Acoustic Non-Destructive Testing Technology in Concrete Bridge Inspection and Pile Foundation Detection

This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview of a certain bridge construction project studied and acoustic non-destructive testing technology and the application of acoustic non-destructive testing technology in actual testing.This analysis hopes to provide some guidelines for acoustic non-destructive testing of modern concrete bridge projects.

Study on the correlation between abdominal infection and psychological stress in children based on nucleic acid detection

BACKGROUND Diagnosing and treating abdominal infection in children remains a challenge.Nucleic acid detection,as a rapid and accurate diagnosis tool,has great significance in this field.AIM To investigate the diagnosis and treatment of abdominal infection by nucleic acid detection and its possible correlation with psychological stress in children.METHODS A total of 50 pediatric patients diagnosed with abdominal infections between September 2020 and July 2021 were included in this study.Intra-abdominal pus samples were collected for pathogen culture,drug susceptibility testing,and broad-spectrum bacterial nucleic acid testing.Psychological stress,anxiety,depression,and coping styles were assessed using the coping with a disease(CODI)scale.RESULTS Based on susceptibility testing,a regimen of cefazoxime,piperacillin/tazobactam,and metronidazole or ornidazole achieved 100%effectiveness in treating appendicitis.Psychological assessments revealed a positive correlation between pressure level and both anxiety(r=0.324,P=0.001)and depressive disorders(r=0.325,P<0.001).Acceptance and distancing as coping strategies were negatively correlated with anxiety and depression,while negative emotional responses were strongly associated with increased anxiety(r=0.574,P<0.001)and depression(r=0.511,P=0.001).Coping strategies such as illusion and escape showed no significant correlation with emotional outcomes.CONCLUSION Nucleic acid testing helps in the diagnosis of abdominal infections in children,and also focuses on children's mental health.

Optical techniques in non-destructive detection of wheat quality:A review

Wheat quality detection is essential to ensure the safety ofwheat circulation and storage.The traditional wheat quality detection methods mainly include artificial sensory evaluation and physicochemical index analysis,which are difficult to meet the requirements for high accuracy and efficiency in modern wheat quality detection due to the disadvantages of subjectivity,destruction of sample integrity and low efficiency.With the rapid development of optical technology,various optical-based methods,using near-infrared spectroscopy technology,hyperspectral imaging technology and terahertz,etc.,have been proposed for wheat quality detection.These methods have the characteristics of nondestructiveness and high efficiency which make them popular in wheat quality detection in recent years.In this paper,various state-of-the-art optical-based techniques of wheat quality detection are analyzed and summarized in detail.Firstly,the principle and process of common optical non-destructive detection methods for wheat quality are introduced.Then,the optical techniques used in these detection methods are divided into seven categories,and the comparison of these technologies and their advantages and disadvantages are further discussed.It shows that terahertz technology is regarded as the most promising wheat quality detection method compared with other optical detection technologies,because it can not only detect most types of wheat deterioration,but also has higher accuracy and efficiency.Finally,the research of optical technology in wheat quality detection is prospected.The future research of optical technology-based wheat quality detection mainly includes the construction of wheat quality optical detection standardization database,the fusion of multiple optical detection technologies and multiple quality index information,the improvement of the anti-interference of optical technology and the industrialization of optical inspection technology for wheat quality.These studies are of great significance to improve the detection technology of wheat and ensure the storage safety of wheat in the future.

Optical generation,detection and non-destructive testing applications of terahertz waves

Optoelectronic terahertz generation and detection play a key role in the applications of non-destructive testing,which involves different areas such as physics,biological,material science,imaging,explosions detection,astronomy applications,semiconductor technology and superconductiong electronics. In this article,we present a reviewof the principle and performance of typical terahertz sources,detectors and non-destructive testing applications. On this basis,the newdevelopment and trends of terahertz radiation detectors are also discussed.

