basing on the particle clustering algorithm and the evaluation equation for driving capability was calculated by Multiple Linear Regression (MLR). Results show that the proposed evaluation method for driving capability in the longitudinal and lateral scenarios can achieve accurate and reliable evaluation results.
Research on Fast Pre-Processing Method of Tunnel Point Cloud Data in Complex Environment
Authors: Zhu Ming , Leng Biao , Xiao Chunhong , Hou Gaopeng , Yao Xiangchen , Li Kai
Published: February 2022

In recent years, the application and research of three-dimensional laser scanning technology in tunnel engineering has continuously emerged, while the shortcomings still exists. This paper conducts research on quick preprocessing method of tunnel point cloud data based on three-dimensional laser scanning. For streamlining the tunnel point cloud model data, comparison analysis discusses are applied to both the downsampling algorithm and the point cloud denoising method respectively. Simulation experiments are introduced to compare the effects of different downsampling algorithms applied to the tunnel point cloud model, analyze the sampling efficiency and performance of each algorithm. Combining with statistical denoising and radius denoising algorithms, a distance denoising based on an iterative filtering model method is proposed. The result shows that this method is suitable for the tunnel point cloud model during the construction period with complex environment, and can effectively eliminate most of the point cloud noise.
Research on Heating and Temperature Control System with Solid Electric Heat Storage Based on Improved Smith Predictive Control
Authors: Liu Chunlei , Wang Yi , Zhang Mengru , Wu Wenjie , Cai Yang , Zhang Zhihong
Published: February 2022

In view of the hysteretic nature of the heating and temperature control system with solid electric heat storage, this paper intends to control the related equipment by improved Smith predictive control method relying on the solid energy storage heating demonstration project of a university. This control method adds an additional regulator to the Smith predictive control method; in this manner, it can appropriately reduce the sensitivity of model accuracy, enhance the adaptability and effectively overcome the influence of delay on system stability, thus creating better robustness. The experimental results indicated that the temperature control accuracy could reach ±1°C.
Study on the Influence of Residual Deformation in Old Subsidence Area on the Safety of New Buildings
Authors: Sun Shiguo , Jia Xinxin , Wei Shuaiying , Xiao Jian
Published: February 2022

The new buildings on the surface of the old subsidence area and the ecological restoration and treatment of the subsidence area are the hot and difficult problems behind the mining of many mining areas. Taking the subsidence area of Laohutai Mine as an engineering example, this paper uses the finite element numerical simulation software to systematically simulate and analyze the stress and deformation of the buildings to be built, raft foundation and foundation soil in different deformation areas. It reveals the deformation and movement law of the building structure at the geometric center area, the maximum negative curvature at the inner edge, the maximum positive curvature at the outer edge and the inflection point of the intersection of positive and negative curvature. The middle zone has the greatest influence on the vertical deformation of the building structure, and the inflection point of the positive and negative curvature has the greatest influence on the inclined deformation of the building structure. The stability of the foundation at four different working conditions is evaluated. Accordingly, it is proposed that reasonable design should be carried out for different regions in architectural design to ensure the safe use of architectural structures.
Study on Temperature Control and Crack Prevention Scheme for Lining Concrete Construction of Spillway Tunnel in Summer
Authors: Ma Shouxun , Hu Shuhong , Wei Baolong , Zhang Lei , Xin Jianda , Sun Changmao , Zheng Lei
Published: February 2022

In view of the characteristics of high strength and thin thickness of spillway tunnel lining concrete, the temperature field and stress field of spillway tunnel lining concrete during summer construction are simulated by using large-scale finite element software SAPTIS, and the risk assessment of lining concrete surface flow maintenance time and internal water passage time on its own cracking during summer construction is analyzed. For a project, the simulation calculation is carried out, and the results show that under the given working conditions, compared with non-flow curing, the surface point stress of surface flow curing for 28 d decreases by 1.34 MPa, and the minimum crack safety factor increases by 0.79 ; the internal middle point stress decreases by 0.75 MPa, and the safety factor increases by 0.31. The cooling time of internal water in lining concrete is longer than the time when the maximum temperature of concrete occurs, which cannot effectively reduce the maximum temperature of internal temperature, but it can reduce the internal tensile stress to a small extent and improve the safety factor. The research results have guiding value for thermal control and crack prevention of lining concrete.
Analysis on Energy Saving Transformation of Central Heating System in Existing Buildings
Authors: Sun Yony , Zhang Hongxi , Xu Huixuan , Liu Yang
Published: February 2022

