Traditional Detection Technology Research Articles

Defect Detection of Micro-Precision Glass Insulated Terminals

Micro-precision Glass Insulated Terminals (referred to as glass terminals) are the core components used in precision electronic equipment and are often used for electrical connections between modules. As a glass terminal, its quality has a great influence on the performance of precision electronic equipment. Due to the limitations of materials and production processes, some of the glass terminals produced have defects, such as missing blocks, pores and cracks. At present, most of the defect detection of glass terminals is done by manual inspection, and rapid detection easily causes eye fatigue, so it is difficult to ensure product quality and production efficiency. The traditional defect detection technology is difficult to effectively detect the very different defects of the glass terminal. Therefore, this paper proposes to use deep learning technology to detect missing blocks. First, preprocess the sample pictures of the missing block defects of the glass terminal, and then train the improved Faster Region-CNN deep learning network for defect detection. According to the test results, the accuracy of the algorithm in detecting missing defects in the glass terminal is as high as 93.52%.

A gated integration method for the detection of unevenly distributed ions bunches in laser resonant ionization mass spectrometry

In laser resonance ionization mass spectrometry (RIMS) systems, pulsed lasers are usually employed to excite and ionize the elements of interest. Therefore, the laser ion signals are clustered and unevenly distributed at the time of appearance. The characteristics of the ions cause difficulties in the use of traditional ion detection technologies, such as the Faraday cup detection method and ion counting method. The gated integration method was proposed herein to measure pulsed laser ion signals. In this method, the intensity information of unevenly distributed ions is continuously converted to voltage amplitude information. Simulation and experiments demonstrated that the proposed method can effectively measure unevenly distributed ion signals with a high linearity over an operating signal range of 3 × 104–2 × 107 count rate within the duration of the pulsed laser (cps-p). In addition, it also can effectively remove the measurement gap between a Faraday cup detection system and a secondary electron multiplier detection system operating in the ion counting mode in laser RIMS.

Forensic Application of Next Generation Sequencing Technology in the Typing of Y Chromosome Genetic Markers.

The paternal inheritance characteristics of Y chromosome have been widely used in the forensic genetics field to detect the genetic markers in the non-recombining block, and used in the studies such as, genetic relationship identification, mixed stain detection, pedigree screen and ethnicity determination. At present, capillary electrophoresis is still the most common detection technology. The commercial detection kits and data analysis and processing system based on this technology are very mature. However, the disadvantages of traditional detection technology have gradually appeared with the rapid growth of bio-information amount, which promotes the renewal of forensic DNA typing technology. In recent years, next generation sequencing （NGS） technology has developed rapidly. This technology has been applied to various fields including forensic genetics and has provided new techniques for the detection of Y chromosome genetic markers. This article describes the current situation and application prospects of the NGS technology in forensic Y chromosome genetic markers detection in order to provide new ideas for future judicial practice.

Rice Freshness Identification Based on Visible Near-Infrared Spectroscopy and Colorimetric Sensor Array

In this work, two methods, which were visible near-infrared spectroscopy (VNIRS) and visible near-infrared spectroscopy combined with colorimetric sensor array (VNIRS-CSA), were used to identify the volatile compound changes of rice samples stored for 0 to 6 months. Principal component analysis (PCA), interval partial least squares (iPLS), and synergy interval partial least squares (SiPLS) were used for qualitative classification. A prediction model was established by linear discriminant analysis (LDA), which was compared with the traditional VNIRS detection technology. The results revealed that the VNIRS-CSA got better performance than VNIRS and exhibited a good result based on iPLS/SiPLS-PCA/LDA models. Furthermore, spectral data from VNIRS-CSA were the best for LDA with a high prediction value of 0.925 after standard normal variate (SNV) processing and variable selection by SiPLS. The research demonstrated that VNIRS-CSA is a quick, accurate, and non-destructive method for monitoring the storage time of rice. The strategy also has the potential for volatile organic components analysis.