Multi-Energy Gamma-Ray Attenuations for Non-Destructive Detection of Hazardous Materials

We present a non-destructive method (NDM) to identify minute quantities of high atomic number (Z) elements in containers such as passenger baggage, goods carrying transport trucks, and environmental samples. This method relies on the fact that photon attenuation varies with its energy and properties of the absorbing medium. Low-energy gamma-ray intensity loss is sensitive to the atomic number of the absorbing medium, while that of higher-energies vary with the density of the medium. To verify the usefulness of this feature for NDM, we carried out simultaneous measurements of intensities of multiple gamma rays of energies 81 to 1408 keV emitted by sources 133Ba (half-life = 10.55 y) and 152Eu (half-life = 13.52 y). By this arrangement, we could detect minute quantities of lead and copper in a bulk medium from energy dependent gamma-ray attenuations. It seems that this method will offer a reliable, low-cost, low-maintenance alternative to X-ray or accelerator-based techniques for the NDM of high-Z materials such as mercury, lead, uranium, and transuranic elements etc.

Stress Detector Supported Galvanic Skin Response System with IoT and LabVIEW GUI

Stress is now a serious disease that exists due to changes in working life and food ecosystems around the world.In general,it is difficult for a person to know if they are under stress.According to previous research,temperature,heart rate variability(HRV),humidity,and blood pressure are used to assess stress levels with the use of instruments.With the development of sensor technology and wireless connectivity,people around the world are adopting and using smart devices.In this study,a bio signal detection device with Internet of Things(IoT)capability with a galvanic skin reaction(GSR)sensor is proposed and built for real-time stress monitoring.The proposed device is based on an Arduino controller and Bluetooth communication.To evaluate the performance of the system,physical stress is created on 10 different participants with three distinct tasks namely reading,visualizing the timer clock,and watching videos.MATLAB analysis is performed for identifying the three different levels of stress and obtaining the threshold values as if the person GSR voltage i.e.,relaxed for<1.75 volts;Normal:between 1.75 and 1.44 volts and stressed:>1.44 volts.In addition,LabVIEW is used as a data acquisition system,and a Blueterm mobile application is also used to view the sensor reading received from the device through Bluetooth communication.

Effects of Pearl Yangxin Anshen Decoction on HAMD and PTSD-SS Scores, Cytokines and Related Metabolites in Patients with Post-Traumatic Stress Disorder

Objective: This paper aims to observe the Pearl Yangxin Anshen Decoction to influence the score of HAMD and PTSD-SS, the changes of the cytokines and the related metabolic product in patients with PTSD. Methods: From June 2015 to May 2016, in the traditional Chinese medicine clinics of Hainan Province People’s Hospital, there were 50 patients with PTSD, the age were from 30 to 60, they were randomly divided into treatment group (25 cases) and control group (25 cases), then compared the scores of HAMD and PTSD-SS between the two groups, searched the changes of cytokines and the related metabolic product. Results: In the treatment group: before and after treatment the scores of PTSD-SS were 65.64 ± 7.02, 28.32 ± 4.18, and the scores of HAMD were 29.28 ± 1.97, 11.72 ± 2.13;In the control group: before and after treatment the scores of PTSD-SS were 63.24 ± 6.16, 31.40 ± 4.29, the scores of HAMD were 30.24 ± 2.05, 13.08 ± 2.30. After 3 months patients in treatment group the scores of PTSD-SS and HAMD were lower than the control group (t = 2.570, P = 0.013, t = -2.1640, P = 0.035). In the control group: before and after 3 months treatment the IL-2 levels respectively were 79.84 ± 26.46 pg/ml, 56.18 ± 22.67 pg/ml, the IL-6 levels respectively were 110.83 ± 47.65 pg/ml, 59.67 ± 44.68 pg/ml, the IL-8 levels respectively were 73.11 ± 78.51 pg/ml, 55.83 ± 81.94 pg/ml, the NE levels respectively were 420.04 ± 674.75 pg/ml, 185.31 ± 417.91 pg/ml, the MDA levels respectively were 112.35 ± 62.87 ng/ml, 60.42.33 ± 53.64 ng/ml, the NO levels were 126.6 ± 47.4 μmol/L, 78.6 ± 45.7 μmol/L, the VIP levels were 396.6 ± 144.4 pg/ml, 122.4 ± 111.5 pg/ml. In the treatment group: before and after 3 months treatment the IL-2 levels respectively were 86.00 ± 32.29 pg/ml, 53.84 ± 27.01 pg/ml, the IL-6 levels respectively were 108.21 ± 44.60 pg/ml, 42.46 ± 42.16 pg/ml, the IL-8 levels respectively were 81.48 ± 94.19 pg/ml, 54.07 ± 84.15 pg/ml, the NE levels respectively were 392.93 ± 592.84 pg/ml, 243.85 ± 588.45 pg/ml, the MDA levels respectively were 117.58 ± 63.37 ng/ml, 45.91 ± 38.94 ng/ml, the NO levels respectively were 135.9 ± 46.4 μmol/L, 72.6 ± 46.6 μmol/L, the VIP levels respectively were 414.0 ± 140.1 pg/ml, 185.8 ± 105.3 pg/ml. In the two groups as the extension of treatment time, the content of IL-2, IL-8, IL-6, NE, MDA, NO, and VIP were gradually reduced, and the level of reduction of the treatment group patients was higher than the control group, the change of ACTH and SOD levels just the opposite. Conclusion: The Pearl Yangxin Anshen Decoction could improve the symptoms of psychological anxiety, depression and other psychological problems in patients with PTSD, and influence the change of cytokines and related metabolites product.

