查看更多>>摘要：? 2022 Elsevier LtdRecent studies have focused on how to develop air quality-monitoring systems through smart sensor networks and the Internet of Things (IoT) technology. These works span a wide range of health research advancements in hospitals to improve air quality architecture and technologies, such as IoT-enabled gas sensors, hardware components and cloud computing. The benefits for comfort and productivity of good indoor air quality (IAQ) conditions in hospitals are an essential need. However, minimal attention has been paid to the review of the development of IoT-based sensory technology for proper IAQ in hospital facilities. Therefore, this study provided classification taxonomy for IoT-enabled IAQ systems and a systematic review of works concerning that classification to address the ambiguity in such trends. To this end, this study checked five databases: ScienceDirect, IEEE Xplore, PubMed, Scopus and Web of Science. A total of 926 papers from 2016 to 2021 were collected, and the retrieved articles were filtered in accordance with the defined inclusion and exclusion criteria to obtain the final set of 27 articles. The collected articles were classified into two categories on the basis of the aim and objective evidence across studies that fit the prespecified inclusion and exclusion criteria. The first category, which contained (n = 10/27) articles (37.03%), was ‘Integrated Indoor–outdoor Monitoring of Air Quality.’ The second category was ‘IAQ Contexts.’ This category contained (n = 17/27) articles (62.97%) and had five subcategories. Consequently, this study revealed new research opportunities, such as motivations, challenges and limitations and recommendations, which require attention for the synergistic integration of interdisciplinary works. Moreover, this extensive study listed a set of open issues and provided innovative key solutions, along with a systematic review, for IAQ-based IoT sensor deployment focusing on hospital facilities. The investigation of the recommended IAQ pollutants and parameters for hospital facilities depended on systematic literature and reliable organisations (Environmental Protection Agency, ISO and World Health Organisation). The required sensors for the most common pollutants and parameters, IoT hardware and devices and the required pollution thresholds utilised in IAQ for hospital facilities were highlighted and discussed. A set of available dataset information related to IAQ and the available resources were presented. The lifecycle of the context of IAQ phases was mapped for the first time, including the procedure sequencing and definition for each context to enhance IAQ-based IoT systems in future. We believe that this study is a useful guide for researchers and practitioners in providing direction and valuable information for ensuring proper IAQ research in future, especially in hospital facilities.
查看更多>>摘要：? 2022Surveillance is the utmost extensively used technology in the current scenario. In real-time, it is immensely applicable in all domains to monitor, identifying the moving objects, and tracking through computer vision. The object detection and classification is an important process in surveillance video. During this task, the visual appearance will change according to the viewing angles, lightening, and distance from the camera. It is necessary to improve the efficiency in real-time detection and classification of objects from surveillance videos. To obtain this, we proposed a fusion of Dolphin Swarm Optimization (DSO) and improved Sine Cosine algorithm (ISCA) based Support Vector Machine (SVM) classifier which includes the following steps: Frame differencing for foreground segmentation, Histogram of Oriented Gradients (HOG) for feature extraction, and DSO-ISCA-SVM classifier for classification. Initially, the surveillance videos are collected and the acquisition of images from the surveillance video camera. Secondly, the moving objects are detected by frame differencing in which the difference between two frames are estimated and compared with the threshold value. Then the shadow and noise are removed. Thirdly, the HOG capture local shapes through gradients. Finally, the proposed DSO-ISCA-SVM classifier accurately classifies the objects from the surveillance video, the DSO-ISCA is used to find the SVM parameters. This proposed technique effectively detects and classify the objects from the surveillance videos. The proposed technique results are compared with other existing methods. The experimental results prove that the proposed method efficiency is better than the existing methods in terms of different evaluation metrics.
查看更多>>摘要：? 2022In practical industrial applications, rolling bearings are in normal operation most of the time, and the inadequacy of the fault data makes the data itself exhibit unbalanced characteristics. The imbalance of data is difficult to meet the training demand of intelligent networks, which in turn causes its low recognition ability. To solve this problem, this paper proposes a new unbalanced fault diagnosis framework, the Wasserstein conditional generation adversarial network, based on hierarchical feature matching. Unlike traditional generative frameworks, which achieve the overall alignment between the generated distribution and the true distribution by adversarial only. The proposed framework unites Wasserstein loss and hierarchical feature matching loss, and constrain the data generation characteristics from the perspective of global and class-specific to improve the validity of the data. Experiments containing real bearing faults demonstrate the generalization performance of the proposed method, and the results show that the proposed method requires only a small number of 10 samples to reach 92% correct diagnosis, which provides a feasible tool for solving the current industrial data imbalance problem.
查看更多>>摘要：? 2022 Elsevier LtdThis paper performed a numerical simulation on corrosion damage identification using embedded piezoceramic (PZT) transducers. Three-dimensional finite element (FE) model of a full-scaled RC beam was generated with experimental validation, where three groups of PZT sensors in depth, width and longitudinal directions of the beam were simulated to evaluate corrosion damage rate correlated to concrete/rebar parameters including mass loss, cross-section loss, elastic modulus, strength and bond-slip relationship at steel–concrete interface. Simulation and experimental results indicated that corrosion severity was well reflected in resonance characteristics of PZT admittance and its derived root mean square deviation (RMSD) as well as mechanical impedance. Based on the results, a new sensitivity index was proposed for evaluating corrosion evolution, which suggested that the optimal sensor location was in the depth direction of the beam within a scope of 400 mm, and corrosion evolution as corrosion initiation and crack propagation stages could be effectively identified.
查看更多>>摘要：? 2022 Elsevier LtdThe TMR (Tunnel MagnetoResistance) sensors are used to replace the original induction coils, and the TMR sensors are arrayed along the x-axis direction, which quantitatively monitor crack propagation through the response sequence of TMR sensors. Firstly, a current dipole model is proposed to characterize the influence of disturbed magnetic induction intensity at the test point, and the method of quantitative monitoring of subsurface crack is proposed. Then, the finite element model of the sensor is established to analyze the disturbed effect of crack propagation on eddy current with different excitation frequencies. Finally, the experiments on the surface and subsurface crack monitoring with different depths are carried out. The experimental results show that the crack propagation can be monitored quantitatively through the response sequence of the TMR sensors. Also, the effect of subsurface crack monitoring can be improved by increasing the longitudinal distance between the test point and the crack (LDTC).
查看更多>>摘要：? 2022The dual-mixer time-difference (DMTD) technique is used for precise low-noise time comparisons. Its digital version (D-DMTD) was also already developed. The paper describes a simple digital improvement of the method that allows to compare phases of harmonic signals with similar frequencies using a digital oscilloscope with mutually phase-locked sampling. The stability of the achieved time difference measurements is below 100 fs for averaging times from one second to almost one day. The presented applications are, for example, comparisons of 10 MHz references or precise measurements of the dispersion in coaxial cables.
查看更多>>摘要：? 2022 Elsevier LtdThe continuous ultrasonic signal is a common acoustic phenomenon, and composite structures pose difficulties for traditional acoustic localization methods due to their anisotropy. To solve this problem, this paper proposes a minimum error indexing method based on frequency domain characteristic vectors. The method acquires signals through distributed sensors on a divided grid structure in advance, constitutes characteristic vectors, and generates an indexing matrix. When a new ultrasonic source occurs at an unknown location, the characteristic vector is formed by the same method and matched with the indexing matrix for ultrasonic source localization. This method is well adapted to complex structures like composite materials. The method was verified by 50 sets of localization experiments for chirp and white noise signals, The results show that the average error is 4.92 cm and 6.27 cm. It provides an idea for structure health monitor of composite materials in the future.
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