Engineering Inspection Research Articles

Digital twin-enhanced robotic system for remote diesel engine assembly defect inspection

Purpose This study aims to streamline and enhance the assembly defect inspection process in diesel engine production. Traditional manual inspection methods are labor-intensive and time-consuming because of the complex structures of the engines and the noisy workshop environment. This study’s robotic system aims to alleviate these challenges by automating the inspection process and enabling easy remote inspection, thereby freeing workers from heavy fieldwork. Design/methodology/approach This study’s system uses a robotic arm to traverse and capture images of key components of the engine. This study uses anomaly detection algorithms to automatically identify defects in the captured images. Additionally, this system is enhanced by digital twin technology, which provides inspectors with various tools to designate components of interest in the engine and assist in defect checking and annotation. This integration facilitates smooth transitions from manual to automatic inspection within a short period. Findings Through evaluations and user studies conducted over a relatively long period, the authors found that the system accelerates and improves the accuracy of engine inspections. The results indicate that the system significantly enhances the efficiency of production processes for manufacturers. Originality/value The system represents a novel approach to engine inspection, leveraging robotic technology and digital twin enhancements to address the limitations of traditional manual inspection methods. By automating and enhancing the inspection process, the system offers manufacturers the opportunity to improve production efficiency and ensure the quality of diesel engines.

Property Valuation in Latvia and Brazil: A Multifaceted Approach Integrating Algorithm, Geographic Information System, Fuzzy Logic, and Civil Engineering Insights

This study aimed to predict residential apartment prices in Latvia and Brazil using algorithms from machine learning, fuzzy logic, and civil engineering principles, with a focus on overcoming multicollinearity challenges. To explore the market dynamics, we conducted four initial experiments in the central regions of Riga and Jelgava (Latvia), as well as São Paulo and Niterói (Brazil). Data were collected from real estate advertisements, supplemented by civil engineering inspections, and analyzed following international valuation standards. The research integrated human decision-making behavior with machine learning and the Apriori algorithm. Our methodology followed five key stages: data collection, data preparation for association rule mining, the generation of association rules, fuzzy logic analysis, and the interpretation of model accuracy. The proposed method achieved a mean absolute percentage error (MAPE) that ranged from 5% to 7%, indicating strong alignment with market trends. These findings offer valuable insights for decision making in urban development, particularly in optimizing renovation priorities and promoting sustainable growth.

Модель автоматизации управления процессом обследования зданий на этапе эксплуатации

The article presents a study of the possibilities of automating the inspection processes of load-bearing building structures, with a special emphasis on the use of CRM systems with specialized modules. Practical examples of the implementation of such systems in the activities of construction organizations are analyzed. The necessity of engineering and technical inspection of buildings at all stages of their life cycle is discussed, based on the relevance of information on the technical condition of structures to ensure the safety of users. A process map has been developed covering various stages, such as data preparation, task creation, accounting and reporting documentation, using Bitrix 24. The key actions involved in each stage are identified, as well as the role and interaction of various departments of the organization. The importance of using BPMN for business process modeling is emphasized, which makes it possible to improve the management and coordination of work, reduce the risks of errors and increase the deadline for completing tasks. The work offers a systematic approach to conducting building surveys, covering key aspects of automation and process organization, which can significantly improve the quality and efficiency of surveys in the construction industry. Such modeling makes it possible to optimize the interaction between specialists, minimize the likelihood of errors and speed up the execution of work, ensuring systematization and control at all stages of the examination.

