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

Meng, Huien; Yang, Wenwei; Yang, Xia

doi:https://doi.org/10.1155/2021/8201780

Journal of Sensors

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Abstract Introduction Results and Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2021 | Article ID 8201780 | https://doi.org/10.1155/2021/8201780

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

Huien Meng,^1,2Wenwei Yang ,^1,2and Xia Yang^2,3

Academic Editor: Bin Gao

Received07 Jul 2021

Revised23 Sept 2021

Accepted05 Oct 2021

Published27 Oct 2021

Abstract

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.

1. Introduction

Compared with other building structures, wooden structures often have the advantages of good seismic performance, short construction period, energy saving, and low carbon. However, as a biological material, timber inevitably suffers from cracks, deformation, loosening, and decay [1] during long-term service, which poses a threat to the overall stability of the structure. Therefore, it is necessary to continuously repair and reinforce the building structure. The repair and reinforcement technologies of timber structures are generally divided into traditional technologies and modern repair technologies [2]. The traditional technology mainly focuses on maintenance and maintenance and renewal. For poor decay, the methods of pick-up, wrapping, and pier connection are generally adopted [3]. For timber column cracks, the method of inlay is generally adopted. For the bending and sag of timber beams, the traditional support-top method and the reinforcement method of lower struts are adopted [4]. Compared with traditional repair technology, modern repair technology mainly introduces new concepts, new processes, and new materials. In terms of component deterioration, materials with specific properties such as in situ reinforcement, anticorrosion, and reinforcement are in situ synthesized at the deterioration site [5, 6]. In terms of component connection reinforcement, the iron components are easy to rust, which will have a certain impact on wooden materials and building appearance [7, 8]. Therefore, more and more iron materials are replaced by fiber composite materials [9, 10], such as carbon fiber strips [11] instead of steel hoop to reinforce cracks and tenon and fiber cloth [12–15] instead of steel plate to reinforce wooden beams. Compared with traditional materials, fiber composite materials have excellent mechanical properties, thin material, strong fire resistance, and have little influence on building appearance. In the aspect of timber column cracks, adhesive or thermoplastic composites can be used to fill [16]. When it does not meet the stress requirements, the bearing capacity can be enhanced by seaming, built-in core material, and grafting [17–19].

Ritter [20] thinks epoxy resin is one of the best timber repair materials. The shrinkage of epoxy resin after curing is very small, which can fill the gap between the base material and the reinforced material [21] and can be in situ repaired without or with little damage to the building structure [22]. In recent years, some scholars have tried to combine epoxy resin with other materials to repair the damaged timber beams. The results show that such composites have good characteristics in the repair process [23–26]. Many scholars have directly filled epoxy resin into the cracks and holes of timber structure to reinforce it [27–29] and found that the strength of timber is generally improved after epoxy resin repair. In practical engineering, the repair and reinforcement technology for timber structure should follow the principles of building authenticity and integrity. At the same time, in order to reduce the repair cost and shorten the construction cycle, the in situ repair is often used for the repair and reinforcement of timber structures. Therefore, the bearing capacity of timber structure in the in situ repair process has become a common concern.

Since the nineteenth century, the emergence of intelligent materials has provided an effective way to realize the health monitoring of engineering structures. Among many smart materials, piezoelectric ceramics, as the main representative of piezoelectric materials, have great application potential in the health monitoring of engineering structures because of their fast reaction speed, wide frequency response range, easy cutting, and low cost and have the characteristics of positive and negative piezoelectric effect [30–35]. The structural health monitoring technology based on piezoelectric ceramics is mainly divided into two categories: active health monitoring technology and passive health monitoring technology [36]. Among them, the passive structural monitoring technology using piezoelectric ceramics is mostly concentrated on structural deformation monitoring and impact load monitoring under environmental loads [37–42]. Active health monitoring technology is commonly used to monitor the damage and early strength development of concrete structures [43–51], the interfacial debonding of structures [52–57], the damage of reinforced concrete structures [58–61], the looseness of thread connections [62], soil compactness and freezing-thawing process [63, 64], and the damage of metal thin plates [55, 65]. In recent years, the health monitoring technology based on piezoelectric ceramics has also played an important role in the field of timber structure health monitoring, including monitoring the damage degree of timber structure [66–69], the change of water content [70], the connection state of components [71, 72], and the damage state of timber specimens during loading [73, 74]. The results of these studies demonstrate the effectiveness, superiority, and accuracy of this method in the health monitoring of timber structure.