On the Foundations of the Ultrasonic Non-Destructive Determination of Stresses in Near-the-Surface Layers of Materials： Review

The foundation of the ultrasonic non-destructive determination of stresses in near-the-surface layers of solids is presented. The method is based on the regularities of Rayleigh wave propagation in solids with initial （residual） stresses. A description of the above mentioned method and examples of stress determination are presented. Examples are considered as applied to the residual stresses arising at electric welding and the operating stresses arising at loading.

A fast and adaptive method for automatic weld defect detection in various real-time X-ray imaging systems

A first and effective method is proposed to detect weld deject adaptively in various Dypes of real-time X-ray images obtained in different conditions. After weld extraction and noise reduction, a proper template of median filter is used to estimate the weld background. After the weld background is subtracted from the original image, an adaptite threshold segmentation algorithm is proposed to obtain the binary image, and then the morphological close and open operation, labeling algorithm and fids＇e alarm eliminating algorithm are applied to pracess the binary image to obtain the defect, ct detection result. At last, a fast realization procedure jbr proposed method is developed. The proposed method is tested in real-time X-ray image,s obtairted in different X-ray imaging sutems. Experiment results show that the proposed method is effective to detect low contrast weld dejects with few .false alarms and is adaptive to various types of real-time X-ray imaging systems.

A novel 4D resolution imaging method for low and medium atomic number objects at the centimeter scale by coincidence detection technique of cosmic-ray muon and its secondary particles

The muon radiography imaging technique for high-atomic-number objects(Z)and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation detection imaging.However,few imaging studies have been reported on low and medium Z objects at the centimeter scale.This paper presents an imaging system that consists of three layers of a position-sensitive detector and four plastic scintillation detectors.It acquires data by coincidence detection technique of cosmic-ray muon and its secondary particles.A 3D imaging algorithm based on the density of the coinciding muon trajectory was developed,and 4D imaging that takes the atomic number dimension into account by considering the secondary particle ratio information was achieved.The resultant reconstructed 3D images could distinguish between a series of cubes with 5-mm-side lengths and 2-mm-intervals.If the imaging time is more than 20 days,this method can distinguish intervals with a width of 1 mm.The 4D images can specify target objects with low,medium,and high Z values.

Current Trends and Perspectives of Detection and Location for Buried Non-Metallic Pipelines

Buried pipelines are an essential component of the urban infrastructure of modern cities.Traditional buried pipes are mainly made of metal materials.With the development of material science and technology in recent years,non-metallic pipes,such as plastic pipes,ceramic pipes,and concrete pipes,are increasingly taking the place of pipes made from metal in various pipeline networks such as water supply,drainage,heat,industry,oil,and gas.The location technologies for the location of the buried metal pipeline have become mature,but detection and location technologies for the non-metallic pipelines are still developing.In this paper,current trends and future perspectives of detection and location of buried non-metallic pipelines are summarized.Initially,this paper reviews and analyzes electromagnetic induction technologies,electromagnetic wave technologies,and other physics-based technologies.It then focuses on acoustic detection and location technologies,and finally introduces emerging technologies.Then the technical characteristics of each detection and location method have been compared,with their strengths and weaknesses identified.The current trends and future perspectives of each buried non-metallic pipeline detection and location technology have also been defined.Finally,some suggestions for the future development of buried non-metallic pipeline detection and location technologies are provided.

