In the process of intelligent bone age assessment for Chinese ethnicity, generalized convolutional network models are not well targeted in extracting specific features in medical skeletal images and lack specificity in training and predicting skeletal developmental features in different ethnicities. This study aims to propose a hybrid improved deep residual network model, ZH05-DL-ResNet50, focusing on intelligent bone age assessment for Chinese ethnicity. In the process of building the ZH05-DL-ResNet50 model. First, multiple overlapping texture enhancement layers are introduced through combinatorial optimization, which can better characterize the global features of hand bone radiographs while using less texture information, reducing the interference of redundant information and freeing up computational power; second, the China-05 ' s spatial focusing mechanism is designed so that the model can intelligently focus on the region of interest, efficiently locate and automatically learn key image information; Finally, the model can be used for intelligent bone age assessment of Chinese ethnicity by constructing a 50-layer residual depth network, the superposition enhancement layer and the focusing mechanism are fused to form the ZH05-DL-ResNet50 model, which mitigates the problem of gradient disappearance and explosion caused by the increase of network depth, and reduces the information loss and depletion of the multi-layer texture superposition features in the focus region of interest. The training was performed using the Chinese ethnographic dataset provided and created by Tsinghua Changgeng Hospital, where 10 % of the radiographs were used as the test set and the rest as the training and validation sets. The overall performance of the models was estimated by comparing the average accuracy and loss values of different models, and the overall performance between model training and model design was evaluated using the data distribution (Distribution) and histogram of bias weight distribution (Histogram). The results showed that the average accuracy of the bone age estimation model was 98.1 % and the average error on the test set was 0.312 years. Evaluation of the model visualization and accuracy comparison showed that the model performed well and was more appropriate and accurate than other bone age estimation models. Therefore, the first intelligent bone age assessment model for Chinese ethnicity, ZH05-DL-ResNet50, was created, which differs from the untargeted nature of other intelligent bone age assessment models, and is used to train and predict hand bone radiographs more appropriately and accurately for Chinese ethnicity.

As an essential component of urban infrastructure construction, polyethylene (PE) pipelines face the challenging task of underground detection due to the complex and dynamic nature of the subsurface environment, diverse installation paths, and the inherent insulating properties of PE materials. In order to address the non-excavation detection of buried PE pipelines, this paper proposes an acoustic method based on the long short-term memory (LSTM) neural network. The study begins by analyzing the propagation and reflection mechanisms of elastic waves in the pipe-soil coupling system, and a impact excitation source is designed to generate the excitation signal. After establishing the experimental environment and collecting experimental data, a comprehensive analysis is conducted, and the LSTM neural network is employed for data classification to determine the presence of buried PE pipelines. Through neural network training, accurate identification of the PE pipeline's existence and prediction of its burial depth are achieved, providing an efficient and reliable solution for buried PE pipeline detection. The practical results demonstrate the significant application prospects of the combined acoustic method and LSTM neural network in buried PE pipeline detection. This research contributes a novel solution to the field of non-destructive PE pipeline detection, with both theoretical and practical implications.

Since polyethylene (PE) pipes are widely used in urban infrastructure development, their precise localization is paramount. The research on the nonexcavation localization of buried PE pipes using acoustic methods holds significant practical significance due to the expensive costs and permit issues associated with traditional excavation-based localization methods. A method based on elastic wave reflection for positioning buried PE pipes is proposed in this article to address the challenges of nonexcavation localization of buried PE pipes. First, fundamental theoretical analysis and finite element simulation were carried out to investigate the propagation and reflection of elastic waves in the soil-PE pipe-coupled system, guiding subsequent experiments. Second, an electromagnetic-driven excitation source is designed to locate buried PE pipelines based on the elastic wave signals reflected by the pipeline. The excitation source is driven by Gaussian pulse-modulated sine waves. Finally, the back projection algorithm (BPA) imaging method generates cross-sectional images of buried PE pipes. The potential economic and environmental benefits of this method are substantial, as it promises to streamline the process of pipeline inspection and maintenance, leading to cost savings. Furthermore, the research paves the way for future advancements in nonexcavation technologies, contributing to the sustainable development of urban infrastructure. In conclusion, this study provides a practical and innovative solution for the nonexcavation positioning of buried PE pipes, influencing the widespread application of acoustic methods in infrastructure management.

