Comprehensive Inspection Research Articles

RELEVANCE OF RESEARCH ON INNOVATIVE SOLUTIONS FOR DETECTING DEFECTS IN FLAT ROOFS

Problem Statement. In Ukraine, the most numerous buildings are those constructed between 1960–1990. As of today, half of them require major repairs. According to current Ukrainian regulatory documents, comprehensive inspections of the entire building should be conducted every 10 years, and at least once every 5 years for buildings or separate elements of buildings that operate under adverse conditions, including roofs. During the full-scale war on the territory of Ukraine, the safety and health of workers are of paramount importance. Especially during air raids, when being on the roof is most dangerous—posing a threat to the life and health of specialists inspecting the roof [1]. The issue of preserving life and health is particularly significant during the Covid-19 pandemic. For example, the International Code Council, the main institution for standardizing building systems in the USA, issued recommendations during the Covid-19 pandemic regarding remote inspection of building structures. The authorities of Los Angeles at the municipal level proposed using this method for building structure inspections [2]. Objective. The article aims to analyze the needs and challenges associated with roof inspections in Ukraine, particularly in the Dnipropetrovsk region, in the context of the ongoing full-scale war. It is necessary to determine the overall volume of roofs requiring inspection, the main defects that arise, and the risks that may occur due to the lack of timely inspections. Additionally, the article needs to outline the main stages of the roof inspection process, identify the necessary knowledge and skills required by qualified specialists for comprehensive roof inspections. Conclusions. Analyzing the total number of buildings and the norms determining the frequency of roof inspections, considering all preparation stages and the skills needed by inspection specialists, as well as the conditions of the full-scale war in which our country finds itself today, it can be concluded that the preparation of such specialists is resource-intensive and requires significant investments of time and effort. Unfortunately, according to IMF data, the population of Ukraine is showing a tendency to decrease. According to statistics, in 2022 the population decreased to 35 million, and by 2023 – to 33.2 million. This leads to a decline in the number of sufficiently qualified specialists who will be able to comprehensively engage in roof inspections. The general review of aspects showed the need to introduce innovative solutions and new approaches in the field of comprehensive roof inspections. This particularly concerns the effective detection of roof defects, the preparation of comprehensive reports, and estimates with maximum savings of time, financial, and human resources.

In vitro comparative quality evaluation of different brands of Amlodipine Tablets Commercially available in Jimma Town, South-western Ethiopia.

The incidence of hypertension in persons 25 years of age and older is estimated to be 46% in Africa, where it is still very common. This concerning rate could be explained by the pharmaceutical markets' accessibility to poor quality antihypertensive drugs. Thus, the purpose of this study was to evaluate and compare the quality different brands of Amlodipine Tablets Commercially available in Jimma Town, South-western Ethiopia. The quality control test was conducted from August 30, 2019 to February 27, 2020 at Jimma University in the Laboratory of Drug Quality Control (JuLaDQ). The laboratory test was carried out in accordance with WHO inspection guidelines and United States Pharmacopeia. A statistically significant was considered when P<0.05. For further comparison of the in-vitro dissolution profiles of amlodipine tablets, model-independent model-dependent parameters and statistical Dunnetts tests for ensuring bioequivalence were used to further compare the in-vitro dissolution profiles. With the exception of brand AMD-5 (1/10), the remaining nine (n = 9) brands were within WHO visual inspection criteria. The quality control parameters such as friability, weight variation, identity, assay, and dissolution test were within the United States Pharmacopeia. The model independent parameters (f1, and f2) confirmed that, all generic products were bio-equivalence, and interchangeable with comparator product. The model dependent approaches revealed the Weibull model (AMD-10), the Zero order (AMD-3), and the Korsemeyer-Peppas models were the most effective predictions for the release of the pharmaceutical substance from the dosage form. The Korsemeyer-Peppas model (r2 ≥0.9695) was the best descriptive model for determining the amlodipine drug kinetics from the point of view of all brands examined. The evaluated amlodipine brand tablets were in line with quality standards. The model independent methods confirmed that the generic brand tablets were interchangeable in clinical practice. The tested products follow more than two drug release kinetics. The study revealed a manifest discrepancy in the dissolution profiles' releases. Therefore, it is strongly advised to use appropriately designed dissolution profile evaluation methods with various pH values in the dissolution media, as well as to do comprehensive visual inspections. This will make it easier to do a thorough investigation of any potential quality issues that might be related to various generic products available in the pharmaceutical market.

