Dynamic Response Characteristic of Building Structure under Blasting Vibration of underneath Tunnel

The vibration induced by blasting excavation of the subway tunnel in complex urban environments may cause harmful effects on adjacent buildings. Investigating the dynamic response of adjacent buildings is a key issue to predict and control blasting hazards. In this paper, the blasting excavation of the subway tunnel right below a building was selected as a case study, and the blast vibrations in the field were monitored. The Hilbert–Huang Transform (HHT) model was used to extract and analyze the time-frequency characteristic parameters of blasting dynamic response signals. By substituting intrinsic mode functions (IMF) component frequency and instantaneous energy for main frequency and blasting total input energy, respectively, the characteristics of time-instantaneous frequency-instantaneous energy of buildings under blasting seismic load were analyzed, and the concept of effective duration of vibration was proposed.

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A Study on Dynamic Response of Tunnel Blasting Beneath Surface Buildings

10.22541/au.162246933.30668840/v1 ◽

2021 ◽

Author(s):

chen huang ◽

youyi zhang ◽

Jun Zhao

Keyword(s):

Dynamic Response ◽

Weight Bearing ◽

Dynamic Responses ◽

Frame Structure ◽

Blasting Vibration ◽

Exterior Wall ◽

Adjacent Buildings ◽

Propagation Law ◽

Blasting Excavation ◽

Tunnel Blasting

In order to study the dynamic response of adjacent buildings in the process of tunnel blasting excavation, taking Yangjia tunnel blasting through a five-story frame structure residential building as an example, the propagation law of blasting seismic wave was analyzed by using HHT method through on-site blasting monitoring. Then, the ALE algorithm in ANSYS/LS-DYNA software was used to establish a three-dimensional numerical model based on the surrounding rock-cutting section-structure coupling to study the dynamic response of adjacent buildings under the blasting vibration of tunnel. The results show that the HHT analysis method can clearly describe the energy distribution of vibration signals in the time and frequency domain. The energy carried by the blasting vibration signal is corresponding to the detonating section, and the maximum energy appears in the cutting section, which further verifying that the vibration effect caused by the cutting hole blasting is the strongest. In the process of tunnel blasting, the dynamic responses of beams, columns and exterior walls of adjacent buildings are not consistent and show different variation rules along the height direction. In addition, the stress centralization mainly occurs in the exterior wall of the building, the joint of the exterior wall and the column, the joint of the exterior wall and the beam, and the joint of the exterior wall and the floor and other non-weight bearing area, indicating that these parts are more likely to damage and crack in the process of tunnel blasting.

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Study on dynamic response of rock foundation pit blasting excavation to adjacent buildings

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/570/4/042034 ◽

2020 ◽

Vol 570 ◽

pp. 042034

Author(s):

Teng-fei Jiang ◽

An-nan Jiang ◽

Xing-sheng Li

Keyword(s):

Dynamic Response ◽

Rock Foundation ◽

Foundation Pit ◽

Adjacent Buildings ◽

Blasting Excavation

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Approach to extracting gear fault feature based on dominant intrinsic mode function

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406214521603 ◽

2014 ◽

Vol 228 (15) ◽

pp. 2810-2819 ◽

Cited By ~ 1

Author(s):

Zhifeng Liu ◽

Bing Luo ◽

Wentong Yang ◽

Ligang Cai ◽

Jingying Zhang

Keyword(s):

Empirical Mode Decomposition ◽

Intrinsic Mode Function ◽

Good Time ◽

Intrinsic Mode Functions ◽

Time Frequency ◽

Mode Function ◽

Mode Decomposition ◽

Gear Fault ◽

Rate Evaluation ◽

Instantaneous Energy

Complex nonlinear and nonstationary signals can be adaptively analyzed by the Hilbert–Huang transform through empirical mode decomposition and the Hilbert transform to generate the instantaneous energy. The instantaneous energy was able to display the local characteristics of the signals and had good time–frequency analysis capability, it is therefore widely applied to the analysis of vibration signals in the field of gear fault diagnosis. However, only a few extracted intrinsic mode functions through empirical mode decomposition can reflect fault feature or closely related to the faults but others are irrelevant. Therefore, the fault feature of the instantaneous energy for all intrinsic mode functions was not obvious and the accuracy of diagnosis was low. Aimed at solving this problem, a fault leading rate evaluation algorithm was proposed that can select those intrinsic mode functions, which reflect fault features (it was called the dominant intrinsic mode function) from all intrinsic mode functions. In the paper, this algorithm was applied to gear fault feature extraction. By calculating the instantaneous energy of the dominant intrinsic mode function the method could accurately extract gear fault feature and improve the accuracy of diagnosis. Both simulated signals and experimental signals of a Klingelnberg bevel gear were analyzed to verify the effectiveness and correctness of the algorithm.