Through the above discussion, it can be found that in the current active health monitoring research on structures, the focus is mainly on the damage monitoring and damage identification of structures and the real-time monitoring of structural damage state under load. The discussion on the monitoring of the surface crack repair state of timber structure is very limited. Based on this, this paper focuses on the repair process of timber structure surface cracks and conducts real-time evaluation of the repair state based on the active sensing technology of piezoelectric ceramics. The epoxy resin was used as the repair material and filled into the cracks artificially set by the timber. The active monitoring was carried out within 0, 1, 2, 3, 12, and 24 h after the repair of the timber specimen, and the change trend of the amplitude of the signal with time was analyzed. In addition, the relationship between the wavelet packet energy of the specimen and the corresponding ultimate load in different time was analyzed by using the wavelet packet analysis method combined with the compressive test. The damage index of the specimen was further calculated, which provides a reference for the quantitative evaluation of the repair state of timber cracks. The results show that the method can quantitatively, effectively, and real-time evaluate the development of timber’s strength in the process of repairing crack and provide a more reliable scheme and diversified choice for solving the monitoring problem of repair process of timber structure.

2. Basic Principles

2.1. Wave Propagation Analysis

In this study, the wave propagation analysis method was used to monitor the repair state of timber surface cracks in real time. The monitoring principle of the wave propagation analysis method comprises an intelligent monitoring system of piezoelectric actuators, piezoelectric sensors, and timber specimens (Figure 1). Lead zirconate titanate (PZT) pasted on one end of the specimen surface is used as the actuator. When the external electric field is excited, the actuator emits a sweep signal. The excited piezoelectric actuator generates high-frequency stress waves propagated with epoxy resin as the medium, owing to the inverse piezoelectric effect of the piezoelectric ceramic. The PZT at the other end of the specimen receives high-frequency stress wave and converts it into electrical signal output. The reflection, diffraction, and transmission of the stress waves are influenced by the curing strength of the epoxy resin, structural characteristics, structural cracks, and other factors during the propagation process, causing amplitude attenuation, energy attenuation, and propagation time delay of the received signal of the piezoelectric sensor. The damage to and damage repair of the structure are identified by analysing the differences in the received signals of the specimens.

2.2. Wavelet Packet Analysis

Wavelet packet analysis is widely used in signal processing, image processing, and quantum mechanics [75, 76]. The wavelet packet transform [77] has been developed based on Fourier analysis and wavelet decomposition. It overcomes the limitations of Fourier analysis in analysing nonstationary signals, solves the problems of constant window size and fixed resolution of short Fourier transform, and optimizes wavelet decomposition that decomposes only low-frequency signals. Wavelet packet decomposition is used to divide the signal into different frequency bands. Based on the analysed signal characteristics, the appropriate frequency band is selected to decompose high- and low-frequency signals. This decomposition has no leakage or redundancy and refines the signal. Therefore, the wavelet packet transform has wide application value in engineering damage monitoring [78, 79].

The wavelet-packet-based energy index (WPEI) is equivalent to the energy of the original monitoring signal; hence, the original monitoring signal energy can be characterized using wavelet packet energy. In this study, the db3 wavelet function was selected to decompose the original signal into five layers, and the wavelet packet energy of the timber specimen signal was determined.

2.3. Damage Diagnosis Method

The RMSD expresses the deviation relationship between the target data and the benchmark data. The damage index based on RMSD [30, 80] is used to evaluate the degree of damage to civil engineering structures. The determination method of the damage index is as follows. The energy vector in the healthy state of the structure is selected as the reference value, and the energy vector of the structure after damage is set as . The damage index of the structure can then be denoted as DI.

The value of DI indicates the attenuation degree of the signal energy value relative to the healthy state. The structure is in a healthy state when and complete functional failure state when . Therefore, the degree of damage to the structure can be evaluated based on the DI value.

3. Experimental Tests

3.1. Materials

The experimental materials used in this study are depicted in Figure 2. Piezoelectric ceramics can be used for structural health monitoring through surface bonding and internal embedding. As embedded sensors cause damage to timber structures, surface bonding was selected in this study; the piezoelectric ceramic sheets were bonded to the surface of the specimens using AB glue to monitor the health of the specimen. For the experimental tests, we utilized the FR 15 mm TL-10.5 K piezoelectric ceramic sensor manufactured by Shenzhen Furong Electroacoustic Technology Co., Ltd. as the drive and sensor (Figure 2(a)); the size of the sensor was 15 mm. Timber specimens were cut from Chinese fir cultivated in southwest China (Figures 2(b) and 2(c)). Epoxy resin is a mixture of A and B at a ratio of 2 : 1 (as shown in Figure 2(d)).