Load Identification in Steel Structural Systems Using Machine Learning Elements: Uniform Length Loads and Point Forces

Actual load identification is a most important task solved in the course of (1) engineering inspections of steel structures, (2) the design of systems rising or restoring the bearing capacity of damaged structural frames, and (3) structural health monitoring. Actual load values are used to determine the stress–strain state (SSS) of a structure and accomplish various engineering objectives. Load identification can involve some uncertainty and require soft computing techniques. Towards this end, the article presents an integrated method combining basic provisions of structural mechanics, machine learning, and artificial neural networks. This method involves decomposing structures into primitives, using machine learning data to make projections, and assembling structures to make final projections for steel frame structures subjected to elastic strain. Final projections serve to identify parameters of point forces and loads distributed along the length of rods. The process of identification means checking the difference between (1) weight coefficient matrices applied to unit loads and (2) actual loads standardized using maximum load values. Cases of neural network training and parameters identification are provided for simple beams. The aim of this research is to enhance the reliability and durability of steel structures by predicting consequences of unfavorable load, including emergency impacts. The novelty of this study lies in the co-use of artificial intelligence elements and structural mechanics methods to predict load parameters using actual displacement curves of structures. This novel approach will enable engineering inspection teams to predict unfavorable load peaks, prevent emergency situations, and identify actual causes of emergencies triggered by excessive loading.

Crack Detection of Curved Surface Structure Based on Multi-Image Stitching Method

The crack detection method based on image processing has been a new achievement in the field of civil engineering inspection in recent years. Column piers are generally used in bridge structures. When a digital camera collects cracks on the pier surface, the loss of crack dimension information leads to errors in crack detection results. In this paper, an image stitching method based on Speed-Up Robust Features (SURFs) is adopted to stitch the surface crack images captured from different angles into a complete crack image to improve the accuracy of the crack detection method based on image processing in curved structures. Based on the proposed method, simulated crack tests of vertical, inclined, and transverse cracks on five different structural surfaces were conducted. The results showed that the influence of structural curvature on the measurement results of vertical cracks is very small and can be ignored. Nevertheless, the loss of depth information at both ends of curved cracks will lead to errors in crack measurement outcomes, and the factors that affect the precision of crack detection include the curvature of the surface and the length of the crack. Compared with inclined cracks, the structural curvature significantly influences the measurement results of transverse cracks, especially the length measurement results of transverse cracks. The image stitching method can effectively reduce the errors caused by the structural curved surface, and the stitching effect of three images is better than that of two images.

Research on the Billing Standard of Highway and Water Transport Test and Inspection in Shandong Province

With the rapid development of China's economy, all sectors of society on the quality and safety of road and water transport projects have gradually increased the importance of road and water transport test, and inspection services market demand and cost share have also increased. Many test and inspection organizations have flooded the market, resulting in malicious competition and price confusion in the test and inspection market. Therefore, providing a set of scientific, reasonable, and standardized test and inspection billing standards is urgently needed to improve the test and inspection management of road and water transport projects and solve the existing problems. Based on this, the project will rely on Shandong Province highway and water transport engineering test and inspection billing standard research project, systematic analysis of Shandong Province highway and water transport engineering test and inspection factors. It is from the cost of scientific management and field research of the characteristics of the system research, for Shandong Province test and inspection charges to provide a more objective, accurate, scientific theoretical basis for calculating, for the further preparation of Shandong Province, highway and water transport engineering test and inspection Billing standards in Shandong Province to lay a solid theoretical foundation.

Multiscale finite element analysis of layer interface effects on cracking in semi-flexible pavements at different temperatures

