Rail Internal Defect Detection Method Based on Enhanced Network Structure and Module Design Using Ultrasonic Images

Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operation of high-speed trains.For this reason,a rail internal defect detection method based on an enhanced network structure and module design using ultrasonic images is proposed in this paper.First,a data augmentation method was used to extend the existing image dataset to obtain appropriate image samples.Second,an enhanced network structure was designed to make full use of the high-level and low-level feature information in the image,which improved the accuracy of defect detection.Subsequently,to optimize the detection performance of the proposed model,the Mish activation function was used to design the block module of the feature extraction network.Finally,the pro-posed rail defect detection model was trained.The experimental results showed that the precision rate and F1score of the proposed method were as high as 98%,while the model’s recall rate reached 99%.Specifically,good detec-tion results were achieved for different types of defects,which provides a reference for the engineering application of internal defect detection.Experimental results verified the effectiveness of the proposed method.

Research and Application of Log Defect Detection and Visualization System Based on Dry Coupling Ultrasonic Method

In order to optimize the wood internal quality detection and evaluation system and improve the comprehensive utilization rate of wood,this paper invented a set of log internal defect detection and visualization system by using the ultrasonic dry coupling agent method.The detection and visualization analysis of internal log defects were realized through log specimen test.The main conclusions show that the accuracy,reliability and practicability of the system for detecting the internal defects of log specimens have been effectively verified.The system can make the edge of the detected image smooth by interpolation algorithm,and the edge detection algorithm can be used to detect and reflect the location of internal defects of logs accurately.The content mentioned above has good application value for meeting the requirement of increasing demand for wood resources and improving the automation level of wood nondestructive testing instruments.

Ultrasonic Sensor-Based Embedded System for Vehicular Collusion Detection and Alert

The efficacy of an automated collision detection system is contingent upon the caliber and volume of data at its disposal. In the event that the data is deficient, incongruous, or erroneous, it has the potential to generate erroneous positive or negative outcomes, thereby compromising the system’s credibility. The occurrence of false positives is observed when the system erroneously identifies genuine activity as collusion. The phenomenon of false negatives arises when the system is unable to identify instances of genuine collusion. Collusion detection systems are required to handle substantial volumes of data in real time, capable of analyzing relationships between different objects. The intricate nature of collusion can pose difficulties in devising and executing efficient systems for its detection. The present study proposes an automated anti-collision system that utilizes sensor devices to detect objects and activate an alert mechanism in the event that the vehicle approaches the object in close proximity. The study introduces a novel methodology for mitigating vehicular accidents by implementing a combined system that integrates collision detection and alert mechanisms. The proposed system comprises an ultrasonic sensor, a microprocessor, and an alarm system. The sensor transmits a signal to the microcontroller, which in turn sends a signal to the warning unit. The warning unit is designed to prevent potential accidents by emitting an audible warning signal through a buzzer. Additionally, the distance information is displayed on an LCD screen. The Proteus Design Suite is utilized for simulation purposes, while Arduino.cc is employed for implementation.

Applications of Ultrasonic Detection Technology in Bridge Concrete Pile Foundation Detection

In this paper,the application strategy of ultrasonic detection technology in the detection of concrete foundation piles is analyzed using a construction project as an example.It includes a basic overview of the project,an overview of ultrasonic testing technology in bridge concrete pile foundation testing,and an analysis of its practical application in the concrete pile foundation testing of this project.The objective of this analysis is to provide some reference for the application of ultrasonic testing technology and the improvement of the quality of bridge concrete pile foundation testing.

