China
Africa
Explore chapters and articles related to this topic
Role of Extreme Environment Electronics in NASA’s Aeronautics Research
Published in John D. Cressler, H. Alan Mantooth, Extreme Environment Electronics, 2017
An example of sensor system development that demonstrates the aforementioned technology trends is an integrated smart leak detection system, referred to as “lick and stick” technology, targeted for a range of applications in launch vehicle propulsion systems [4,5]. The smart sensor system shown in Figure 5.4a includes a microsensor array fabricated by microfabrication (often referred to as microelectromechanical system [MEMS])–based technology, featuring two hydrogen sensors and a hydrocarbon sensor used to detect fuel leaks. The sensor array has been incorporated into a smart sensor system that provides a complete unit with signal conditioning electronics, power, data storage, and telemetry. This system has a surface area near the size of a postage stamp and is intended to be applied, like a postage stamp, where and when needed within a vehicle without rewiring of the vehicle system. Other smart sensor systems have been developed for fire detection, environmental monitoring, and emissions monitoring purposes [6,7]. One approach is to place a number of these sensor systems in a region, and the resulting measurements are then fed (wired or wirelessly) into a central processing hub to allow an understanding of the region or environment (Figure 5.4b). The wireless approach has been demonstrated previously for environmental monitoring applications [6].
Telemetry Frames and Packets
Published in Stephen Horan, Introduction to PCM Telemetering Systems, 2017
Using a particular packet format is not as important as controlling and accessing the software running on the computers using the protocols. Figure 6.25 illustrates one example of how the control software may be configured [Fan00; Jian00]. The data acquisition computer system integrates the sensor array, the associated data acquisition electronics, and the supporting software. The collected data includes Global Positioning System (GPS) time and position, accelerometer, atmospheric pressure, and radio propagation measurements. The computer in this example collects the data and passes it over the Internet to a data server computer using the LabVIEW® data socket support software. The data server formats the data into a format where they are accessed using a standard Web browser. The data user on the client computer then accesses the data server over the Internet and the data acquisition computer sends the data to the user’s Web browser. While this example uses LabVIEW®, designers use other software as well. The common feature is that the designer utilizes standard TCP/IP services to support the data transfer.
Application of pulse compression technique in metal materials cracks detection with LF-EMATs
Published in Nondestructive Testing and Evaluation, 2023
Min He, Wenze Shi, Chao Lu, Yao Chen, Liping Zhao, Dexiu Dong, Guangdeng Zeng
Shear Vertical wave (SV) has been a research hotspot for domestic and foreign scholars due to its unique detection advantages. Ogi et al. [13,14] first proposed a line-focusing electromagnetic acoustic transducer (LF-EMAT) design method and found that the directionality of the SV wave excited by this probe was significantly better than that of the conventional angled SV wave EMAT. Dhayalan et al. [15] designed a two-dimensional numerical model of the meander-line coil (MLC) EMAT to simulate the generation of SV waves and verified the accuracy of the numerical model experimentally. Wang et al. [16] proposed a unidirectional LF-EMAT design method based on two MLCs that could produce enhanced SV waves in one direction and verified the effectiveness of this probe for defect detection. Liang et al. [17] investigated the effect of sensor array parameters on the directionality of SV-wave phased array EMAT and found that the higher number of array elements, the higher SV wave main lobe amplitude, the narrower main lobe width, and the better directivity. Huang et al. [18] clarified the selection method of the LF-EMAT focus position and found that the focus position should be appropriately close to the excitation coil for improving the signal amplitude.
Machine Learning Based Quantitative Damage Monitoring of Composite Structure
Published in International Journal of Smart and Nano Materials, 2022
Xinlin Qing, Yunlai Liao, Yihan Wang, Binqiang Chen, Fanghong Zhang, Yishou Wang
The damage diagnosis algorithm is the core of damage monitoring based on ultrasonic guided wave. A variety of damage monitoring algorithms have been developed, including phased array [44–46], delay and sum (DAS) [47,48], tomography [49,50], elliptical weighted distribution damage imaging [51–53], time reversal [54,55], and other methods. In phased array algorithm, several PZTs in the sensor network are used to form a dense sensor array. It is the same as the principle of a radar that the phase of excitation signal of each PZT can be adjusted independently so that Lamb wave propagation can be focused on the specific direction for the far field or on the specific location for the near field because of the sum of Lamb wave field excited by all PZTs. In the DAS algorithm, according to the damage scattering signal received by multiple pitch-catch paths, the damage is located according to the group velocity and the propagation time of guided wave. In the tomography algorithm, sensors are usually arranged around the monitored area and form a great number of transmitting-receiving paths. The monitoring principle is that the signal changes of guided wave varying with the damage are fusing to contour the damage. More details about these algorithms can be found in literature [6].
Nanomaterial-based gas sensors: A review
Published in Instrumentation Science & Technology, 2018
Ke Xu, Chuhan Fu, Zhijun Gao, Fanan Wei, Yu Ying, Chong Xu, Guojiang Fu
In 2016, Cavallari et al.[22] demonstrated the selectivity to diabetes biomarkers by a nonspecific impedance-metric chemical sensor array, which was a mixture of materials based on GO, as a method for simultaneous investigation of water and gas analyte multivariate systems. It was found that the electrical impedance of bare graphene either oxidized or after reduction showed high specificity for ammonia. The sensitivity of the GO film capacitor was 10.4%/ppm of ammonia dissolved in ultrapure water, while the RGO resistance was 1.8%/ppm for gaseous ammonia. The specificity of ammonia of the exposed and reducible GO could be appropriately adjusted by the GO composite with cerium oxide and cyclodextrin to detect acetone. Therefore, the bonding of GO-based composites and electronic nose arrays were essential for the separation of acetone from alcohols and ammonia after basic component analysis, as shown in Figure 1. These results represented the first step in the application of impedance chemical resistance sensor arrays from graphene oxide composites to noninvasive, portable, and potentially low-cost instruments for the diagnosis of diabetes mellitus.