Acoustic wave detection of laser shock peening

In order to overcome the existing disadvantages of offline laser shock peening detection methods, an online detection method based on acoustic wave signals energy is provided. During the laser shock peening, an acoustic emission sen- sor at a defined position is used to collect the acoustic wave signals that propagate in the air. The acoustic wave signal is sampled, stored, digitally filtered and analyzed by the online laser shock peening detection system. Then the system gets the acoustic wave signal energy to measure the quality of the laser shock peening by establishing the correspondence between the acoustic wave signal energy and the laser pulse energy. The surface residual stresses of the samples are measured by X-ray stress analysis instrument to verify the reliability. The results show that both the surface residual stress and acoustic wave signal energy are increased with the laser pulse energy, and their growth trends are consistent. Finally, the empirical formula between the surface residual stress and the acoustic wave signal energy is established by the cubic equation fitting, which will provide a theoretical basis for the real-time online detection of laser shock peening.

Higher-Order Statistics for Automatic Weld Defect Detection

Image processing and image analysis are the main aspects for obtaining information from digital image owing to the fact that this techniques give the desired details in most of the applications generally and Non-Destructive testing specifically. This paper presents a proposed method for the automatic detection of weld defects in radiographic images. Firstly, the radiographic images were enhanced using adaptive histogram equalization and are filtered using mean and wiener filters. Secondly, the welding area is selected from the radiography image. Thirdly, the Cepstral features are extracted from the Higher-Order Spectra (Bispectrum and Trispectrum). Finally, neural networks are used for feature matching. The proposed method is tested using 100 radiographic images in the presence of noise and image blurring. Results show that in spite of time consumption, the proposed method yields best results for the automatic detection of weld defects in radiography images when the features were extracted from the Trispectrum of the image.

Model Tests of Pile Defect Detection

The pile, as an important foundation style, is being used in engineering practice. Defects of different types and damages of different degrees easily occur during the process of pile construction. So, dietecting defects of the pile is very important. As so far, there are some difficult problems in pile defect detection. Based on stress wave theory, some of these typical difficult problems were studied through model tests. The analyses of the test results are carried out and some significant results of the low-strain method are obtained, when a pile has a gradually-decreasing crosssection part, the amplitude of the reflective signal originating from the defect is dependent on the decreasing value of the rate of crosssection β. No apparent signal reflected from the necking appeares on the velocity response curve when the value of β is less than about 3. 5 %.

Hardness-Based Non-destructive Method for Developing Location Specific S-N Curves for Fatigue Life Evaluation

This paper first describes the importance of using location specific S-N curves for fatigue damage assessment of existing steel structures. It discusses the existing concepts and methods for developing S-N curves using empirical formulae and monotonic strength parameters, such as the ultimate tensile strength and hardness. It also discusses relationships among these monotonic parameters. Then it presents formulae for developing hardness-based full range S-N curves for medium strength steels. The formulae are verified using experimental data obtained from both monotonic and cyclic testing. Finally, it describes the advantages of these hardness-based formulae for developing location specific S-N curves as hardness testing is a non-destructive test which can be carried out on specific locations in structures.

