Method and device for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data

Abstract

The present invention discloses a method and device for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data, which belongs to the field of structural health monitoring. The method includes: collecting the admittance value of the tensile and compressive stress structure to be identified under different sweeping frequencies and loads; setting the sensitive frequency band segmentation step to segment the sweeping frequency range, and using the standard deviation as the sensitivity index to calculate the sensitivity of all sub-frequency bands obtained by segmentation; selecting the sub-frequency band with the largest sensitivity as the tensile and compressive stress sensitive frequency band. The present invention measures the electrical impedance spectrum of the stressed structure from the initial state to the damaged state through a PZT sensor, and uses a sensitivity analysis method to identify the tensile and compressive stress sensitive frequency bands suitable for the entire health monitoring cycle from the piezoresistive impedance spectrum reflecting the stress state changes of the structure to be identified. The present invention is easy to implement, can accurately distinguish the stress sensitive frequency bands of the structure under tension or compression, has practical engineering application value, and is expected to promote the development of EMI-based SHM technology.

Description

Technical Field

[0001] The present invention belongs to the technical field of motors, and more specifically, relates to a method and device for identifying a tensile-compressive stress sensitive frequency band based on piezoresistive impedance data. Background Art

[0002] Most civil infrastructures, such as bridges, buildings, water supply pipelines, offshore platforms, nuclear power plants, and oil tanks, are load-bearing components that can transfer loads to the foundation. They are sometimes exposed to harsh environments and service loads during their life cycle. In particular, extreme events including earthquakes, typhoons, explosions, and traffic overloads can cause dramatic changes in the internal stress of the structure. Once the stress exceeds the tensile and compressive strength values ​​of the structure, it will inevitably lead to changes in the stress state of the structure. Excessive tensile / compressive stress will cause the structural performance to deteriorate and the bearing capacity to decrease. Therefore, accurate monitoring of the tensile and compressive stress of the structure is very important. As one of the most widely used civil engineering structures, concrete structures have been continuously invested in construction production and monitoring and maintenance. Especially in large-span and high-rise building infrastructures, the changes in stress in key parts of concrete components such as beams and columns are crucial to the overall structural safety. It is very important to develop reliable structural health monitoring (SHM) technology and deploy reasonable SHM systems for civil infrastructure to ensure structural safety and promote life cycle management.

[0003] In the past few decades, the research and application of local health monitoring of key components of main structures have been increasing through the use of intelligent sensors such as fiber optic sensors and piezoelectric sensors. Among them, the monitoring technology based on electromechanical impedance (EMI), that is, using piezoelectric ceramics (lead (Pb)-zirconate (Zr)-titanate (Ti); PZT) as sensors and actuators, has been gradually applied to the practice of concrete SHM technology in the past two decades. PZT sensors have high frequency stimulation, low cost and far-field immunity, and have high sensitivity to concrete strength development, load-induced distributed microcracks and cumulative impact damage. They also show potential advantages in the identification of compressive and tensile stresses. When PZT is coupled to the structure, the change in stress will cause the change in the dynamic stiffness of the PZT drive point, while the effects of tensile and compressive stresses on the dynamic stiffness of the structure are essentially opposite, so the effects on the piezoelectric admittance signal are completely different. In the EMI-based structural tensile and compressive stress identification technology, the selection of the optimal frequency range plays an important role in improving the sensitivity of tensile and compressive stress identification, because the incorrect frequency range will lead to incorrect stress detection results and provide false alarms.

[0004] At present, there are three main types of research on sensitive frequency bands in piezoresistive impedance technology. The first is an empirical method, which roughly determines the sensitive frequency band range by observing the resonance peak position of the admittance curve before and after the stress change; the second is a statistical method, such as segmenting and calculating the root mean square deviation (RMSD) of the sub-bands based on the two segments of the admittance curve measured before and after the stress change to determine the sensitive frequency band; the third is through artificial intelligence methods, such as using artificial neural networks to learn historical data to identify sensitive frequency bands, but it is necessary to build a complex network layer and a large amount of training data. The current research methods are mostly focused on the initial state and the destruction (damage) state, and cannot achieve continuous identification. In addition, the existing methods are only applicable to the selection of sensitive frequency bands for structural damage identification, and no research focuses on the selection of sensitive frequency bands for structural tensile and compressive stress. The change in structural dynamic stiffness caused by stress is completely different from the change in structural mechanical impedance caused by damage, resulting in different frequency bands for the admittance signal to be sensitive to stress. The existing methods can only distinguish the response sensitive frequency bands before and after structural damage, and cannot distinguish the selection of sensitive signal frequency bands caused by tensile and compressive stress. Therefore, it is urgent to propose a stress-sensitive impedance spectrum frequency band automatic selection method.