Machine Vision AI in Railroad Safety: Advanced Inspection Techniques

This article explores the transformative impact of machine vision AI in railroad safety, focusing on advanced inspection techniques. It examines the integration of technologies such as line scan cameras, LiDAR, and IoT sensors in enabling comprehensive 360-degree inspections of railway infrastructure and rolling stock. The article discusses key innovations in continuous monitoring, data processing, and AI-driven analysis, highlighting their potential to significantly enhance defect detection accuracy, reduce maintenance costs, and prevent accidents. Real-world applications in structural integrity assessment and overhead line inspection are presented, along with an analysis of current challenges and future developments in the field. The article underscores the paradigm shift from reactive to proactive maintenance strategies, promising a safer and more efficient future for rail transport.

Anatomical Approach for the Evaluation of the Nipple-Areolar Complex.

The nipple-areolar complex (NAC) is an anatomically unique region from which several normal variants and pathologies arise. Understanding its anatomy is crucial for accurate clinical and imaging assessments, aiding with differential diagnosis, and ensuring radiologic-pathologic concordance. Mammography and US are commonly used for NAC evaluation; however, these are susceptible to technical limitations such as tissue superimposition and artifacts, compromising visualization of abnormalities in this area. Although MRI offers higher sensitivity, it is not the initial evaluation modality. A comprehensive clinical inspection is necessary because it may reveal abnormalities not apparent on imaging. This article offers an anatomical approach to the NAC evaluation, simplifying differential diagnoses by reviewing imaging techniques and clinical features of common NAC abnormalities.

3D GPR Detection and Case Analysis of Collapse Hazards for an International Airport Runway

Abstract The safety of airport runways is crucial for ensuring the operation of airports and the safety of aircraft flights during taking off and landing. All current methods for assessing airport runways primarily focus on surface routine inspections or surveys, lacking both the capability and available technologies for comprehensive detection of runway and its underground conditions. In this paper, considering a specific airport runway in China that experienced collapse hazards due to cavities, three-dimensional ground-penetrating radar (3D GPR) is explored for detecting potential hazards on the runway and its surroundings. By analyzing the detection data, the formation and distribution of collapses were examined clearly based on B-scan and C-Scan, and then assessed obviously the safety conditions of the airport runway. The research work and its findings provide a new valuable insight of NDT method for guiding comprehensive inspections and maintenance of large airport runways.

Structure and Fungicidal Activity of Secondary Metabolites Isolated from Trichoderma hamatum b-3.

Two new harziane diterpenes (1-2), five undescribed cyclonerane sesquiterpenes (3-7), and three known compounds, 11-cycloneren-3, 7, 10-triol (8), harziandione (9), and dehydroacetic acid (10), were isolated from Trichoderma hamatum b-3. Their structures were elucidated via comprehensive inspection of spectral evidence in HRESIMS and 1D and 2D NMR, and the absolute configuration of 1-8 was confirmed by NMR, ECD calculation, as well as Mosher's method. In vitro fungicidal activity showed that some compounds showed great inhibitory activity against pathogenic fungi, including Fusarium graminearum, Sclerotinia sclerotiorum, Botrytis cinerea, and Rhizoctonia solani, among which compound 10 showed 100% inhibition of S. sclerotiorum and B. cinerea. The in vivo activity test showed that compound 10 was 65.8% effective against B. cinerea and compound 10 can be used as a lead compound for the development of biopesticides that inhibit B. cinerea. This study elucidated the bioactivity of secondary metabolites of T. hamatum and indicated the direction for the subsequent development of the biological control activity of T. hamatum.

