DEVELOPMENT AND ERROR ANALYSIS OF AN INSPECTING SYSTEM FOR MEASURING THE ROTATIONAL INERTIA OF BULLETS

介绍了一种用于测量弹丸转动惯量的高精度测量仪器，该仪器利用双悬丝扭摆机构、光电计时系统提取摆动周期信息，由MCS-51系列单片机组成的测量系统进行数据处理，并由LED显示器测量结果。文中阐述了仪器的工作原理， 推导了所需的计算公式，分析了产生测量误差的因素，进行了定量精度分析，给出了实验结果与测量精度。

A MACHINE VISION SYSTEM FOR INSPECTING WOOD SURFACE DEFECTS BY USING NEURAL NETWORK

With the development of wood industry, the processing of wood products becomemore significant. This paper discusses the developmen of machine vision system used to inspect andclassny the various types of defects of wood suxface. The surface defeds means the variations ofcolour and textUre. The machine vision system is to dated undesirable "defecs" that can appear onthe surface of rough wood lwnber. A neural network was used within the Blackboard framework fora labeling verification step of the high-level recognition module of vision system. The system hasbere successfully tested on a number of boards from several different species.

New Robotic Technologies for Inspecting Two Pole Electric Generators while the Rotor Remains in Place

The electric generator is a highly stressed plant component requiring periodic inspection and maintenance to reduce the risk of a costly forced outage. This paper briefly introduces two new robotic technologies for performing fast and reliable inspections of two pole electric generators with minimal mechanical disassembly requirements. The first robotic system is designed to inspect within the generator rotor and stator air gap, while the second robotic system is designed to inspect the generator retaining rings. An overview of the design and construction of each system is provided, along with an explanation of the capabilities and benefits they bring to the power station owner.

The Use of Damage Modes in Periodic Inspecting Autoclave

According to the operation characteristics of autoclave, the possible defects are analyzed by damage modes, the inspection methods are selected contrapuntally, and the causes of the defects affecting the safe operation of the equipment are analyzed. This study effectively improves the quality of inspection work and plays an important role in strengthening the management of equipment use and reducing accidents.

High-efficiency inspecting method for mobile robots based on task planning for heat transfer tubes in a steam generator

Many heat transfer tubes are distributed on the tube plates of a steam generator that requires periodic inspection by robots.Existing inspection robots are usually involved in issues:Robots with manipulators need complicated installation due to their fixed base;tube mobile robots suffer from low running efficiency because of their structural restricts.Since there are thousands of tubes to be checked,task planning is essential to guarantee the precise,orderly,and efficient inspection process.Most in-service robots check the task tubes using row-by-row and column-bycolumn planning.This leads to unnecessary inspections,resulting in a long shutdown and affecting the regular operation of a nuclear power plant.Therefore,this paper introduces the structure and control system of a dexterous robot and proposes a task planning method.This method proceeds into three steps:task allocation,base position search,and sequence planning.To allocate the task regions,this method calculates the tool work matrix and proposes a criterion to evaluate a sub-region.And then all tasks contained in the sub-region are considered globally to search the base positions.Lastly,we apply an improved ant colony algorithm for base sequence planning and determine the inspection orders according to the planned path.We validated the optimized algorithm by conducting task planning experiments using our robot on a tube sheet.The results show that the proposed method can accomplish full task coverage with few repetitive or redundant inspections and it increases the efficiency by 33.31% compared to the traditional planning algorithms.

A Railway Fastener Inspection Method Based on Abnormal Sample Generation

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

Enhanced air-coupled impact echo technique by phase analysis of signals from multiple sensors

This paper presents an air-coupled impact echo(IE)technique that relies on the phase spectrum of the collected data to find the frequencies corresponding to the reflections from delaminations.The proposed technique takes advantage of the fact that the IE compression wave is not a propagating wave,but it is the 1st order symmetrical(S1)mode Lamb wave at zero group velocity(S1-ZGV).Therefore,it searches the phase spectra of the data collected by multiple sensors to locate the frequency corresponding to the lowest phase difference.As a result,the technique reduces the effect of propagating waves,including the direct acoustic wave and ambient noise.It is named the Constant Phase IE(CPIE).The performance of the CPIE is experimentally compared with the regular amplitude spectrum-based IE technique and two other multisensor IE techniques.The CPIE shows a performance advantage,especially in a noisy environment.

