A density detection method for steel tube concrete column used for waste incineration power generation

Abstract

The present application relates to the field of density detection technology, and specifically to a density detection method for steel tube concrete columns used for waste incineration power generation, the method comprising: obtaining ultrasonic signals at each measuring point in the steel tube concrete column at each time; determining the peak variation coefficient and frequency domain offset coefficient of each measuring point in each time period; obtaining the noise interference index of each time period of each measuring point; determining the effective information inclusion degree of each time period of each measuring point; determining the filter window size of each time period of each measuring point; using a filtering algorithm to denoise the ultrasonic signals of each time period of each measuring point, and obtaining a binary image of each measuring point through ultrasonic imaging technology to perform density detection on the steel tube concrete column. The present application can improve the denoising effect of ultrasonic signals and the accuracy of ultrasonic imaging of steel tube concrete columns, and improve the accuracy of density detection of steel tube concrete columns.

Description

Technical Field

[0001] The present application relates to the technical field of density detection, and in particular to a density detection method for steel tube concrete columns used for waste incineration power generation. Background Art

[0002] Steel tube concrete column is one of the most common concrete components and is widely used in various buildings. Since the concrete material will shrink during the solidification and hardening process, various defects will occur inside the steel tube concrete column. These defects often have a certain impact on the bearing capacity of the steel tube concrete column. Therefore, it is necessary to conduct density testing on the inside of the steel tube concrete column without damaging it. Therefore, non-destructive testing technology has gradually developed.

[0003] Ultrasonic testing is a modern physical technology. As a method of non-destructive testing, it is widely used in non-destructive testing of steel tube concrete columns because of its convenience, speed, low cost and no restrictions on the size and shape of concrete components. Finally, it is combined with the TR-MUSIC (Time Reversal-Multiple Signal Classification) algorithm for ultrasonic imaging to quickly obtain the defects in the steel tube concrete column. However, although this algorithm has high imaging resolution and fast calculation speed, it is highly sensitive to noise. In addition to the electrical noise generated by electromagnetic interference, vibration interference, and temperature interference in steel tube concrete columns, the concrete itself has a low density and large energy attenuation. It contains various sand and stone aggregates and impurities of different sizes, a complex structure, and low acoustic impedance. The matching degree between the air and the probe is poor, which will lead to strong reflection and diffraction of sound waves, further enhancing the interference of noise, resulting in low detection accuracy when non-destructive testing technology is used to detect the density of steel tube concrete columns. Therefore, in the process of denoising the ultrasonic signal of the steel tube concrete column using a filtering algorithm, if the filter window size is set too large, effective information may be lost, and if the filter window size is set too small, the denoising effect may be poor, which ultimately makes it difficult to distinguish between effective information and noise, thereby reducing the detection accuracy. Summary of the invention

[0004] In order to solve the above technical problems, a method for detecting the density of steel tube concrete columns used for waste incineration power generation is provided to solve the existing problems.

[0005] The solution to the technical problem of the present application is to provide a method for detecting the density of a steel tube concrete column for waste incineration power generation, comprising the following steps:

[0006] Obtain the ultrasonic signal at each measuring point in the steel tube concrete column at each time;

[0007] The ultrasonic signal of each measuring point at all times is divided into multiple time periods; according to the difference in the peak value of the ultrasonic signal in each time period of each measuring point and the difference in the interval time between the peaks, the peak change coefficient of each time period of each measuring point is determined;

[0008] Analyze the difference in the change of the ultrasonic signal in the frequency domain between different time periods, and determine the frequency domain offset coefficient of each time period of each measuring point; based on the peak change coefficient and the frequency domain offset coefficient, obtain the noise interference index of each time period of each measuring point;

[0009] According to the fluctuation difference of the ultrasonic signal in different time periods at each measuring point and the degree of confusion of the wave crest change of the ultrasonic signal, the effective information inclusion degree of each time period at each measuring point is determined;

[0010] Based on the noise interference index and the effective information inclusion degree, the filter window size of each time period of each measuring point is determined; a filtering algorithm is used to denoise the ultrasonic signal of each time period of each measuring point, and a binary image of each measuring point is obtained through ultrasonic imaging technology to perform density detection on the steel tube concrete column.

[0011] Preferably, determining the peak variation coefficient of each measuring point in each time period includes:

[0012] A peak detection algorithm is used to obtain all the peaks of the ultrasonic signal at all times in each time period of each measuring point, and the peaks are recorded as the signal peaks in each time period of each measuring point;

[0013] Calculate the time interval between each signal peak and the previous signal peak in each time period of each measuring point as the interval time length of each signal peak in each time period of each measuring point;

[0014] The variance of all signal peaks in each time period of each measuring point is calculated and recorded as the first variance; the product of the variance of the interval duration of all signal peaks in each time period of each measuring point and the first variance is used as the peak variation coefficient of each time period of each measuring point.