Post-earthquake inspection of high-speed railway viaducts with multi-scale task interaction deep learning strategy

Automated computer vision-based inspections of railway infrastructures, such as component type, damaged status, and location, have been investigated actively by resorting to task-specific deep learning models. However, task-specific models that fulfill these separate inspection tasks encountered bottlenecks in improving inference accuracy, and bring huge computational costs. Multi-task deep learning, which can fulfill these inspection tasks concurrently, has yet to be fully investigated in the context of structural inspection. In this study, a multi-scale task interaction deep learning strategy is presented towards component recognition, damage segmentation, and depth estimation for a comprehensive post-earthquake inspection of high-speed railway viaducts. Three modules for multi-scale task interaction were proposed to modify the multi-task deep neural network, taking full advantage of task commonalities at multiple scales. The proposed method was validated with a large-scale image dataset of high-speed railway viaducts. Component recognition and depth estimation were incorporated to implement multi-task learning since they have higher pattern affinities at multiple scales. Results reported that mean Intersection over Unions of testing samples of component and damage tasks were 91.2% and 72.1%, RMSE of depth estimation was 1.54 m. Compared with single-task cases, training time, inference duration, and FLOPs of the multi-task model were reduced by 23%, 30%, 27% respectively. Results showed improvement in both inference accuracy and training efficiency, substantiating the superiority of the proposed strategy.

Design of Bayesian evaluation test for missile damage effectiveness based on multiple damage level standards

The qualified missile damage effectiveness is an important guarantee for giving full play to combat effectiveness. In order to test whether the missile damage effectiveness meets the standard, it is particularly necessary to carry out damage effectiveness identification test research. In view of the limitation that the existing "single-shot damage probability" damage effectiveness quantitative characterization index is difficult to fully describe the missile damage effectiveness based on a single damage standard, considering the different damage level results formed by a single missile hitting the target, the damage effectiveness is characterized by the probability of occurrence of different damage level results. Missile identification from the perspective of multiple damage level standards is conducive to comprehensive inspection of missile damage effectiveness. In addition, in order to overcome the problem of insufficient information in small sample missile assembly tests, the Bayesian method is combined with the system contribution degree to fuse multi-source prior information in the identification test design, and a test scheme with full information utilization and controllable risks for both parties is designed. The example shows that compared with the quantitative characterization index of a single damage standard, this study can fully describe the missile damage effectiveness, and compared with the improved binomial distribution hypothesis test method, the superiority of this method is verified.

Development of track geometry inspection equipment for high-speed comprehensive inspection train in China

Development of track geometry inspection equipment for high-speed comprehensive inspection train in China

Sensor placement method for water distribution networks based on sampling of non-bandlimited graph signals

Monitoring water distribution networks (WDNs) requires careful consideration of sensor placement, which is essential for obtaining comprehensive information about the network. A natural graphical structure underlies WDN, making graph sampling theory advantageous for selecting monitoring nodes. However, graph sampling theory is only applied only to restrictive band-limited signals, while the pressure data of WDN is a restrictive non-band-limited signal. To address this issue, this paper presents an approximate conversion method for transforming non-band-limited signals into band-limited signals, accompanied by an optimal spectrum threshold formula. This formula is used to perform spectral screening in the graph frequency domain, effectively converting non-band-limited signals into band-limited signals that preserve the major frequency components while ignoring smaller-value frequency components. By sampling band-limited signal, we identify sampling nodes that perfectly recover the signal. These sampling nodes act as monitoring nodes that can perform a comprehensive inspection of the WDN and accurately locate leaks. The accuracy of our method in recovering the signal and locating the leak is demonstrated by comparing it with two existing sensor placement optimization methods.

