scholarly journals Experimental Research on Shear Failure Monitoring of Composite Rocks Using Piezoelectric Active Sensing Approach

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1376 ◽  
Author(s):  
Yang Liu ◽  
Yicheng Ye ◽  
Qihu Wang ◽  
Weiqi Wang
Keyword(s):  
Shear Failure ◽  
Wavelet Packet ◽  
Failure Process ◽  
Damage Index ◽  
Active Sensing ◽  
Wavelet Packet Analysis ◽  
Engineering Structures ◽  
Damage Indices ◽  
Monitoring Test ◽  
Failure Monitoring

Underground space engineering structures are generally subject to extensive damages and significant deformation. Given that composite rocks are prone to shear failure, which cannot be accurately monitored, the piezoelectric active sensing method and wavelet packet analysis method were employed to conduct a shear failure monitoring test on composite rocks in this study. For the experiment, specimens were prepared for the simulation of the composite rocks using cement. Two pairs of piezoelectric smart aggregates (SAs) were embedded in the composite specimens. When the specimens were tested using the direct shear apparatus, an active sensing-based monitoring test was conducted using the embedded SAs. Moreover, a wavelet packet analysis was conducted to compute the energy of the monitoring signal; thus allowing for the determination of the shear damage index of the composite specimens and the quantitative characterization of the shear failure process. The results indicated that upon the shear failure of the composite specimens, the amplitudes and peak values of the monitoring signals decreased significantly, and the shear failure and damage indices of the composite specimens increased abruptly and approached a value of 1. The feasibility and reliability of the piezoelectric active sensing method, with respect to the monitoring of the shear failure of composite rocks, was therefore experimentally demonstrated in this study.

scholarly journals Real-Time Monitoring of Timber-Surface Crack Repair Using Piezoelectric Ceramics

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Huien Meng ◽  
Wenwei Yang ◽  
Xia Yang
Keyword(s):  
Real Time ◽  
Lead Zirconate Titanate ◽  
Surface Crack ◽  
Wavelet Packet ◽  
Damage Index ◽  
Piezoelectric Ceramics ◽  
Strength Development ◽  
Active Sensing ◽  
Surface Cracks ◽  
Crack Repair

Real-time assessment of timber-surface crack repair is crucial to the stability and safety of timber structures. Epoxy resin was used to repair timber cracks, and the active sensing technique using piezoelectric ceramics was applied to monitor the repair process of timber surface cracks in real time. Sixteen wood samples were designed for axial compression tests and active monitoring tests. A pair of lead zirconate titanate patches was pasted on the surface of the timber specimens as actuators and sensors for signal transmission and reception, through wavelet packet analysis, the variations in the signal amplitude, and wavelet coefficients. The relationship between the wavelet packet energy of the monitoring signal and the ultimate bearing capacity of the specimens at different periods after grouting was established. Based on the root-mean-square deviation, the damage index, DI, was introduced to evaluate the repair degree of timber surface cracks quantitatively. The results showed that the active sensing method can evaluate the strength development in timber-surface crack repair in real time.

scholarly journals Tension Monitoring of Wedge Connection Using Piezoceramic Transducers and Wavelet Packet Analysis Method

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 364
Author(s):  
Xiaoyu Zhang ◽  
Liuyu Zhang ◽  
Laijun Liu ◽  
Linsheng Huo
Keyword(s):  
Energy Transfer ◽  
Stress Wave ◽  
Wavelet Packet ◽  
Active Sensing ◽  
Analysis Method ◽  
Wavelet Packet Analysis ◽  
Monitoring Method ◽  
Anchorage System ◽  
Steel Strand ◽  
Contact Surfaces

