Bending fatigue damage detection method for reinforced concrete beams used in waste incineration power generation

Abstract

The present application relates to the technical field of concrete acoustic wave detection, and specifically to a method for detecting bending fatigue damage of reinforced concrete beams used for waste incineration power generation, the method comprising: obtaining discrete acoustic emission signals at various positions on the reinforced concrete beam during waste incineration power generation; obtaining the crack damage intensity value of each discrete acoustic emission signal according to the numerical fluctuation of each discrete acoustic emission signal and the local numerical fluctuation and clustering of all peak values; obtaining the damage difference index between adjacent positions according to the difference in the acoustic emission discrete signals and their crack damage intensity values ​​at adjacent positions on the reinforced concrete beam; obtaining the bending fatigue damage detection result of the reinforced concrete beam according to the numerical distribution of the damage difference index between all adjacent positions on the reinforced concrete beam. The present application can improve the accuracy of bending fatigue damage detection of reinforced concrete beams.

Description

Technical Field

[0001] The present application relates to the technical field of concrete acoustic wave detection, and in particular to a method for detecting bending fatigue damage of reinforced concrete beams used for waste incineration power generation. Background Art

[0002] Waste incineration power generation is a technology that converts the heat energy generated by the burning of waste into electrical energy. It can not only reduce the amount of landfill, but also achieve energy reuse. However, the ambient temperature generated during the waste incineration process will affect the surrounding structures through conduction, convection, etc. Long-term high temperature environment will cause the performance of concrete and steel bars to change, rapidly age and become damaged.

[0003] The existing detection method for bending fatigue damage of reinforced concrete beams is usually carried out in a non-destructive manner. The commonly used acoustic wave detection technology determines whether the reinforced concrete beam is damaged by receiving the stress wave changes generated by the structural changes inside the reinforced concrete beam. However, when analyzing the collected acoustic emission signals, the stress changes caused by slight scratches and cracks on the concrete beam are ignored, which affects the intensity of the acoustic emission signal. As a result, the signal feature analysis is relatively limited, and the degree of damage to the reinforced concrete beam cannot be fully evaluated, resulting in poor accuracy in the detection of bending fatigue damage of reinforced concrete beams. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a bending fatigue damage detection method for reinforced concrete beams used for waste incineration power generation to solve the existing problems.

[0005] The bending fatigue damage detection method of reinforced concrete beams for waste incineration power generation in this application adopts the following technical solutions:

[0006] An embodiment of the present application provides a method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation, the method comprising the following steps:

[0007] S1, obtain the discrete acoustic emission signals at various locations on the reinforced concrete beam during waste incineration power generation;

[0008] S2, according to the numerical fluctuation of each acoustic emission discrete signal and the local numerical fluctuation of all peak values, the crack confidence of each peak value is obtained;

[0009] S3, obtaining the crack damage intensity value of each acoustic emission discrete signal according to the numerical clustering of the crack confidence of all peak values ​​in each acoustic emission discrete signal;

[0010] S4, according to the difference of acoustic emission discrete signals and crack damage intensity values ​​at adjacent positions on the reinforced concrete beam, the damage difference index between adjacent positions is obtained;

[0011] S5, according to the numerical distribution of the damage difference index between all adjacent positions on the reinforced concrete beam, the damage assessment index of the reinforced concrete beam is obtained; according to the damage assessment index of the reinforced concrete beam, the bending fatigue damage detection result of the reinforced concrete beam is obtained.

[0012] Furthermore, the method for obtaining the crack confidence of each peak value includes:

[0013] For each acoustic emission discrete signal, the peak significance index of each peak is obtained according to the position and value distribution of all peaks of the acoustic emission discrete signal;

[0014] The coefficient of variation of all data in a preset window centered on each peak is calculated; the crack confidence of each peak is obtained according to the coefficient of variation and the peak significance index of each peak; the coefficient of variation and the peak significance index of each peak are both positively correlated with the crack confidence of each peak.

