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Heterodyne principle. φ 1 and φ 2 (phase 1 and 2) are the wrapped phase functions and λ 1 , λ 2 correspond to the unwrapped phase function [62].
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![Figure 2. General principle of radio transmission [53].](publication/357177411/figure/fig2/AS:1103103151603712@1640011694076/General-principle-of-radio-transmission-53_Q320.jpg)
![Figure 4. Vibration model [54].](publication/357177411/figure/fig3/AS:1103103151603713@1640011694211/Vibration-model-54_Q320.jpg)
Non-Invasive Inspection (NII) has become a fundamental tool in modern industrial maintenance strategies. Remote and online inspection features keep operators fully aware of the health of industrial assets whilst saving money, lives, production and the environment. This paper conducted crucial research to identify suitable sensing techniques for mac...
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Citations
... Vibration-based condition monitoring of the wind turbine (WT) gearbox [1] has gained significant attention due to its numerous benefits including the fact that it is noninvasive, reliable, cost effective and makes for early fault detection [2][3][4]. Several studies have employed vibration data for fault recognition in WT gearboxes [5][6][7]. The vibration signals are pre-processed before being fed to a Machine learning (ML) model [8]. ...
Vibration-based fault diagnosis from rotary machinery requires prior feature extraction, feature selection, or dimensionality reduction. Feature extraction is tedious, and computationally expensive. Feature selection presents unique challenges intrinsic to the method adopted. Nonlinear dimensionality reduction may be achieved through kernel transformations , however there is often a trade-off in information to achieve this. Given the above, this study proposes a novel autoencoder (AE) pre-processing framework for vibration-based fault diagnosis in wind turbine (WT) gearboxes. In this study, AEs are used to learn the features of WT gearbox vibration data while simultaneously compressing the data, obviating the need for costly feature engineering and dimensionality reduction. The effectiveness of the proposed framework was evaluated by training genetically optimized linear discriminant analysis (LDA), multilayer perceptron (MLP), and random forest (RF) models, with the AE's latent space features. The models were evaluated using known classification metrics. The results showed that the performance of the models depends on the size of the AE's latent space. As the size of the AE's latent space increased, the quality of features extracted improved until a plateau was observed at a latent space dimension of 10. The AE pre-processed genetically optimized RF, MLP, and LDA models, designated AE-Pre-GO-RF, AE-Pre-GO-MLP, and AE-Pre-GO-LDA, were evaluated for accuracy, sensitivity, and specificity in the classification of seven (7) gearbox fault conditions. The AE-Pre-GO-RF model outperformed its counterparts, scoring 100% for all evaluated metrics, though with the longest training time (239.50 sec). Comparable results were found comparing this study with similar investigations involving traditional vibration processing techniques. More so, it was established that effective fault diagnosis of the WT gearbox can be achieved through manifold learning with AEs without expensive feature engineering. ARTICLE HISTORY
... In addition, each of these methods requires the installation of dedicated sensor in a strictly defined location on the equipment, which increases the complexity of the design, production costs, and machine operation [5,18]. The method proposed in this paper allows the use of a vibroacoustic signal, nowadays increasingly used for diagnostic purposes [3], to estimate the mass intensity of the fuel that feeds a turbine engine. ...
This paper proposes the use of vibroacoustic signal parameters to estimate the fuel consumption of a miniature GTM-400 engine. The method for testing engine vibrations is presented, followed by an analysis of the results obtained. Two vibration point measures were selected to build a fuel consumption model. The models obtained were verified, after which those that best describe the real fuel consumption of the engine were selected. The paper proves that the vibration signal, in addition to its applications in jet engine diagnostics, can be used to determine engine performance, which can contribute to reducing the complexity of construction and increasing the economics of engine operation.
... An emerging trend in fault detection is the development of non-invasive mo systems with one of the main advantages being that minimal to no alterations w required to the existing set-up [40]. Despite this, the term non-invasive is not cle fined, and according to the review published by M. Alotaibi et al. [58] on nonmonitoring techniques, two opinions are most common. The first one is that nonis a synonym to non-destructive, where the diagnosis is performed without dama component in question; the second opinion is that non-invasive refers to monitori out any device contact [58]. ...
... Despite this, the term non-invasive is not cle fined, and according to the review published by M. Alotaibi et al. [58] on nonmonitoring techniques, two opinions are most common. The first one is that nonis a synonym to non-destructive, where the diagnosis is performed without dama component in question; the second opinion is that non-invasive refers to monitori out any device contact [58]. Based on this, this sub-section describes both types invasive techniques in further detail. ...
... An emerging trend in fault detection is the development of non-invasive monitoring systems with one of the main advantages being that minimal to no alterations would be required to the existing set-up [40]. Despite this, the term non-invasive is not clearly defined, and according to the review published by M. Alotaibi et al. [58] on non-invasive monitoring techniques, two opinions are most common. The first one is that non-invasive is a synonym to non-destructive, where the diagnosis is performed without damaging the component in question; the second opinion is that non-invasive refers to monitoring without any device contact [58]. ...