[0005] Therefore, it is necessary to establish a simple and effective selection method that can cover the entire process of stress change of the stress structure to be identified, and determine the sensitive frequency band range in the electrical impedance measurement during the monitoring period of the stress structure to be identified. Summary of the invention

[0006] In view of the above defects or improvement needs of the prior art, the present invention provides a method and device for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data, which aims to realize the identification of tensile and compressive stress sensitive frequency bands during the entire monitoring period of the entire stress failure process of the stress structure to be identified.

[0007] To achieve the above object, according to one aspect of the present invention, a method for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data is provided, comprising:

[0008] S1. Collect the admittance value of the stress structure to be identified under different sweep frequencies and loads;

[0009] S2. Set the sensitive frequency band segmentation step to segment the frequency sweep range, and use the standard deviation as the sensitivity index to calculate the sensitivity of all sub-frequency bands obtained by segmentation;

[0010] S3. Select the sub-frequency band with the greatest sensitivity as the tensile and compressive stress sensitive frequency band.

[0011] Furthermore, the standard deviation of the admittance value within the sub-band sweep frequency range is used as the sensitivity index of the sub-band:

[0012]

[0013]

[0014] Among them, S k represents the sensitivity of the kth sub-band, n is the number of frequencies in the sub-band, represents the standard deviation of the admittance value of the structure to be stress identified under a fixed sweep frequency and different load responses; x ij refers to the admittance value at the i-th frequency and the j-th load response; q refers to the total number of load conditions, Refers to the admittance value x of all responses i1 , x i2 , …, x ij The mean of .

[0015] Furthermore, the sensitive frequency band segmentation step size is set to 50kHz.

[0016] The present invention also provides a system for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data, comprising: a computer-readable storage medium and a processor; the computer-readable storage medium is used to store executable instructions; the processor is used to read the executable instructions stored in the computer-readable storage medium and execute the above-mentioned method for identifying structural tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data.

[0017] According to another aspect of the present invention, a device for identifying a tensile and compressive stress sensitive frequency band based on piezoresistive impedance data is provided, comprising:

[0018] A data acquisition module is used to collect the admittance value of the stress structure to be identified under different sweep frequencies and loads;

[0019] The sub-band sensitivity calculation module is used to set the sensitive frequency band segmentation step to segment the frequency sweep range, and calculate the sensitivity of all sub-bands obtained by segmentation using the standard deviation as the sensitivity index;

[0020] The result output module is used to select the sub-frequency band with the greatest sensitivity as the sensitive frequency band of structural tensile and compressive stress.

[0021] Furthermore, the sub-band sensitivity calculation module uses the standard deviation of the admittance value within the sub-band sweep frequency range as the sensitivity index of the sub-band:

[0022]

[0023]

[0024] Among them, S k represents the sensitivity of the kth sub-band, n is the number of frequencies in the sub-band, represents the standard deviation of the admittance value of the structure to be stress identified under a fixed sweep frequency and different load responses; x ij refers to the admittance value at the i-th frequency and the j-th load response; q refers to the total number of load conditions, Refers to the admittance value x of all responses i1 , x i2 , …, x ij The mean of .

[0025] Furthermore, the sensitive frequency band segmentation step size is set to 50kHz.

[0026] In general, compared with the prior art, the above technical solution conceived by the present invention can achieve the following beneficial effects.

[0027] (1) The method provided by the present invention uses a PZT sensor to measure the electrical impedance spectrum of the structure to be identified from the initial state to the load-damaged state, and adopts a sensitivity analysis method based on standard deviation. It can quickly identify two different stress-sensitive frequency bands of structural tension and compression that are suitable for the entire health monitoring cycle from the piezoelectric impedance spectrum reflecting the stress change of the stress structure to be identified.

[0028] (2) Compared with artificial intelligence and other methods that require the construction of complex computing models, the computing method proposed in the present invention is easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of the process of identifying the sensitive frequency band of structural tensile and compressive stresses based on the standard deviation method of the present invention;

[0030] Figure 2 It is a schematic diagram of the installation of the measuring specimen and the sensor according to the example of the present invention;

[0031] Figure 3 It is the admittance line diagram of PZT1 under the loading condition of this paper under the pressure of the measured specimen;

[0032] Figure 4 It is the admittance line diagram of PZT2 under the loading condition of this paper under the pressure of the measured specimen;

[0033] Figure 5 It is a line graph of the PZT1 sensitivity calculation results of the measured specimen in each frequency band;

[0034] Figure 6 It is a line graph of the PZT2 sensitivity calculation results of the measured specimen in each frequency band;

[0035] Figure 7 It is a schematic diagram of the position of the PZT1 compressive stress sensitive frequency band of the measured specimen in the frequency-by-frequency admittance value standard deviation curve;