[0015] Further, the peak significance index of each peak is obtained according to the position and value distribution of all peaks of the acoustic emission discrete signal, including:

[0016] Obtaining the maximum value and the mean value of each acoustic emission discrete signal, and recording the difference between the maximum value and the mean value as the maximum difference value of each acoustic emission discrete signal;

[0017] The ratio of each peak value of the acoustic emission discrete signal to the maximum value is calculated, which is recorded as the amplitude proportion of each peak value; the mean of the time difference between each peak value and other peak values ​​is obtained, which is recorded as the distribution discrete value of each peak value; according to the amplitude proportion, distribution discrete value and maximum difference value of each peak value in the acoustic emission discrete signal, the peak significance index of each peak value is obtained.

[0018] Further, the peak significance index of each peak is obtained according to the amplitude proportion, distribution discrete value and maximum difference value of each peak in the acoustic emission discrete signal, including: recording the peak significance index of the i-th peak as , ; In the formula, is the peak significance index of the i-th peak; B is the maximum difference value; is the amplitude proportion of the i-th peak; is the distribution discrete value of the i-th peak.

[0019] Furthermore, the crack damage intensity value of each acoustic emission discrete signal is obtained according to the numerical clustering of the crack confidence of all peak values ​​in each acoustic emission discrete signal, including:

[0020] The crack confidences of all peak values ​​in each acoustic emission discrete signal are clustered to obtain each cluster; the mean of all elements in each cluster is calculated and recorded as the first mean; the difference between the maximum and minimum values ​​of the first mean of all clusters is recorded as the overall difference; the cluster with the largest first mean is recorded as the crack feature cluster; the crack feature strength is obtained according to the numerical distribution and overall difference of all elements in the crack feature cluster;

[0021] The crack damage intensity value of each acoustic emission discrete signal is obtained according to the crack characteristic intensity and the number of elements in the crack characteristic cluster.

[0022] Furthermore, the method for obtaining the crack characteristic strength includes: calculating the variance of all elements in the crack characteristic cluster; and taking the sum of the variance and the overall difference as the crack characteristic strength.

[0023] Furthermore, the method of obtaining the crack damage intensity value of each acoustic emission discrete signal according to the crack characteristic intensity and the number of elements in the crack characteristic cluster includes: calculating the ratio of the number of elements in the crack characteristic cluster to the number of all peak values, recorded as the crack proportion; and taking the ratio of the crack characteristic intensity to the crack proportion as the crack damage intensity value of each acoustic emission discrete signal.

[0024] Furthermore, the method for obtaining the damage difference index between adjacent positions includes:

[0025] For the acoustic emission discrete signals at any two adjacent positions on the reinforced concrete beam, the difference between the acoustic emission discrete signals at the two adjacent positions is calculated, which is recorded as the first difference; the difference in crack damage intensity values ​​of the acoustic emission discrete signals at the two adjacent positions is obtained, which is recorded as the second difference; and the product of the first difference and the second difference is recorded as the damage difference index between the two adjacent positions.

[0026] Furthermore, the method for obtaining the damage assessment index of the reinforced concrete beam comprises:

[0027] The mean and variance of the damage difference index between all adjacent positions on the reinforced concrete beam are calculated and recorded as the first mean and the first variance, respectively; the product of the first mean and the first variance is used as the damage assessment index of the reinforced concrete beam.

[0028] Furthermore, the bending fatigue damage detection result of the reinforced concrete beam is obtained according to the damage assessment index of the reinforced concrete beam, including: if the normalized value of the damage assessment index is greater than a preset damage threshold, the reinforced concrete beam has bending fatigue damage; otherwise, the working condition of the reinforced concrete beam is normal.

