查看更多>>摘要：Inflatable structures are increasingly used in aerospace engineering. However, the space survivability and durability of such structures are of particular concern due to material aging in space environment and unex-pected external impact threats. Thus, it is very urgent to in-situ monitor and assess structural health condition for space inflatable structures. Since inflatable structures are often lightweight, large-sized and flexible, their low-frequency vibration response contains much information about structural health condition. To facilitate in-situ structural health monitoring of space inflatable structures, this paper developed a miniature low-frequency dynamic stiffness measurement prototype. The prototype is capable of generating two channels of swept-sine excitation signals, and concurrently acquiring six channels of response signals. Recorded data is communi-cated and downlinked from the host spacecraft to the ground, and then the dynamic stiffness is derived to determine structural health condition. To validate the developed prototype, two simulated inflatable space structures are fabricated and tested, including an inflatable boom and an inflatable torus, and then Macro-Fiber Composite transducers are attached on two specimens as actuators and sensors in tests. Experimental studies show that the prototype functions well and the outputted results are consistent with that measured by large-bulked commercial ground devices. Additionally, the multi-channel functionality of the prototype is verified by carrying out the multi-input multi-output test. In summary, the prototype features small size, light weight, and low power consumption, which has the potential for future space applications.
查看更多>>摘要：Today COVID-19 pandemic articulates high stress on clinical resources around the world. At present, physical and viral tests are slowly emerging, and there is a need for robust pandemic detection that biomedical sensors can aid. The utility of biomedical sensors is correlated with the medical instruments with physiological metrics. These Biomedical sensors are integrated with the systematic device to track the target analytes with a biomedical component. The COVID-19 patients' samples are collected, and biomarkers are detected using four sensors: blood pressure sensor, G-FET based biosensor, electrochemical sensor, and potentiometric sensor with different quantifiable measures. The imputed data is then profiled with chest X-ray images from the Covid-19 patients. Multi-Layer Perceptron (MLP), an AI model, is deployed to identify the hidden signatures with biomarkers. The performance of the biosensor is measured with three parameters such as sensitivity, specificity and detection limit by generating the calibration plots that accurately fits the model.
查看更多>>摘要：The rate of development of technology and its associated security issues are increasing in integrated circuit industry. This provides a space for implanting dormant nature of threats, named Hardware Trojan (HT) in various process of integrated circuits (IC) design. The impact of HT's emanates the encrypted signals, privacy disruption, performance degradation or denial of service. The threat models are unimaginable and it can be intruded at any stage which complicates the HT detection process. Therefore, a deep learning-based malicious module identification method is proposed in this work by implementing stacked autoencoder and stacked sparse autoencoder model. The simulation results shows that the proposed stacked sparse autoencoder outperforms the best in detecting the malicious modifications with an average accuracy of 97.53%, true positive rate of 93% and moreover the true negative rate achieved is 98.14% which proves the effectiveness of sparsity nature in extracting suitable features in the proposed schemes.
查看更多>>摘要：Aiming at the problems of low accuracy of parameter collection in traditional systems, low comprehensiveness of collection results, and poor system robustness, a Nanosensors-based multi-parameter real-time collection system of human body motion is designed in this work. According to the overall frame structure of the parameter acquisition system, the system hardware design is realized by using Nanosensors and nodes, radiofrequency chip MC13201, and a multi-parameter acquisition circuit. Based on hardware design, the time synchronization algorithm based on virtual time stamp is used to realize the time synchronization among sub-nodes of the sensor, and the COPS algorithm is used to identify the bad parameters and control the parameter acquisition error, to realize the effective collection of multiple parameters of human motion. The experimental results show that the system has an 80% higher accuracy rate, 83% higher degree of comprehensiveness, better robustness, and higher practical application value.
查看更多>>摘要：This paper aims to investigate the use of ultrasonic guided wave (GW) propagation mechanism and the assessment of debonding in a sandwich composite structure (SCS) using a multi-step approach. Towards this, a series of GW propagation-based laboratory experiments and numerical simulations have been carried out on the SCS sample. The debonding regions of variable size and locations were assessed using a pre-defined network of piezoelectric lead zirconate transducers (PZT). Besides, several artificial masses were also placed in the SCS to validate the multi-step structural health monitoring (SHM) strategy. The SHM approach uses a proposed quick damage identification matrix maps and an improved elliptical wave processing (EWP) strategy of the registered GW signals to detect the locations of debonding and other damages in the SCS. The benefit of the proposed damage identification map is to locate the damaged area (sectors) quickly. This identification step is followed by applying the damage localization step using the improved EWP only on the previously identified damage sector region. The proposed EWP has shown the potential to effectively locate the hidden multiple debonding regions and damages in the SCS with a reduced number of calculations using a step-wise approach that uses only a selected number of grid points. The paper shows the effectiveness of the proposed approach based on data gathered from numerical simulations and experimental studies. Thus, using the above-mentioned SHM strategy debondings and damages present within and outside the sensor network are localized. The results were cross verified with nondestructive testing (NDT) methods such as infrared thermography and laser Doppler vibrometry.