A steel strand is widely used in long span prestressed concrete bridges. The safety and stability of a steel strand are important issues during its operation period. A steel strand is usually subjected to various types of prestress loss which loosens the anchorage system, negatively impacting the stability of the structure and even leading to severe accidents. In this paper, the authors propose a wavelet packet analysis method to monitor the looseness of the wedge anchorage system by using stress wave-based active sensing. As a commonly used piezoceramic material, lead zirconate titanate (PZT) is employed with a strong piezoelectric effect. In the proposed active sensing approach, PZT patches are used as sensors and actuators to monitor the steel strand looseness. The anchorage system consists of the steel strand, wedges and barrel, which forms two different direct contact surfaces to monitor the tension force. PZT patches are pasted on the surface of each steel strand, corresponding wedge and barrel, respectively. Different combinations of PZTs are formed to monitor the anchoring state of the steel strand according to the position of the PZT patches. In this monitoring method of two contact surfaces, one PZT patch is used as an actuator to generate a stress wave and the other corresponding PZT patch is used as a sensor to detect the propagated waves through the wedge anchorage system. The function of these two PZTs were exchanged with the changing of transmission direction. The wavelet packet analysis method is utilized to analyze the transmitted signal between PZT patches through the steel strand anchorage system. Compared with the wavelet packet energy of received signals under different PZT combinations, it could be found that the wavelet packet energy increased with the increasing of anchorage system tightness. Therefore, the wavelet packet energy of received signal could be used to monitor the tightness of the steel strand during operation. Additionally, the wavelet packet energy of the received signals are different when the same PZT combination exchanges the energy transfer direction. With the comparison on the received signals of different combinations of PZTs, the optimal energy transfer path corresponding to different contact surfaces of the steel strand could be determined and the optimal experimental results are achieved.

On-Line Time-Series Damage State Estimation Using Correlation Analysis and Ultrasonic Broadband Active Sensing

2009 ◽  
Author(s):  
Subhasish Mohanty ◽  
Jun Wei ◽  
Aditi Chattopadhyay ◽  
Pedro Peralta
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
State Estimation ◽  
Damage Index ◽  
Active Sensing ◽  
Damage State ◽  
Damage Indices ◽  
Dual Sensor ◽  
Damage States ◽  
Damage Condition

This paper proposes an approach to estimate the fatigue-induced damage state of a metallic structure under biaxial cyclic load. An ultrasonic based technique for broadband active sensing is used. A novel damage index estimation technique based on dual sensor signals is developed that removes the contribution from high frequency input dependant noise. The scalar damage index at any particular damage condition is evaluated using a nonparametric system identification approach such as correlation analysis. The time series estimation of the damage indices (or damage states) shows good correlation with visual measurements of crack length. The time series 2σ error bound was also evaluated to study the effect of measurement noise on damage state estimation.

scholarly journals Interface Debonding Detection of Precast Segmental Concrete Beams (PSCBs) Using Piezoceramic Transducer-Based Active Sensing Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yang Liu ◽  
Ming Zhang ◽  
Xinfeng Yin ◽  
Chuang Hei ◽  
Lei Wang
Keyword(s):  
Concrete Beams ◽  
Wavelet Packet ◽  
Damage Index ◽  
High Strength ◽  
Frequency Domain Analysis ◽  
Interface Debonding ◽  
Active Sensing ◽  
Periodic Loading ◽  
Debonding Detection ◽  
Epoxy Resin Adhesive

An active sensing approach using piezoceramic induced stress wave is proposed to provide monitoring and early warning for the development of interface debonding damage of precast segmental concrete beams (PSCBs). Three concrete specimens with toothed interfaces were fabricated and bonded with high-strength epoxy resin adhesive to form PSCBs. Smart aggregates (SAs) embedded in concrete specimens are used as actuators and sensors. The PSCBs are subjected to periodic loading with hydraulic jack to test the different degrees of debonding damage. The experimental results of time-domain and frequency-domain analysis clearly show that the amplitude of the signal received by the piezoceramic sensor is reduced when debonding crack occurs. The energy analysis and damage index based on wavelet packet can be used to determine the existence and severity of interface debonding damage in PSCBs. The experimental research validates the feasibility of monitoring the interface debonding damage in PSCBs using SA transducers based on active sensing technique.