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Time-frequency analysis study on picking-up dynamic response characteristic on high speed train wheel-track coupling system

Proceedings of 2012 International Conference on Measurement, Information and Control ◽

10.1109/mic.2012.6273459 ◽

2012 ◽

Author(s):

Yan Gao ◽

Jianhui Lin ◽

Shuangxi Chen

Keyword(s):

Dynamic Response ◽

Frequency Analysis ◽

High Speed ◽

Response Characteristic ◽

High Speed Train ◽

Analysis Study ◽

Time Frequency ◽

Coupling System ◽

Dynamic Response Characteristic ◽

Wheel Track

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Dual mass MEMS gyroscope temperature drift compensation based on TFPF-MEA-BP algorithm

Sensor Review ◽

10.1108/sr-09-2020-0205 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Huiliang Cao ◽

Rang Cui ◽

Wei Liu ◽

Tiancheng Ma ◽

Zekai Zhang ◽

...

Keyword(s):

Training Data ◽

Experimental Result ◽

Intrinsic Mode Functions ◽

Temperature Drift ◽

Connection Weight ◽

Bp Network ◽

Content Type ◽

Mems Gyroscope ◽

Time Frequency ◽

Drift Compensation

Purpose To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network. Design/methodology/approach First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals and temperature drift signals. Then, TFPF denoises the mixed-signal, the noise signal is directly removed and the denoised sub-sequence is reconstructed, which is used as training data to train the MEA optimized BP to obtain a temperature drift compensation model. Finally, the gyro’s temperature characteristic sequence is processed by the trained model. Findings The experimental result proved the superiority of this method, the bias stability value of the compensation signal is 1.279 × 10–3°/h and the angular velocity random walk value is 2.132 × 10–5°/h/vHz, which is improved compared to the 3.361°/h and 1.673 × 10–2°/h/vHz of the original output signal of the gyro. Originality/value This study proposes a multi-dimensional processing method, which treats different noises separately, effectively protects the low-frequency characteristics and provides a high-precision training set for drift modeling. TFPF can be optimized by SEVMD parallel processing in reducing noise and retaining static characteristics, MEA algorithm can search for better threshold and connection weight of BP network and improve the model’s compensation effect.

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Feature Extraction Strategy with Improved Permutation Entropy and Its Application in Fault Diagnosis of Bearings

Shock and Vibration ◽

10.1155/2018/1063645 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12 ◽

Cited By ~ 3

Author(s):

Fan Jiang ◽

Zhencai Zhu ◽

Wei Li ◽

Bo Wu ◽

Zhe Tong ◽

...

Keyword(s):

Feature Extraction ◽

Fault Diagnosis ◽

Optimal Number ◽

Permutation Entropy ◽

Support Vector ◽

Intrinsic Mode Functions ◽

Vibration Signals ◽

Time Frequency ◽

Bearing Fault ◽

Bearing Fault Diagnosis

Feature extraction is one of the most difficult aspects of mechanical fault diagnosis, and it is directly related to the accuracy of bearing fault diagnosis. In this study, improved permutation entropy (IPE) is defined as the feature for bearing fault diagnosis. In this method, ensemble empirical mode decomposition (EEMD), a self-adaptive time-frequency analysis method, is used to process the vibration signals, and a set of intrinsic mode functions (IMFs) can thus be obtained. A feature extraction strategy based on statistical analysis is then presented for IPE, where the so-called optimal number of permutation entropy (PE) values used for an IPE is adaptively selected. The obtained IPE-based samples are then input to a support vector machine (SVM) model. Subsequently, a trained SVM can be constructed as the classifier for bearing fault diagnosis. Finally, experimental vibration signals are applied to validate the effectiveness of the proposed method, and the results show that the proposed method can effectively and accurately diagnose bearing faults, such as inner race faults, outer race faults, and ball faults.

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Dynamic Response of Composite Steel Lining Structure under Blast Loading

Shock and Vibration ◽

10.1155/2020/2693659 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Desen Kong ◽

Yu Xu ◽

Cheng Song

Keyword(s):

Dynamic Response ◽

Emergency Response ◽

Steel Plate ◽

Axial Stress ◽

Subway Tunnel ◽

Analysis Software ◽

Research Results ◽

Protection Method ◽

Lining Structure ◽

Composite Steel

According to the advantages of high tensile resistance and high shear strength of composite steel plate, a new antiexplosion protection method of composite steel plate lining structure is put forward. The numerical model of explosion impact of subway tunnel with composite steel plate lining structure was established by dynamic analysis software. The transient dynamic response of lining structure with the composite steel plate was simulated when explosion occurred. The research results show that the influence of explosive quantity on each point of composite steel plate lining structure is different and the change of acceleration near the centre of the detonation source is generally greater than the multiple of the increase of explosive quantity. The increase of velocity and displacement is basically consistent with the quantity of explosive. The influence of axial stress on the lining structure is the least, and the influence of the lining structure is greater in the y-direction than in the x-direction. The research results can provide the plan and basis for the emergency response of the subway tunnel.

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