Detection of Cracks in Aerospace Turbine Disks Using an Ultrasonic Phased Array C-scan Device

Crack detection in an aerospace turbine disk is essential for aircraft-quality detection.With the unique circular stepped structure and superalloy material properties of aerospace turbine disk,it is difficult for the traditional ultrasonic testing method to perform efficient and accurate testing.In this study,ultrasound phased array detection technology was applied to the non-destructive testing of aviation turbine disks:(i)A phased array ultrasonic c-scan device for detecting aerospace turbine disk cracks(PAUDA)was developed which consists of phased array ultrasonic,transducers,a computer,a displacement encoder,and a rotating scanner;(ii)The influence of the detection parameters include frequency,wave-type,and elements number of the ultrasonic phased array probe on the detection results on the near-surface and the far surface of the aerospace turbine disk is analyzed;(iii)Specimens with flat-bottom-hole(FBH)defects were scanned by the developed PAUDA and the results were analyzed and compared with the conventional single probe ultrasonic water immersion testing.The experiment shows that by using the ultrasonic phased array c-scan to scan the turbine disk the accuracy of the detection can be significantly improved which is of greater accuracy and higher efficiency than traditional immersion testing.

Development of an Integrated CMUTs-Based Resonant Biosensor for Label-Free Detection of DNA with Improved Selectivity by Ethylene-Glycol Alkanethiols

Gravimetric resonant-inspired biosensors have attracted increasing attention in industrial and point-ofcare applications,enabling label-free detection of biomarkers such as DNA and antibodies.Capacitive micromachined ultrasonic transducers(CMUTs)are promising tools for developing miniaturized highperformance biosensing complementary metal–oxide–silicon(CMOS)platforms.However,their operability is limited by inefficient functionalization,aggregation,crosstalk in the buffer,and the requirement for an external high-voltage(HV)power supply.In this study,we aimed to propose a CMUTs-based resonant biosensor integrated with a CMOS front–end interface coupled with ethylene–glycol alkanethiols to detect single-stranded DNA oligonucleotides with large specificity.The topography of the functionalized surface was characterized by energy-dispersive X-ray microanalysis.Improved selectivity for onchip hybridization was demonstrated by comparing complementary and non-complementary singlestranded DNA oligonucleotides using fluorescence imaging technology.The sensor array was further characterized using a five-element lumped equivalent model.The 4 mm^(2) application-specific integrated circuit chip was designed and developed through 0.18 lm HV bipolar-CMOS-double diffused metal–oxide–silicon(DMOS)technology(BCD)to generate on-chip 20 V HV boosting and to track feedback frequency under a standard 1.8 V supply,with a total power consumption of 3.8 mW in a continuous mode.The measured results indicated a detection sensitivity of 7.943×10^(-3) lmol·L^(-1)·Hz^(-1) over a concentration range of 1 to 100 lmol·L^(-1).In conclusion,the label-free biosensing of DNA under dry conditions was successfully demonstrated using a microfabricated CMUT array with a 2 MHz frequency on CMOS electronics with an internal HV supplier.Moreover,ethylene–glycol alkanethiols successfully deposited self-assembled monolayers on aluminum electrodes,which has never been attempted thus far on CMUTs,to enhance the selectivity of bio-functionalization.The findings of this study indicate the possibility of full-on-chip DNA biosensing with CMUTs.

Damage Detection and Material Property Reconstruction of Composite Laminates Using Laser Ultrasonic Technique

Laser ultrasonic technique has received increasing attentions in the past decade due to its contactless nature and a wide range of applications have been reported. In this review,applications of laser ultrasonic technique developed at Nanjing University of Aeronautics and Astronautics(NUAA)as well as elsewhere for non-destructive testing in composite laminates are presented. The principles of generating and detecting in a laser ultrasonic system are introduced,three different system configurations are also introduced with each configuration's advantages and disadvantages explained. More importantly,two major applications developed at NUAA for composite laminates are presented including damage detection,stiffness reconstruction and fatigue life prediction. Both applications are realized by a fixed-point PZT sensor and scanning pulse laser based on the linear reciprocal theorem. Analytical method and numerical models are employed and developed to realize the functionalities.