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

Stray current corrosion has become one of the important failure factors of buried steel pipelines. In this paper, the propagation law of stray current in soil was simulated and analyzed based on Comsol Multiphysics software, and the relationship between the decay law of stray current potential and soil resistivity was obtained. The effect of the damaged area of the anticorrosive layer, soil oxygen concentration, soil pore saturation and other factors on the pipeline ground potential at the inflow and outflow point of stray current is simulated and analyzed. The damaged area of the anticorrosive layer has a more obvious effect, the current density at the defect edge is higher than that at the center, and the outflow stray current density at the damaged point of the anticorrosive layer increases with the decrease of the damaged area of the anticorrosive layer, and the corrosion becomes more intense. Oxygen is mainly consumed at the inflow of stray current, and oxygen reduction reaction occurs. With the increase of soil porosity, the diffusion coefficient of oxygen decreases, while the conductivity of soil electrolyte increases. As the influence of soil electrolyte conductivity is larger than that of oxygen diffusion coefficient, the corrosion becomes more intense with the increase of soil porosity. The research in this paper has important guiding significance for further understanding of stray current corrosion mechanism of buried steel pipelines.

Harmonic magnetic field focus detection technology has been utilized for in-service pipeline defect detection due to its advantage in providing high-sensitivity and noncontact detection. However, this technology encounters interference from background signals and noise during high lift-off detection, which limits the accuracy of defect signal extraction. To quickly and robustly identify pipe defects, this work discloses a novel defect signal extraction method for multiple-harmonic magnetic field detection technology. The proposed method is insensitive to noise interference, effectively extracting defect signals even under high-intensity noise conditions. A pipe defect model based on magnetic dipole moments is established for simulation analysis, and a pipeline test platform is built for experimental validation. The results demonstrate that the proposed method can identify defects from signals with a low signal-to-noise ratio of 5.7 dB and locate pipes, welds, and defects with high resolution.

随着轨道交通、高压直流输电系统的建设,埋地钢质管道受到越来越多的直流杂散电流干扰,由此引发的安全问题受到政府和企业的重视.本文以直流杂散电流为对象,论述了直流干扰的不同来源以及对埋地钢质管道的腐蚀机理;综述了不同来源的直流杂散电流干扰规律的研究现状;总结了现行标准中的直流杂散电流评价准则,并提出了建议;综述了各种直流杂散电流检测与防护技术,分析了各自技术的适用范围及特点;并且对直流杂散电流干扰规律以及检测防护研究方向进行了展望.

Generally, transmission lines and buried pipelines constantly share the same corridor to save land and public resources during urban construction. In this paper, the electromagnetic interference of high-voltage transmission lines on the surrounding buried steel pipelines is studied by considering a public corridor. This corridor comprises a 220 kV AC transmission line project and buried metal pipelines in Shanghai. The Current Distribution, Electromagnetic Field, Grounding and Soil Structure Analysis (CDEGS) software is used to study the AC interference situation in this corridor. The level of interferences caused by the AC transmission lines on the pipelines under normal load and single-phase fault conditions is investigated. Zinc strip mitigation measures are set up for the normal load and single-phase fault operation results, effectively reducing the degree of AC interference on the pipelines. Moreover, several new mitigation measures are proposed. The safe implementation of the stable and reliable operation of the transmission line and pipelines is ensured in this paper. The research conclusions can provide reference and guidance for solving the problem of AC interference generated by high-voltage transmission lines on the surrounding buried pipelines and generate new ideas designing of mitigation measures.