Outlier Detection and Forecasting for Bridge Health Monitoring Based on Time Series Intervention Analysis

The method of time series analysis,applied by establishing appropriate mathematical models for bridge health monitoring data and making forecasts of structural future behavior,stands out as a novel and viable research direction for bridge state assessment.However,outliers inevitably exist in the monitoring data due to various interventions,which reduce the precision of model fitting and affect the forecasting results.Therefore,the identification of outliers is crucial for the accurate interpretation of the monitoring data.In this study,a time series model combined with outlier information for bridge health monitoring is established using intervention analysis theory,and the forecasting of the structural responses is carried out.There are three techniques that we focus on:(1)the modeling of seasonal autoregressive integrated moving average(SARIMA)model;(2)the methodology for outlier identification and amendment under the circumstances that the occurrence time and type of outliers are known and unknown;(3)forecasting of the model with outlier effects.The method was tested with a case study using monitoring data on a real bridge.The establishment of the original SARIMA model without considering outliers is first discussed,including the stationarity,order determination,parameter estimation and diagnostic checking of the model.Then the time-by-time iterative procedure for outlier detection,which is implemented by appropriate test statistics of the residuals,is performed.The SARIMA-outlier model is subsequently built.Finally,a comparative analysis of the forecasting performance between the original model and SARIMA-outlier model is carried out.The results demonstrate that proper time series models are effective in mining the characteristic law of bridge monitoring data.When the influence of outliers is taken into account,the fitted precision of the model is significantly improved and the accuracy and the reliability of the forecast are strengthened.

Improving tree health assessment accuracy at low temperatures:considering the effect of trunk ice content on electrical resistance and stress wave tomography

Accurate decay detection and health assessment of trees at low temperatures is an important issue for forest management and ecology in cold areas.Low temperature ice formation on tree health assessment is unknown.Because electric resistance tomography and stress wave tomography are two widely used methods for the detection of tree decay,this study investigated the effect of ice content on trunk electrical resistance and stress wave velocity to improve tree health assessment accuracy.Moisture content,trunk electrical resistance and stress wave velocity using time domain reflectometry were carried out on Larix gmelinii and Populus simonii.Ice content is based on moisture content data.The ice content of both species showed a trend of increasing and then decreasing.This was opposite with ambient temperatures.With the decrease of temperatures,daily average ice content increased,but the range narrowed gradually and both electrical resistance and stress wave velocity increased.Both increased rapidly near 0℃,mainly caused by ice formation(phase change and freezing of free water)in live trees.In addition,both are positively correlated with ice content.The results suggest that ice content should be considered for improving the accuracy of tree decay detection and health evaluation using electric resistance tomography and stress wave velocity methods under low temperatures.

Predicting Violence-Induced Stress in an Arabic Social Media Forum

Social Media such as Facebook plays a substantial role in virtual com-munities by sharing ideas and ideologies among different populations over time.Social interaction analysis aids in defining people’s emotions and aids in assessing public attitudes,towards different issues such as violence against women and chil-dren.In this paper,we proposed an Arabic language prediction model to identify the issue of Violence-Induced Stress in social media.We searched for Arabic posts of many countries through Facebook application programming interface(API).We discovered that the stress state of a battered woman is usually related to her friend’s stress states on Facebook.We applied a large real database from Facebook platforms to analytically investigate the correlation of violence-induced stress states and the victim interactions on social media.We extracted a set of tex-tual,spatial,and interaction attributes from various features.Therefore,we are proposing a hybrid model–an interaction graph model incorporated in a deep learning neural model to leverage post content and interaction data for vio-lence-induced stress detection.Experiments depict that our proposed hybrid mod-el can enhance the prediction performance by 10%in F1-measure.Also,considering the user interaction information can learn an interesting phenomenon,where,the sparse social interactions of violence-induced stress stressed victims is higher by around 15%percent non-battered users,signifying that the structure of the friends of such victims is less connected than non-stressed users.

长输油气管道内检测技术

管道内检测技术是长输油气管道内检测最有效的方法之一,是长输油气管道缺陷检测、评估与完整性评价的重要手段。随着我国能源行业的高速发展,管道成为能源输送的最有效载体,这对管道内检测技术提出了新的挑战,应运而生多种新的检测方法与解决方案。梳理了长输油气管道内检测技术的发展过程,阐述了长输油气管道内检测技术的国内外研究现状,针对长输油气管道内检测现存在的问题,对新技术、新方法的原理、应用情况进行归纳总结,并提出管道内检测行业的未来展望。