Automatic Road Tunnel Crack Inspection Based on Crack Area Sensing and Multiscale Semantic Segmentation

The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safetyand performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of roadtunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combinedwith a deep neural network model is an effective means to realize the localization and identification of crackdefects on the surface of road tunnels.We propose a complete set of automatic inspection methods for identifyingcracks on the walls of road tunnels as a solution to the problem of difficulty in identifying cracks during manualmaintenance. First, a set of equipment applied to the real-time acquisition of high-definition images of walls inroad tunnels is designed. Images of walls in road tunnels are acquired based on the designed equipment, whereimages containing crack defects are manually identified and selected. Subsequently, the training and validationsets used to construct the crack inspection model are obtained based on the acquired images, whereas the regionscontaining cracks and the pixels of the cracks are finely labeled. After that, a crack area sensing module is designedbased on the proposed you only look once version 7 model combined with coordinate attention mechanism (CAYOLOV7) network to locate the crack regions in the road tunnel surface images. Only subimages containingcracks are acquired and sent to the multiscale semantic segmentation module for extraction of the pixels to whichthe cracks belong based on the DeepLab V3+ network. The precision and recall of the crack region localizationon the surface of a road tunnel based on our proposed method are 82.4% and 93.8%, respectively. Moreover, themean intersection over union (MIoU) and pixel accuracy (PA) values for achieving pixel-level detection accuracyare 76.84% and 78.29%, respectively. The experimental results on the dataset show that our proposed two-stagedetection method outperforms other state-of-the-art models in crack region localization and detection. Based onour proposedmethod, the images captured on the surface of a road tunnel can complete crack detection at a speed often frames/second, and the detection accuracy can reach 0.25 mm, which meets the requirements for maintenanceof an actual project. The designed CA-YOLO V7 network enables precise localization of the area to which a crackbelongs in images acquired under different environmental and lighting conditions in road tunnels. The improvedDeepLab V3+ network based on lightweighting is able to extract crack morphology in a given region more quicklywhile maintaining segmentation accuracy. The established model combines defect localization and segmentationmodels for the first time, realizing pixel-level defect localization and extraction on the surface of road tunnelsin complex environments, and is capable of determining the actual size of cracks based on the physical coordinatesystemafter camera calibration. The trainedmodelhas highaccuracy andcanbe extendedandapplied to embeddedcomputing devices for the assessment and repair of damaged areas in different types of road tunnels.

Progression of e-ticketing implementation for state transportation agencies for asphalt materials

E-ticketing,which has been promoted by the Federal Highway Administration(FHWA)“every day counts”(EDC)initiative,utilizes software applications to digitally track and store information regarding highway construction materials paid by state transportation agencies(STAs)by weight in unit bid contract structures.STAs often face implementation barriers such as institutional inertia,or the resistance by stakeholders to adopt changes from the status quo,including new technologies.The purpose of this paper is to determine the progression of STA e-ticketing policy adoption,specifically with a focus on asphalt paving operations,due to the COVID-19 pandemic.To accomplish this research effort,previous FHWA data,National Cooperative Highway Research Program(NCHRP)data,and other literatures are reviewed to determine an implementation baseline.Additional data is collected from the American Association of State Highway and Transportation Officials Committee on Con-struction to gain current feedback from STAs and their highway contractor partners after the COVID-19 pandemic.Additionally,a case study featuring the Kentucky Transportation Cabinet(KYTC),the Kentucky Association of Highway Contractors(KAHC),and the Plantmix Asphalt Industry of Kentucky(PAIKY)is performed to provide more in-depth analysis.The major finding includes a statistically significant result indicating increased imple-mentation of e-ticketing for asphalt operations within the last two years,along with noting benefits including employee safety,task loading,and project documentation along with concerns regarding cellular connectivity and procurement responsibilities.These findings indicate the importance of STAs investing in partnership with con-tractors to improve stakeholder buy-in before proceeding towards e-ticketing adoption.

High-speed railway track components inspection framework based on YOLOv8 with high-performance model deployment

Railway inspection poses significant challenges due to the extensive use of various components in vast railway networks,especially in the case of high-speed railways.These networks demand high maintenance but offer only limited inspection windows.In response,this study focuses on developing a high-performance rail inspection system tailored for high-speed railways and railroads with constrained inspection timeframes.This system leverages the latest artificial intelligence advancements,incorporating YOLOv8 for detection.Our research introduces an efficient model inference pipeline based on a producer-consumer model,effectively utilizing parallel processing and concurrent computing to enhance performance.The deployment of this pipeline,implemented using C++,TensorRT,float16 quantization,and oneTBB,represents a significant departure from traditional sequential processing methods.The results are remarkable,showcasing a substantial increase in processing speed:from 38.93 Frames Per Second(FPS)to 281.06 FPS on a desktop system equipped with an Nvidia RTX A6000 GPU and from 19.50 FPS to 200.26 FPS on the Nvidia Jetson AGX Orin edge computing platform.This proposed framework has the potential to meet the real-time inspection requirements of high-speed railways.