[0029] This application has at least the following beneficial effects:

[0030] The present application analyzes the amplitude variation characteristics of the acoustic emission signal, evaluates the significance of each peak signal, and then constructs a crack confidence by combining the local characteristics of each peak to evaluate the possibility of the existence of cracks; further, the crack characteristics of the bending fatigue damage process of the reinforced concrete beam are analyzed, and the crack damage intensity value is constructed by the crack confidence and the crack state at different times, so as to achieve a preliminary evaluation of the damage degree of the reinforced concrete beam; finally, the influence of the change in the intensity of the acoustic emission signal collected by the acoustic emission sensor at different positions on the damage assessment of the reinforced concrete beam is analyzed, and a damage difference index between each acoustic emission discrete signal is constructed, and the influence of the crack position is comprehensively considered to obtain the damage assessment index of the reinforced concrete beam to achieve a comprehensive detection of the damage of the reinforced concrete beam; the present application takes into account that the different crack positions will cause differences in the intensity of each acoustic emission signal, and realizes the evaluation of the difference in the intensity of all acoustic emission signals, and comprehensively considers the influence of the slight scratches on the concrete beam and the stress changes caused by the cracks on the acoustic emission signal intensity, thereby improving the detection accuracy of the bending damage of the reinforced concrete beam. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 A flowchart of the steps of the method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation provided in this application;

[0033] Figure 2 A schematic diagram of peak detection of a discrete acoustic emission signal provided by an embodiment of the present application;

[0034] Figure 3 A block diagram for obtaining crack confidence provided in one embodiment of the present application. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0036] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0037] The specific scheme of the bending fatigue damage detection method of reinforced concrete beams for waste incineration power generation provided by the present application is described in detail below with reference to the accompanying drawings.

[0038] An embodiment of the present application provides a method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation. Specifically, the following method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation is provided. Figure 1 , the method comprises the following steps:

[0039] S1, obtain the discrete acoustic emission signals at various locations on the reinforced concrete beam during waste incineration power generation.

[0040] A specific scenario of the embodiment of the present application is the bending fatigue damage detection scenario of reinforced concrete beams; bending fatigue damage is a process in which materials gradually accumulate and eventually cause material damage under the action of alternating stress, especially bending stress. During the waste incineration process, a long period of high temperature environment will cause changes in the properties of concrete and steel bars, rapid aging and damage. Therefore, in order to ensure the service life of reinforced concrete beams, it is necessary to use acoustic wave detection technology to receive the stress waves generated by bending fatigue damage inside reinforced concrete beams and locate the damage position.

[0041] This embodiment uses acoustic emission sensors to detect reinforced concrete beams near the incinerator when waste is incinerated for power generation. Specifically, x=5 acoustic emission sensors are arranged at equal distances on the entire reinforced concrete beam. Among them, the acoustic emission sensors all have built-in amplifiers to increase the signal strength; the coupling agent is vacuum silicone grease to ensure the smooth propagation of the acoustic emission signal. The data acquisition frequency is 1MHz, and the threshold is 45dB; it should be noted that each acoustic emission sensor will collect an acoustic emission signal.

[0042] After the acoustic emission signal is obtained, the acoustic emission signal collected by each sensor is denoised by the wavelet denoising algorithm, and then the amplitude of each acoustic emission signal at each moment is obtained by the parameter analysis method, and the continuous signal data is converted into discrete numerical data at a time interval of 1us, and x acoustic emission discrete signals are obtained by arranging them in the order of the collected time. In order to eliminate the dimension between the data, all acoustic emission discrete signals are normalized by Z-score to complete the preprocessing of the data. Wavelet denoising, parameter analysis, and Z-score normalization algorithm are well-known technologies and will not be repeated here.

[0043] In the bending fatigue damage detection process of reinforced concrete beams, the process of cracks generated during the bending process of reinforced concrete beams will affect the intensity of the acoustic wave signal. Therefore, this embodiment comprehensively evaluates the bending fatigue damage degree of reinforced concrete beams by analyzing the differences between the acoustic emission discrete signals at different positions and comprehensively considering the crack factor.

[0044] S2: According to the numerical fluctuation of each acoustic emission discrete signal and the local numerical fluctuation of all peak values, the crack confidence of each peak value is obtained.