The SG‐Climbot: An Adaptable, Efficient, Inspection and Repair Robot for Steam Generator Heat Transfer Tube Sheet

ABSTRACTThe steam generator plays a crucial role as a safety component and protective barrier in nuclear power plants. Regular inspection and repair of heat transfer tubes, which operate in high‐temperature, high‐pressure, corrosive, and abrasive environments for extended periods, are essential. Inspection and repair robots move inside the steam generator to conduct comprehensive inspections and evaluations of the heat transfer tubes. However, existing robots have relatively simple execution devices and fixed movement methods, resulting in poor adaptability to different specifications of tube sheets and limited flexibility in handling maintenance tasks. In response to these limitations, the SG‐Climbot, a quadruped crawling tube sheet inspection and repair robot, has been proposed. This robot is designed to adapt to full‐specification tube sheets and operate efficiently by conducting inspections while moving. By comparing different motion modes, a robot configuration with a quadruped parallel structure was suggested. Kinematic and static analyses were conducted, resulting in the development of both forward and inverse kinematic models, along with the identification of conditions leading to tipping. Using parametric modeling and optimization design, optimized design parameters were obtained. Finite element simulation analysis was performed on the overall structure and main components, leading to an optimized structural model. Finally, based on the design model and computational analysis, a prototype was developed and tested. The experimental results indicate that the robot has achieved the expected functionality and performance targets. Its efficient maintenance operation mode of conducting inspections while moving provides a basis for the autonomous and intelligent development of steam generators.

Implementation of a low-cost comprehensive pavement inspection system

Assessing the condition of roads is crucial to the maintenance and rehabilitation process as a country's progress is closely linked to its transport infrastructure. Therefore, it is essential to have well-maintained roads and to be able to control and monitor them properly. Technological advancements have transformed the way pavement inspections are carried out. This study presents an innovative approach that combines stereo cameras and a GPS module for efficient and accurate data collection. This integration of low-cost technologies provides a detailed three-dimensional view of pavements, complemented by accurate geospatial information. The experimental results showed that the 3D images of pavement damage had a relative volume measurement error of 0.80 %. Unlike traditional systems such as LIDAR and ground-penetrating radar, which involve more expensive technologies, the proposed method offers a cost-effective solution. This methodology not only simplifies the inspection process but also improves the planning and execution of road maintenance and repair activities. Its low cost makes it a viable option for various projects and applications in road infrastructure.

Development of a Small-Sized Urban Cable Conduit Inspection Robot

Cable conduits are crucial for urban power transmission and distribution systems. However, current conduit robots are often large and susceptible to tilting issues, which hampers the effective and intelligent inspection of these conduits. Therefore, there is an urgent need to develop a smaller-sized conduit inspection robot to address these challenges. Based on an in-depth analysis of the characteristics of the cable conduit working environment and the associated functional requirements, this study successfully developed a small-scale urban cable conduit inspection robot prototype. This development was grounded in relevant design theories, simulation analyses, and experimental tests. The test results demonstrate that the robot’s bracing module effectively prevents tilting within the conduit. Additionally, the detection module enables comprehensive 360-degree conduit inspections, and the vacuuming module meets the negative pressure requirements for efficient absorption of dust and foreign matter. The robot has met the expected design goals, effectively enhanced the automation of the cable conduit construction process, and improved the quality control of cable laying.

The application and development of drone vision technology in railway inspection industry

The inspection and preventive maintenance of railway facilities and their surrounding environments are critical tasks for ensuring the safety of railway operations. Inspection is the prerequisite for maintenance, and therefore, comprehensive inspection and maintenance methods can effectively reduce operational risks and ensure safe train operations. This paper summarizes the application of drone vision technology in railway inspections, analyzing the use of drones for the inspection of high-altitude equipment and environments, ground-level equipment and environments, and disaster prevention and control. It also reviews the recent applications of drone vision inspection technology in the railway industry, identifies the constraints, and offers a perspective on future developments.

