CN108061759A - A kind of Reason of Hydraulic Structural Damage recognition methods based on piezoelectric ceramics - Google Patents
A kind of Reason of Hydraulic Structural Damage recognition methods based on piezoelectric ceramics Download PDFInfo
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Abstract
The invention discloses a kind of Reason of Hydraulic Structural Damage recognition methods based on piezoelectric ceramics, including actively monitoring process and passive monitoring process.The electric signal that the present invention is monitored using piezoceramic transducer, by a series of analyzing and processing, the damage of concrete for hydraulic structure can be therefrom efficiently identified out, particularly crack damage, the position that undamaged generation and damage occur and the degree damaged can be accurately determined with.The present invention can carry out the non-destructive tests of concrete for hydraulic structure, small, high sensitivity in Monitoring System for Dam Safety with piezoelectric ceramics monitoring technology, and fast response time can obtain larger application in safety monitoring system.
Description
Technical Field
The invention relates to a hydraulic concrete structure damage identification method, in particular to a hydraulic concrete structure damage identification method based on piezoelectric ceramics.
Background
The hydraulic concrete structure is subjected to dead load, hydrostatic pressure, wind load and temperature change, and the rock mass internal force of surrounding rock masses is also subjected to extreme loads, such as unfavorable loads of earthquake, extra-large flood, drought and the like, and is influenced by the deterioration of material performance and defects in design, construction and management, so that damage is inevitably generated, and the damage identification of the state of the hydraulic concrete structure is vital to ensure the healthy operation of the hydraulic concrete structure. The piezoelectric ceramic has low cost and high sensitivity, and is widely used in structural damage detection and identification.
In concrete dams, the main manifestation of damage is cracks, early cracks of concrete are difficult to find, and if tiny cracks are ignored to develop, the tiny cracks are likely to gradually expand to form macro cracks under the influence of water pressure, physical and chemical attack and environment. If the concrete dam has macroscopic cracks, the stress concentration phenomenon is easy to occur, so that the structure of the part is damaged, and finally the whole structure is possibly damaged. Therefore, when the hydraulic concrete structure is not damaged in a large area or is damaged in a small area, the health condition of the hydraulic concrete structure needs to be fed back in time, rationalized opinions are put forward, and the hydraulic concrete structure is prevented from being damaged in the bud.
The method selects a proper monitoring method to carry out health monitoring on hydraulic concrete structures such as dams and the like, identifies structural damage as early as possible, and has important significance for ensuring normal operation of the structure, reducing economic and social benefit loss and guaranteeing life and property safety of people.
Since the discovery of piezoelectric effect, the damage monitoring of structures by using piezoelectric ceramics to make sensors is widely applied in various fields. The piezoelectric ceramic integrates sensing and driving functions, is small in size, sensitive in response, wide in frequency response range, low in price and easy to cut, and the piezoelectric ceramic is made into a sensor for monitoring structural damage, so that not only can the local damage of a structure be identified, but also the overall damage of the structure can be identified. Meanwhile, the structure can be monitored continuously and in real time for a long time. Therefore, the piezoelectric ceramic sensing technology is of great significance in identifying damage of the hydraulic concrete structure.
However, the signals collected in the prior art inevitably contain noise, so that the signal-to-noise ratio of the response data is small, and useful signals containing characteristic parameters are often submerged in the noise, so that a certain signal noise reduction method and a certain signal analysis method are required to extract useful information reflecting the safety state of the structure. In addition, since the hydraulic structure generally has a large size and a high degree of freedom, a problem of a false mode exists in the mode parameter identification process, and therefore the problem needs to be improved, so that the damage identification method has a practical application value.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a hydraulic concrete structure damage identification method based on piezoelectric ceramics, which can solve the defects in the prior art.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the following technical scheme:
the hydraulic concrete structure damage identification method based on piezoelectric ceramics comprises an active monitoring process and a passive monitoring process, wherein the active monitoring process and the passive monitoring process respectively comprise the following steps:
the active monitoring process comprises the following steps:
s11: eliminating trend items of actually measured signals y (t) of the piezoelectric ceramic sensor by using a moving average method; where t is a time signal.