[0045] By analyzing the influence of bending fatigue damage on reinforced concrete beams, it is found that when reinforced concrete beams are subjected to bending damage, cracks will be generated, and the size and number of cracks are closely related to the severity of the bending damage. If the cracks are relatively small and few, although the amplitude of the acoustic emission signal at the fine cracks will suddenly increase, the increase is limited, and the health of the reinforced concrete beam is still good at this time; if the bending damage of the reinforced concrete beam is serious and a large number of significant cracks appear, the same acoustic emission discrete signal of the collected acoustic emission signal will have multiple peaks. Since the sizes of the cracks are different, the peaks in the same acoustic emission discrete signal will also have large differences, and the number of peaks in the same acoustic emission discrete signal is large, which indicates that the bending fatigue damage of the reinforced concrete beam is large.

[0046] In summary, when the degree of bending damage is greater, the number of cracks inside or on the surface of the reinforced concrete beam is greater, and in the most severely damaged area, the cracks are more significant and denser. This embodiment characterizes the degree of cracks based on the peak characteristics of the acoustic emission discrete signal.

[0047] First, the AMPD peak search algorithm is used to process each acoustic emission discrete signal to obtain all the peaks in each acoustic emission discrete signal. Figure 2 As shown, the horizontal axis is the position order of the elements in the acoustic emission discrete signal, the vertical axis is the normalized amplitude of the elements, a1 is the acoustic emission discrete signal, a2 is the detected peak value, and the AMPD peak search algorithm is a well-known technology and will not be described here. The maximum value and mean value of each acoustic emission discrete signal are obtained, and the difference between the maximum value and the mean value is recorded as the maximum difference value of each acoustic emission discrete signal;

[0048] For each acoustic emission discrete signal, calculate the ratio of each peak value of the acoustic emission discrete signal to the maximum value, and record it as the amplitude proportion of each peak value; obtain the mean value of the time difference between each peak value and other peak values, and record it as the distribution discrete value of each peak value; according to the amplitude proportion, distribution discrete value and maximum difference value of each peak value in the acoustic emission discrete signal, obtain the peak significance index of each peak value;

[0049] The peak significance index of each peak is obtained by recording the peak significance index of the i-th peak as , ; In the formula, is the peak significance index of the i-th peak; B is the maximum difference value; is the amplitude proportion of the i-th peak; is the distribution discrete value of the i-th peak.

[0050] It can be understood that, in this embodiment, the difference between two numerical values ​​represents the calculation of the absolute value of the difference between the two numerical values.

[0051] If the maximum difference value is larger, it means that the difference between the maximum peak and the average acoustic emission signal amplitude is more significant, and the possibility of crack existence is greater; if the amplitude proportion of the i-th peak is larger, it means that the i-th peak is significantly larger than all peaks; the smaller the distribution discrete value is, the smaller the distance between the i-th peak position and other peak positions is, and the more dense the peaks are, then the peak significance index of the i-th peak is The larger it is, the greater the possibility that the acoustic emission signal will scan a crack at the i-th peak moment.

[0052] Furthermore, the coefficient of variation of all data in a preset window centered on each peak is calculated; wherein, in this embodiment, the length of the window is 9. The crack confidence of each peak is obtained according to the coefficient of variation and the peak significance index of each peak; the coefficient of variation and the peak significance index of each peak are both positively correlated with the crack confidence of each peak.

[0053] It should be noted that a positive correlation means that there is a same-direction change relationship between the independent variable and the dependent variable, where the larger the independent variable, the larger the dependent variable; the specific form of the positive correlation is determined by actual application and this application does not impose any special restrictions.

[0054] In this embodiment, the product of the coefficient of variation and the peak significance index of each peak is used as the crack confidence of each peak. As another embodiment of the present application, the sum of the coefficient of variation and the peak significance index of each peak can be calculated as the crack confidence of each peak.

