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The distribution of the permafrost in the Tibetan Plateau has dramatically changed due to climate change, expressed as increasing permafrost degradation, thawing depth deepening and disappearance of island permafrost. These changes have serious impacts on the local ecological environment and the stability of engineering infrastructures. Ground penetrating radar (GPR) is used to detect permafrost active layer depth, the upper limit of permafrost and the thawing of permafrost with the season’s changes. Due to the influence of complex structure in the permafrost layer, it is difficult to effectively characterize the accurate structure within the permafrost on the radar profile. In order to get the high resolution GPR profile in the Tibetan Plateau, the reverse time migration (RTM) imaging method was applied to GPR real data. In this paper, RTM algorithm is proven to be correct through the groove’s model of forward modeling data. In the Beiluhe region, the imaging result of GPR RTM profiles show that the RTM of GPR makes use of diffracted energy to properly position the reflections caused by the gravels, pebbles, cobbles and small discontinuities. It can accurately determine the depth of the active layer bottom interface in the migration section. In order to prove the accuracy of interpretation results of real data RTM section, we set up the three dielectric constant models based on the real data RTM profiles and geological information, and obtained the model data RTM profiles, which can prove the accuracy of interpretation results of three-line RTM profiles. The results of three-line RTM bears great significance for the study of complex structure and freezing and thawing process of permafrost at the Beiluhe region on the Tibetan Plateau.
Yao Wang; Zhihong Fu; Xinglin Lu; Shanqiang Qin; Haowen Wang; Xiujuan Wang. Imaging of the Internal Structure of Permafrost in the Tibetan Plateau Using Ground Penetrating Radar. Electronics 2019, 9, 56 .
AMA StyleYao Wang, Zhihong Fu, Xinglin Lu, Shanqiang Qin, Haowen Wang, Xiujuan Wang. Imaging of the Internal Structure of Permafrost in the Tibetan Plateau Using Ground Penetrating Radar. Electronics. 2019; 9 (1):56.
Chicago/Turabian StyleYao Wang; Zhihong Fu; Xinglin Lu; Shanqiang Qin; Haowen Wang; Xiujuan Wang. 2019. "Imaging of the Internal Structure of Permafrost in the Tibetan Plateau Using Ground Penetrating Radar." Electronics 9, no. 1: 56.
The tunnel seismic method allows for the detection of the geology in front of a tunnel face for the safety of tunnel construction. Conventional geophones have problems such as a narrow spectral width, low sensitivity, and poor coupling with the tunnel wall. To tackle issues above, we propose a semi-automatic coupling geophone equipped with a piezoelectric sensor with a spectral range of 10-5000 Hz and a sensitivity of 2.8 V/g. After the geophone was manually pushed into the borehole, it automatically coupled with the tunnel wall under the pressure of the springs within the device. A comparative experiment showed that the data spectrum acquired by the semi-automatic coupling geophone was much higher than that of the conventional geophone equipped with the same piezoelectric sensor. The seismic data were processed in combination with forward modeling. The imaging results also show that the data acquired by the semi-automatic coupling geophone were more in line with the actual geological conditions. In addition, the semi-automatic coupling geophone's installation requires a lower amount of time and cost. In summary, the semi-automatic coupling geophone is able to efficiently acquire seismic data with high fidelity, which can provide a reference for tunnel construction safety.
Yao Wang; Nengyi Fu; Zhihong Fu; Xinglin Lu; Xian Liao; Haowen Wang; Shanqiang Qin. A Semi-Automatic Coupling Geophone for Tunnel Seismic Detection. Sensors 2019, 19, 3734 .
AMA StyleYao Wang, Nengyi Fu, Zhihong Fu, Xinglin Lu, Xian Liao, Haowen Wang, Shanqiang Qin. A Semi-Automatic Coupling Geophone for Tunnel Seismic Detection. Sensors. 2019; 19 (17):3734.
Chicago/Turabian StyleYao Wang; Nengyi Fu; Zhihong Fu; Xinglin Lu; Xian Liao; Haowen Wang; Shanqiang Qin. 2019. "A Semi-Automatic Coupling Geophone for Tunnel Seismic Detection." Sensors 19, no. 17: 3734.
The grounding device plays performs the role of releasing a lightning current and a fault current in the power system, and the corrosion of the conductor will cause damage to the grounding body, which threatens the safe operation of the power system. The grounding grid corrosion detection technology and equipment guarantee the safe operation of the power system. This paper discusses the research status of grounding corrosion and topological detection in detail and introduces the basic principles, research difficulties and existing problems of the methods such as the electric network method, electromagnetic field method, electrochemical method, ultrasonic detection method and electromagnetic imaging method. The methods of electromagnetic imaging and time difference positioning proposed in recent years have been also discussed in detail. The paper points out that the application of grounding grid corrosion detection distance engineering still faces great challenges and that multi-disciplinary, multi-information fusion, new sensing technology, big data platforms and intelligent computing will be the trends to follow in research on grounding grid fault, corrosion detection and life prediction.