The effects of carbon nanofibres (CNFs), titanium nanoparticles (Ti) and CNF-Ti fillers on the water absorption and mechanical properties of the composites were studied. The results showed that with the increase in filler mass fraction, the water absorption and mechanical properties of epoxy resin composites showed a trend of first increasing and then decreasing. When 6% CNF-Ti filler was added, the water absorption and diffusion coefficients of the composites were reduced to 2.32% and 1.04 +/- 0.05 x 10(-6) m(2)/s, and their tensile and impact strengths were improved by 200% and 124.55%, respectively, compared with the pure resin. However, when the filler was added in excess, agglomerates were generated inside the composite, which can affect the performance of the composite to a great extent. The above experimental results were verified by morphology observations via scanning electron microscopy.

The field fingerprint method (FSM), a new online corrosion monitoring method, has a good application prospect. Of all the corrosion defects of pressure pipes, local small corrosion pits are the most commonly seen, and it is also the focus of FSM research. Based on the FSM method, this paper conducts experimental research on the common round and rectangular small corrosion pits of pressure pipes. The results show that the FSM method is sensitive to small volume defects, and the small corrosion pits with the minimum detectable depth of 0.5 mm can accurately reflect the defect growth process, this being of great significance to the safe operation of pipelines.

本文基于谐波激励源和对称差分式磁聚焦谐波磁场检测探头搭建的实验平台,提出基于合成孔径雷达技术的数据处理方法.将低频正弦信号搭载高频正弦信号的谐波激励信号加载在探头上,激发谐波磁场进行管道检测,信号处理系统将数据点相量化,使其具有方向和大小,经过计算可得数据点的实部和虚部,进而可得检测过程的相位变化以表征管道的缺陷信息.通过管道缺陷检测示例可以验证此种处理方法的有效性,该算法灵敏度高,具有较高工程实用性.

为实现埋地钢质管道阴极保护状态的远程监测,基于FPGA技术提出了一种埋地钢质管道牺牲阳极智能阴极保护系统设计方法.现场可编程门阵列(FPGA)作为并行处理单元实现阴极保护参数的采集.采用无线4G和以太网2 种高速通讯方式用于远程实时监控和本地数据重复读取,解决了因网络中断导致的数据丢失问题.实验结果表明:设计的智能阴极保护系统具有采集准确、存储可靠、监控及时的特点,能够满足现场工程应用的需求.

When lightning strikes the transmission line tower, the lightning current flows into the soil along the tower grounding device, causing serious AC interference with nearby steel-buried pipelines. To tackle this problem, this paper uses CDEGS, the professional power analysis software, to establish a three-dimensional (3D) simulation model for the transmission line and surrounding pipelines based on the actual engineering information. This model predicts the coating stress voltage of steel pipelines in public corridors when typical lightning strikes towers. Lightning current includes the first return and subsequent return strokes. Resistance and inductance couplings are considered in the calculation. In addition, the paper uses COMSOL Multiphysics software to calculate the distribution of potential and current density on the surface of adjacent pipe under the first lightning return stroke, providing a new analysis idea for mitigating the AC interference caused by the lightning current. The conclusions of this paper can be used as a reference for the analysis of transmission line AC interference with adjacent steel-buried pipelines in lightning strikes.

为解决带包覆层金属管道全周向检测问题,提出一种不拆包覆层的旋转激励磁场检测方法.在管道表面沿周向布置3 组励磁线圈并通入三相电流产生磁场,使管体产生的感应涡流中心沿着激励磁场矢量方向进行迁移,从而检测管体全周向的缺陷信息.基于有限元法研究了探头的工作原理,通过将隧道磁阻(TMR)传感器沿管体周向布置,测量管道径向的磁场强度以识别缺陷特征.实验研究表明:该方法可穿透管道包覆层,有效识别管道上的缺陷.