This paper presents comprehensive research work on the crack initiation behavior of Semi Flexible Pavements (SFP) with the help of a one-way coupled multiscale modelling approach. The study focuses on elucidating the influence of layer interface conditions on potential cracking patterns under different temperature conditions. By integrating material properties at both local (mixture) and global (pavement) scales using a local de-homogenization approach, the interlocking effect was addressed within the asphalt binder's mesoscale properties. CT-image based mesostructure was employed to reconstruct the Representative Volume Element (RVE). Cohesive Zone Model (CZM) was utilized to simulate cracking initiation within the RVEs, with simulation results validated against practical engineering inspections. Additionally, a potential macroscopic failure index was introduced for SFP. It was found that the typical macroscopic failure indexes utilized for AC pavement may not be suitable for SFP due to the higher degree of heterogeneity. Analysis showed that SFP layer's coarse aggregate and cement grout at the bottom may experience compressive stress, while asphalt binder beneath the tire load may face high tensile stresses. Regardless of the interface conditions, top-down cracking was found to be the dominating failure mode in SFP. Besides, the vulnerable area in bonded interface SFP shifts from under tire load to the adjacent area with the rise in pavement temperature, while bottom-up cracking may appear only in unbonded interface SFP under low temperature conditions. Subsequent analysis demonstrated that top-down cracking is prominent in bonded interface SFP, especially at higher temperatures, compared to unbonded interface SFP. It is expected that critical observations for SFP highlighted above will certainly help in understanding critical failure modes and, hence, designing and constructing durable SFP structures.

Effect of using scan body accessories and inter-implant distances on the accuracy of complete arch implant digital impressions: An in vitro study.

To introduce a novel design for scan body accessory parts that are reusable, easy to attach and detach without permanent change of the scan body, and can be used with different inter-implant distances to enhance the accuracy of complete arch implant scans. A maxillary polymethylmethacrylate (PMMA) model with a soft tissue replica was fabricated with four implant analogs located at tooth positions 17, 13, 22, and 27 with 18, 25, and 30mm inter-implant distances. Four scan bodies (SBs) were attached to the implants. The model was scanned with a laboratory scanner to be used as a reference scan. A total of 40 scans were made with the same intraoral scanner and they were divided equally into two groups. Group A: Complete arch implant scans without scan body accessories (n = 20), and Group B: Complete arch implant scans with scan body accessories (n = 20). Intraoral scans were exported and superimposed on the reference scan using reverse engineering inspection software to be evaluated for 3D deviations, angular deviations, and linear deviations. Statistical analysis was performed with student t-test and analysis of variance (ANOVA) with repeated measures followed by post hoc adjusted Bonferroni test. The level of significance was set at P = 0.05. The scan body accessories decreased both the 3D and linear deviations, with a statistically significant difference at SB4 for the 3D deviation (P = 0.043) and the linear inter-implant discrepancies between SB1-SB2 and SB3-SB4 (P = 0.029 and < 0.001), respectively. However, there was no statistically significant difference in angular deviation between the study groups. Implant positions had significant differences within each group. A significant improvement in the accuracy of the complete arch implant digital impression was achieved by using the scan body accessories, particularly in reducing the 3D and linear deviations at the most distant implant positions.

Multi-Level Hazard Detection Using a UAV-Mounted Multi-Sensor for Levee Inspection

This paper introduces a developed multi-sensor integrated system comprising a thermal infrared camera, an RGB camera, and a LiDAR sensor, mounted on a lightweight unmanned aerial vehicle (UAV). This system is applied to the inspection tasks of levee engineering, enabling the real-time, rapid, all-day, all-round, and non-contact acquisition of multi-source data for levee structures and their surrounding environments. Our aim is to address the inefficiencies, high costs, limited data diversity, and potential safety hazards associated with traditional methods, particularly concerning the structural safety of dam bodies. In the preprocessing stage of multi-source data, techniques such as thermal infrared data enhancement and multi-source data alignment are employed to enhance data quality and consistency. Subsequently, a multi-level approach to detecting and screening suspected risk areas is implemented, facilitating the rapid localization of potential hazard zones and assisting in assessing the urgency of addressing these concerns. The reliability of the developed multi-sensor equipment and the multi-level suspected hazard detection algorithm is validated through on-site levee engineering inspections conducted during flood disasters. The application reliably detects and locates suspected hazards, significantly reducing the time and resource costs associated with levee inspections. Moreover, it mitigates safety risks for personnel engaged in levee inspections. Therefore, this method provides reliable data support and technical services for levee inspection, hazard identification, flood control, and disaster reduction.