S12: carrying out signal noise reduction by using an improved empirical mode decomposition method to obtain a pre-processed signal which is close to a baseline and has no noise superposition;
s13: decomposing the signal obtained in the step S12 by using a wavelet packet;
s14: solving a wavelet packet energy spectrum of the signal;
s15: establishing a damage indication index so as to identify the damage degree of the structure and position the damage;
the passive monitoring process comprises the following steps:
s21: eliminating trend terms of actually measured signals of the piezoelectric ceramic sensor by using a sliding average method;
s22: carrying out signal noise reduction by using an improved empirical mode decomposition method to obtain a pre-processed signal which is close to a baseline and has no noise superposition;
s23: extracting a free vibration response from the signal obtained in step S22;
s24: carrying out modal parameter identification on the free vibration data;
s25: and establishing a damage indication index, and judging whether damage occurs or not and determining the damage degree.
Further, the step S12 specifically includes the following steps:
s12.1: obtaining the first IMF signal cl(t)，l＝1,2,3，…，；
S12.2: subtracting c from f (t)l(t) obtaining rl(t), i.e. rl(t)＝f(t)-cl(t); will r isl(t) repeating the above steps as raw data to obtain a second IMF-conditioned component c of f (t)2(t), repeating the above steps for n times to obtain n IMF-conditioned components of the signal f (t); wherein f (t) is the deterministic component of the actually measured signal y (t) in step S11.
Further, the step S12.1 specifically includes the following steps:
s12.11: let k be 2;
s12.12: the upper envelope u is obtained by interpolation between all local maxima by means of the Gaussian processk-1(t) and the lower envelope vk-1(t)；
S12.13: calculating the mean value m of the upper and lower envelope lines by the formula (1)k-1(t)：
S12.14: subtracting m from f (t)k-1(t) finding a new data sequence h with a reduced frequencyk-1(t), namely:
hk-1(t)＝f(t)-mk-1(t) (2)
wherein f (t) is the deterministic component of the actually measured signal y (t) in step S11;
s12.15: judging whether K is equal to K, wherein K is the maximum iteration number: if yes, ending; otherwise, continuing to step S12.16;
s12.16: if h isk-1(t) IMF Condition is met, then hk-1(t) is the k-1 component of f (t); otherwise, it ordersk is k +1, and then the process returns to step S12.12.
Further, the step S14 specifically includes the following steps:
s14.1: response signal wavelet packet decomposition coefficient is extracted through formula (3)
Where R (t) represents the new data series, ψ, after denoisingj,h,i(t) is a wavelet packet having a scale index j, a position index h, and a frequency index i;
s14.2: reconstructing the wavelet packet decomposition coefficient, extracting signals of each frequency band range, and solving the wavelet packet energy spectrum E of the signals:
wherein,represents the energy of the ith frequency band, as shown in equation (5);
wherein,to representThe reconstructed signal of (a) is then reconstructed,
further, in step S15, the process of identifying the structural damage degree is as follows: a signal emitter is selected to emit a waveform signal, and the structural damage degree is identified by receiving the amplitude of a signal piezoelectric ceramic sensor: if the amplitude of the received signal is smaller than that under the lossless working condition, judging that the monitored region has damage; if the amplitude of the received signal is equal to the amplitude under lossless conditions, it is determined that no damage exists in the monitored region.
Further, in step S23, a free vibration response is extracted from the preprocessed data by a random subtraction method.
Further, the damage indication index in step S25 is a natural frequency index, and the j-th order natural frequency index fnjAs shown in formula (6):
wherein f isujIs the j-th order natural frequency, f, of the lossless structuredjIs the j-th order natural frequency in the state of structural damage.