Ultrasonic flaw detection of discontinuous defects in magnesium alloy materials

Phased array ultrasonic testing, an effective ultrasonic testing(UT) technology, has been widely used in steel inspection because of its high accuracy, sensitivity, and efficiency. However, as its application in as-cast magnesium alloys has just begun, more research is needed. Considering the important role of the gain compensation in quantifying defects in magnesium alloys by ultrasonic phased array technology, the effects of microstructure, the position, size, and overlap of defects, and boundary distance(distance from the defect position to the side surface of the test casting) on gain compensation of as-cast AZ80 and AZ31 magnesium alloys were studied. Results show the gain compensation increases with the increase of grain size. There is a strict linear positive correlation between gain compensation and defect depth, but such relationship no longer exists due to the defects overlap, orientation and boundary distance. In addition, there is a strict linear negative correlation between the gain compensation and defect size.

Laser ultrasonic technique for surface defects detection of 6061 aluminum alloy

In order to estimate and detect the surface defect depth of metals, the transmission method of laser ultrasonic surface waves is used in this work. The laser ultrasonic detection platform taking use of thermoelastic mechanism as acoustic signal excitation method and interference receiver as acoustic signal receiver method was built, by which B-scan images of detected specimens with surface defects were collected to establish the relationship between the transmission coefficient and depth of the surface defect. Experimental results show that the amplitude of transmitted acoustic signal is related to the depth of surface defect. At last, a fitted curve of transmission coefficient using measured experimental data is obtained to estimate depth of surface defect on the 6061 aluminum alloy. Furthermore, a surface defect depth of 0.3 mm is estimated by the fitting curve with an estimated error of 16%. Therefore, a experimental method using the transmission method by laser ultrasonic is presented in this paper.

Defect detection in brazed weldment with lattice structure using ultrasonic Lamb wave technique

In this paper, defects detection in brazed weldment with lattice structure is studied using ultrasonic Lamb wave. Based on the ultrasonic guided wave theory, the frequency dispersion curves for phase and group velocity of I Cr18Ni9Ti are obtained by solving the Rayleigh-Lamb equation. The incident angles of different modes are determined through theoretical calculation and experimental analyses. Artificial defects of through-wall slots with different dimensions are made and tested. Experimental scattering effects of the fundamental symmetric mode S2 and asymmetric modes A1 and A0 are analysed and compared. The results show that mode Ao is suitable for detecting artificial defect, and the amplitude of the received signals are in good agreement with the defect size. Brazed weldment specimen containing lack of brazing with certain dimensions is made. Using the same methodology, scattering effects produced by weld defects are measured. The results show that the clutter wave brought about by the filler metal will certainly disturbs the identification of defect signal. But, when the defect is 3.0 mm in width, the presented mode Ao could be used potentially.

Internal Defects Detection Method of the Railway Track Based on Generalization Features Cluster Under Ultrasonic Images

There may be several internal defects in railway track work that have different shapes and distribution rules,and these defects affect the safety of high-speed trains.Establishing reliable detection models and methods for these internal defects remains a challenging task.To address this challenge,in this study,an intelligent detection method based on a generalization feature cluster is proposed for internal defects of railway tracks.First,the defects are classified and counted according to their shape and location features.Then,generalized features of the internal defects are extracted and formulated based on the maximum difference between different types of defects and the maximum tolerance among same defects’types.Finally,the extracted generalized features are expressed by function constraints,and formulated as generalization feature clusters to classify and identify internal defects in the railway track.Furthermore,to improve the detection reliability and speed,a reduced-dimension method of the generalization feature clusters is presented in this paper.Based on this reduced-dimension feature and strongly constrained generalized features,the K-means clustering algorithm is developed for defect clustering,and good clustering results are achieved.Regarding the defects in the rail head region,the clustering accuracy is over 95%,and the Davies-Bouldin index(DBI)index is negligible,which indicates the validation of the proposed generalization features with strong constraints.Experimental results prove that the accuracy of the proposed method based on generalization feature clusters is up to 97.55%,and the average detection time is 0.12 s/frame,which indicates that it performs well in adaptability,high accuracy,and detection speed under complex working environments.The proposed algorithm can effectively detect internal defects in railway tracks using an established generalization feature cluster model.