[0055] If the peak significance index and coefficient of variation of the peak are larger, it means that the signal amplitude corresponding to the peak point is not only significant, but also has high volatility in the local range. Therefore, the greater the crack confidence corresponding to the peak value, the greater the possibility that the acoustic emission signal will scan a significant crack at the peak moment.

[0056] It should be noted that: when the center of the window is near the two ends of the acoustic emission discrete signal, causing the window to exceed the sequence range, the excess part of the window is filled using the mean filling method; the coefficient of variation can indicate the degree of fluctuation of the acoustic emission signal amplitude near each peak point.

[0057] The block diagram for obtaining crack confidence is as follows: Figure 3 shown.

[0058] S3, obtaining the crack damage intensity value of each acoustic emission discrete signal according to the numerical clustering of the crack confidence of all peak values ​​in each acoustic emission discrete signal.

[0059] In order to further eliminate the interference of noise, extract the real cracks, and preliminarily evaluate the bending damage degree of reinforced concrete beams according to the crack status at different times. Cluster the crack confidence of all peaks in each acoustic emission discrete signal to obtain each cluster; calculate the mean of all elements in each cluster, record it as the first mean; record the difference between the maximum and minimum values ​​of the first mean of all clusters as the overall difference; record the cluster with the largest first mean as the crack feature cluster; obtain the crack feature strength according to the numerical distribution and overall difference of all elements in the crack feature cluster;

[0060] Calculate the variance of all elements in the crack feature cluster; take the sum of the variance and the overall difference as the crack feature strength;

[0061] The crack damage intensity value of each acoustic emission discrete signal is obtained according to the crack characteristic intensity and the number of elements in the crack characteristic cluster;

[0062] The calculation of the crack damage intensity value includes: calculating the ratio of the number of elements in the crack characteristic cluster to the number of all peaks, recorded as the crack proportion; and taking the ratio of the crack characteristic intensity to the crack proportion as the crack damage intensity value of each acoustic emission discrete signal.

[0063] In this embodiment, the crack confidence of all peak values ​​is used as the input of the K-means clustering algorithm, the number of clusters is set to 2, and the output of the algorithm is two clusters. The K-means clustering algorithm is a well-known technology and will not be described here. As other embodiments of the present application, a density clustering algorithm may be used, and the present application does not limit it.

[0064] The larger the variance of all elements in the crack feature cluster, the greater the difference between the confidence levels of each peak crack in the crack feature cluster, which is consistent with the characteristics of inconsistent damage of each crack; if the overall difference is larger, it means that the difference between the crack feature cluster and other signal peaks is larger, and the damage degree is higher; if the crack proportion is smaller, it means that the number of elements in the crack feature cluster accounts for a larger proportion of all peaks, which means that the more cracks there are, the greater the crack damage intensity value is, indicating that the crack damage degree caused by the bending damage of the reinforced concrete beam is higher, thus achieving a preliminary assessment of the bending damage degree in the reinforced concrete beam.

[0065] S4, according to the difference of the acoustic emission discrete signals and crack damage intensity values ​​at adjacent positions on the reinforced concrete beam, the damage difference index between adjacent positions is obtained.

[0066] Due to the different crack locations in the reinforced concrete beam, the intensity of the acoustic emission signal collected by the acoustic emission sensors at different locations will change. Therefore, the degree of damage to the reinforced concrete beam can be evaluated by calculating the consistency between the data obtained by each sensor.

[0067] Specifically, for the acoustic emission discrete signals at any two adjacent positions on the reinforced concrete beam, the difference between the acoustic emission discrete signals at the two adjacent positions is calculated, which is recorded as the first difference; the difference in crack damage intensity values ​​of the acoustic emission discrete signals at the two adjacent positions is obtained, which is recorded as the second difference; and the product of the first difference and the second difference is recorded as the damage difference index between the acoustic emission discrete signals at the two adjacent positions.

[0068] It should be noted that the present embodiment uses the DTW distance to represent the difference between two discrete signals. As other embodiments of the present application, the inverse normalized value of the cosine similarity may be used, and the present application does not limit this.