Simulation and Experiment of Underwater Target Active Electromagnetic Detection Based on SLF/ELF artificial Source

In view of the detection performance constraints brought by the further application of demagnation and noise reduction technology to traditional sonar and magnetic anomaly detection technology, in order to explore the possibility and detection mode of active electromagnetic (EM) detection technology applied to underwater large target detection and positioning, the active EM detection method for underwater targets based on SLF/ELF artificial EM field source is established in this paper, and the active EM detection method of underwater target is modeled and simulated by Ansys Maxwell, the magnetic anomaly field induced by underwater target is calculated and analyzed. Then, the key parameters of the underwater target active EM detection system are listed based on the simulation, and a underwater target active EM detection prototype has been developed. Finally, the simulation results and prototype parameters of the active EM detection method of underwater targets are verified by the scaled ratio experiment. The results show that the parameters of prototype system designed according to the simulation results are correct and effective, and the active EM detection technology based on SLF/ELF can be applied to the underwater large target detection.

Video Face Recognition of Virtual Currency Trading System Based on Deep Learning Algorithms

Virtual currency trading develops rapidly, taking up a large proportion in the whole economy, and has become an important part of people’s daily life. Firstly, a reliable virtual currency trading system model is proposed, which is composed of four participant platforms, providers and payers, mainly including the purchase of virtual currency, purchase of virtual goods or services, exchange of virtual currency and other trading activities. In order to monitor possible collusion fraud in virtual currency transactions, payers are introduced to prevent collusion attacks. Video face detection algorithm based on multi-task Cascaded Convolutional Networks is designed and implemented to solve the problems of pose, light and occlusion in the virtual currency trading system. The algorithm utilizes the inherent correlation between detection and calibration to improve the detection performance under the framework of deep cascading tasks. Furthermore, the paper utilizes the three-tiered architecture combined with the well-designed VNN algorithm to realize the face detection and the rough location of key points. Meanwhile, on the basis of in-depth study and analysis of traditional face detection technology, a face detection algorithm based on Harr features and AdaBoost is implemented for comparison and analysis with the aforementioned algorithm. The experimental results show that the method based on MTCNN deep learning network can better extract effective features about faces in videos and achieve more accurate detection. Compared with the traditional method based on AdaBoost and cascade structure, the positive detection rate is much improved.

Microdroplet extraction assisted ultrasensitive Raman detection in complex oil.

The Raman detection of trace substances in complex oil is still a great challenge at present because of the strong disturbance of background activity and the suppression of intensity in spectra caused by complicated components. In this work, a simple and robust approach based on microdroplet liquid-liquid extraction for the real-time Raman spectroscopy monitoring of trace substances in complex oil is reported. Based on unbalanced chemical potentials between water and oil on a microfluidic chip, a target trace molecule is extracted from complex mineral oil to a water microdroplet. Benefiting from the real-time fluorescence intensities of fluorescein in a water microdroplet, the extraction performance is investigated and optimized. The optimal water microdroplet is implemented for the Raman detection of furfural in a complex mineral oil, a typical trace performance marker in electric power equipment, and this exhibits excellent sensitivity with a limit of detection (LOD) of 26 ppb. Compared to traditional detection technology for trace substances in complex oil (high performance liquid chromatography, HPLC), this method greatly simplified the process of measurement, reduced the volume of sample required, had a fast measurement time, and exhibited the prospect of real-time monitoring applications with high sensitivity, which not only promotes the development of oil quality but also enlarges existing knowledge related to using Raman spectroscopy in chem-/bio-sensing.

Application of acoustic imaging technology in power transformer condition evaluation

Power transformer is the core equipment of the power system. Its operation status directly affects the security and reliability of the whole system. Therefore, it is of great significance to evaluate its status timely and accurately. Acoustic imaging technology is first used in medical, communication and other fields, which can effectively sense abnormal sound and locate it accurately, which greatly improves the work efficiency. This paper introduces the application of acoustic imaging technology in live detection of power transformer. The result shows that the combination of acoustic imaging technology and traditional live detection technology can improve the working efficiency of live detection and the accuracy of transformer condition evaluation, which is conducive to maintaining the safe and reliable operation of power grid.