A study on the application of an improved adaptive neural network in prestressed bridge engineering inspection

Abstract In recent years, there have been mixed evaluations of the performance of pre-stressed bridges in society. Based on this, this study proposes to integrate adaptive neural networks with BP networks to build a bridge tolerance detection model and combines support vector machines and radial basis function networks to build a bridge wind vibration detection model. The results showed that in the detection results of angle adjustment and detachment, Sample 1 was the closest to the true value, with a difference of only 0.01. As the number of samples increased, the difference became larger, and the difference in sample 5 reached its maximum value of 0.3. The turbulence level of 0.5% had the lowest initial vibration wind speed at a wind attack angle of 10°, with a maximum value of 21m/s. This indicates that the proposed combination model should be more accurate in detecting the tolerance of bridges and more timely in detecting wind-induced vibration risks. In general, research methods have a significant technical value for the safety maintenance of bridge engineering.

Research on combination of periodic inspection and data-driven maintenance system of turbofan engine

In the field of aviation, turbofan engine is a crucial high-precision component of an aircraft which requires rigorous maintenance to ensure the running stability, safety, and efficiency. To reduce the high cost of general maintenance, the system of combination of periodic inspection and Data-driven maintenance is a meaningful research trend. In this pattern, the engine's condition study over sensor data serves as the foundation for the maintenance, to meet the safety requirements, improved sensor data processing and interpretation and precise prediction model plays important role. In this study, Long Short-Term Memory (LSTM) architecture was used to estimate RUL (remaining useful life) and support periodic inspection. The experiments were taken by using the dataset of FD001 and FD003 in Turbofan engine degradation dataset that contains operating and degradation information of several turbofan engines. After being analysed by different evaluation methods, the algorithm is capable to discover the features that hidden among sensor data, which indicates that the model has promising results for predictive maintenance. Therefore, the Data-driven maintenance structure that integrated with LSTM architecture is proposed as an application method. Furthermore, considering all aspects of the real application, management tools, Kubernetes and Kubeflow are introduced in this paper. Finally, regularly scheduled inspection is introduced, with the help of estimated RUL, inspection can be applied by parts rather than removing engine for overhaul and replacement of all parts including parts in good condition.

The Relationship between Complete Vehicle and Components in Narrowband Radiation Emission Limits in the Standard of ECE R10

The narrowband radiated emission limit curve of the vehicle has changed significantly in the sixth revision of ECER 10. In this article, the emission value of electromagnetic waves at different distances in different frequency bands is measured. Meanwhile, the correspondence between the narrowband radiation emission limits of the whole vehicle and the components is explored. Finally, the correspondence between the far field and near field applicable to narrowband radiation emission of components in automotive inspection engineering is proposed.

The Influence of Wind Speed on the Thermal Imaging Clarity Based Inspection for Transmission Line Conductors

Infrared thermal inspection is the primary way to detect transmission line conductor faults. Nevertheless, the conventional inspections are carried out at low wind speeds, causing high investment and low efficiency. Besides, the relationship between wind speed and infrared image clarity of transmission lines has yet to be investigated. In this paper, a temperature difference-based definition of infrared imaging contrast that quantifies image clarity is firstly proposed. To explore the relationship between thermal imaging contrast and wind speed, thermal cycling tests are carried out. Based on tests and membership frequency research, a method for predicting whether a clear image could be obtained is derived. In addition, the accuracy of the proposed method is verified in a natural environment. The results show that wind speed is the only variable that affects infrared imaging contrast. High clarity image can be acquired when the contrast ranges from 0.35 to 0.78. Moreover, the average error between the practical and calculated values of contrast in the natural test is 9.1%, indicating that the proposed method is effective. The conclusion in this work provides feasible guiding significance for the infrared thermal imaging inspection engineering of overhead transmission lines.