By comparing the indexes before and after the energy-saving transformation, the heating system in the northern cold region after the transformation of the existing pipe network is studied. Taking a renovation project in severe cold area as an example, the energy-saving renovation of heating system is analyzed. Through data collation and comparison, after the renovation, all energy-saving indexes of heating pipe network meet the requirements of heat users, and good results are achieved. After the renovation, the water consumption and electricity consumption in heating season are saved by 24% and 21%, and the cost of heating system is saved by 335,100 yuan compared with that before the renovation. After the transformation, the user satisfaction is increased by 59%, and the energy-saving effect is remarkable.
Numerical Simulation Study of Anti-Large Deformation Bolt Structure
Authors: Wang Rongrong , Zha WenHua
Published: February 2022

In order to study the mechanics of the anti-deformation hemp anchor rod, and numerical simulation was carried out with ANSYS finitengen software, the mechanics characteristics of a single spiral anchor and a hemp anchor rod under different spiral rings were compared and analyzed. The results show that for a single screw anchor, the number of spiral turns has a greater effect on the stretch elongation rate of the anchor test piece, and the more spiral turns, the greater the elongation when the anchor is destroyed, and the structural deformation of the anchor rod force is greater, which is the main reason for the increase of the elongation with the increase of the number of spiral rings. The hemp anchor is affected by the number and spacing of spiral rings, and does not produce yield stage and destruction stage when stretching, which indicates that the hemp anchor has better ability to resist shearing and deformation. In engineering applications, the ability of hemp anchor rod to resist large deformation of surrounding rock can be effectively improved, the effect of roadway support can be ensured, and the research results provide theoretical basis for the application and parameter design of hemp anchor.
Study on Rock Cutting Mechanism and Efficient Shield Tunneling Control in Mixed-Ground with Different Strengths
Authors: Shi Hongbing , Huang Xing , Liu Bin , Luan Shuai , Li Linfeng , Liu Shaoran , Lu Xingli
Published: February 2022

Mixed ground condition exerts very significant influences on the rock fragmentation mechanism, rock cutting efficiency, and operational parameters selection of the shield boring machine. In order to reveal the rock cutting mechanism when the shield tunnel boring machine advances through the mixed grounds in Line 13 of the Shenzhen Metro Tunnels, according to several linear cutting tests were conducted using a constant cross-section disc-cutter and five rock types with different strengths. The change of disc-cutter cutting force and rock boreability index were analyzed, and some suggestions were proposed to fulfill the safe and efficient tunneling of the shield machine in mixed ground conditions. The results of this study can offer useful suggestions for the operation parameter selection of the shield tunnel boring machine tunneling through the mixed ground in the Shenzhen Metro Line 13 and similar projects.
Vibration Mitigation of Tunnel Structures via a Novel Passive Tuned Mass Damper
Authors: Cheng Z P , Qiao X L , Cheng Z B
Published: February 2022

In this work, a novel passive tuned mass damper is introduced to mitigate the harmful vibrations in tunnel structures under moving trains/vehicles. First, a mechanism with inertial amplification effect is introduced. The transfer function of an SDOF system with the proposed inertial amplification system (SDOF-IAM) is presented. The adjustability of the proposed IAM is discussed. Second, replacing the SDOF by using the SDOF-IAM system, a novel passive tuned mass damper is proposed. Superior to the traditional TMD, the geometrical parameters of the present IAM-TMD can be changed to adjust to the vibration mitigation property of the TMD. A parametric study is also conducted to evaluate the influences of the geometrical parameters on the critical parameters of the TMD (the anti-resonant frequency, the effective mass parameter, and so on). Superior to the TMD, the vibration mitigation effect of the IAM-TMD can be adjusted effectively, which can be used to suppress vibrations of tunnel structures under moving trains.
The Feasibility Study of Quantitative Flaw Detection of Grouted Sleeve Connection by Ultrasonics
Authors: Zhang Lu , Fang Zhenmin , Li Hongyu , Zhao Yunliang , Jiang Zishi
Published: February 2022