[0069] If the damage degree of the reinforced concrete beam is very small or there is no damage, the signal difference between adjacent positions represented by the first difference is small, and the difference in crack damage intensity values ​​of the acoustic emission discrete signals at adjacent positions represented by the second difference is small, so the damage difference index is small; if the reinforced concrete beam is seriously damaged, due to the different crack positions, the intensity difference of the acoustic emission signals obtained by the sensor at different positions will be large, and the difference between the crack damage intensity values ​​of each acoustic emission discrete signal is generally large, so the damage difference index is large.

[0070] S5, according to the numerical distribution of the damage difference index between all adjacent positions on the reinforced concrete beam, the damage assessment index of the reinforced concrete beam is obtained; according to the damage assessment index of the reinforced concrete beam, the bending fatigue damage detection result of the reinforced concrete beam is obtained.

[0071] In order to further comprehensively evaluate the bending fatigue damage status of reinforced concrete beams, the damage differences between all adjacent positions on the reinforced concrete beams are combined to determine the possibility of damage to the reinforced concrete beams.

[0072] Specifically, the mean and variance of the damage difference index between the discrete acoustic emission signals at all adjacent positions on the reinforced concrete beam are calculated and recorded as the first mean and the first variance, respectively; the product of the first mean and the first variance is used as the damage assessment index of the reinforced concrete beam.

[0073] Among them, the larger the mean, the greater the possibility of serious damage on the reinforced concrete beam; the larger the variance, the greater the difference in the intensity of the acoustic emission signals obtained by each sensor; therefore, the larger the damage index, the more serious the damage to the reinforced concrete beam; if the damage index is smaller, it means that the signals collected by each sensor are more consistent, and the crack damage intensity value of each acoustic emission discrete signal is smaller, it means that the possibility that the reinforced concrete beam is not damaged or the damage is small is greater.

[0074] The damage assessment index is normalized. If the normalized value of the damage assessment index is greater than the preset damage threshold, the reinforced concrete beam has bending fatigue damage; otherwise, the working condition of the reinforced concrete beam is normal.

[0075] If the normalized damage assessment index is greater than the preset damage threshold of 0.5, it means that the bending damage of the reinforced concrete beam is serious and it is necessary to maintain and repair the reinforced concrete beam in time to avoid danger; if the normalized damage assessment index is less than or equal to the preset damage threshold of 0.5, it means that the bending damage of the reinforced concrete beam is small or not damaged and is in good condition. A bending fatigue damage detection method for reinforced concrete beams used for waste incineration power generation has been realized.

[0076] Through the above description of the implementation method in combination with the accompanying drawings, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0077] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A method for detecting bending fatigue damage of reinforced concrete beams used for waste incineration power generation, characterized in that: The method comprises the following steps: S1, obtain the discrete acoustic emission signals at various locations on the reinforced concrete beam during waste incineration power generation; S2, according to the numerical fluctuation of each acoustic emission discrete signal and the local numerical fluctuation of all peak values, the crack confidence of each peak value is obtained; S3, obtaining the crack damage intensity value of each acoustic emission discrete signal according to the numerical clustering of the crack confidence of all peak values ​​in each acoustic emission discrete signal; S4, according to the difference of acoustic emission discrete signals and crack damage intensity values ​​at adjacent positions on the reinforced concrete beam, the damage difference index between adjacent positions is obtained; S5, obtaining a damage assessment index of the reinforced concrete beam according to the numerical distribution of the damage difference index between all adjacent positions on the reinforced concrete beam; obtaining a bending fatigue damage detection result of the reinforced concrete beam according to the damage assessment index of the reinforced concrete beam; The method for obtaining the crack confidence of each peak value includes: For each acoustic emission discrete signal, the peak significance index of each peak is obtained according to the position and value distribution of all peaks of the acoustic emission discrete signal; Calculate the coefficient of variation of all data in a preset window centered on each peak value; obtain the crack confidence of each peak value according to the coefficient of variation and the peak significance index of each peak value; the coefficient of variation and the peak significance index of each peak value are both positively correlated with the crack confidence of each peak value; The crack damage intensity value of each acoustic emission discrete signal is obtained according to the numerical clustering of the crack confidence of all peak values ​​in each acoustic emission discrete signal, including: The crack confidences of all peak values ​​in each acoustic emission discrete signal are clustered to obtain each cluster; the mean of all elements in each cluster is calculated and recorded as the first mean; the difference between the maximum and minimum values ​​of the first mean of all clusters is recorded as the overall difference; the cluster with the largest first mean is recorded as the crack feature cluster; the crack feature strength is obtained according to the numerical distribution and overall difference of all elements in the crack feature cluster; The crack damage intensity value of each acoustic emission discrete signal is obtained according to the crack characteristic intensity and the number of elements in the crack characteristic cluster; The method for obtaining the damage difference index between adjacent positions includes: For the acoustic emission discrete signals at any two adjacent positions on the reinforced concrete beam, the difference between the acoustic emission discrete signals at the two adjacent positions is calculated, which is recorded as the first difference; the difference in crack damage intensity values ​​of the acoustic emission discrete signals at the two adjacent positions is obtained, which is recorded as the second difference; and the product of the first difference and the second difference is recorded as the damage difference index between the two adjacent positions.