A new paradigm for construction safety management in China: Introducing knowledge graph and accident database into the early-stage of BIM

Significant progress has been made in managing construction safety risks based on Building Information Modelling (BIM) technology. BIM is active in all stages of construction, including5 planning, design, pre-construction and construction. However, the causes of risks and accidents are complex and can be related to humans, the environment, data and project portraits. The current construction safety risk management process lacks scientific reference and efficiency in conducting comprehensive inspections for specific projects. The uneven and substandard data quality in BIM models significantly undermines their effectiveness. This article introduces a knowledge graph and accident database through data crawling and structuring, with the use and analysis of an accident causation model, providing key risk elements and management directions for safety managers who require a high level of attention during the early-stage of BIM. The obtained knowledge graph was subjected to data mining analysis to explore the causes of accidents, considering the combined effect of multiple factors, such as “case-date-cause” and “case-address-cause”. The paradigm can be recognized by the BIM, and through the secondary development on the development side, a data interface is constructed to transfer the knowledge graph into the BIM. The approach mentioned in the article can provide standard and structured data for the BIM model, analysing high-risk points of projects, which is valuable for engineering applications.

Instrumentation of the Eiffel Tower for Continuous Monitoring

The Eiffel Tower stands as a historic and iconic monument in the city of Paris. With a total height of 330 meters and constructed with wrought iron, it features a lattice metal structure. Completed in 1889 after two years of construction, the tower was initially designed for a 20-year lifespan. Now over 130 years old and welcoming millions of visitors annually, it has become a compelling example of extending the lifespan of a structure through vigilant surveillance and maintenance. Historically, the Eiffel Tower's surveillance program primarily consisted of repeated comprehensive and detailed inspections. Since 2021, it has been equipped with sensors to continuously monitor its overall behaviour. This instrumentation includes motoring of the spire’s inclination, as well as monitoring displacements, deformations, and vibrations in its four pillars. Temperature and humidity measurements are also acquired across the structure, to help providing a comprehensive analysis. This paper presents the implemented instrumentation, addressing challenges related to its deployment, and proposes a first analysis two years after the beginning of the campaign. Seasonal movements and trends are identified, and a brief dynamic study is conducted. Finally, the paper discusses the approach of instrumentation for exceptional structures to complete ongoing surveillance.

Drive-by modal identification of railway bridges via on-board measurements from a single railroad vehicle

The global railway network spans over one million kilometers of tracks, and this extensive infrastructure is set to expand even further. The objective is to promote rail transportation as an environmentally sustainable solution to address the growing demands of mobility. A significant portion of these tracks spans across bridge structures, which must also accommodate the rising demands for mobility and increased travel speeds, placing additional demands in terms of imposed loads. At the same time, bridges worldwide suffer from aging, leading to the deterioration of their structural integrity. Such combined effects necessitate monitoring the structural health of bridges to ensure the quality and safety of railway networks by detecting possible alterations in their response characteristics. Traditional Structural Health Monitoring (SHM) techniques use stationary sensors affixed to the bridge structure, enabling the direct assessment of the collected data. While such approaches are reliable, they present limitations in the comprehensive inspection of multiple railway bridges within a network. As an alternative, mobile vibration-based sensing, utilizing sensors on passing trains, presents the potential to gather data from multiple railway bridges using only a few sensors installed on board trains. Furthermore, operating the sensor-equipped trains at frequent intervals allows for collecting continuous data, offering valuable insights into the ongoing deterioration of bridges. In light of this, our work proposes a model-based methodology for extracting the modal frequencies of bridges based on acceleration data collected from traversing trains. Our approach hinges on Kalman filtering for estimating the state and input of the train and employs a subspace identification method to ascertain the frequencies of the bridge. The ultimate goal is to develop a drive-by bridge monitoring scheme that accommodates the assessment of the remaining lifespan of bridges as well as timely repairs in the event of damage, ensuring the safety and reliability of rail transportation.