Grouted sleeve connection has been widely used to connect rebars in prefabricated concrete (PC) structures. Due to the complexities of materials and internal configurations, the flaws or defects are inevitable, which may cause the negative impact on the mechanical properties of reinforcement sleeve connection, ultimately leading to the hidden risk in the PC structures. It is challenging to explore a reliable and efficient flaw detection method for the grouting sleeve. In this paper, an active grout defects detection approach for grouted sleeve connectors using UT wave measurement is proposed, where piezoelectric-lead-zirconate-titanate (PZT) transducer are mounted on surface of the sleeve as transmitter and receivers; and experimental study is carried out to validate the feasibility of the proposed method. In order to investigate the effect of grout defects on UT wave measurement, five grouted sleeve specimens with different degrees of the artificial grout defects are designed and analysis on the PZT transducer was used for measurement. By comparing the PZT transducers measurement of different specimens with different grout defects under an identical impulse excitation signal, the grout defect is detected. Experimental results indicate grout defect leads to decrease in PZT transducers measurement UT energy, the relationship between the UT energy ratio and the internal grouting flaws is established: the UT energy decreases with the increment of flaw size. Therefore, the UT method provides a feasible option to evaluate the internal flaws of grouted sleeve connection.
Research on Anti-Noise Ability of Offshore Platform Health Monitoring System Based on Strain Mode Structural Damage Identification
Authors: Ye Hailin , Liu Lu , Qi Wenhao
Published: February 2022

Strain modal structural damage identification is widely used in offshore platform health monitoring. However, due to the limitation of structural testing technology, the complex marine environment around the offshore platform structure is superimposed, such as wind, wave, tidal current and other dynamic environments. In the actual test, many factors interfere with modal identification and damage detection, which brings a certain amount of errors to the identification of modal parameters of offshore platform structure, Thus, the accuracy of loss identification of offshore platform structure is affected. In this paper, the health monitoring system of offshore platform based on strain mode structural damage identification is studied by analyzing the damage identification effect of strain mode structure under different degrees of environmental noise superimposed by single member damage and multi member damage. The research results show that strain mode damage identification can not only accurately locate members, which has better anti-noise ability, but the anti-noise ability under multi member loss is also lower than that under single damage condition. For single member damage, it has better damage identification effect within 10% noise level, and for multi member damage, it just has better damage identification effect within 8% noise level. The research results of this paper find out the base number of damage identification ability of jacket platform structure based on modal parameters, which is a great significance for using strain modal damage identification method in offshore platform structure health monitoring.
Nonlinear Stress Analysis of Key Joints of Steel Truss Bridge
Authors: Liu Zhenlei , Sun Hao
Published: February 2022

Steel truss bridges are widely used in bridge engineering for the advantages of good ability of spanning capacity, construction and light self-weight. Main trusses are the main stressed component of steel truss bridge. And the main truss are made of truss members connected by integral joints. So, the safety of integral joints are very important for normal operation of steel truss bridge. The superstructure of the continuous steel truss bridge with double decks was selected as the engineering example. The software, MIDAS/CIVIL is used to establish the full finite element model of the continuous steel truss bridge. Based on the results of the full bridge model, the 3D finite element model integral joint considering material nonlinearity was established by software Abaqus. The stress distribution of the integral joint under the unfavorable external force were analyzed and compared. The results showed that the most parts of the integral joint are in elastic stage, and the stress distribution is inhomogeneous. The stresses of integral joint are greater than that of truss members. Except for individual stress concentration areas, the stresses in the center area of the integral joint are greater than the stress at the edge. All in all, the safety of integral joints for the engineering example can be guaranteed.
Research and Analysis on Fire Simulation of Underground Pipe Gallery Based on Pyrosim Software
Authors: Chen Yang , Liu Gang , Gao Hong
Published: February 2022

In order to analyze the influence of the abrupt section of the underground pipe gallery on the spread of smoke, this paper uses fire simulation software to establish a numerical model to study and analyze the pipe gallery with abrupt sections. The simulation results show that under the condition of working condition 2, the temperature of the pipe gallery increases and then decreases. The highest temperature is at 182s, and the highest temperature is 698.51°C; in the sudden change section, the smoke spreading rate decreases, and the smoke peak The surface presents a “convex” shape; due to the thermal effect pressure difference and the mechanical wind pressure difference, when the wind speed in the pipe gallery is 0-50s, the wind speed changes greatly; when the inlet wind speed is 1m/s, the wind speed in the pipe gallery will eventually Tend to be 2.5m/s.
Analysis of Data Exchange between BIM Design Software and Performance Analysis Software Based on Revit
Authors: Yang Ting , Xu Jinyi , Nie Xian
Published: February 2022

Performance-based analysis of buildings is a process of guiding the design process through simulation analysis in the early stage of engineering design, and it is an inevitable trend of BIM technology development. In the process of BIM forward design, it can effectively improve the efficiency of forward design. How to break through the data interaction barrier between design software and performance analysis software and effectively use BIM design software data for performance analysis is an urgent problem to be solved in the industry. Based on the Revit platform, this paper analyzes the methods and requirements of BIM data transmission, realizes the performance analysis of data conversion based on Revit through cases, and finally summarizes a set of prerequisites, methods and key points of development requirements based on secondary development. The research results will provide reference for the later development of data conversion plug-ins and other tools, and promote the development of BIM data collection and transmission.
Study on Optimal Operation of Boiler-assisted Air Source Heat Pump Heating System
Authors: Sun Yong , Liu Shuaishuai , Liu Yang , Chen Jing , Yang Yiwei , Xue Keli , Shi Yongjiang
Published: February 2022