[0036] Figure 8It is a schematic diagram of the position of the PZT2 tensile stress sensitive frequency band of the measured specimen in the frequency-by-frequency admittance value standard deviation curve;

[0037] Fig. 9 It is a schematic diagram of the position of the PZT1 compressive stress sensitive frequency band of the measured specimen in the piezoresistive impedance data;

[0038] Fig.10 This is a partial enlargement of the PZT1 compressive stress sensitive frequency band of the test specimen;

[0039] Fig.11 It is a schematic diagram of the location of the PZT2 tensile stress sensitive frequency band of the measured specimen in the piezoresistive impedance data;

[0040] Fig.12 It is a local enlarged diagram of the PZT2 tensile stress sensitive frequency band of the measured specimen. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0042] The structural tensile and compressive stress sensitive frequency band identification method for piezoelectric impedance data provided by the present invention is used for electrical impedance spectrum analysis of the entire process from the initial state to the loaded failure state of the stress structure to be identified. In this example, the stress structure to be identified is subjected to two conventional loads, tension and pressure, and the electrical impedance spectrum of the structure to be identified from the initial state to the loaded failure state is measured by a PZT sensor.

[0043] Figure 1 FIG. 1 is a schematic diagram of a sensitive frequency band identification process based on standard deviation, which includes the following steps:

[0044] (1) Collect the admittance value of the stress structure to be identified under different sweep frequencies and loads;

[0045] (2) Setting the length of the sensitive frequency band, dividing the sweep frequency range into segments, and calculating the sensitivity of all sub-bands;

[0046] The present invention adopts a sensitivity analysis method based on standard deviation to calculate the standard deviation of the admittance value of the stress structure to be identified under different sweep frequencies and loads, and uses the standard deviation of the admittance value within the sweep frequency range of the sub-band as the sensitivity index of the sub-band. The total number of sub-bands obtained by segmentation is recorded as m, the number of frequencies in the sub-band is n, and the calculation formula of the standard deviation is as follows:

[0047]

[0048]

[0049] Among them, x ij Refers to the admittance value at the i-th frequency and the j-th load response; Refers to the admittance value x of all responses i1 , x i2 , …, x ij The mean value of; q refers to the total number of load cases; S represents the standard deviation of the admittance value of the structure to be stress identified under a fixed sweep frequency and different load responses; k Indicates the sensitivity of the kth sub-band.

[0050] (3) Select the sub-frequency band with the highest sensitivity as the sensitive frequency band of structural tensile and compressive stress.

[0051] In the implementation example, the experimental specimen is a four-point bending reinforced concrete beam, the length, width and height of the reinforced concrete beam are 2m, 0.15m and 0.22m respectively. Figure 2 As shown. The top longitudinally has two threaded steel bars with a diameter and strength of 12mm and 335MPa, respectively, and the bottom longitudinally has two threaded steel bars with a diameter and strength of 8mm and 235MPa, respectively. Prestressed steel strands are set at the bottom of the beam, with a nominal diameter of 15.2mm and a strength of 1830MPa. Two PZT sheets are respectively pasted to the mid-span of the beam and distributed along the height of the section. PZT1 and PZT2 are 82.5mm above and below the neutral axis, respectively, to measure the real part data of the electromechanical coupling impedance under compressive stress and tensile stress of the component. An impedance analyzer was used to measure the admittance signals of PZT under loads of 0kN, 2kN, 6kN, 10kN, 20kN, 30kN, 40kN, 45kN, 50kN, 60kN, 70kN, 80kN, 90kN, 100kN, 110kN, 120kN, 130kN, 140kN, 150kN and 160kN.

[0052] The real part data of the electromechanical coupling impedance in the test frequency band of 0.04kHz to 300kHz were selected as the acquisition characterization information. The step size was set to 375Hz. The electromechanical coupling impedance of PZT under loads of 0kN, 2kN, 6kN, 10kN, 20kN, 30kN, 40kN, 45kN, 50kN, 60kN, 70kN, 80kN, 90kN, 100kN, 110kN, 120kN, 130kN, 140kN, 150kN and 160kN was measured respectively. The results are shown in Figure 2. Figure 3 and Figure 4 shown.

[0053] For the same PZT, a total of 801 sets of data were obtained in the actual measurement process. The sub-band length was set to 50kHz, corresponding to about 134 sets of continuous samples, and the total number of sub-bands divided was 668. The sensitivity of each sub-band was calculated, and the band with the highest sensitivity was selected.