2. The method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation according to claim 1, characterized in that: The peak significance index of each peak is obtained according to the position and value distribution of all peaks of the acoustic emission discrete signal, including: Obtaining the maximum value and the mean value of each acoustic emission discrete signal, and recording the difference between the maximum value and the mean value as the maximum difference value of each acoustic emission discrete signal; The ratio of each peak value of the acoustic emission discrete signal to the maximum value is calculated, which is recorded as the amplitude proportion of each peak value; the mean of the time difference between each peak value and other peak values ​​is obtained, which is recorded as the distribution discrete value of each peak value; according to the amplitude proportion, distribution discrete value and maximum difference value of each peak value in the acoustic emission discrete signal, the peak significance index of each peak value is obtained.

3. The method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation according to claim 2, characterized in that: The peak significance index of each peak is obtained according to the amplitude proportion, distribution discrete value and maximum difference value of each peak in the acoustic emission discrete signal, including: recording the peak significance index of the i-th peak as , ; In the formula, is the peak significance index of the i-th peak; B is the maximum difference value; is the amplitude proportion of the i-th peak; is the distribution discrete value of the i-th peak.

4. The method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation according to claim 1, characterized in that: The method for obtaining the crack characteristic strength includes: calculating the variance of all elements in the crack characteristic cluster; and taking the sum of the variance and the overall difference as the crack characteristic strength.

5. The method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation according to claim 1, characterized in that: The method of obtaining the crack damage intensity value of each acoustic emission discrete signal according to the crack characteristic intensity and the number of elements in the crack characteristic cluster includes: calculating the ratio of the number of elements in the crack characteristic cluster to the number of all peak values, recorded as the crack proportion; and taking the ratio of the crack characteristic intensity to the crack proportion as the crack damage intensity value of each acoustic emission discrete signal.

6. The method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation according to claim 1, characterized in that: The method for obtaining the damage assessment index of the reinforced concrete beam comprises: The mean and variance of the damage difference index between all adjacent positions on the reinforced concrete beam are calculated and recorded as the first mean and the first variance, respectively; the product of the first mean and the first variance is used as the damage assessment index of the reinforced concrete beam.

7. The method for detecting bending fatigue damage of reinforced concrete beams for waste incineration power generation according to claim 1, characterized in that: The bending fatigue damage detection result of the reinforced concrete beam is obtained according to the damage assessment index of the reinforced concrete beam, including: if the normalized value of the damage assessment index is greater than a preset damage threshold, the reinforced concrete beam has bending fatigue damage; otherwise, the working condition of the reinforced concrete beam is normal.

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