Inspection Area Research Articles

Chemical Vapor Deposition of a Single-Crystalline MoS2 Monolayer through Anisotropic 2D Crystal Growth on Stepped Sapphire Surface.

Recently, a step-flow growth mode has been proposed to break the inherent molybdenum disulfide (MoS2) crystal domain bimodality and yield a single-crystalline MoS2 monolayer on commonly employed sapphire substrates. This work reveals an alternative growth mechanism during the metal-organic chemical vapor deposition (MOCVD) of a single-crystalline MoS2 monolayer through anisotropic 2D crystal growth. During early growth stages, the epitaxial symmetry and commensurability of sapphire terraces rather than the sapphire step inclination ultimately govern the MoS2 crystal orientation. Strikingly, as the MoS2 crystals continue to grow laterally, the sapphire steps transform the MoS2 crystal geometry into diamond-shaped domains presumably by anisotropic diffusion of ad-species and facet development. Even though these MoS2 domains nucleate on sapphire with predominantly bimodal 0 and 60° azimuthal rotation, the individual domains reach lateral dimensions of up to 200 nm before merging seamlessly into a single-crystalline MoS2 monolayer upon coalescence. Plan-view transmission electron microscopy reveals the single-crystalline nature across 50 μm by 50 μm inspection areas. As a result, the median carrier mobility of MoS2 monolayers peaks at 25 cm2 V-1 s-1 with the highest value reaching 28 cm2 V-1 s-1. This work details synthesis-structure correlations and the possibilities to tune the structure and material properties through substrate topography toward various applications in nanoelectronics, catalysis, and nanotechnology. Moreover, shape modulation through anisotropic growth phenomena on stepped surfaces can provide opportunities for nanopatterning for a wide range of materials.

Aplikasi Pendataan Prohibited Item Divisi Keamanan Penerbangan Bandara Kualanamu

Current technological developments can be said to be growing very rapidly, starting from small devices such as mobile phones, to computer devices which are increasingly developing over time and are increasingly able to meet human needs with access that is very easy for users to understand. As technological progress continues to accelerate in this day and age, Almost all data collection, whether inventory or anything else, already uses a computerized system. There are many benefits to be gained from the computerization of a system, including the resulting data being more accurate, reducing errors when entering data, and more time efficiency, faster and more practical. This is the author's reference for building an application that can record all items that are detained or scattered in the Kualanamu airport security inspection area. All items that will be data that were previously entered manually are computerized. It is hoped that this application will be able to help and reduce data entry errors that have occurred so far. The author created a Prohibited Item data collection system and monthly reports that make it easier for passengers if they later want to take back items that have been detained

Study on departure passenger movement during security check process at airport terminal based on an improved cellular automata model

Airport security check is a crucial part of air travel, and the efficiency of this process directly impacts the overall airport experience. This article presents a study on the modelling and simulation of movement of departure passengers during security check at airport terminals, with a particular emphasis on elucidating microscopic properties such as passenger flow patterns, individual movement dynamics and especially queuing phenomena. In order to solve the unreasonable path problem caused by direct application of cellular automata model, we propose an improved cellular automata model in which a new concept of horizontal restrain floor field is innovatively introduced. Considering the factors of spatial distance, number of queuing people and potential queuing people, a checkpoint selection probability model is embedded into the CA model. The results show that the queuing behavior of passengers is influenced by various factors from three aspects: (i) selection strategy of checkpoint, (ii) spatial layout of inspection area, (iii) arrival interval and verification time. The findings of this study can be used by airport operators to have better understanding of departure passengers’ movements at a micro level, improve the efficiency of the security check process and enhance the airport experience for passengers. Some measures can be taken to reduce the queue waiting time, such as personnel guidance, information signage, planning wider entrance and more queue lanes, replacing the manual verification with ticket inspection machines and so on.