Measurement of the concentration distribution of hydrogen jets using adaptive stream stripe- background oriented schlieren (ASS-BOS)

Hydrogen leakage diagnosis has attracted more and more attention, especially in the high-pressure hydrogen system of fuel cell vehicles, where the chance of deflagration is quite high. Traditional methods for detecting gas leaks rely on stationary sensor measurements and manual inspections. Manual inspections are time and resource-consuming, and it is challenging to achieve real-time, comprehensive inspections in large spaces. In this study, a new Adaptive Stream Stripe-Background Oriented Schlieren (ASS-BOS) method for hydrogen jet visualization is proposed. Three different background patterns, namely random scatter background, checkerboard background, and stripe background, are designed for multiple experiments. The results show that when observing hydrogen jets in the far-field region (low-density gradient), ASS-BOS has higher accuracy and resolution, detects larger background displacements, and shows more turbulence details. In addition, the concentration distribution of the hydrogen jet is reconstructed using ASS-BOS. We compare the concentration of the hydrogen jet obtained from the inversion of the ASS-BOS method with the experimental results measured by the sensor. We find that the average error is 3.45%, indicating that ASS-BOS can accurately reconstruct the concentration distribution of the hydrogen jet.

Comprehensive Inspection Solution for Boiler Water Wall Tube Corrosion

A substantial number of domestic coal-fired boilers, most of which have been in operation for numerous years, are susceptible to corrosion and tube ruptures within their high-temperature environment, often resulting in unplanned shutdowns. Despite the annual planned maintenance shutdowns, which involve routine inspections of water wall and furnace tubes to detect potential corrosion and erosion, the current non-destructive testing methods are generally localized. This approach, particularly with the considerable height variation of the water wall tubes (ranging from approximately 10 to 25 meters), may overlook segments with severe corrosion during localized ultrasonic thickness gauging. Although the experience of inspection teams reduces the chance of defect oversight, the demand for a comprehensive and effective inspection technique remains a priority for boiler operators. This study utilizes the characteristic of guided waves to propagate over a certain distance along pipelines, initiating an exploration into a comprehensive inspection solution for water wall tubes. Finite element simulation results demonstrate the suitability of utilizing a 120 kHz frequency for shear horizontal mode (SH0) testing on the fire side of water wall tubes. This mode effectively screens for localized corrosion within a 3-meter range. In the field of on-site boiler inspection, electromagnetic coils are employed to generate guided waves within water wall tubes. The gathered signals from each electromagnetic guided wave testing (EMGWT) are consolidated into a distribution map, indicating suspicious signal locations. Pulse eddy current testing (PECT) is employed to identify potential issues with guided waves without requiring surface preparation. If PECT reveals anomalies, the affected surface is polished, and phased array ultrasonic testing (PAUT) is conducted to quantitatively measure the remaining wall thickness due to corrosion. The theoretical exploration and on-site inspection outcomes affirm the feasibility of this approach, aimed at enhancing operational safety for boiler water wall tubes and mitigating the risks of tube ruptures and leaks. This comprehensive inspection solution amalgamates three advanced detection technologies, each capitalizing on its unique inspection characteristics to facilitate corrosion screening, corrosion scanning, and wall thickness sizing. Through the integration of these technologies, the overall inspection strategy ensures the utmost level of reliability.

Обеспечение безопасности труда горнорабочих совершенствованием электрических сетей при подземной добыче руд

In recent years, more attention has been paid to the increase in energy consumption by mining enterprises operating mines due to the need to replace the installed electric equipment and implement automated process management systems in mining and transport areas of the mine, which ultimately ensures safe and faultless operation of power supply system at various voltage levels in both individual subdivisions and the entire mine. During the experimental studies and solving problems, safe conditions for maintaining electric installations of the mine and maintenance personnel will be ensured. Weaknesses of the grid insulation and its elements have been detected; stable values for the resistance of motor insulation, switching equipment, laid cables, and the relevant probability distribution densities have been provided. This enables the replacement of individual unstable sectors of the power grid with new cables and equipment, which will significantly improve the safety of mining operations in the conditions of a high-altitude mine. It has been established that the motors used as actuators for scraper winches and fans must be replaced with motors of similar power equipped with organosilicon insulation or filling of frontal parts with enamel paint. The conducted studies enable the development of a comprehensive inspection methodology of the mine power supply system’s insulation elements and its application for further studies at other mines.