Analysis of failure in concrete and reinforced-concrete beams for the smart aggregate–based monitoring system

2019 ◽  
Vol 19 (2) ◽  
pp. 463-480 ◽  
Author(s):  
Azadeh Noori Hoshyar ◽  
Bijan Samali ◽  
Ranjith Liyanapathirana ◽  
Saber Taghavipour
Keyword(s):  
Reinforced Concrete ◽  
Root Mean Square ◽  
Concrete Beams ◽  
Wavelet Packet ◽  
Damage Index ◽  
Reinforced Concrete Beams ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Damage Indices ◽  
Smart Aggregate

Monitoring of structures and defining the severity of damages that occur under loading are essential in practical applications of civil infrastructure. In this article, we analyze failure using a smart aggregate sensor–based approach. The signals captured by smart aggregate sensors mounted on the structure under loading are de-noised using wavelet de-noising technique to prevent misdirection of the event interpretation of what is happening in the material. The performance of different mother wavelets on the de-noising process was investigated and analyzed. The objective is to identify the optimal mother wavelet for assessing and potentially reducing the effects of existing noise on signal properties for structural damage detection. In addition, we propose two innovative damage indices, entropy-based dispersion and entropy-based beta, for diagnostic purposes. The proposed entropy-based dispersion damage index is based on the modified wavelet packet tree and root mean square deviation, whereas the entropy-based beta damage index is based on the modified wavelet packet tree and slope of linear regression (beta). In both damage indices, the modified wavelet packet tree uses entropy as a high-level feature. Theoretical and experimental analyses are derived by computing indices on smart aggregate–based sensor data for concrete and reinforced-concrete beams. Validity assessment of the proposed indices was addressed through a comparative analysis with root mean square deviation damage index (benchmark) and the loading history. The proposed indices recognized the cracks faster than other measures and well before major cracking incurs in the structure. This article is expected to be beneficial for smart aggregate–based structural health monitoring applications particularly when damages occurred under loading.

Real-time localization of micro-damage in concrete beams using DIC technology and wavelet packet analysis

2021 ◽  
pp. 104198
Author(s):  
Kaiyang Zhou ◽  
Dong Lei ◽  
Jintao He ◽  
Pei Zhang ◽  
Pengxiang Bai ◽  
...  
Keyword(s):  
Real Time ◽  
Concrete Beams ◽  
Wavelet Packet ◽  
Wavelet Packet Analysis ◽  
Damage In Concrete

scholarly journals Vehicle speed measurement by on-board acoustic signal processing

2018 ◽  
Vol 51 (5-6) ◽  
pp. 138-149 ◽  
Author(s):  
Hüseyin Göksu
Keyword(s):  
Relative Motion ◽  
Wavelet Packet ◽  
Absolute Error ◽  
Frequency Resolution ◽  
Vehicle Speed ◽  
Air Conditioner ◽  
Wavelet Packet Analysis ◽  
Time Frequency ◽  
Speed Sensor ◽  
Frequency Domain Methods

Estimation of vehicle speed by analysis of drive-by noise is a known technique. The methods used in this kind of practice generally estimate the velocity of the vehicle with respect to the microphone(s), so they rely on the relative motion of the vehicle to the microphone(s). There are also other methods that do not rely on this technique. For example, recent research has shown that there is a statistical correlation between vehicle speed and drive-by noise emissions spectra. This does not rely on the relative motion of the vehicle with respect to the microphone(s) so it inspires us to consider the possibility of predicting velocity of the vehicle using an on-board microphone. This has the potential for the development of a new kind of speed sensor. For this purpose we record sound signal from a vehicle under speed variation using an on-board microphone. Sound emissions from a vehicle are very complex, which is from the engine, the exhaust, the air conditioner, other mechanical parts, tires, and air resistance. These emissions carry both stationary and non-stationary information. We propose to make the analysis by wavelet packet analysis, rather than traditional time or frequency domain methods. Wavelet packet analysis, by providing arbitrary time-frequency resolution, enables analyzing signals of stationary and non-stationary nature. It has better time representation than Fourier analysis and better high-frequency resolution than Wavelet analysis. Subsignals from the wavelet packet analysis are analyzed further by Norm Entropy, Log Energy Entropy, and Energy. These features are evaluated by feeding them into a multilayer perceptron. Norm entropy achieves the best prediction with 97.89% average accuracy with 1.11 km/h mean absolute error which corresponds to 2.11% relative error. Time sensitivity is ±0.453 s and is open to improvement by varying the window width. The results indicate that, with further tests at other speed ranges, with other vehicles and under dynamic conditions, this method can be extended to the design of a new kind of vehicle speed sensor.

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