Application of Compactness Detection to Complicated Concrete-Filled Steel Tube by Ultrasonic Method

An example of using ultrasonic method to detect the compactness of complicated concrete-filled steel tube in certain high-rise building was discussed in this study.Because of the particularity of the complicated concrete-filled steel tubular column,the plane detection method and embedded sounding pipe method were adopted in the process of effectively detecting the column.According to the results of the plane detection method and embedded sounding pipe method,the cementing status of steel tube and concrete can be concluded,which cannot be judged by the hammering method in the rectangular steel tube-reinforced concrete.

Study on the concentrated SF_6 quantitative intelligent ultrasonic detection system

In order to realize on-line quantitative detection on SF6 and effective control of nlnning state of SF6 high voltage power supply system, a concentrated SF6 quantitative ultrasonic on-line deteetion system has been developed based on the actual demand of electric power system consumers. There are four major characteristics in this system. Firstly, the gas of maximum 64 detection points is transferred through the specific air path to the detection devices to he detected and analyzed, thereby the electrical lines and the complicated installation of the collectors can be avoided; secondly, the differential technique is used to shield the influence of environmental factors, which effectively improves the accuracy of the acoustic detection; thirdly, the SF6 coneentration is determined by the speed and phase in the ultrasonic wave trans- mission process, therefore there is no secondary pollution for the purely physical means; finally, the ma- ture embedded technique is applied in this system to improve its intelligence and stability.

Automatic defect detection in ultrasonic TOFD D-scan data using image processing methods

In ultrasonic time of flight diffraction （TOFD） D-scan image, only a small fraction represents defects, whereas the majority is redundant. Because of the low contrast between defect and background image, it is difficult to manually interpret TOFD image. In addition, due to the nature of the weak amplitude of ultrasonic diffracted signals, the human factor introduces inconsistency into the interpretation. In order to automatically distinguish weld defects from the D-scan image, a defect detection method based on image processing technique is proposed. First, image pre-processing including clutter and noise suppression is conducted. Second, information entropy based image segmentation technique is employed to extract defects in the pre-processed image. At last, mathematical morphology based post-processing is carried out. The experimental results show that with the proposed method, TOFD can be used for automatic weld defect detection with satisfactory level of reliability.

Fast recognition algorithm of underwater micro-terrain based on ultrasonic detection

An algorithm was proposed to fast recognize three types of underwater micro-terrain, i.e. the level, the gradient and the uneven. With pendulum single beam bathymeter, the hard level concrete floor, the random uneven floor and the gradient wood panel (8-) were ultrasonically detected 20 times, respectively. The results show that the algorithm is right from fact that the first clustering values of the uneven are all less than the threshold value of 60.0% that is obtained by the level and gradient samples. The algorithm based on the dynamic clustering theory can effectively eliminate the influences of the exceptional elevation values produced by the disturbances resulted from the grazing angle, the characteristic of bottom material and environmental noises, and its real-time capability is good. Thus, the algorithm provides a foundation for the next restructuring of the micro-terrain.

A gas kick early detection method outside riser based on Doppler ultrasonic wave during deepwater drilling