Has the advantages that: the invention discloses a hydraulic concrete structure damage identification method based on piezoelectric ceramics, which can effectively identify hydraulic concrete damage, particularly crack damage, by utilizing an electric signal monitored by a piezoelectric ceramic sensor through a series of analysis and treatment, namely accurately judge whether damage occurs or not, and the position and the degree of the damage. The hydraulic concrete damage identification system can be used for identifying hydraulic concrete damage by applying a piezoelectric ceramic monitoring technology in a dam safety monitoring system, is small in size, high in sensitivity and high in response speed, and can be greatly applied to the safety monitoring system.
Drawings
FIG. 1 is a flow chart of a method in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of the embedding position of a piezoceramic sensor during active monitoring according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an active monitoring test system for a reinforced concrete beam according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the position of a joint cut in the active monitoring test of a reinforced concrete beam in the embodiment of the invention;
FIG. 5 is a graph of received signals of ERPS-2 with different damage levels according to an embodiment of the present invention;
FIG. 6 is a graph of total energy indicators for six damage conditions in accordance with an embodiment of the present invention;
fig. 7 is a natural frequency index under each damage condition during passive monitoring in the embodiment of the present invention.
Detailed Description
The technical solution of the present invention will be further described with reference to the following detailed description and accompanying drawings.
The specific embodiment discloses a hydraulic concrete structure damage identification method based on piezoelectric ceramics, as shown in fig. 1, the method comprises an active monitoring process and a passive monitoring process, which are respectively as follows:
the active monitoring process comprises the following steps:
s11: eliminating trend items of actually measured signals y (t) of the piezoelectric ceramic sensor by using a moving average method; where t is a time signal.
S12: carrying out signal noise reduction by using an improved empirical mode decomposition method to obtain a pre-processed signal which is close to a baseline and has no noise superposition;
s13: decomposing the signal obtained in the step S12 by using a wavelet packet;
s14: solving a wavelet packet energy spectrum of the signal;
s15: establishing a damage indication index so as to identify the damage degree of the structure and position the damage;
the passive monitoring process comprises the following steps:
s21: eliminating trend terms of actually measured signals of the piezoelectric ceramic sensor by using a sliding average method;
s22: carrying out signal noise reduction by using an improved empirical mode decomposition method to obtain a pre-processed signal which is close to a baseline and has no noise superposition;
s23: extracting a free vibration response from the signal obtained in step S22;
s24: carrying out modal parameter identification on the free vibration data;
s25: and establishing a damage indication index, and judging whether damage occurs or not and determining the damage degree.
Step S12 specifically includes the following steps:
s12.1: obtaining the first IMF signal cl(t)，l＝1,2,3，…，；
S12.2: subtracting c from f (t)l(t) obtaining rl(t), i.e. rl(t)＝f(t)-cl(t); will r isl(t) repeating the above steps as raw data to obtain a second IMF-conditioned component c of f (t)2(t), repeating the above steps for n times to obtain n IMF-conditioned components of the signal f (t); wherein f (t) is the deterministic component of the actually measured signal y (t) in step S11.
The Intrinsic Mode Function (IMF) needs to satisfy two basic conditions, also called IMF conditions:
1. the number of the extreme points and the zero-crossing points of the whole data segment should be the same or similar, and at most one difference is needed.
2. The local mean is zero. At any point, the mean of the upper envelope curve fitted with the finite number of local maximum points and the lower envelope curve fitted with the finite number of local minimum points is zero.
Step S12.1 specifically includes the following steps:
s12.11: let k be 2;
s12.12: the upper envelope u is obtained by interpolation between all local maxima by means of the Gaussian processk-1(t) and the lower envelope vk-1(t)；
S12.13: calculating the mean value m of the upper and lower envelope lines by the formula (1)k-1(t)：
S12.14: subtracting m from f (t)k-1(t) finding a new data sequence h with a reduced frequencyk-1(t), namely:
hk-1(t)＝f(t)-mk-1(t) (2)
wherein f (t) is the deterministic component of the actually measured signal y (t) in step S11;
s12.15: judging whether K is equal to K, wherein K is the maximum iteration number: if yes, ending; otherwise, continuing to step S12.16;
s12.16: if h isk-1(t) IMF Condition is met, then hk-1(t) is the k-1 component of f (t); otherwise, let k be k +1, and then return to performing step S12.12.