Analysis of the Application of Bridge Rapid Inspection and Evaluation Technology

Rapid bridge inspection and evaluation mainly uses information technology to test the quality of bridge infrastructure and structures,integrates the test results with the existing management system,completes the bridge status assessment,establishes information management files to provide bridge disease problem inspection and analysis,and provides support for the application of disposal measures.This paper briefly discusses the necessity of applying rapid inspection and evaluation technology and analyzes the bridge’s rapid inspection and evaluation content,inspection system,and application process.We look forward to the future application prospects of this technology and supporting those in this field.

Shelton Vision pushes the needle on Al-assisted quality control

MANCHESTER,UK-Having successfully demonstrated its WebSpector automated fabric inspection system detecting faults on camouflage fabrics at speeds of up to 100metres a minute during ITMA 2023,BTMA member Shelton Vision has secured an unprecedented number of new orders in many fields of the textile industry.The company has subsequently been recruiting additional staff in order to beef up its operations to meet delivery times and to grow capacity for the ongoing increased demand.

Analysis of Safety Assessment and Testing of Heavy Traffic Vehicles on Old Bridges Without Data

This article presents a real-life project that aimed to evaluate the safety of traffic vehicles on old bridges without any prior data.The project involved various safety inspections,including conventional,static,and dynamic load inspections and safety assessments.After conducting these tests,it was concluded that the structure of the old bridge is relatively safe,with only a few bumps.The bridge could function normally following appropriate treatment.The analysis provides valuable insights into the assessment of the quality and safety of such bridges to ensure the safe driving of heavy vehicles.

Defect Inspection Technology for Steel Truss Suspension Bridges

Steel truss suspension bridges are prone to developing defects after prolonged use.These defects may include corrosion of the main cable or the steel truss.To ensure the normal and safe functioning of the suspension bridge,it is necessary to inspect for defects promptly,understand the cause of the defect,and locate it through the use of inspection technology.By promptly addressing defects,the suspension bridge’s safety can be ensured.The author has analyzed the common defects and causes of steel truss suspension bridges and proposed specific inspection technologies.This research is intended to aid in the timely discovery of steel truss suspension bridge defects.

A novel approach to identifying the ultrasonic echoes for inspecting well cementing quality

In this paper, it is presented that an approach based on Continuous Wavelet Thansform(CWT) and Fourier Transform(FT) for identifying ultrasonic echoes in inspecting oil well cementing quality. First, CWT is used to process echo signals. Then spectra of the processing results in some specilic scale-time segments are calculated as pattern features. The research results show that theoretical calculations basically agree with experimental results. Compared with the aPproach based on the spectra or Discrete Wavlet Transform, our approach has advantages of fine analyzing scales, stable features and high recognizing rate. It is very suitable to identify echo signals whose spectra vary with time.

A mask R-CNN based method for inspecting cable brackets in aircraft

In the aviation industry,cable bracket is one of the most common parts.The traditional assembly state inspection method of cable bracket is to manually compare by viewing 3 D models.The purpose of this paper is to address the problem of inefficiency of traditional inspection method.In order to solve the problem that machine learning algorithm requires large dataset and manually labeling of dataset is a laborious and time-consuming task,a simulation platform is developed to automatically generate synthetic realistic brackets images with pixel-level annotations based on 3 D digital mock-up.In order to obtain accurate shapes of brackets from 2 D image,a brackets recognizer based on Mask R-CNN is trained.In addition,a semi-automatic cable bracket inspection method is proposed.With this method,the inspector can easily obtain the inspection result only by taking a picture with a portable device,such as augmented reality(AR)glasses.The inspection task will be automatically executed via bracket recognition and matching.The experimental result shows that the proposed method for automatically labeling dataset is valid and the proposed cable bracket inspection method can effectively inspect cable bracket in the aircraft.Finally,a prototype system based on client-server framework has been developed for validation purpose.