(a)

(b)

(c)

(d)

3.2. Test Device

The monitoring device used for active health monitoring tests consisted of the multifunctional piezoelectric signal monitoring and analysis system produced by Jiangsu Sanchuan Intelligent Technology Co., Ltd., the power amplifier of piezoelectric ceramic loads, and the timber specimen (Figure 3). Based on the principle of wave propagation analysis, the actuator on the timber structure specimen was connected to the analogue signal channel port on the signal monitoring and analysis system. The power amplifier was attached to the signal monitoring and analysis system using a wire. The sensor was connected to the signal receiving port in the power amplifier, and the computer terminal was linked to other channel ports in the signal monitoring and analysis system. The data were collected and stored using SCHYPZTV3 software.

Active monitoring tests were performed in the form of an excitation and a reception. PZT at both ends of each specimen was used as a driver and sensor for signal transmission and reception. Scan frequency sine-wave was adopted as the monitoring signal. Because of the different frequency response ranges for each material, several experimental pretests were conducted before the formal tests to determine the frequency response range of the Chinese fir structure. In other words, the time-domain waveform of the collected signal was obtained by continuously adjusting the sweep frequency range, and the time period of the large-signal amplitude was determined. The approximate sweep frequency range of the time period was calculated based on the sweep frequency time. Finally, the specimen was excited again according to the calculated sweep frequency range. The process was repeated until the sweep frequency range of the test specimen was determined. A sweep frequency range of 20–270 kHz was obtained using the above method, and the sweep time of sweep sine-wave signal was 250.5 ms.

During the working process of the monitoring system, the signal is influenced by the external working environment, such as temperature and humidity variations, current and voltage fluctuations, and some electronic equipment used for the work. Real-time filtering was performed during the acquisition process, in which the filtering topology of anti-Chebyshev band-pass of order 5 was adopted, to reduce the interference of external factors. The filtering range was 30–250 kHz. Moreover, multiple excitations were conducted in each test until the signal waveform became stable to prevent the uncertainty of test results caused by random errors, and the data was then saved and exported. The test and filtering parameters of the swept sine-wave signal are listed in Table 1.

The test equipment consisted of a servo-pressure testing machine and timber specimens (Figure 4). The displacement method was applied for loading the timber specimens at a speed of 0.5 mm/min to ensure good contact between each timber specimen surface and the pressure test machine. The ultimate load of each specimen was then recorded.

3.3. Test Procedure

Sixteen timber specimens, each with a size of (), were designed. The height was in the grain direction, and compression tests was performed in the grain direction. The specimens were divided into groups A and D. Group A consisted of two noncracked specimens, denoted A1 and A2. Group D specimens had cracks along the timber grain direction. The crack width “” was 10 mm, crack depth “” was 15 mm, and crack height “” was 150 mm. Fourteen timber specimens were in group D, denoted D1–D14. Timber specimens A1–A2 and D1–D12 were used for the compression tests along the grain direction, and specimens D13–D14 were used for active monitoring tests. For the active monitoring test specimens, AB glue was applied to fix two PZT sheets at the predetermined position before the tests (Figure 5). The schematic of the active monitoring method in monitoring the strength development of epoxy resin after filling it into timber cracks is also shown in Figure 5.

Active monitoring and grain compression tests were conducted simultaneously to establish the relationship between the energy index and the timber strength after epoxy resin injection. Group A specimens were only used for longitudinal compression tests under axial compression, which were performed before group D specimen tests. The cracks on the group D specimens were filled with epoxy resin. When the curing times of the epoxy resin were 0, 1, 2, 3, 12, and 24 h, two specimens were selected sequentially according to the specimen number for the compression test. Specimens D13 and D14 were subjected to active monitoring tests before setting the crack damage to monitor the initial signal “YS” without damage, and the initial signal “LF” with damage after crack setting was assessed. Finally, the active monitoring tests were carried out at 0, 1, 2, 3, 12, and 24 h after epoxy resin filling. The parameters and test conditions are listed in Table 2.