An electric boiler assisted air source heat pump heating system is used in a residential heat exchange station in Shijiazhuang for heating. However, in the actual operation process, there is a problem that the heating demand cannot be met. This paper studies the heating system. The results show that the problems are mainly manifested in two aspects: on the one hand, the operation strategy of heat exchange station is unreasonable; On the other hand, because of the close arrangement of heat pump units, the array cold island effect is produced, which affects the heating operation. Put forward a reasonable operation scheme for two aspects, and provide a reference case for central heating operation of air source heat pump in northern China.
Synthesis of Hexagonal Gold Nanoparticles and Study of its Optical and Near-field Distribution Properties by Discrete Dipole Approximation
Authors: Ge Linlin , Tang Junqi
Published: February 2022

Anisotropic nanostructures with unique physical and chemical properties have been widely applied in optical, electronic, magnetic, and catalytic fields. This paper described the synthesis of hexagonal gold nanoplates (HAuNPs) by trisodium citrate and ascorbic acid. The optical and near-field distribution properties of hexagonal gold nanoplates were studied by discrete dipole approximation method. Simulation results showed that due to the shape anisotropy of HAuNPs, the optical properties of HAuNPs were significant differences between the horizontal orientation and vertical orientation.
Analysis of Microstructure and Performance of Laser Cladding WC-Fe316L Alloy on the Surface of 27SiMn Steel
Authors: Li Chuanzhu , Ni Yuji , Wang Mingdi , Lu Zheng , Zhang Pengcheng
Published: February 2022

In order to solve the problem that the hydraulic support column is affected by the sulfur and chlorine water vapor in the mine, the inner wall will inevitably have different forms of defects, such as surface wear and surface corrosion. The pure Fe316L cladding layer and the WC-Fe316L composite cladding layer with the hard phase WC mass fractions of 10%, 20%, and 30% were prepared on the 27SiMn steel substrate for hydraulic support column by homogenizing broadband laser head. The phase composition, microstructure, microhardness and wear resistance of four cladding samples were studied. The results show that the pure Fe316L cladding layer forms a good metallurgical bond with the substrat, the surface of the cladding layer has no crack defects, and the shape is good. The average microhardness of the pure Fe316L cladding layer is increased by 1.4 times compared with the 27SiMn steel base, and it is increased to 331.2HV0.5. At the same time, the wear rate of the pure Fe316L cladding layer is reduced by 30.8% compared with that of the matrix. The mass fraction of WC particles is 10 %, 20%, and 30% of the WC-Fe316L cladding layer’s microhardness is 1.6, 1.7 and 2.0 times higher than that of the 27SiMn steel matrix to 369.9HV0.5, 408.6HV0.5 and 481.6HV0.5, and each WC The wear rate of Fe316L composite cladding layer was reduced by 45.8%, 66.0% and 82.3% compared with the matri composite cladding layer. The addition of WC particles helps to strengthen the solid solution strengthening and fine-grain strengthening of the composite cladding layer, and the unmelted WC particles also strengthen the dispersion strengthening effect of the composite cladding layer.
Characteristic Curve Fitting Method of Wind Speed and Wind Turbine Output Based on Abnormal Data Cleaning
Authors: Han Bitong , Xie Hongbin , Shan Yu , Liu Ruichen , Cao Shengxian
Published: February 2022

The characteristic curve of wind speed and power reflects the output state of wind turbine, and its characteristics are helpful to the accurate prediction of wind power. With the improvement of wind turbine power generation technology and other engineering applications, the data collected by SCADA system contains a large number of outliers, which makes it difficult to accurately fit the wind speed power curve. Firstly, this paper analyzes the types and causes of outliers in the actual data of wind turbines. Then, an abnormal data cleaning method based on Tukey’s method considering the operation parameters of wind turbines is proposed to clean the data of 12 wind turbines. Finally, the new data are clustered separately in the wind speed range by K-means, and the wind speed power characteristic curve is fitted. Compared with the uncleaned data, this method can significantly improve the fitting accuracy of wind speed power characteristic curve.
Semantic Segmentation and Defect Detection of Aerial Insulators of Transmission Lines
Authors: Wang Shengli , Zhou Zhangpeng , Zhao Wenbin
Published: February 2022