Development of enzymatic electrochemical biosensors for organophosphorus pesticide detection

The enzymatic electrochemical biosensor has the advantages of simple operation, speed, and integration in the detection of organophosphorus pesticide (OPs) residues. It has the potential to become the best alternative to the traditional OP detection technology. This article introduces the OP identification principle of different enzymes, the OP detection mechanism of several common sensors, and the enzyme assembly method. In addition, the article discusses application of nanomaterials in sensor preparation and sensor performance parameters in the past decade. The related content of early sensors is outside the scope of this article.

Real TimeDetection and Tracking Method of Pilot’sHeadPositionBased on MTCNN-DeepSORT

In view of the problems of the traditional head detection and tracking technology in pilot cabin simulation training, such as low precision, poor real-time performance and easy to be interfered by the outside world, we propose a head detection and tracking method based on MTCNN-DeepSORT combined with deep learning method. Firstly, the continuous video images in the cockpit are preprocessed by computer vision, and then the processed images are extracted by convolution neural network to detect the face. At the same time, the facial feature points are marked. Through the spatial coordinate calculation of the obtained facial feature points, the pilot’s head posture angle is obtained, and then combined with DeepSORT tracking algorithm can track the pilot’s head continuously and in real time, and finally complete the detection and tracking of pilot’s head position. The experimental results show that the method based on MTCNN-DeepSORT has higher detection accuracy, better real-time performance and stronger robustness than the traditional methods.

Fewer-layer conductive metal-organic Langmuir-Blodgett films as electrocatalysts enable an ultralow detection limit of H2O2

The detection of low-concentration hydrogen peroxide (H2O2) has important theoretical-significance and practical value in many fields, such as medical science, biological chemistry, and food safety inspection. Traditional commercial H2O2 test paper and detection technology can only reach the detection limit of 10−3–10−5 (mass fraction). In this paper, we report a simple method to prepare 2D MOF (metal-organic frameworks) [Co3(HOB)2]n films based on Langmuir-Blodgett (LB) method combined with layer-by-layer growth technique. Even 3-layer [Co3(HOB)2]n films can realize the lowest H2O2 detection limit of 1.05 × 10−8 wt% (3.08 nmol·L−1) based on the resultant 2D MOF catalyst. Meanwhile, density functional theory (DFT) calculations revealed that Co2+ ions of the LB films decreased the energy of [HOOH] transforming into [HO2] during the H2O2 reduction reactions, thus speeding up the decomposition of H2O2.

The research of aptamer biosensor technologies for detection of microorganism.

The activities and transmissions of microorganisms are closely related to human, and all kinds of diseases caused by pathogenic microorganisms have attracted attention in the world and brought many challenges to human health and public health. The traditional microbial detection technologies have characteristics of longer detection cycle and complicated processes, therefore, which can no longer meet the detection requirements in the field of public health. At present, it is the focus to develop and design a novel, rapid, and simple microbial detection method in the field of public health. Herein, this article summarized the development of aptamer biosensor technologies for detection of microorganism in the aspect of bacteria, viruses, and toxins in detail, including optical aptamer sensors such as fluorometry and colorimetry, electrochemical aptamer sensors, and other technologies combined with aptamer. KEY POINTS: • Aptamer biosensor is a good platform for microbial detection. • Aptamer biosensors include optical sensors and electrochemical sensors. • Aptamer sensors have been widely used in the detection of bacteria, viruses, and other microorganisms.