The feasibility of gas kick early detection outside the riser was analyzed based on gas-liquid multiphase flow theory.Then an experimental platform for gas kick early detection based on Doppler ultrasonic wave was established and the propagation experiments in two-phase flow of gas-water(sucrose solutions)were conducted.The time and frequency domains of the Doppler ultrasonic wave signals during the experiments were analyzed.The results show that:(1)No matter the pump was on or off,the detected average Doppler ultrasonic signal voltage increased first and then decreased with the increase of the gas void fraction,and had a quadratic function relation with gas void fraction,so the average voltage change of the monitored signals can be used to deduce the approximate gas void fraction.The Doppler ultrasonic wave signal voltage was significantly reduced in magnitude and variation in the solution with higher viscosity,and the viscosity has stronger impact on the magnitude of signal than density.(2)When the pump was stopped,the Doppler shift increased with the increase of gas void fraction,and the two showed a nearly linear relation,so the detected amount of Doppler shift can reflect the variation of gas void fraction quantitatively.When the pump was on,the sound energy produced by frequency converter had a more significant impact on amplitude spectrum than gas void fraction,so it is impossible to determine whether gas kick occurs by frequency domain signal analysis.(3)This method is a non-contact measurement,with no contact with the drilling fluid and no disruption to the drilling operation.It can quantitatively characterize the gas void fraction according to the change of Doppler ultrasonic signal,enabling earlier detection of gas kick.

Application of ultrasonic CT method in nondestructive detection of interior defects in large scale concrete structural member of bridge

The ultrasonic computed tomography （USCT） method is derived from the basic principles of X-ray section scanning. This method records the arriving times of ultrasonic wave between the probes and the sources to ealculate the elastic wave velocity values in the section using the arrival times. Through analyzed the distribution Of elastic wave velocity in aim area, the information of the strength and the homogeneity of the investigated zone could be got indirectly. The authors introduced the operational principle of USCT and a practical case of using this method to detect the interior defects in large scale concrete structural member. Compared with other exploration methods, this method is more efficient and accurate.

A Review on Prerequisites of a Set-Up for Particle Detection by Ultrasonic Waves in Aluminium Melts

In many applications in aluminium industry, the number of inclusion-critical products increases and the quality of those products depend on the inclusion concentration and size. In order to improve the quality of aluminium products and the effectiveness of the processes, a reliable and cheaper on-line detection method is needed. Ultrasonic detection has been used in steel industry, but relatively rare in aluminium industry, although it would theoretically allow for an online non-intrusive detection of the cleanliness of the melt. In this work, the current information on ultrasonic inclusion detection was gathered and recommendations were provided on the Prerequisites for a set-up for ultrasonic detection of non-metallic inclusions in aluminium as a contribution on previous works. It has been concluded that ultrasonic waves seem promising, and should be experimented more on an industrial level to have a clear view on the potentials of the method.

Robust Damage Detection and Localization Under Complex Environmental Conditions Using Singular Value Decomposition-based Feature Extraction and One-dimensional Convolutional Neural Network

Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions(EOC),which are inevitable in the normal inspection of civil and mechanical structures.This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network(1D-CNN).After singular value decomposition-based feature extraction processing,a temporal robust damage index(TRDI)is extracted,and the effect of EOCs is well removed.Hence,even for the signals with a very large temperature-varying range and low signal-to-noise ratios(SNRs),the final damage detection and localization accuracy retain perfect 100%.Verifications are conducted on two different experimental datasets.The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises,and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20℃to 60℃.It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly,showing great potential for application in complex and unknown EOC.

APPROACH OF IMPROVING PRECISION IN ULTRASONIC DOPPLER BLOODSTREAM SPEED MEASUREMENT BY CHAOS-BASED FREQUENCY DETECTING

It is critical for cerebral vascular disease diagnosis through Doppler to detect the maximum and the minimum of the carotid blood flow speed accurately. A kind of Duffing system under an external periodic power with dump is introduced in the letter, numerical analysis is carried out by four-order Runge-Kutta method. An oscillator array is designed according to the frequency of the ultrasonic wave. When the external signals are inputted, computational algorithm is used to scan the array in turn and analyze the result, and the frequency can be determined. Based on the methods above, detecting the carotid blood flow speed accurately is realized. The Signal-to-Noise Ratio (SNR) of-20.23dB is obtained by the result of experiments. In conclusion, the SNR has been improved and the precision of the measured bloodstream speed has been increased, which can be 0.069% to 0.13%.