Passenger Queuing Analysis Method of Security Inspection and Ticket-Checking Area without Archway Metal Detector in Metro Stations

In order to avoid the congestion in front of the entrance gate units, it is necessary to analyse and optimise the queuing situation at the planning and design stage. The security inspection area and the ticket-checking area were jointly considered, and a queuing congestion analysis method was proposed. Firstly, the research problem was stated. Then, the problem of calculating the number of passengers in each subarea at any time was transformed into the problem of calculating the transit time of each passenger in each subarea. The transit time was divided into basic transit time and additional transit time. Based on the velocity-density relationship, a quantisation method for basic transit time was proposed related to passenger arrival time. The additional transit time was determined by the moment when the passengers left the subarea according to the sequence of arrival of passengers, the number of queuing passengers in the subarea and the congestion of the subarea to be entered. Finally, the queuing situation of passengers in each subarea at any moment was obtained through passenger flow recursion. Examples showed that the proposed method can deal with multiple working conditions and avoid the tedious and time-consuming scene construction process of the microsimulation software.

Lean back or lean in? Exploring social loafing in human–robot teams

Introduction: Thanks to technological advances, robots are now being used for a wide range of tasks in the workplace. They are often introduced as team partners to assist workers. This teaming is typically associated with positive effects on work performance and outcomes. However, little is known about whether typical performance-reducing effects that occur in human teams also occur in human–robot teams. For example, it is not clear whether social loafing, defined as reduced individual effort on a task performed in a team compared to a task performed alone, can also occur in human–robot teams.Methods: We investigated this question in an experimental study in which participants worked on an industrial defect inspection task that required them to search for manufacturing defects on circuit boards. One group of participants worked on the task alone, while the other group worked with a robot team partner, receiving boards that had already been inspected by the robot. The robot was quite reliable and marked defects on the boards before handing them over to the human. However, it missed 5 defects. The dependent behavioural measures of interest were effort, operationalised as inspection time and area inspected on the board, and defect detection performance. In addition, subjects rated their subjective effort, performance, and perceived responsibility for the task.Results: Participants in both groups inspected almost the entire board surface, took their time searching, and rated their subjective effort as high. However, participants working in a team with the robot found on average 3.3 defects. People working alone found significantly more defects on these 5 occasions–an average of 4.2.Discussion: This suggests that participants may have searched the boards less attentively when working with a robot team partner. The participants in our study seemed to have maintained the motor effort to search the boards, but it appears that the search was carried out with less mental effort and less attention to the information being sampled. Changes in mental effort are much harder to measure, but need to be minimised to ensure good performance.

Fault Location Method for Overhead Power Line Based on a Multi-Hypothetical Sequential Analysis Using the Armitage Algorithm

The use of modern methods for determining the fault location (FL) on overhead power lines (OHPLs), which have high accuracy and speed, contributes to the reliable operation of power systems. Various physical principles are used in FL devices for OHPLs, as well as various algorithms for calculating the distance to the FL. Some algorithms for FL on OHPLs use emergency mode parameters (EMP); other algorithms use measurement results based on wave methods. Many random factors that determine the magnitude of the error in calculating the distance to the FL affect the operation of FL devices by EMP. Methods based on deterministic procedures used in well-known FL devices for OHPLs do not take into account the influence of random factors, which significantly increases the time to search for the fault. The authors have developed a method of FL on OHPLs based on a multi-hypothetical sequential analysis using the Armitage algorithm. The task of recognizing a faulted section of an OHPL is formulated as a statistical problem. To do this, the inspection area of the OHPL is divided into many sections, followed by the implementation of the procedure for FL. The developed method makes it possible to adapt the distortions of currents and voltages on the emergency mode oscillograms to the conditions for estimating their parameters. The results of the calculations proved that the implementation of the developed method has practically no effect on the speed of the FL algorithm for the OHPL by EMP. This ensures the uniqueness of determining the faulted section of the OHPL under the influence of random factors, which leads to a significant reduction in the inspection area of the OHPL. The application of the developed method in FL devices for OHPLs will ensure the required reliability of power supply to consumers and reduce losses from power outages by minimizing the time to search for a fault.