[0015] Preferably, determining the frequency domain offset coefficient of each time period of each measuring point includes:

[0016] Perform frequency domain analysis on the ultrasonic signals at all times in each time period of each measuring point to obtain the spectrum diagram of each time period of each measuring point;

[0017] A peak detection algorithm is used to obtain all peaks in the spectrum diagram, which are recorded as the amplitude peaks of each time period at each measuring point;

[0018] The frequency corresponding to the maximum value of all amplitude peaks in each time period of each measuring point is taken as the fundamental frequency of each time period of each measuring point;

[0019] Using an envelope extraction algorithm, the number of envelopes of the spectrum diagram in each time period of each measuring point is obtained;

[0020] The mean of the fundamental frequency differences between each time period of each measuring point and all other time periods is taken as the fundamental frequency difference of each time period of each measuring point;

[0021] The mean of the difference in the number of envelopes between each time period of each measuring point and all other time periods is taken as the difference in the number of envelopes of each time period of each measuring point;

[0022] The sum of the fundamental frequency difference and the envelope difference is used as the frequency domain offset coefficient of each time period of each measuring point.

[0023] Preferably, the noise interference index of each time period of each measuring point is the product of the peak variation coefficient and the frequency domain offset coefficient.

[0024] Preferably, the determining of the effective information inclusion degree of each time period of each measuring point includes:

[0025] Analyze the difference in the ultrasonic signal fluctuations between different time periods at each measuring point, as well as the difference in the corresponding amplitude of the envelope line in the spectrum diagram, and determine the consistency coefficient of each time period at each measuring point;

[0026] Calculate the information entropy of all signal peaks in each time period of each measuring point; take the sum of the variance of all amplitude peaks in each time period of each measuring point and the information entropy as the signal chaos degree in each time period of each measuring point;

[0027] The ratio of the consistency coefficient to the signal chaos is used as the effective information inclusion degree of each time period of each measuring point.

[0028] Preferably, determining the consistency coefficient of each time period of each measuring point includes:

[0029] The sum of the differences between the ultrasonic signals of each time period of each measuring point and all other time periods is taken as the signal fluctuation difference of each time period of each measuring point;

[0030] The maximum value of all envelope amplitudes in the spectrum diagram of each measuring point in each time period is taken as the maximum envelope amplitude of each measuring point in each time period;

[0031] The sum of the differences between the maximum envelope amplitudes of each time period of each measuring point and all other time periods is taken as the signal amplitude difference of each time period of each measuring point;

[0032] The reciprocal of the sum of the signal fluctuation difference and the signal amplitude difference is taken as the consistency coefficient of each time period of each measuring point.

[0033] Preferably, the filter window size of each time period of each measuring point is: ,in, For the The first The filter window size for each time period, For the The first The window adjustment factor for each time period, To preset the first threshold, To preset the second threshold, Indicates calculating the maximum value. is the ceiling function.

[0034] Preferably, the window adjustment factor is a normalized result of the ratio of the noise interference index to the effective information inclusion degree.

[0035] Preferably, obtaining a binary image of each measuring point includes:

[0036] The ultrasonic imaging algorithm is used to image the denoised ultrasonic signals in all time periods of each measuring point to obtain the ultrasonic topography of each measuring point;

[0037] The ultrasonic topography of each measuring point is binarized to obtain a binary image of each measuring point.

[0038] Preferably, the density test of the steel tube concrete column includes:

[0039] Match the binary image of each measuring point with the standard binary image obtained from the database to obtain the matching value of the binary image of each measuring point; obtain the segmentation threshold of the matching value of the binary image of all measuring points;

[0040] If the matching value is less than or equal to the segmentation threshold, the steel tube concrete column at the corresponding measuring point has defects; otherwise, the steel tube concrete column at the corresponding measuring point does not have defects.

[0041] This application has at least the following beneficial effects:

[0042] The present application determines the peak variation coefficient of each time period of each measuring point according to the difference variation of the peak value of the ultrasonic signal in each time period of each measuring point and the difference variation of the interval time between the peaks, analyzes the difference of the change of the ultrasonic signal in the frequency domain between different time periods, and determines the frequency domain offset coefficient of each time period of each measuring point; obtains the noise interference index of each time period of each measuring point, which has the beneficial effect of analyzing the difference of the peak variation of the ultrasonic signal and the difference of the peak variation in the spectrum diagram to reflect the difference degree of the peak fluctuation of the ultrasonic signal, and then reflects the situation of the ultrasonic signal being interfered by noise in each time period, so as to measure the strength of denoising the ultrasonic signal; determines the noise interference index of each time period of each measuring point according to the difference of the fluctuation of the ultrasonic signal in different time periods of each measuring point and the degree of confusion of the peak variation of the ultrasonic signal. The effective information inclusion rate of the time period has the beneficial effect of taking into account the effective information contained in the reflected signal generated during the collection of the ultrasonic signal, so as to subsequently determine the size of the filter window according to the amount of effective information contained, so as to avoid losing too much effective information; determine the filter window size of each time period of each measuring point; use a filtering algorithm to denoise the ultrasonic signal of each time period of each measuring point, and obtain a binary image of each measuring point through ultrasonic imaging technology, and perform density detection on the steel tube concrete column. The beneficial effect of this is that the interference of the ultrasonic signal and the amount of effective information contained are analyzed, and the filtering window of the filtering algorithm is adjusted, thereby improving the denoising effect of the ultrasonic signal and the accuracy of ultrasonic imaging of the steel tube concrete column while ensuring the effectiveness of the information, and improving the accuracy of the density detection of the steel tube concrete column. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The following is a further detailed description of a density detection method for steel tube concrete columns used for waste incineration power generation in the present application in conjunction with the accompanying drawings.

[0044] Figure 1 A flow chart of the steps of a method for detecting the density of a steel tube concrete column for waste incineration power generation provided in an embodiment of the present application;

[0045] Figure 2 A schematic diagram of probe placement in a phased array ultrasonic acquisition device provided in an embodiment of the present application;

[0046] Figure 3 A flowchart of the steps of a method for obtaining a frequency domain offset coefficient for each time period of each measuring point provided in an embodiment of the present application;

[0047] Figure 4 A flowchart of the steps of a method for obtaining the effective information inclusion degree of each time period at each measuring point provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of this application more clear, the following is a further detailed description of a density detection method of a steel tube concrete column for waste incineration power generation proposed in this application in combination with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0049] 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.

[0050] See also Figure 1 , which shows a flow chart of the steps of a method for detecting the density of a steel tube concrete column for waste incineration power generation provided by an embodiment of the present application, the method comprising the following steps:

[0051] Step 1: Obtain the ultrasonic signal of each measuring point in the steel tube concrete column at each time.

[0052] After the concrete pouring is completed and the interior of the steel tube concrete column is basically solidified, ultrasonic testing is performed on it to detect whether there are defects such as voids inside. Therefore, the ultrasonic echo signal of the steel tube concrete column is collected by the pair measurement method, and the grid points are arranged. When arranging the points, it is ensured that the measuring line is horizontal, the measuring points on the opposite surfaces of the front and back and the left and right are aligned, and the surface of the measuring points is flat and defect-free. The transmitting probe of the phased array ultrasonic acquisition equipment is placed on a measuring point at one end of a single side of the steel tube concrete column, and the receiving probe is placed on the other end of the measuring point at the corresponding position on the opposite side of the steel tube concrete column. The spacing between the measuring points is d, where the transmitting probe is used to transmit ultrasonic waves, and the frequency of the transmitted ultrasonic waves is , the ultrasonic wave passes through the steel tube concrete column and is received by the receiving probe at the other end. The frequency of the received ultrasonic wave is set to , the sampling time is Finally, the received ultrasonic signals are sorted in chronological order to obtain the ultrasonic signals of each measuring point at each moment.

[0053] In this embodiment, the probe placement diagram of the phased array ultrasonic acquisition device is as follows: Figure 2 As shown, for the steel tube concrete column ABCD-A1B1C1D1, a transmitting probe T is placed in each grid of the AA1DD1 surface, and a receiving probe R is placed in each grid of the BB1C1C surface opposite to the AA1D1D surface. Accordingly, a transmitting probe T is placed in each grid of the AA1B1B surface, and a receiving probe R is placed in each grid of the CC1DD1 surface opposite to the AA1B1B surface. Each receiving probe R serves as a measuring point.

[0054] Preferably, in this embodiment, the spacing between the measuring points is 100 mm, the frequency of the transmitted ultrasonic wave is 50 MHz, the frequency of the received ultrasonic wave is set to 500 MHz, and the sampling time is 5 s, which can be set by the implementer according to the actual situation.

[0055] At this point, the ultrasonic signal at each measuring point in the steel tube concrete column at each moment is obtained.

[0056] Step 2: Divide the ultrasonic signal of each measuring point at all times into multiple time periods; determine the peak variation coefficient of each measuring point in each time period according to the difference in the peak value of the ultrasonic signal in each time period of each measuring point and the difference in the interval time between the peaks.

[0057] When using ultrasound to detect the density of steel tube concrete columns, if the density of the steel tube concrete columns is good and there are no defects such as voids inside, the ultrasonic waves emitted by the transmitting probe will be received by the receiving probe after a certain degree of attenuation. That is, if the ultrasonic wave does not encounter an interface or obstacle during propagation, it will propagate normally. Secondly, in addition to the normally propagated ultrasonic signals, the collected ultrasonic signals also contain reflected signals generated by the boundaries of the steel tube concrete columns. Finally, multiple ultrasonic signals are collected at a single measuring point.