The Chinese national standard, GB/T 1931-2009, was adopted in this study, considering the influence of timber moisture content on signal. Before the tests, each specimen was placed in an oven (Figure 6(a)). The specimen was baked at () °C for 8 h, weighed immediately, and then weighed every 2 h. When the difference between the last two weighing masses did not exceed 0.5% of the specimen mass, the specimen was considered to be dry and baked to dry completely according to this method. Subsequently, group D specimens were bonded with piezoelectric ceramic plates, and the cracks on the specimens were processed (Figure 6(b)). Finally, the epoxy resin was poured into the cracks (Figure 6(c)), and active monitoring and compression tests were performed based on the above time nodes.

4. Results and Discussion

4.1. Result Analysis of Signal Amplitude

Figures 7 and 8 show the time-domain signal response of the specimens D13 and D14 before and after the crack is set. In the legend, “YS” represents the time-domain signal before the crack is set, and “LF” represents the time-domain signal after the crack is set. It can be seen from the figures that the signal amplitude of the specimen before setting crack is significantly greater than after setting crack. The main reason is that the stress wave propagates based on the timber specimen as the medium, when the crack damage occurs in the specimen, the stress wave will occur reflection, refraction, and diffraction phenomena, and the energy loss will occur at the crack damage interface, which will result in the receiving signals of the PZT patches at the corresponding position weaker than that at the intact interface, and the corresponding signal amplitude is also smaller.

The active monitoring test results for the time-domain signals received by specimens D13 and D14 at 0, 1, 2, 3, 12, and 24 h are shown in Figures 9 and 10. With an increase in the curing time of epoxy resin, the signal amplitude received by the PZT sensor increased. During the curing process of the epoxy resin, the propagation strength of the stress waves depended on the transfer medium state. With an increase in the epoxy resin pouring time, the stress waves gradually transformed from liquid to solid, and the propagation strength of the stress waves increased; hence, the improvement in the signal amplitude was predictable. Although the signal amplitude trends of the specimens were similar, each specimen still exhibited unique properties. This difference occurs because the growth of trees is cyclical and divided into growth and dormancy periods, indicating that timber is a heterogeneous material. Thus, each specimen exhibited different signal amplitude characteristics. The variation in the signal amplitude preliminarily indicated that this monitoring method could effectively identify the development of timber strength after epoxy resin filling.

(a)

(b)

(a)

(b)

4.2. Result Analysis of Wavelet Packet Energy

Through the wavelet decomposition of the original signal, the “db3” wavelet transform was used for five-level decomposition to verify the reliability of the proposed method further, and the wavelet coefficients in 32 frequency bands at the last layer were obtained (Figures 11 and 12). For specimen D13 (Figure 11), only specific signal bands (bands 2, 3, 4, and 7) were sensitive to changes in epoxy curing. Frequency bands 3 and 4 were most sensitive to wavelet coefficient’s changes in the tests, and frequency band 7 exhibited a slight change (“amplified” diagram in Figure 11). Moreover, the variations in the wavelet coefficients in each frequency band were similar, and the wavelet coefficients increased with the epoxy resin curing time. For specimen D14, the changes were most significant in frequency bands 3, 4, and 7. It can be observed from the “amplified” diagram in Figure 12 that it is similar to specimen D13; the wavelet coefficient increased with increasing curing time in each frequency band.

Two groups of specimens under the same working conditions were designed to verify the reliability of the proposed method. In addition, the change in energy spectrum distribution could be attributed to the epoxy resin poured into the artificially set crack. The epoxy resin acts as the propagation medium of stress wave propagation. The epoxy resin was initially in a liquid form, which had an attenuation effect on energy, and the corresponding wavelet coefficient was small. In 1–12 h, the epoxy resin gradually changed from liquid to solid. The epoxy resin curing weakened the energy attenuation, and the corresponding wavelet coefficient increased. Interestingly, the frequency band 4 of specimen D13 showed that the wavelet coefficient of 24 h is slightly smaller than that 12 h’s. However, in the frequency band 3 of specimen D14, the wavelet coefficient within 12 h and 24 h are close, indicating that the curing of epoxy resin was basically completed.

The curing strength was significantly reflected in the wavelet coefficient of the PZT output signal, showing the possibility of determining the development of timber surface-crack repair strength using the wavelet coefficient.