NDT & METROLOGY – Improving Efficiency in Aerospace Manufacturing utilizing the Multi-Modality Approach

Historically, the approach in the aerospace industry has been that the CMM (also known as Metrology) and NDT departments are often independent organizational units, resulting in potential synergies often being recognized late or not at all. Combining NDT with Metrology is the main use case described in this paper, additionally also combinations of complementary NDT modalities like for instance Thermography - Dry and Wet Ultrasonic inspection and much more are possible. This paper is describing the use case of a Multi-Modality Project realized at a TIER 1 Supplier in Germany, but also giving an overview about other possible implementations. Dry inspection alternatives to the classic wet ultrasonic inspection area also mentioned in this paper.

AUTOMATED PIPELINE INSPECTION USING UNMANNED AERIAL VEHICLES

Monitoring the condition of pipelines and site facilities of the oil and gas trunk transportation system, as well as other facilities of the oil and gas complex, allows you to collect the necessary information quickly, getting into hard-to-reach places where land transport or a person cannot get to, and reduce the response time to emergency situations and eliminate their consequences.
 The paper considers the existing designs of unmanned aerial vehicles used in systems for remote monitoring of technological facilities, analyzes their advantages and disadvantages while inspecting the linear part of the trunk pipeline. Two variants for automated platforms placing along the route for taking off and recharging unmanned aerial vehicles are proposed. The first variant allows more thorough inspection while flying around, the second one allows using fewer platforms and longer inspection area.

Online monitoring of crack dynamic development using attention-based deep networks

Crack inspection is an essential means to guarantee the healthy service state of infrastructure. However, conventional methods suffer from bottlenecks such as wide blind inspection areas and low efficiency, which make it difficult to reveal the real-time development of cracks. This paper proposes an online crack analysis framework based on deep learning, aiming to effectively broaden the inspectable area and provide real-time feedback on crack development information. The proposed framework includes: (1) Lightweight attention-based crack segmentation U-shape network (CrackSeU). CrackSeU, in comparison to conventional segmentation networks, demonstrates improved fusion between multi-level and multi-scale features. According to the experimental results, CrackSeU achieves enhanced crack segmentation with reduced computation and parameters compared to several advanced network models. (2) Simple and efficient quantitative characterization algorithm. In light of the crack segmentation results, the algorithm can further quantify the actual size of cracks in the physical world, which is convenient for engineers to grasp the structural security status. (3) An online crack monitoring system incorporating the above algorithms. It enables visualization and quantitative monitoring of crack development and establishes a solid foundation for structural safety evaluation. The engineering feasibility and broad application prospect of the proposed framework are further verified by an indoor full-scale concrete beam loading test.

Lamb wave based damage imaging under nonlinear chirp excitation

Considering a trade-off between temporal-spatial resolution and multi-mode nature of Lamb waves, tone bursts with short durations are usually used as excitations in Lamb wave based damage detection. A short-duration excitation usually requires a large amplitude to carry sufficient energy so as to obtain response signals with enough signal-to-noise ratio and cover a large inspection area. In this paper, an alternative Lamb wave damage imaging method using nonlinear chirp (nonlinear frequency modulation, NLFM) excitation with a long duration and a small amplitude is proposed. The signal processing techniques of pulse compression and dispersion compensation are adopted to compress the long-duration wave packets of response signals into short ones. Compared with conventional tone burst excitations with short durations and small amplitudes, due to the long duration of the nonlinear chirp excitation and the use of pulse compression, sufficient energy can be applied to transducers under small amplitude excitations so the image contrast in imaging will not degrade. Furthermore, as large amplitude excitations are no longer required, high voltage amplifiers are not necessary so the hardware of the Lamb wave testing system is simplified. Experiments on a carbon steel plate with an artificial crack are carried out and Lamb wave signals are collected using a linear array consisting of nine PZTs. Experimental results under the NLFM signal and conventional tone bursts are provided. Experimental results show that under the condition of the same excitation amplitude, the proposed method under the NLFM excitation can achieve better imaging quality compared with methods under conventional tone bursts.