The industrial sector is a crucial economic pillar, seeing annual increases in the production output. In the last few years, a greater emphasis has been placed on the efficient and sustainable use of resources within industry. The use of compressed air in this field is hence gaining interest. These systems have numerous benefits, such as relative low investment costs and reliability; however, they suffer from low-energy efficiency and are highly susceptible to faults. Conventional detection systems, such as ultrasonic leak detection, can be used to identify faults. However, these methods are time consuming, meaning that leakages are often left unattended, contributing to additional energy wastage. Studies published in this area often focus on the supply side rather than the demand side of pneumatic systems. This paper offers a novel review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology of fault detection methods on the demand side of compressed air systems, leading towards a comprehensive understanding of smart and sustainable pneumatic systems. Fifty-three studies were classified and reviewed under the following three areas: (a) demand parameters which help in identifying fault sources; (b) approaches taken to analyse the parametric data; and (c) the role of Artificial Intelligence (AI) in pneumatic fault monitoring systems. This review shows that fault detection on the demand side has received greater importance in the last five years and that data analysis is crucial for AI to be implemented correctly. Nevertheless, it is clear that further research in this sector is essential, in order to investigate more complex systems. It is envisaged that this study can promote the adoption of such systems, contributing to an energy-efficient and cost-effective industry.
... The electrochemical detection method adds the possibility for patients to actively monitor their own health. The development of non-invasive biosensors utilizing nanomaterials as diagnostic tools is one of the approach to solve these issues [1]. With a quick and low-cost point-of-care testing system, this approach (electrochemical detection) aims to assist people in keeping track of their health conditions [2]. ...
The green synthesized nanoparticles have multiple functions because of their ecological origin and biocompatibility. The silver-chitosan nanoparticles (Ag-CS NPs) were synthesized using the microwave-assisted green synthesis method at different reaction temperatures of 80–120 °C. The Ag-CS NPs nanoparticles have spherical shapes, with an average particle size between 19 and 49 nm. The in vitro antioxidant potential of Ag-CS NPs was examined, and the obtained IC50 value was 36.94 µgml−1. The antibacterial activity against Vibrio cholerae and Staphylococcus Aureus produced maximum inhibition zones of 11.1 mm and 9 mm, respectively. The biosensing ability of Ag-CS NPs for dopamine using differential pulse voltammetry (DPV) showed a LOD of 0.01 µM, with a linear range of 0.1–60 µM, which is less than 0.3–3 mM for detecting DA in urine samples. These findings demonstrate the potential of Ag-CS NPs as an inexpensive antioxidant and antibacterial agent. The proposed sensor was successfully applied to rapidly detect dopamine in human urine.
Graphical abstract
... A periodic maintenance strategy involves planned and periodic repairs/replacements of equipment. It is still one of the predominant maintenance strategies used in practice for those technical assets for which it is impossible to implement diagnostic measures, e.g., for technical or economic reasons [71]. For example, more information can be found in the works [72,73]. ...
Recently, there has been a growing interest in issues related to maintenance performance management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies indicate a lack of research on the systematic literature reviews and surveys of studies that would focus on the evolution of Industry 4.0 technologies used in the maintenance area in a cross-sectional manner. Therefore, the paper reviews the existing literature to present an up-to-date and content-relevant analysis in this field. The proposed methodology includes bibliometric performance analysis and a review of the systematic literature. First, the general bibliometric analysis was conducted based on the literature in Scopus and Web of Science databases. Later, the systematic search was performed using the Primo multi-search tool following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The main inclusion criteria included the publication dates (studies published from 2012–2022), studies published in English, and studies found in the selected databases. In addition, the authors focused on research work within the scope of the Maintenance 4.0 study. Therefore, papers within the following research fields were selected: (a) augmented reality, (b) virtual reality, (c) system architecture, (d) data-driven decision, (e) Operator 4.0, and (f) cybersecurity. This resulted in the selection of the 214 most relevant papers in the investigated area. Finally, the selected articles in this review were categorized into five groups: (1) Data-driven decision-making in Maintenance 4.0, (2) Operator 4.0, (3) Virtual and Augmented reality in maintenance, 4) Maintenance system architecture, and 5) Cybersecurity in maintenance. The obtained results have led the authors to specify the main research problems and trends related to the analyzed area and to identify the main research gaps for future investigation from academic and engineering perspectives.
... Guided waves, ultrasound, vibration and magnetic-based techniques have been also frequently implemented but they mainly suppose direct contact with the objects. A detailed review of non-invasive inspection techniques used in condition monitoring is represented in [44]. ...
It is a challenge for mining enterprises to diagnose the belt conveyors, which length can be tens of kilometres and the number of idlers reaches several thousand. All of them require inspection, which is infeasible to perform using monitoring sensors, such as accelerometers. The authors proposed a novel method for the rotational speed measurement of idlers based on image data analysis. The relation is assumed of the rotation speed decrease due to internal defects. The procedure of visual data processing is verified on the real conveyor idlers. The remote sensing method can be applied in mobile inspection robots such as UAVs or UGVs as well as for manual camera recordings. The accuracy of the proposed method is 0.13-0.67% error depending on the speed range, which is provided by the standard sampling rates (30-60 FPS) and video resolution (1280 x 720 px). Recommendations are formulated for method implementation in practice.