开展医疗保障经办机构飞行检查的问题及其产生因素的质性研究

目的梳理总结我国开展医疗保障(以下简称“医保”)经办机构飞行检查的问题及其产生因素,为完善我国医保基金飞行检查机制,加强对医保经办机构的监管提供建议和参考。方法于2022年7—9月,采用典型抽样法,选取4个省份的医保专家进行半结构式访谈,样本量的确定以不再出现新的信息为标准,运用colaizzi七步分析法对获取的资料进行归纳分析。结果通过对11名专家访谈资料的分析,归纳提炼开展医保经办机构飞行检查的问题,包括力度不足、队伍构成不健全、缺乏具体内容及标准等,以及导致问题产生的因素,包括选择效应、缺乏标准化做法、区域差异等。结论医保经办机构的行为及工作效率影响着医保基金安全,对其进行监管十分必要,但开展医保经办机构飞行检查的过程中存在诸多问题。建议推进制度建设,加大飞行检查力度;丰富队伍构成,提升飞行检查质量;完善指标建立,规范飞行检查内容。

Surface form inspection with contact coordinate measurement:a review

Parts with high-quality freeform surfaces have been widely used in industries,which require strict quality control during the manufacturing process.Among all the industrial inspection methods,contact measurement with coordinate measuring machines or computer numerical control machine tool is a fundamental technique due to its high accuracy,robustness,and universality.In this paper,the existing research in the contact measurement field is systematically reviewed.First,different configurations of the measuring machines are introduced in detail,which may have influence on the corresponding sampling and inspection path generation criteria.Then,the entire inspection pipeline is divided into two stages,namely the pre-inspection and post-inspection stages.The typical methods of each sub-stage are systematically overviewed and classified,including sampling,accessibility analysis,inspection path generation,probe tip radius compensation,surface reconstruction,and uncertainty analysis.Apart from those classical research,the applications of the emerging deep learning technique in some specific tasks of measurement are introduced.Furthermore,some potential and promising trends are provided for future investigation.

Damage detection with image processing: a comparative study

Large structures,such as bridges,highways,etc.,need to be inspected to evaluate their actual physical and functional condition,to predict future conditions,and to help decision makers allocating maintenance and rehabilitation resources.The assessment of civil infrastructure condition is carried out through information obtained by inspection and/or monitoring operations.Traditional techniques in structural health monitoring(SHM)involve visual inspection related to inspection standards that can be time-consuming data collection,expensive,labor intensive,and dangerous.To address these limitations,machine vision-based inspection procedures have increasingly been investigated within the research community.In this context,this paper proposes and compares four different computer vision procedures to identify damage by image processing:Otsu method thresholding,Markov random fields segmentation,RGB color detection technique,and K-means clustering algorithm.The first method is based on segmentation by thresholding that returns a binary image from a grayscale image.The Markov random fields technique uses a probabilistic approach to assign labels to model the spatial dependencies in image pixels.The RGB technique uses color detection to evaluate the defect extensions.Finally,K-means algorithm is based on Euclidean distance for clustering of the images.The benefits and limitations of each technique are discussed,and the challenges of using the techniques are highlighted.To show the effectiveness of the described techniques in damage detection of civil infrastructures,a case study is presented.Results show that various types of corrosion and cracks can be detected by image processing techniques making the proposed techniques a suitable tool for the prediction of the damage evolution in civil infrastructures.

上海市公共卫生监督技术服务机构消毒产品检验能力现况调查

目的 掌握本市公共卫生监督技术服务机构消毒产品检验能力现状,为完善对该类机构的指导与管理提供科学依据。方法 2021年8—11月,采用信息查询、问卷和现场调查的方法对上海市公共卫生监督技术服务机构中具备消毒产品领域资质的检验检测机构进行调查,描述和分析机构基本情况、专业技术人员、业务能力和业务开展等。结果 调查机构34家,其中企业制机构18家(52.9%)、事业制机构16家(47.1%)。企业制机构和事业制机构在从业人数、实验室面积和专业技术人员的分布上均存在明显差异(P <0.05)。72.2%的企业制机构为小微企业[5.6%微型企业(<10人),66.6%小型企业(10~<100人)],事业制机构从业人数均在100人以上;83.3%的企业制机构实验室面积为2 000 m2以下,87.5%的事业制机构为2 000 m2以上;企业制机构的专业技术人员年龄结构更年轻,学历相对较低,毕业于卫生相关专业的较少,无职称人员占比较高。消毒产品检验能力较为全面的机构占5.9%,各机构检验能力数(以方法计)7~344项,85.3%的机构检验能力数少于30项,只有5.9%的机构能力数达到100项以上。55.9%的机构消毒产品检验领域年业务额为0,41.2%的机构该领域占年总业务额不超过5.0%,2020年较2019年报告量呈明显增加。结论 本市第三方机构在消毒产品检验能力储备、人员能力等方面有待进一步提升,应加强技术能力储备、优化技术人才培养、拓展消毒产品业务领域。建议相关部门加强对机构的指导和引导,进一步加强质量控制机构管理协调职能,推动公共卫生监督技术服务机构健康发展。