Estimation of the residual service life of reinforced concrete beams of an industrial facility taking into account corrosion wear

Introduction. Corrosion damage of reinforcement and concrete is an important factor reducing durability of industrial facilities. The article presents the methodology and results of probabilistic calculation of residual life of separate reinforced concrete structures of an industrial building as well as of reinforced concrete structures working in the system. A three-storey open stand with dimensions in terms of 30 × 15 m and 25 m in height is considered. The calculated parameters of the actual state of the structures are obtained on the basis of experimental diagnostic studies.&#x0D; &#x0D; Materials and methods. According to the results of a full-scale field engineering inspection using standard and non-standard methods of non-destructive testing, the most damaged structures of the framework — reinforced concrete floor beams have been determined. The degree of corrosion damage of working reinforcement and compressed concrete has been determined. The method of probabilistic calculation of a reinforced concrete beam with regard for corrosion deterioration is outlined. The limiting bending moment in the beam section is considered as a nonlinear function of two random arguments — the strength of concrete and the strength of reinforcement. A linear law of corrosion damage accumulation is adopted. The probabilistic characteristics of the limiting bending moment are found by the Monte Carlo method on the basis of the normative method of calculation of a rectangular reinforced concrete section with double reinforcement. The reliability index has been used to determine the numerical values of the probability of failure and operating time.&#x0D; &#x0D; Results. Statistical characteristics of bending moment limit changing in time from the beginning of concrete protective properties exhaustion to element failure have been obtained. Lifetime before failure for a given guaranteed safety is found out.&#x0D; &#x0D; Conclusions. The practical application of the probabilistic method combined with field survey data to solve the problem of assessing the residual service life of reinforced concrete beams of a real industrial building is shown.

Intelligent Dynamic Test System for Vehicle Engine Based on 5G Internet of Things

With the development of the automobile industry, the improvement of the reliability test level and the intelligent fault diagnosis level of the engine, as the heart component of the automobile and the assembly with the highest failure rate, becomes more and more important. In a context where technology is being upgraded, the development of intelligent automotive engine inspection system based on IoT thinking is set to become the major trend in the future. The objective of this article would be to have better knowledge about smart car engine system in the 5G IoT era. It is also through the study, a dynamic testing and characterization of the engine. The performance of the automobile engine, especially the dynamic performance, is further optimized. In this article, we focus on the PUMAOPEN test system of AVL and the system under test, the state management of the test process, and the intelligent transformation of key components. The results show that: studies and analyses the dynamic working conditions of intelligent vehicles on the Internet of Things, and compares the dynamic working conditions with the steady working conditions from qualitative to quantitative. By analyzing the influence of throttle opening change rate and speed change rate on dynamic performance and engine dynamic torque estimation, the fast sensing and response-ability in the engine testing process is improved. When the engine is accelerated by the experimental method presented in this article, and when the throttle opening is more than 30% and the engine speed varies at 100 and 200 rpm/s, the output value of the torque is higher than the output value of the steady-state torque or has little difference with the output value of the steady-state torque, and tends to be stable. In deceleration performance, the dynamic output torque of the engine is asymmetric. And it will deviate from the steady-state output torque, showing different dynamic response characteristics in different working sections. Throttle delay, overshoot characteristics, mechanical inertia, inflation coefficient, air–fuel ratio, and ignition advance angle when engine speed changes sharply will make engine dynamic characteristics deviate from steady-state characteristics.

Experimental study of dynamic splitting-tensile properties of precast concrete samples under different strain rates