Application of Pseudo-color Image Feature-Level Fusion in Nondestructive Testing of Wire Ropes

Among the many nondestructive testing methods of ferromagnetic materials, magnetic flux leakage (MFL) testing is a very mature technology. Due to the single source of target information in traditional MFL detection technology, the recognition accuracy is low. Infrared image is a color artificially given, so it is also a pseudo-color image. We use the feature-level image fusion technology to fuse color infrared images and pseudo-color MFL images and quantitatively identify the defect feature vectors after fusion. A wavelet noise reduction algorithm is used to perform noise reduction processing on the MFL signal and used the pseudo-color transform method to convert the noise-reduced MFL signal into a pseudo-color image. For the collected infrared images of the wire rope, we use an image segmentation algorithm to extract the defective parts. The color moments and texture features of the pseudo-color MFL defect image and the color infrared defect image are extracted for feature-level fusion and trained as the input of the nearest neighbor algorithm. The final experimental results prove that the fusion of the two images information has achieved good results and the defect recognition rate has been improved.

Research Progress of 3D Printing Microfluidic Chip

Because of the advantages of microfluidic technology, such as high detection speed, high accuracy and low reagent loss, it has obvious advantages over the traditional detection technology. So recently, microfluidic technology has been widely used in life science and medical diagnosis. However, the microfluidic chip processing technology is mostly developed from semiconductor processing technology, which has the characteristics of high cost and high technical requirements, which are also important factors limiting the development of microfluidic technology. In recent years, 3D printing technology has become more and more mature, so using 3D printing technology to make microfluidic chips has attracted the attention of many researchers. Compared with the traditional microfluidic chip processing technology, 3D printing microfluidic chip technology has been widely concerned because of its advantages of fast design and processing speed, wide material adaptability and low cost. At present, the processing methods of microfluidic chip mainly include micro stereolithography, deposition molding, ink-jet printing and so on. In this paper, the main research progress of 3D printing microfluidic chips at home and abroad and the future development direction are reviewed. At last, the applications of microfluidic chip processing technology in analytical chemistry, life science, medical diagnosis and other fields are prospected.

Application of Image Restoration in On-Line Detection of Optical Element Damage

With the continuous development of technology, Image processing methods based on computer vision began to shine in the field of image processing. There are many easily damaged optical equipment, traditional off-line detection technology requires analysis of components in optical devices after disassembly. Therefore, offline detection technology cannot guarantee the efficiency of the device, It also affects the cost and life of the equipment. Therefore, the research on the online detection technology of optical component damage has become an urgent problem to be solved. In this paper, an online damage detection method for optical elements based on image restoration is proposed. Then, the whole image and block image are processed by this method to verify the processing effect.

Comparison of Detection Technology for Runway Incursion Prevention in Airport Hot Spot

The prevention of runway incursion in hot spot of airports has always been one of the research hot spots in the field of international civil aviation. The detection of aircraft and vehicles in hot spots of airports has important significance in preventing runway incursion. This paper briefly introduces and analyzes several major technical systems used in the detection of active targets in hot spots of airports, and points out that microwave phased-array radar can provide parameters such as the distance, angle, speed, and direction of detection of targets. Compared with the traditional detection technology system, microwave phased-array radar has the advantages of high detection accuracy, low comprehensive cost, and easier acceptance.

200 Gbps/Lane IM/DD Technologies for Short Reach Optical Interconnects

Client-side optics are facing an ever-increasing upgrading pace, driven by upcoming 5G related services and datacenter applications. The demand for a single lane data rate is soon approaching 200 Gbps. To meet such high-speed requirement, all segments of traditional intensity modulation direct detection (IM/DD) technologies are being challenged. The characteristics of electrical and optoelectronic components and the performance of modulation, coding, and digital signal processing (DSP) techniques are being stretched to their limits. In this context, we witnessed technological breakthroughs in several aspects, including development of broadband devices, novel modulation formats and coding, and high-performance DSP algorithms for the past few years. A great momentum has been accumulated to overcome the aforementioned challenges. In this article, we focus on IM/DD transmissions, and provide an overview of recent research and development efforts on key enabling technologies for 200 Gbps per lane and beyond. Our recent demonstrations of 200 Gbps short-reach transmissions with 4-level pulse amplitude modulation (PAM) and discrete multitone signals are also presented as examples to show the system requirements in terms of device characteristics and DSP performance. Apart from digital coherent technologies and advanced direct detection systems, such as Stokes–vector and Kramers–Kronig schemes, we expect high-speed IM/DD systems will remain advantageous in terms of system cost, power consumption, and footprint for short reach applications in the short- to mid- term perspective.