Zhihong Fu; Xiujuan Wang; Qian Wang; Xiaobin Xu; Nengyi Fu; Shanqiang Qin; Wang; Xu; Fu; Qin. Advances and Challenges of Corrosion and Topology Detection of Grounding Grid. Applied Sciences 2019, 9, 2290 .
AMA StyleZhihong Fu, Xiujuan Wang, Qian Wang, Xiaobin Xu, Nengyi Fu, Shanqiang Qin, Wang, Xu, Fu, Qin. Advances and Challenges of Corrosion and Topology Detection of Grounding Grid. Applied Sciences. 2019; 9 (11):2290.
Chicago/Turabian StyleZhihong Fu; Xiujuan Wang; Qian Wang; Xiaobin Xu; Nengyi Fu; Shanqiang Qin; Wang; Xu; Fu; Qin. 2019. "Advances and Challenges of Corrosion and Topology Detection of Grounding Grid." Applied Sciences 9, no. 11: 2290.
Transient electromagnetic (TEM) soundings are being increasingly used in engineering applications of environmental and regional surveys and shallow metal detection. Efficient and real time of the processing of the observed TEM data is the trend for the engineering geophysical prospecting and detection instrument in modern times. This letter presents a fast resistivity imaging method of TEM using artificial neural networks. The input-output mapping relations of neural networks are established based on the TEM response characteristics under different transmitter loop devices. The built network could map the recorded TEM data and quickly obtain the resistivity image. The proposed method offers accuracy and fast computation for resistivity imaging, and only 9.003 s costs for the calculation of 142 measured points' data. Feasibility and technical attractiveness of the proposed method in fast resistivity imaging of TEM mean that it is well suited for instantaneous of survey results to a client. The proposed TEM imaging method can be used in real time so that the recorded TEM data can be calculated without retraining, which avoids time-consuming iteration and inversion computation.
Shanqiang Qin; Yao Wang; Zhengyu Xu; Xian Liao; Longhuan Liu; Zhihong Fu. Fast Resistivity Imaging of Transient Electromagnetic Using ANN. IEEE Geoscience and Remote Sensing Letters 2019, 16, 1373 -1377.
AMA StyleShanqiang Qin, Yao Wang, Zhengyu Xu, Xian Liao, Longhuan Liu, Zhihong Fu. Fast Resistivity Imaging of Transient Electromagnetic Using ANN. IEEE Geoscience and Remote Sensing Letters. 2019; 16 (9):1373-1377.
Chicago/Turabian StyleShanqiang Qin; Yao Wang; Zhengyu Xu; Xian Liao; Longhuan Liu; Zhihong Fu. 2019. "Fast Resistivity Imaging of Transient Electromagnetic Using ANN." IEEE Geoscience and Remote Sensing Letters 16, no. 9: 1373-1377.
An air-coil sensor (ACS) is a type of induction magnetometer used to measure the variation of a magnetic field. Due to the limited bandwidth of the coil, its output signal is distorted, a phenomenon known as the transition process. To measure the magnetic field accurately, the relationship must be confirmed by calibration. However, conventional methods require a uniform magnetic field with various frequencies to ensure the induced electromotive force is controllable. The time taken to acquire the signal correlates with the number of test frequencies, and the equipment used to generate the uniform magnetic field must be tailored to the shape of the ACS under test. This paper proposes a time-domain feedback calibration method for ACS to avoid the above constraints. An algorithm is applied to relieve the dependence of the calibration file on the input signal, so that the calibration file will not be affected by the calculation error of the input signal nor be limited by the uniform magnetic field, and the accuracy of the calibration file can be evaluated by the feedback signal. The exponential current, which contains a variety of frequency components, is selected as the calibration signal to shorten the time of data collection. The equipment used to generate the calibration signal is simple, which is suitable for on-site calibration. The scheme can be used for rapid calibration of various air-core coils, and provides a better solution for realizing embedded self-test of ACS.
Haowen Wang; Zhihong Fu; Yao Wang; Hengming Tai; Shanqiang Qin; Xian Liao. A time-domain feedback calibration method for air-coil magnetic sensor. Measurement 2018, 135, 61 -70.
AMA StyleHaowen Wang, Zhihong Fu, Yao Wang, Hengming Tai, Shanqiang Qin, Xian Liao. A time-domain feedback calibration method for air-coil magnetic sensor. Measurement. 2018; 135 ():61-70.
Chicago/Turabian StyleHaowen Wang; Zhihong Fu; Yao Wang; Hengming Tai; Shanqiang Qin; Xian Liao. 2018. "A time-domain feedback calibration method for air-coil magnetic sensor." Measurement 135, no. : 61-70.