针对埋地钢质管道损伤不开挖检测问题,提出一种非接触式谐波磁场检测方法.利用调频载波原理将高频信号叠加到低频信号上构建谐波激励信号,通过聚焦阵列增强激励信号的空间辐射能量和靶向性;采用三维矢量隧道磁阻差分传感器阵列对磁场信号进行采集.采用双稳随机共振(SR)算法增强目标信号能量并采用局域均值分解(LMD)算法进行自适应时频分析.仿真与实验结果表明,该检测方法能够对缺陷信号进行有效提取与辨识,实现埋地管道损伤的不开挖检测.

The field fingerprint method is a new type of pipeline corrosion on-line monitoring method, which can realize long-term monitoring of pipelines in all directions. However, the existing equipment is mainly developed by foreign manufacturers based on DC excitation sources. The current is generally tens of amperes or even hundreds of amperes, and the cables are prone to heat. The corrosion monitoring system developed in this paper based on the field fingerprint method uses an embedded industrial control motherboard as the core, which can run the operating system, realizes the intelligentization of the equipment and has strong scalability in function; the AC excitation based on the digital output of the single-chip microcomputer is carefully designed. The current source avoids the influence of DC excitation; the adopted amplifying circuit has low noise and high common-mode rejection ratio, which can effectively extract the sampled signal. The data shows that the various parameters of this equipment are stable, and the operation is stable, which meets the requirements of on-site use.

FSM (field signature method) is a new non plug-in on-line monitoring method for pipeline corrosion. The traditional FSM corrosion monitoring equipment is generally a single machine to copy data or collect terminal client wireless transmission data, which is not convenient for data management. In this paper, cloud service is introduced into the monitoring system, and the FSM corrosion monitoring system based on cloud server is developed, which realizes the functions of real-time, online and remote control. The monitoring system can obtain the current status data of the monitored pipeline in real time, and calculate the corrosion parameters of the pipeline according to the data sent back by the measuring device. The system can draw trend diagram and morphology diagram according to the calculated corrosion parameters, display database data tables and relevant charts, and send monitoring information regularly.

AC-FSM is a new technology of external monitoring the internal corrosion for oil and gas pipelines. The current source stability of the FSM equipment is one of the important factors affecting the monitoring accuracy. According to the equipment requirements, a precision current source with adjustable frequency is designed. With C8051MCU as the control core, DAC conversion and differential amplifier are used to control the frequency and the current amount. The experiment shows that the output of excitation power supply has good consistency, the changing range was less than 0.3 %. When the temperature changes, under the condition of low frequency 5Hz, the change of current is less than 0.5 %, under the condition of high frequency 102Hz, the change of current is less than 0.4 %, which avoids the influence of temperature drift. This equipment is suitable for the long period operation of oil and gas pipelines in the field.

To improve the wear resistance of friction components coated with epoxy resin, a titanium-multi-walled carbon nanotubes (Ti-MWCNT) reinforced epoxy resin composite coating was designed and prepared by combining metal nanoparticles and inorganic nanoparticles into a hybrid filler using Ti nanoparticles and MWCNT as raw materials. The changes in functional groups of pure resin and Ti-MWCNT reinforced epoxy resin composites were analyzed using infrared spectroscopy. The hardness, fracture toughness and tribological properties of pure resin and Ti-MWCNT-reinforced epoxy resin composite coatings with different contents of Ti-MWCNT filler (0, 2 wt.

The DC FSM equipment used for monitoring the inner corrosion of oil and gas pipeline has problems such as low safety, vulnerable to interference and low signal-to-noise ratio. The AC FSM is developed to avoid the above problems. This paper introduce the design of data acquisition and analysis software for the AC FSM equipment, which including data preprocessing module, pipeline corrosion calculation module and data analysis and display module. The experiment showed that the software can display the internal corrosion morphology of the pipeline in the monitoring area in 3D, reflecting the internal corrosion location. The defect quantification of the software is consistent with the actual situation, indicating the effectiveness of the software.