Step S14 specifically includes the following steps:
s14.1: response signal wavelet packet decomposition coefficient is extracted through formula (3)
Where R (t) represents the new data series, ψ, after denoisingj,h,i(t) is a wavelet packet having a scale index j, a position index h, and a frequency index i;
s14.2: reconstructing the wavelet packet decomposition coefficient, extracting signals of each frequency band range, and solving the wavelet packet energy spectrum E of the signals:
wherein,represents the energy of the ith frequency band, as shown in equation (5);
wherein,to representThe reconstructed signal of (a) is then reconstructed,
in step S15, the process of identifying the structural damage degree is as follows: a signal emitter is selected to emit a waveform signal, and the structural damage degree is identified by receiving the amplitude of a signal piezoelectric ceramic sensor: if the amplitude of the received signal is smaller than that under the lossless working condition, judging that the monitored region has damage; if the amplitude of the received signal is equal to the amplitude under lossless conditions, it is determined that no damage exists in the monitored region.
In step S23, a free vibration response is extracted from the preprocessed data by a random subtraction method.
The damage indication index in step S25 is a natural frequency index, a j-th order natural frequency index fnjAs shown in formula (6):
wherein f isujIs the j-th order natural frequency, f, of the lossless structuredjIs the j-th order natural frequency in the state of structural damage.
The sectional dimension of the reinforced concrete beam designed by the embodiment is 150mm × 150mm × 550 mm. The piezoceramic sensor is a cylinder with a cross-section diameter of 30mm and a thickness of 35 mm. 3 piezoelectric ceramic sensors are embedded in the reinforced concrete beam, and the polarization directions of the sensors are along the length direction of the reinforced concrete beam. The size of the reinforced concrete beam, the arrangement position of the reinforcing steel bars, and the burying position of the piezoelectric ceramic sensor are shown in fig. 2.
ERPS-1 is used as a driving sensor, and is connected to a waveform generator during test, and ERPS-2 and ERPS-3 are used as receivers. An active monitoring system for reinforced concrete beams is shown in figure 3.
Firstly, when the reinforced concrete beam is in a non-damage state, the ERPS-1 transmits signals, and the ERPS-2 and the ERPS-3 receive the signals respectively. After the measurement, a slit with the thickness of 5mm is cut at the center of the beam by a cutting and cutting machine, the ERPS-1 is also used for transmitting signals, and the ERPS-2 and the ERPS-3 are respectively used for receiving signals. The seam was then deepened to 10mm, 15mm, …, 30mm and the test repeated. The test conditions are shown in table 1, and the reinforced concrete beam cuts are shown in fig. 4.
TABLE 1 active monitoring test for reinforced concrete beam
An Agilent waveform generator is used for transmitting sine waves of 92kHz and 10Vpp, and signal data under lossless working conditions and six damage working conditions are collected. And (4) comparing and analyzing the received signals of the ERPS-2 under different damage working conditions, and researching the relation between the response signals and the damage degree. FIG. 5 shows signals received by ERPS-2 when the reinforced concrete beam is not damaged, the crack depth is 5mm, and the depth is 10mm, and the sampling frequency of the signals is 1000 Hz. It can be seen from the figure that the signal amplitude with damage is smaller than the signal amplitude for the lossless regime, and the signal amplitude decreases as the crack depth increases. The test result shows that the amplitude of the signal received by the piezoelectric sensor is reduced along with the increase of the damage degree, and the change of the signal amplitude can preliminarily diagnose the existence and the damage degree of the structural damage.