... On the other hand, the non-contact based method provides more advantages [10] such that it cannot destruct the bridge surface by equipment [11], it has high precision, high efficient and high flexibility characteristics [12], and it can be operated in real time [13]. The non-contact method usually utilizes optical centric devices such as laser beam [14], radar [15,16], acoustic [17], thermal model [18], and image-based measurements [19,20]. Furthermore, the image-based methods are mainly grouped into two approaches: computer vision approach [21] and photogrammetric restitution approach [22]. ...
Burgeoning off-the-selves Digital Single Lens Reflector (DSLR) cameras have been gaining attentions as a fast and affordable tool for conducting deformation monitoring of man-made engineering structures. When a sub millimetre of accuracy is sought, deliberate concerns of their usage must be considered since lingering systematic errors in the imaging process plaque such non metric cameras. This paper discusses a close range photogrammetric method to conduct structure deformation monitoring of the bridge using the digital DSLR camera. The bridge is located in Malang Municipality, East Java province, Indonesia. There are more than 100 images of the bridge’s concrete pillars were photographed using convergent photogrammetric network at distance variations between 5m to 30m long on each epoch. Then, the coordinates of around 550 captured retro-reflective markers attached on the pillars facade are calculated using self-calibrating bundle adjustment method. The coordinate differences of the markers from the two consecutive epochs are detected with a magnitude between 0.03 mm to 6 mm with a sub-millimetre precision measurement level. However, by using global congruency testing and a localization of deformation testing, it is confirmed that the bridge pillar’s structures are remain stable between those epochs.
... Difficulties that may be faced by patients are living far away, for example, people living in rural areas, elderly patients, and patients who are unable to move [37]. Remote inspection can also reduce costs and speed up early detection [38]. Moreover, a smart mobile application to monitor visual function in diabetic retinopathy and age-related macular degeneration patients already existed and is being investigated [39]. ...
Recent years, advances in the internet and communication technology have enabled the proliferation of digital medical devices with innovations in the form of health applications, including for visual acuity examination. However, the validity of these applications remains unclear. The limited mobility and health service during the COVID-19 pandemic underscores the urgent need to conduct research that validates these electronic device-based applications. Thus, this study aims to critically analyze whether the electronic device-based application is able to provide a valid and high-quality visual acuity examination. A systematic review was conducted through studies search on PubMed, MEDLINE, Springer, and Cochrane Library using specific keywords. After the studies were selected through inclusion and exclusion criteria, extraction was carried out. Publications from 2011 to the end of 2021 were reviewed, yielding in 1409 studies, of which 19 were included. The results showed a lower systematic bias for distance visual acuity testing with electronic device-based applications compared to standard reference tests with a mean difference of -0.08 to 0.10 logMAR. The validity of the near visual acuity examination with the application shows better results than the distance examination which is marked by smaller 95% limits of agreement range. The results of the analysis of Bland-Altman plots in all the studies reviewed showed that the accuracy of the examination results tended to increase in patients who had better visual acuity. In practice, the use of electronic device-based applications for visual acuity examination can increase the work effectiveness of medical personnel and the proliferation of digital medical devices. It can also be one of the breakthroughs in the field of remote medical services and support the implementation of telemedicine policies.
... Numerous experimental studies support the use of AE-based methodologies and other non-destructive techniques to diagnose or detect fault components in mechanical systems, particularly wear monitoring [8][9][10][11][12][13]. Chen et al. [14,15] investigated the link between the tribo-surface and friction coefficient, as well as the sliding speed and friction noise, using a reciprocating system. ...
When friction processes occur, wear is generated. The generation of wear also leads to airborne noise. There have been many research studies on wear and its correlation with airborne noise, but most research has focused on experimental aspects, and theoretical models are rare. Furthermore, analytical models do not fully account for the wear and airborne noise generation, especially at an asperitical level. One model was developed that gave a reasonable quantification for the relationship between wear and airborne noise generation at an asperitical level under room temperature. In this paper, the accuracy of the model is assessed at higher temperatures. Two materials were set up on a tribometer (aluminium and iron) at 300 RPM. The samples were tested at two different temperatures (40 and 60 degrees) and two different loads were applied (10 N and 20 N). The model computed the predicted wear and sound pressure, and it was compared with the experimental results. The errors are larger for the wear than when the model was validated at room temperature. However, the increase in the error for the sound pressure was smaller at higher temperatures (approximately 20–30%). This is due to the assumptions that were made in the initial model, which are exacerbated when higher temperatures are applied. For example, flash temperatures were neglected in the original model. However, when initial heat is applied, the effects of flash temperatures could be more significant than when no heat is applied. Further refinements could improve the accuracy of the model to increase its validity in a wider temperature range.
The article presents a safety system for monitoring an employee which serve as early warning systems for anticipating potential negative events. The system has two main functions: locating the worker and monitoring the worker parameters such as pulse, temperature, accelerometric measurement. The system is designed to help in emergency situations at large industrial facilities.