[0054] The sensitivity results of all sub-bands of PZT1 and PZT2 are shown in Figure 5 and Figure 6 shown. Figure 5 The results show that under loading conditions, the sensitivity index of the 460th sub-band of PZT1 is the highest, reaching 0.0069, and the sweep frequency range of the 460th sub-band is 172.142kHz to 222.010kHz; Figure 6 The results show that under the loading conditions of this paper, the sensitivity index of the 431st sub-band of PZT2 is the highest, reaching 0.0200, and the sweep frequency range of the 431st sub-band is 161.269kHz~211.137kHz. Regarding the calculation results of the sub-band sweep frequency range, considering the convenience of image display, Figure 5 , Figure 6 , Figure 7 , Figure 8 , Fig. 9 , Fig.10 , Fig.11 and Fig.12 When displayed in the table, all values ​​are rounded to the integer.

[0055] Figure 7 and Figure 8 The PZT1 sensitive band for identifying compressive stress and the PZT2 sensitive band for identifying tensile stress are at all frequency sensitivity positions, from Figure 7 and Figure 8 From the results, it can be found that the compressive stress sensitive frequency band is completely different from the tensile stress sensitive frequency band. The selected compressive stress sensitive frequency band is 172-222kHz, while the tensile stress sensitive frequency band is 161-211kHz. Fig. 9 and Fig.11 The positions of the tensile and compressive stress sensitive frequency bands of PZT1 and PZT2 of the stress structure to be identified in the spectrum curve of the whole monitoring process are shown in the figure. Fig.10 and Fig.12 They are respectively partial enlarged schematic diagrams of the tensile and compressive stress sensitive frequency bands of PZT1 and PZT2 of the stress structure to be identified. From the results in the figure, it can be found that the sweep frequency range corresponding to the tensile and compressive stress sensitive frequency bands contains the densest resonant peaks of the admittance value changes under loading conditions. The area with the densest resonant peaks happens to be the key area reflecting the changes in the dynamic characteristics of the structure, which is the main basis for the identification of tensile and compressive stresses in the practice of EMI-based SHM technology, indicating that the calculation results of the present invention are accurate and effective.

[0056] It can be seen from this that the tensile and compressive stress sensitive frequency band identification method for piezoresistive impedance data provided by the present invention can select the two stress sensitive frequency bands of tension and compression, and can realize the piezoresistive impedance spectrum analysis of the stress structure to be identified from the initial state to the entire process of loading and destruction. The implementation process is concise and can accurately identify the tensile and compressive stress sensitive frequency bands in the entire monitoring period, which is expected to promote the development of EMI-based SHM technology.

[0057] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data, characterized in that: include: S1. Collect the admittance value of the tensile and compressive stress structure to be identified under different sweep frequencies and loads; S2. Set the sensitive frequency band segmentation step to segment the frequency sweep range, and use the standard deviation as the sensitivity index to calculate the sensitivity of all sub-frequency bands obtained by segmentation; use the standard deviation of the admittance value within the sub-frequency band sweep frequency range as the sensitivity index of the sub-frequency band: Among them, S k represents the sensitivity of the kth sub-band, n is the number of frequencies in the sub-band, represents the standard deviation of the admittance value of the tensile and compressive stress structure to be identified under a fixed sweep frequency and different load responses; x ij refers to the admittance value at the i-th frequency and the j-th load response; q refers to the total number of load conditions, Refers to the admittance value x of all responses i1 , x i2 , …, x ij The mean of S3. Select the sub-frequency band with the greatest sensitivity as the tensile and compressive stress sensitive frequency band.

2. According to claim 1, a method for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data is characterized in that: The sensitive frequency band segmentation step is set to 50kHz.

3. A system for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data, characterized in that: include: A computer readable storage medium and a processor; The computer-readable storage medium is used to store executable instructions; The processor is used to read the executable instructions stored in the computer-readable storage medium to execute the tensile and compressive stress sensitive frequency band identification method based on piezoresistive impedance data according to claim 1 or 2.

4. A device for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data, characterized in that: include: A data acquisition module is used to collect the admittance values ​​of the tensile and compressive stress structures to be identified under different sweep frequencies and loads; The sub-band sensitivity calculation module is used to set the sensitive frequency band segmentation step to segment the frequency sweep range, and use the standard deviation as the sensitivity index to calculate the sensitivity of all sub-bands obtained by segmentation; the sub-band sensitivity calculation module uses the standard deviation of the admittance value within the sub-band frequency sweep range as the sensitivity index of the sub-band: Among them, S k represents the sensitivity of the kth sub-band, n is the number of frequencies in the sub-band, represents the standard deviation of the admittance value of the structure to be stress identified under a fixed sweep frequency and different load responses; x ij refers to the admittance value at the i-th frequency and the j-th load response; q refers to the total number of load conditions, Refers to the admittance value x of all responses i1 , x i2 , …, x ij The mean of The result output module is used to select the sub-frequency band with the greatest sensitivity as the tensile and compressive stress sensitive frequency band.

5. The device for identifying tensile and compressive stress sensitive frequency bands based on piezoresistive impedance data according to claim 4, characterized in that: The sensitive frequency band segmentation step size is set to 50kHz.

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