This study investigated the dynamic splitting and tensile properties of the precast concrete core samples under different strain rates using the split-Hopkinson pressure bar (SHPB). The dynamic splitting-tensile strength (DSTS), stress–strain curves, and damage patterns of concrete were analyzed. The modified Weibull statistical model was utilized to analyze the discrete features of DSTS and strain rate effects of the precast concrete samples. Besides, the fractal theory was applied to calculate the fractal dimension of surface cracks on core specimens. The relationships between the fractal dimension, splitting-tensile strength, and strain rate effect were also presented. Consequently, it was found that the stress–strain curves of different strength grades of concrete specimens displayed similar patterns. The DSTS of precast concrete exhibited an apparent impact-strengthening effect. And the modified Weibull model proposed in this paper could accurately predict the distribution of DSTS at different strain rates of precast concrete, which provided a theoretical reference for the strength prediction of precast concrete in practical engineering practices. Furthermore, the fractal dimension could qualitatively characterize the failure evolution trend and extent of splitting-tensile damages, providing a new research direction to investigate crack patterns and dynamic mechanical properties of precast concrete members in future engineering inspection and maintenance.

Prospects of Consumer-Grade UAVs for Overpass Bridges Pier Pads Alignment

The use of Unmanned Aerial Vehicles (UAVs) for surveying is at the forefront of their use in the Architectural Engineering and Construction (AEC) industry. UAVs make accessing hard-to-reach construction regions simpler and more cost-effective because of their small size, ease of mobility, and the wealth of information given by their integrated sensors. Accordingly, their use is thriving in different AEC sectors such as the management and inspection of engineering facilities such as concrete bridges. Overpass bridge engineering inspections are still applied using high accuracy surveying instruments in situ to ensure meeting the quality standards of construction. One important application is to measure the bridge pier caps centerline fitting using total stations, which is costly in terms of time and labor. Therefore, in this article, a new approach based on consumer-grade UAV imaging is proposed for replacing the traditional surveying techniques which are expected to improve automation and reduce time and cost. The proposed method utilized a sequence of processes on the UAV point clouds of the bridge concrete pier caps to finally extract the pier pads center and check their alignment. In two experiments, point clouds are created using DJI Phantom 3 images taken over bridge pier projects under construction, and concrete pad centers are then estimated and compared to the reference total station measurements. The results of both tests reveal the ability of the proposed method to attain the required accuracy for the pads’ alignment, as the root mean square error (RMSE) is one centimeter and two centimeters for the first and second tests, respectively. In addition, the new approach can reduce implementation time and the project budget.

Computer-vision-guided semi-autonomous concrete crack repair for infrastructure maintenance using a robotic arm

Engineering inspection and maintenance technologies play an important role in safety, operation, maintenance and management of buildings. In project construction control, supervision of engineering quality is a difficult task. To address such inspection and maintenance issues, this study presents a computer-vision-guided semi-autonomous robotic system for identification and repair of concrete cracks, and humans can make repair plans for this system. Concrete cracks are characterized through computer vision, and a crack feature database is established. Furthermore, a trajectory generation and coordinate transformation method is designed to determine the robotic execution coordinates. In addition, a knowledge base repair method is examined to make appropriate decisions on repair technology for concrete cracks, and a robotic arm is designed for crack repair. Finally, simulations and experiments are conducted, proving the feasibility of the repair method proposed. The result of this study can potentially improve the performance of on-site automatic concrete crack repair, while addressing such issues as high accident rate, low efficiency, and big loss of skilled workers.

Corrosion Risk Estimation and Cause Analysis on Turbofan Engine

Turbofan engine parts are subject to corrosion. This degradation is only very difficult to observe outside of engine dismantling on predefined inspection dates. On the other hand, it is necessary to go specifically to observe the impacted parts to notice this wear. This inspection process is long, expensive and rarely carried out with the aim of detecting a corrosion effect. The provision of an indicator to alert on potential corrosion and to target parts is highly anticipated. Better still, if the origin of this corrosion can be identified by numerical methods, it will then be possible to improve the calculation of the lifespan of the part and to space out engine inspections.&#x0D; We offer an indicator estimating if an engine part is corroded. In addition to the alert subject to this estimate, we also offer a graphical means to interpret this detection.

Discussion on the Mutual Influence and Measures of Engineering Inspection and Construction Quality Control

Discussion on the Mutual Influence and Measures of Engineering Inspection and Construction Quality Control