Research on Fault Detection Algorithm of Pantograph Based on Edge Computing Image Processing

Traditional pantograph detection technology has installed a large number of various types of sensors on the pantograph, which is not conducive to the flow characteristics of the pantograph. Traditional detection technology can neither monitor the operation status of the pantograph in real time, nor guarantee the safe operation of the entire train. The existing schemes are only manual solutions, and intelligent real-time monitoring is performed without error, and a lot of labor costs are required. Focusing on the shortcomings of traditional pantographs in sliding plate wear and sliding plate crack detection, an improved mean filtering algorithm is proposed to optimize the image of pantograph, and the adaptive Canny edge detection technology is used to accurately calculate the skateboard wear. Firstly, the improved image algorithm is used to pre-treat the pantograph slide wear and crack length, then the improved mean filtering algorithm is combined with adaptive Canny operator for image optimization detection, and finally the edge calculation is used for crack identification. An optimized real-time on-line detection technology is proposed, which can accurately measure the wear and tear of skateboards and cracks. For different experimental environments, the optimization algorithm proposed in this paper is used to detect pantographs in real time. The experimental results show that, compared with the traditional detection algorithm, the detection accuracy of sliding plate wear can reach 0.5 mm, and and that of sliding plate cracks can reach 0.4 mm. The crack recognition accuracy of skates is as high as 93%.

基于二次相位超表面的大视场紧凑型全Stokes偏振测量方法

Polarization is one of the inherent characteristics of light, but the polarization information of electromagnetic waves is lost by traditional intensity and spectral detection technology. At the same time, not only the devices and technologies based on polarimetry have the problem of limited field of view, but also the measuring systems are complicated. In this paper, a compact large field-of-view polarimeter was designed based on dielectric metasurface, which realized the detection of the angle and polarization state of the incident light. The device was composed of 2×2 quadratic phase metasurfaces, each of which realized the symmetry transformation for a specific polarization, that is, the rotational symmetry of the incident angle was converted into the translational symmetry of focus in the focal plane. The theory of the symmetry transformation of the quadratic phase made it possible to characterize the angle of incidence by measuring the offset of the focus over a wide angle range (−40°—+40°). On this basis, the influence of oblique incidence on the measurement of Stokes parameters was elaborated, and the modified Stokes formula was obtained. The Stokes parameters of the incident light can be calculated by utilizing the intensities of the four focal points and the modified Stokes formula. The measured Stokes parameters agree well with the theoretical values, when the field-of-view is 0°, 20°, and 40°.

A survey of video capsule endoscope system based on wireless energy transfer technology

The wireless capsule endoscope system allows clinicians to directly observe the image of the inner wall of the human gastrointestinal tract and obtain the most intuitive information at the lesion. Compared with traditional endoscopic detection technology, its painless, non-invasive, safe and convenient, full gastrointestinal detection features make this technology a research focus in the field of medical devices at home and abroad. As a new non-invasive detection technology for gastrointestinal diseases, the working time, image frame rate and image quality of the existing wireless capsule endoscope system cannot fully meet the needs in clinical applications. The cause of these problems lies in the capsule. The internal space of the speculum is limited, and only the button battery can be used as the energy source. Therefore, it is necessary to design a video capsule endoscope based on wireless energy transmission technology. This article is a review of Zhu Zhanquan, Xue Kaifeng, Lu Ruiqi and other scholars.