Unmanned aircraft path planning for construction safety inspections

With its flexible and convenient features, the Unmanned Aircraft System (UAS) provides an efficient platform for safety inspections in hazardous areas. Yet sparse studies have explored path planning for construction safety inspections. This research developed a multi-precision unmanned aircraft path planning system (MP-UAS) by using MATLAB for safety inspections on partially known 3D exterior construction environments. Firstly, a detailed house-building checklist and monitoring levels are formulated. Subsequently, based on the principle of merging pixel points in four neighborhoods, the Four-neighborhood Growing algorithm extracts information from the point cloud grid model to divide inspection areas. Finally, the Ant Colony Optimization (ACO) combined with four-element optimization achieves a full coverage optimal design of UAS path in two-dimensional planes above the inspection area. The system greatly reduces the path length and minimizes energy consumption while meeting requirements of coverage accuracy in the validation case, and is expected to facilitate safety inspection and decision-making.

Wireless Human Motion Detection with a Highly Sensitive Wearable Pressure Sensing Technology

AbstractWireless flexible sensing devices using inductive‐capacitive (LC) resonator‐enabled transmission technologies are attractive in the areas of human motion detection, health inspection, and implantable medical devices. However, challenges remain in LC‐based wireless sensing devices, including low device sensitivity/resolution and slow signal readout speed based on sweeping excitation frequencies. Herein, an LC resonator‐based wireless pressure sensing technology (LC‐WPS) is proposed for flexible contact pressure measurements in a real‐time manner. It includes a fully flexible passive LC pressure sensor and a signal‐reading circuit for wireless communication with the sensor and real‐time data processing. The passive sensor detects external pressure by the changes in resonant frequency. Importantly, by optimizing the design of the LC resonator in the sensor, the LC‐WPS converts the pressure‐dependent resonant frequency into circuit output voltage to a great extent, achieving a high sensitivity (1.23 × 10−2 kPa−1) and resolution (54 Pa) within a pressure range of 0–15 kPa. In addition, the LC‐WPS utilizes a single operating frequency (i.e., 13.56 MHz) instead of sweeping the operating frequencies to identify the sensor resonant frequency, featuring fast and real‐time data analysis and processing. Real‐time monitoring of human motions, such as laryngeal movement, neck bending and wrist rotation, is demonstrated, verifying the applicability of the LC‐WPS in the fields of wearable medical care and sports biomechanics.

From contact lens to 'Dream Lens' - Cultural History of Vision Correction Technology.

This paper traces how medical technologies to correct vision were introduced and changed in Korean society until the introduction of Orthokeratology called 'Dream Lens' in the late 1990s. First of all, I outlines the historical background of the introduction and spread of the relatively unfamiliar and expensive Orthokeratology, which is said to "cure" myopia and astigmatism by pressing the cornea. 'Dream Lens', a 'lens for correcting corneal refractive error', was a popular vision correction technology in terms of its name, treatment method, and effect. Not only was it introduced with a name similar to contact lens used instead of glasses from decades ago, but the way it was attached to and removed from the cornea was also similar. On the other hand, the public was already familiar with the principle of correcting the refractive index by pressing the cornea and improving visual acuity in the long term, just like LASIK which became popular in the mid-1990s. The use of contact lens which was similar in terms of the name 'lens' and the effect of 'correcting vision', and the trend of LASIK which was similar in principle of controlling corneal refraction, was a historical stage that helped soft landing of orthokeratology. However, from contact lens, vision correction technology did not settle down without any conflict. There was a conflict between medical experts traditionally responsible for optometry and production of spectacles and lens, and opticians who were newly in charge of that area. Ophthalmologists who have been in charge of optometry and prescriptions for a long time had no choice but to hand over some of the inspection areas to opticians due to the rapidly increasing number of opticians and the implementation of the optician system in 1989. And they had no choice but to watch the expansion of the business of opticians who manufactured glasses based on their own vision tests and sold them together with contact lens. Instead, corneal resection, which is not a technique for correcting visual acuity due to corneal refractive error, but a surgical technique for treating the corneal refractive error itself, has become an ophthalmologist's unique task. In addition, Dream Lens, which corrects corneal refractive error using a similar principle, has also become an object of professional medical practice because it required more precise examination and treatment than eyeglasses or contact lenses. By understanding the process by which vision correction technologies, from contact lens to dream lens, have been introduced into Korean society over the past few decades, this paper gives a new understanding how different medical technologies with the same or similar purposes are settling down, and the tension between experts in charge of them.