Specimens D1–D12 were evaluated at 0, 1, 2, 3, 12, and 24 h after filling the cracks with epoxy resin to characterize the linear relationship between the energy index and the strength development of repaired timber. Two specimens were selected at each time point, and the test results are presented in Table 3, and the load-displacement curves are shown in Figure 13. The ultimate bearing capacity of two specimens corresponding to six time nodes and the ultimate bearing capacity of group A specimens under nondamage state were recorded, and the average value of each data was calculated. The specimens underwent uneven stress and eccentric failure during compression, owing to the artificial crack installation in group D specimens; consequently, the ultimate bearing capacities of the specimens with crack damage were lower than those without crack damage. After pouring the epoxy resin into the cracks and with epoxy resin curing, its strength increased, reinforcing the timber specimens and improving their ultimate bearing capacity. The filled epoxy resin exhibited a reinforcing effect on the timber specimens but could not fully recover their bearing capacities.

(a)

(b)

(c)

Based on the wavelet packet analysis method, the wavelet packet energy of the specimen was calculated, and the wavelet packet energy of each specimen was compared with its ultimate bearing capacity. The columnar diagram represents the wavelet packet energy of the specimen, and the point-line diagram showed the ultimate bearing capacity of the specimen at the corresponding time node (Figures 14 and 15). The wavelet packet energy of specimens D13 and D14 showed a similar trend with the measured ultimate bearing capacity. With an increase in time, the wavelet packet energy and the ultimate bearing capacity increased. Therefore, the wavelet packet energy of the signal was closely related to the ultimate bearing capacity of the specimens. Furthermore, the axial compression tests also verified the effectiveness of the active monitoring test method.

Equation (1) was reviewed to evaluate the damage indexes of the specimens quantitatively. The damage indexes of specimens D13 and D14 within 0, 1, 2, 3, 12, and 24 h and those of artificial fracture initial state “LF” were calculated. The initial damage index of specimen D13 was 0.492. When the epoxy resin was applied, the damage index decreased to 0.381. With an increase in curing time, the damage index decreased gradually and reached 0.186 at 24 h. For specimen D14, the damage index decreased from 0.645 to 0.190. Figures 16 and 17 are plotted to analyse the variation comprehensively. It was observed that the calculation results for specimens D13 and D14 were slightly different but showed similar changes. The damage index changed significantly within 2 h from the initial state “LF” to the epoxy resin, showing a sharp decline. From 2 to 24 h, the damage index of the specimen changed slowly and finally tended to be gentle, indicating that the epoxy resin curing was completed. Based on the damage index variation, the proposed method can be used as a reference for real-time monitoring of the repair state of timber surface cracks.

5. Conclusion and Future Work

In this study, the active sensing technique based on piezoelectric ceramics was applied to monitor the strength development of timber surface cracks repaired with epoxy resin. A pair of PZT patches were pasted on both sides of the crack to transmit and receive signals and achieve active sensing. In the active monitoring tests, the epoxy resin was adopted as the medium for stress wave propagation. With an increase in the curing time of the epoxy resin, the state gradually transformed from liquid to solid, the propagation ability of stress wave improved, and the signals received by the PZT patch were enhanced. The analysis results of the time-domain signal amplitude and wavelet packet energy showed that with an increase in curing time of epoxy resin, the signal amplitude and the wavelet packet energy increased. When the curing time reached 24 h, the signal amplitude and wavelet packet energy tended to be stable, indicating that the curing process of the epoxy resin was completed. The above experimental results demonstrate the effectiveness of the active monitoring method. The comparison between the wavelet packet energy of the signal and the ultimate load during the corresponding period indicated that there was an excellent correlation between the wavelet packet energy of each specimen and the ultimate load. In addition, the damage index of each stage of the specimen was calculated. It was found that the damage index of specimen D13 decreased from 0.492 to 0.186, and that of specimen D14 decreased from 0.645 to 0.190, indicating that the damage index is useful for evaluating the crack repair strength. The active monitoring and compression test results showed that the active sensing technique using piezoelectric ceramics can monitor the strength development during timber-surface crack repair in real time.

In future studies, the application of the active sensing technique based on the stress wave and the damage index based on the wavelet packet in the real-time monitoring of repair and reinforcement of large timber structures should be investigated further. In addition, the effects of environmental temperature, humidity, epoxy resin, bond layer, and timber microstructure should be considered comprehensively.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This research was supported in part by the Natural Science Foundation Project of Ningxia Province (no. 2021AAC03095), in part by the Funding Project of First-Class Discipline Construction of Universities in Ningxia under grant NXYLXK2021A03, and Graduate Innovation Project of Ningxia University (grant number GIP2021049).

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