The results of analyzing the received signals of ERPS-2 and ERPS-3 under the same damage condition and exploring the relationship between the relative position between the piezoelectric sensor and the crack and the response signal are shown in FIG. 6. It can be seen from fig. 6 that as the crack depth increases, the total energy index decreases, which conforms to the rule that the larger the damage degree is, the more the stress wave propagates in the structure and encounters the crack damage to attenuate the energy. The total energy index of ERPS-3 is greater than that of ERPS-2, because the embedded position of ERPS-2 is closer to the crack, the attenuation degree of the received stress wave is greater, and therefore the total energy is smaller. The indicator can therefore be used for the initial localization of damage, with the crack location on the side of the piezoelectric sensor having the smaller overall energy indicator.
For passive monitoring, firstly, trend elimination and noise reduction are carried out on the collected measured data of each measuring point by using a moving average method, then free vibration response extraction processing is carried out on the processed data, and then the self-vibration frequency and the vibration mode are identified by using an STD method. The natural frequency index under each condition is calculated by using the frequency and the mode shape, as shown in fig. 7.
As can be seen from fig. 7, as the damage degree increases, the natural frequency index curve of each step generally increases, so the damage degree of the structure can be identified by the natural frequency index.
The judgment of damage location can be determined by means of signal difference of monitoring parts of different sensors, the propagation mode of the vibration source is from the center to the periphery, waves generated by vibration of the vibration source are received by the sensors arranged around the vibration source, and the damage occurrence of the structure is gradually checked along the propagation direction of the waves. Comparing the wave received by the sensor with the wave in a nondestructive state, when the wave is transmitted to the first sensor, if the characteristic of the wave received by the sensor is changed, indicating that damage occurs between the vibration source and the first sensor, and thus completing the positioning of the damage; if the characteristics of the wave are not changed, it is indicated that no damage occurs between the vibration source and the first sensor, verification is continuously carried out on the position of the next sensor, and if the characteristics of the next wave are changed, it is indicated that damage occurs between the first sensor and the second sensor, so that the damage positioning is completed; if the wave characteristic is not changed, the damage between the first sensor and the second sensor is not generated, and the verification is continued to the position of the next sensor until the sensor with the changed wave characteristic or the last sensor is verified. The amplitude index of the signal may be selected for quantification of changes in the characteristics of the wave.
Claims (7)
1. A hydraulic concrete structure damage identification method based on piezoelectric ceramics is characterized in that: the method comprises an active monitoring process and a passive monitoring process, which are respectively as follows:
the active monitoring process comprises the following steps:
s11: eliminating trend items of actually measured signals y (t) of the piezoelectric ceramic sensor by using a moving average method; where t is a time signal.
S12: carrying out signal noise reduction by using an improved empirical mode decomposition method to obtain a pre-processed signal which is close to a baseline and has no noise superposition;
s13: decomposing the signal obtained in the step S12 by using a wavelet packet;
s14: solving a wavelet packet energy spectrum of the signal;
s15: establishing a damage indication index so as to identify the damage degree of the structure and position the damage;
the passive monitoring process comprises the following steps:
s21: eliminating trend terms of actually measured signals of the piezoelectric ceramic sensor by using a sliding average method;
s22: carrying out signal noise reduction by using an improved empirical mode decomposition method to obtain a pre-processed signal which is close to a baseline and has no noise superposition;
s23: extracting a free vibration response from the signal obtained in step S22;
s24: carrying out modal parameter identification on the free vibration data;
s25: and establishing a damage indication index, and judging whether damage occurs or not and determining the damage degree.
2. The hydraulic concrete structure damage identification method based on piezoelectric ceramics as claimed in claim 1, characterized in that: the step S12 specifically includes the following steps:
s12.1: obtaining the first IMF signal cl(t)，l＝1,2,3，…，；
S12.2: subtracting c from f (t)l(t) obtaining rl(t), i.e. rl(t)＝f(t)-cl(t); will r isl(t) repeating the above steps as raw data to obtain a second IMF-conditioned component c of f (t)2(t), repeating the above steps for n times to obtain n IMF-conditioned components of the signal f (t); wherein f (t) is the deterministic component of the actually measured signal y (t) in step S11.