Aiming at the problems of low accuracy and poor generalization ability of insulator defect detection in complex aerial images by existing insulator defect detection algorithms, the possibility of using semantic segmentation technology to simplify insulator features in complex images is explored. The semantic segmentation model DeepLabv3 is cascaded with the target detector yolov3 to realize the semantic segmentation of insulators in aerial images and the detection of defects. The experimental results show that the use of the strategy of semantic segmentation and target detection can increase the accuracy of insulator defect detection by 12.58%, which effectively improves the performance of the detection model.
PARS-NET: a novel deep learning framework using parallel residual conventional neural networks for sparse-view CT reconstruction
Authors: Khodajou-Chokami H. , Hosseini S.A. , Ay M.R.
Published: February 2022

Sparse-view computed tomography (CT) is recently proposed as
a promising method to speed up data acquisition and alleviate the
issue of CT high dose delivery to the patients. However, traditional
reconstruction algorithms are time-consuming and suffer from image
degradation when faced with sparse-view data. To address this
problem, we propose a new framework based on deep learning (DL) that
can quickly produce high-quality CT images from sparsely sampled
projections and is able for clinical use. Our DL-based proposed
model is based on the convolution, and residual neural networks in a
parallel manner, named the parallel residual neural network
(PARS-Net). Besides, our proposed PARS-Net model benefits from a
loss based on the geodesic distance to effectively reflect image
structures. Experiments have been performed on the combination of
two large-scale CT datasets consisting of CT images of whole-body
patients for different sparse projection views including 120, 60,
and 30 views. Our experimental results show that PARS-Net is 4–5
times faster than the state-of-the-art DL-based models, with fewer
memory requirements, better performance in other objective quality
evaluations, and improved visual quality. Results showed that our
PARS-Net model was superior to the latest methods, demonstrating the
feasibility of using this model for high-quality CT image
reconstruction from sparsely sampled projections.
Production and measuring methods and procedures in precision optical cavities production
Authors: Beneš Jiří , Procháska František , Rail Zdeněk , Tomka David , Pravdová Lenka , Číp Ondřej
Published: February 2022

This work presents the development of the production process of individual parts of the Fabry-Perot type laser resonator. It describes the acquired knowledge in the field of production of very precise optical standards, cavities, and lenses. In addition, it describes the measurement methods used in production. The work is intended for industry and science.
Remote data acquisition with wireless communication for a quad-GEM detector
Authors: Bhattacharyya R. , Sahu S. , Sahu P.K.
Published: February 2022

The advantages of remote data acquisition (DAQ) in
experimental setup are manifold. It is useful to store the time
series data continuously without human intervention. Moreover,
specific modification in the experimental setup for remote DAQ is
also beneficial to avoid proximity to the radiation zone in the high
energy physics experiments, and thus radiation exposure is
minimized. In this article, a novel method of DAQ is explored for
Gas Electron Multiplier (GEM) detectors employing HC-12 wireless
serial communication module following both SCPI and non-standard
protocols. Dedicated Laboratory Virtual Instrument Engineering
Workbench (LabVIEW) based software interfacing is also developed for
communication and control. As a proof of concept of the feasibility
of the proposed method, the typical gain of a quad-GEM detector is
estimated. Measuring instruments (a quad-scaler built in-house and a
commercially procured picoammeter) are interfaced with the wireless
transmission system for this purpose. Data transferred through
wireless communication are utilized for estimating the normalized
gain of a quad-GEM detector for a given interval of time. The
details of the design of the wireless communication system,
fabrication procedure, remote DAQ system, experimental arrangement,
and results are presented in this article.
Coupled mode of cloud, atmospheric circulation, and sea ice controlled by wave-3 pattern in Antarctic winter
Authors: Wang Yunhe , Yuan Xiaojun , Cane Mark A
Published: February 2022

This study examines coupled relationships among clouds, atmospheric circulation, and sea ice in Antarctic winter. We find that the wave-3 pattern dominates the leading covariability mode among cloud, atmospheric circulation, and sea ice. Both horizontal transport and vertical motion contribute to cloud formation, resulting in maximum cloud anomalies spatially between maximum meridional wind and pressure anomalies in the coupled system. The radiative effect of the clouds related to the wave-3 pattern can generate sea ice anomalies up to 12 cm thick in one month in the Amundsen Sea. It also strengthens the sea ice anomalies that are directly induced by low-level atmospheric circulation anomalies. In addition, the radiative forcing of the leading cloud mode in the lower troposphere is suppressed by the dynamic and thermodynamic effects of the circulation anomalies. These discoveries provide a better understanding of Antarctica’s interactive processes, and also offer physical evidence for climate model validations.