MODEL OF A CHAOTIC ULTRA-WIDEBAND INFORMATION TRANSMISSION SYSTEM FOR WIRELESS SENSOR NETWORKS

Distributer measuring systems, consisting of interconnected wireless sensor nodes with autonomous supply, have plenty of applications in different areas of engineering end technology. Therefore, wireless sensor network design and optimization is a vital problem in informational technologies and computer engineering. Regardless of particular application and architecture, a wireless sensor network consists of several small sensor nodes somehow distributed in an area of inspection. Such a design ensures a distributed parameter measuring, according to which, each node performs preprocessing procedures for the data, which are to be aggregated by a so-called sink node and sent via other networks, e.g., wired or wireless local area network. For healthcare solutions, it is important to ensure a stable connection with the network and server back-end to provide a high-level analysis based on predicting methods of machine learning algorithms. This paper describes an application of an ultra-wideband communication model based on chaos synchronization as a low-power and efficient alternative solution for building wireless sensor networks. Thus, using chaotic signals as information carriers in wireless communication has several advantages, including a wide smooth spectrum, high information capability, cybersecurity, and low power consumption. The synchronization problem is one of the most vital tasks to be solved to design a chaos application for ultra-wide-band communication. Being well-studied for periodic signals, modern synchronization theory contains plenty of solutions for classical telecommunication and radio engineering systems, however, it is not developed enough for chaotic systems. Hence, a one-directional dissipative synchronization between two Chen systems is studied in the first section. The second section is devoted to the computer simulation of the model, described in the previous section. All the models built and the simulations performed have been done using MATLAB/Simulink software. The negative impact of channel noise and inequality of system parameters is considered. The possible way how to improve technical characteristics is also provided. Proposed models are to be used to design and develop low-cost wireless sensor networks for multi-channel healthcare solutions.

Inspection of Enamel Removal Using Infrared Thermal Imaging and Machine Learning Techniques.

Within aerospace and automotive manufacturing, the majority of quality assurance is through inspection or tests at various steps during manufacturing and assembly. Such tests do not tend to capture or make use of process data for in-process inspection and certification at the point of manufacture. Inspection of the product during manufacturing can potentially detect defects, thus allowing consistent product quality and reducing scrappage. However, a review of the literature has revealed a lack of any significant research in the area of inspection during the manufacturing of terminations. This work utilises infrared thermal imaging and machine learning techniques for inspection of the enamel removal process on Litz wire, typically used for aerospace and automotive applications. Infrared thermal imaging was utilised to inspect bundles of Litz wire containing those with and without enamel. The temperature profiles of the wires with or without enamel were recorded and then machine learning techniques were utilised for automated inspection of enamel removal. The feasibility of various classifier models for identifying the remaining enamel on a set of enamelled copper wires was evaluated. A comparison of the performance of classifier models in terms of classification accuracy is presented. The best model for enamel classification accuracy was the Gaussian Mixture Model with expectation maximisation; it achieved a training accuracy of 85% and enamel classification accuracy of 100% with the fastest evaluation time of 1.05 s. The support vector classification model achieved both the training and enamel classification accuracy of more than 82%; however, it suffered the drawback of a higher evaluation time of 134 s.

Enhanced low-dose x-ray sensing nature of nanocrystalline CaWO4 sensor

Extensive research on the development of superior sensitive X-ray sensors by many researchers is due to their increased demand in numerous fields, like medical radiography, security inspection, and scientific research areas. Especially in healthcare, repeated or long-term high-dose X-ray exposure on patients may cause serious health hazards. Therefore, developing a superior sensing low dose X-ray sensor is essential. In this present work, a nanocrystalline CaWO4 thick film above an interdigitated electrode was developed as a direct conversion X-ray sensor that operates at different low doses (mGy) using an intraoral pulsed X-ray (70 keV) machine. The X-ray instigated photocurrent of nano-CaWO4 thick film was examined under different applied bias to obtain superior sensitivity of the device. The nano-CaWO4 thick film exhibit sensitivity of 10 nC/mGycm3 at 0.20 mGy (0.06 s) low dose under 5 V applied bias. A suitable mechanism was proposed to explain the nano-CaWO4 thick film sensing behaviour at different biased conditions.