3. The hydraulic concrete structure damage identification method based on piezoelectric ceramics as claimed in claim 1, characterized in that: the step S12.1 specifically includes the steps of:
s12.11: let k be 2;
s12.12: by the Gaussian process in allInterpolation between local maxima to obtain the upper envelope uk-1(t) and the lower envelope vk-1(t)；
S12.13: calculating the mean value m of the upper and lower envelope lines by the formula (1)k-1(t)：
S12.14: subtracting m from f (t)k-1(t) finding a new data sequence h with a reduced frequencyk-1(t), namely:
hk-1(t)＝f(t)-mk-1(t) (2)
wherein f (t) is the deterministic component of the actually measured signal y (t) in step S11;
s12.15: judging whether K is equal to K, wherein K is the maximum iteration number: if yes, ending; otherwise, continuing to step S12.16;
s12.16: if h isk-1(t) IMF Condition is met, then hk-1(t) is the k-1 component of f (t); otherwise, let k be k +1, and then return to performing step S12.12.
4. The hydraulic concrete structure damage identification method based on piezoelectric ceramics as claimed in claim 1, characterized in that: the step S14 specifically includes the following steps:
s14.1: response signal wavelet packet decomposition coefficient is extracted through formula (3)
Where R (t) represents the new data series, ψ, after denoisingj,h,i(t) is a wavelet packet having a scale index j, a position index h, and a frequency index i;
s14.2: reconstructing the wavelet packet decomposition coefficient, extracting signals of each frequency band range, and solving the wavelet packet energy spectrum E of the signals:
wherein,represents the energy of the ith frequency band, as shown in equation (5);
wherein,to representThe reconstructed signal of (2).
5. The hydraulic concrete structure damage identification method based on piezoelectric ceramics as claimed in claim 1, characterized in that: in step S15, the process of identifying the structural damage degree is as follows: a signal emitter is selected to emit a waveform signal, and the structural damage degree is identified by receiving the amplitude of a signal piezoelectric ceramic sensor: if the amplitude of the received signal is smaller than that under the lossless working condition, judging that the monitored region has damage; if the amplitude of the received signal is equal to the amplitude under lossless conditions, it is determined that no damage exists in the monitored region.
6. The hydraulic concrete structure damage identification method based on piezoelectric ceramics as claimed in claim 1, characterized in that: in step S23, a free vibration response is extracted from the preprocessed data by a random subtraction method.
7. The piezoceramic-based hydraulic work of claim 1The concrete structure damage identification method is characterized by comprising the following steps: the damage indication index in step S25 is a natural frequency index, a j-th order natural frequency index fnjAs shown in formula (6):
wherein f isujIs the j-th order natural frequency, f, of the lossless structuredjIs the j-th order natural frequency in the state of structural damage.
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| CN112362756A (en) * | 2020-11-24 | 2021-02-12 | 长沙理工大学 | Concrete structure damage monitoring method and system based on deep learning |
| CN112378958A (en) * | 2020-10-23 | 2021-02-19 | 华中科技大学 | Structural damage identification method and system |
| CN113640217A (en) * | 2021-10-13 | 2021-11-12 | 武汉地震工程研究院有限公司 | System for monitoring bonding state of concrete interface by steel bonding method |
| CN117349601A (en) * | 2023-12-06 | 2024-01-05 | 济南大学 | Concrete damage classification method and system based on piezoelectric vibration waves |
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| CN113640217B (en) * | 2021-10-13 | 2022-01-21 | 武汉地震工程研究院有限公司 | System for monitoring bonding state of concrete interface by steel bonding method |
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| CN117349601B (en) * | 2023-12-06 | 2024-03-05 | 济南大学 | Concrete damage classification method and system based on piezoelectric vibration waves |
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