查看更多>>摘要：In this study, a new passive camera system for heavy cylindrical forging measurement, based on silhouettes in images, is developed. New methods for making such a system more resistant to the negative effects of the industrial environment have been proposed. This includes weighted edge filtering based on complementary information about the edge quality in an image. The recorded measurement median errors were +/- 0.12 mm and +/- 0.14 mm. Moreover, the 95% confidence intervals were +/- 0.5 mm and +/- 1 mm for the forging axis and diameter measurements, respectively. Both results were achieved in a measurement volume of 6 x 6 x 2 m during the measurement of glowing hot forgings in industrial conditions. The results surpass those of the state-of-the-art method, mainly in the case of axis straightness measurement, by approximately 50%. The measurement is fast, and it provides feedback about the axis straightness for its subsequent correction.
查看更多>>摘要：Chatter is normally detected by time-frequency analysis, among which VMD has a perfect theoretical basis. However, the algorithm directly used for chatter detection may have low accuracy and efficiency due to the initial parameters that are difficult to determine. Therefore, a novel method based on fast iterative variational mode decomposition (FI-VMD) is proposed to solve these issues. The simulation process shows FI-VMD is almost equivalent to the extraction accuracy of VMD, but when the energy of chatter signal is very small, FI-VMD is better than VMD. Moreover, since the initial frequency is the true frequency in the FI-VMD iteration process, its calculation efficiency is much faster than that of VMD. Furthermore, the proposed energy ratio difference has strong robustness in stable cutting condition. When chatter occurs, it is more sensitive to chatter than energy ratio. Compared with an optimized VMD, the proposed method is more suitable for online chatter detection.
查看更多>>摘要：Digital volume correlation (DVC) quantifies internal 3D displacement and strain fields by correlating the volume images of a tested object acquired at different states. When using X-ray CT-based DVC, the number of projections is a key parameter that affects the acquisition time and quality of reconstructed volumetric images, and therefore the precision and temporal resolutions of DVC measurement. More projections result in high-quality volume images for DVC calculation but longer acquisition time and pronounced thermal drifts of the X-ray source. Few projections lead to quicker acquisition and fewer thermal drifts, but may degrade image quality and thus induce larger DVC measurement errors. Selecting an appropriate number of projections during CT imaging is therefore of practical significance for DVC measurement. To solve this dilemma, the effect of the number of projections on DVC measurements with X-ray CT is experimentally investigated in this work. First, numerically simulated speckle volume images with different numbers of projections were reconstructed by using FDK (Feldkamp) al-gorithm, and the influence of the number of projections on DVC measurement was analyzed. Then, real rescan and compression experiments performed on a copper foam sample were carried out to further study the effect of projection number on DVC measurements. Both simulation and real experiments show that more projections result in longer imaging time but higher quality volume image and DVC measurement. DVC measurement errors decrease with the increase of projections at different decline rates. Therefore, an appropriate number of pro-jections can be specified based on the results according to the requirements of DVC measurement precision and temporal resolution. For the specific X-ray CT device used in this real compression experiment, 36 ~ 60 pro-jections are suggested to balance measurement precision and temporal resolution, and more than 720 projections are necessary for pursuing higher accuracy.
查看更多>>摘要：Vision-based displacement sensors (VDSs) are drawing attention as next-generation methods for monitoring buildings due to easy installation, however, there is a further need to develop integrated techniques both to obtain displacement at desired positions and to assess dynamic characteristics with high-precision. This study aimed to develop an automated framework to assess the dynamic characteristics of buildings through the derivation of lateral stiffness using a marker-free vision-based displacement sensor (MVDS). The MVDS utilizes image convex hull optimization to measure displacement at user-defined positions without ancillary markers. Then, the dynamic characteristics were estimated from eigenvalue analysis by reconstructing the equation of motion based on lateral stiffness derived through linear regression in load-displacement curves using the measured displacement data. From numerical simulation and shake table test, the results showed that the proposed framework enables monitoring of the dynamic characteristics where frequency domain exceeded the Nyquist frequency of the sensor compared to FFT-based analysis.
查看更多>>摘要：A novel leak localization method is presented based on the forward and backward transient analysis. The approach applies discrepancies between results from the forward and backward transient simulations by the Method of Characteristics (MOC) to locate potential leaks along a pipeline. This method is supposed to provide high localization efficiency because it does not need to perform any inverse calibration procedure, as demonstrated in leak exercises in both elastic and viscoelastic pipelines. The performance of the developed method is then validated through a simulated oil conveyance pipeline system in a noisy environment. The extensive applications and analyses reveal that the noise in the viscoelastic pipe is amplified gradually in the forward and backward MOC due to the numerical computation of the convolution integral terms, which thus could affect to a certain extent the accuracy of the developed method in practical applications.
NSTL
Elsevier