Association between food control inspection grades and regional incidence of infectious foodborne diseases in Finland

ABSTRACT We studied regional food control inspection grades and their relation to regional incidence of domestically acquired foodborne diseases (caused by Campylobacter spp. Salmonella spp. enterohemorrhagic Escherichia coli (EHEC), and Listeria monocytogenes) using food control inspection data of local food business operators and infectious disease data from 2014 to 2019 from Finland. We observed that inferior overall inspection grades were associated with increased incidence of Salmonella infections (p=0.02). Specifically, inferior grades on cleanliness of facilities, surfaces, and equipment were associated with increased incidence of Salmonella infections (p=0.04). For this topical inspection area, a high effect size was also seen for Campylobacter infections (p=0.06). Of the individual inspection items, an association between increased incidence of Campylobacter infections and inferior grades on storage of foodstuffs (p=0.01) and verification of hygiene proficiency (p=0.03) was observed. These results suggest that food control recognizes non-compliances that may predispose to foodborne diseases.

Emission and occupational health risk assessment of harmful contaminants in various processes in a typical semiconductor manufacturing industry building

Workers in semiconductor factories have occupational health risks from exposure to chemical substances. This work analyzed hazardous chemical substances in the key process of a semiconductor factory in China, and studied cancer and non-cancer health risks and occupational health risks of workers. Research results show that more than half of the processes contain compounds such as hydrogen fluoride, chlorine, hydrogen chloride, ammonia and 2-propanol, and their concentrations vary greatly depending on the process. The occupational exposure index (Ei) of some processes is greater than 1, which means that there are adverse occupational health risks, including wet etching (WETCH), physical vapour deposition (PVD), furnace process (FUR), chemicals storehouse (CS) and diffusion (from inspection area). The pollutants with a high contribution rate to Ei vary with the process, and WETCH (operating area) has the highest contribution rate of sulphuric acid (93.33%). The Hazard Quotient (HQi) of PVD and CS is far greater than 1, indicating that there is a non-cancer risk. The lifetime cancer risk (LCRi) of wastewater treatment and CS is greater than 10−4, which indicates a risk of cancer. The General Engineer has higher health risks than the Duty Engineer due to the higher exposure frequency.

Non-Contact MEMS-Sensor Array Inspection of Composites and Metallic Parts Using Lamb Waves

Abstract Composite materials are becoming more popular in the aerospace industry, because of their physical properties. In quality assurance and in-service inspection, there is a need for fast, non-contact, high-quality, non-destructive inspection techniques. The most common approach is to perform the inspection using water-coupled high-frequency transducers. Full wavefield techniques are promising to replace the conventional inspection approach. However, these are currently performed by a laser vibrometer setup, which has drawbacks. As an alternative, a low-cost micro-electro-mechanical system (MEMS) sensor array and dedicated processing scheme are presented enabling fast inspection of large samples. This inspection approach uses a piezoelectric actuator to excite the composite or metallic part with Lamb waves. An array of MEMS sensors records the energy that radiates into the surrounding air. A dedicated processing scheme will translate the measured wavefield into a thickness map of the inspected part. For composite parts, the material’s anisotropy needs to be taken into account for accurate thickness mapping. In principle, all relevant defects show up as local thickness reductions. The results in this paper are obtained with a MEMS-sensor array of 128 elements capable of detecting ultrasound up to 250 kHz at a typical stand-off distance of 100 mm. Defects up to 6 mm in diameter could be detected in thick panels, and defects as small as 2.5 mm could be detected in thin panels. A full-size fuselage experiment shows that the method is also suited for fast inspection of large inspection areas.

DAMAGE DETECTION METHOD FOR LARGE CEILINGS USING IMAGE DIFFERENCING AND GRAD-CAM PROCEDURES

The authors suggest a novel detection method for ceiling damage using image differencing and Grad-CAM. The proposed method requires the latest image and the past image of the facility to compare. It adjusts the difference due to camera position, sunlight condition, etc. The authors show validity of this method showing four pairs of input images. The proposed method can appropriately detect damaged areas with better accuracy for facility inspection by narrowing the areas of inspection using image differencing and Grad-CAM procedures.