[0058] Since there are many mechanical equipment in waste incineration power plants and they are often in operation, the incineration of waste will also cause the temperature in local areas of the power plant to be higher. Therefore, there will be more environmental noise during the measurement process. The ultrasonic signal collected in the absence of noise interference is a number of non-equally spaced prominent peaks with a high degree of waveform similarity. When there is noise interference, there will be more peaks in the received ultrasonic signal, and the regularity of the peaks is lower, which may cover up the original ultrasonic reflection signal.

[0059] Based on the above analysis, in order to accurately analyze the interference of noise in ultrasonic signals, the ultrasonic signals of each measuring point at all times are divided, and the fluctuation of ultrasonic signals in each time period is analyzed, specifically:

[0060] Divide the ultrasonic signal of each measuring point at all times into multiple time periods;

[0061] Preferably, in this embodiment, each ultrasonic signal at each measuring point at all times As a time period, thereby obtaining multiple time periods.

[0062] Furthermore, according to the characteristics that when there is noise interference, there will be more peaks in the received ultrasonic signal, and the regularity of the peaks is low, the peaks generated in each time period and the degree of change in the time interval between the peaks are analyzed, and the peak variation coefficient is constructed, which is specifically:

[0063] A peak detection algorithm is used to obtain all the peaks of the ultrasonic signal at all times in each time period of each measuring point, and the peaks are recorded as the signal peaks in each time period of each measuring point;

[0064] Preferably, in this embodiment, an automatic multiscale-based peak detection (AMPD) algorithm is used to obtain all peaks, wherein the AMPD algorithm is a well-known technology and will not be described in detail here.

[0065] Calculate the variance of all signal peaks in each time period at each measuring point, and record it as the first variance;

[0066] Calculate the time interval between each signal peak and the previous signal peak in each time period of each measuring point as the interval time length of each signal peak in each time period of each measuring point;

[0067] Calculate the product of the variance of the interval durations of all signal peaks in each time period at each measuring point and the first variance as the peak variation coefficient in each time period at each measuring point;

[0068] It should be noted that the time interval between the first signal peak in each time period of each measuring point and the last signal peak in the previous time period is used as the interval duration of the first signal peak in each time period of each measuring point, and the interval duration of the first signal peak in the first time period of each measuring point is not calculated.

[0069] It should be noted that when waste incineration power generation is in progress, various mechanical equipment in the power plant are running at a high intensity, generating more mechanical noise, which in turn leads to more noise in each time period, more peaks formed due to the noise in each time period, and the more drastic the change in the peaks, the larger the first variance, and the greater the difference in the interval time between each peak, and the greater the degree of change, then the greater the variance of the interval time of all signal peaks in each time period, the greater the obtained peak variation coefficient, indicating that the difference between the peaks is large, the peak regularity in the received ultrasonic signal is low, and the degree of noise interference is greater.

[0070] At this point, the peak variation coefficient of each measuring point in each time period is obtained.

[0071] Step 3, analyze the differences in the changes of the ultrasonic signal in the frequency domain between different time periods of each measuring point, and determine the frequency domain offset coefficient of each time period of each measuring point; based on the peak variation coefficient and the frequency domain offset coefficient, obtain the noise interference index of each time period of each measuring point.

[0072] Furthermore, since the ultrasonic signal collected in the absence of noise interference has fewer envelopes in the frequency domain and is relatively smooth, when there is noise interference, the frequency fundamental envelope of the collected ultrasonic signal will shift in the frequency domain, and the envelope fluctuation in the frequency will be more intense. Based on the above analysis, the frequency fundamental envelope shift of the ultrasonic signal in the frequency domain and the change in the number of envelopes in the frequency are analyzed, and the frequency domain shift coefficient is constructed to reflect the degree of noise interference on the collected ultrasonic signal, specifically:

[0073] Perform frequency domain analysis on the ultrasonic signals at all times in each time period of each measuring point to obtain the spectrum of each time period of each measuring point;

[0074] Preferably, in this embodiment, Fourier transform is used to obtain the frequency spectrum of each measuring point in each time period, wherein Fourier transform is a well-known technology and will not be described in detail here.

[0075] A peak detection algorithm is used to obtain all peaks in the spectrum diagram of each measuring point in each time period, which are recorded as the amplitude peak of each measuring point in each time period;

[0076] The frequency corresponding to the maximum value of all amplitude peaks in each time period of each measuring point is taken as the fundamental frequency of each time period of each measuring point;

[0077] Preferably, in this embodiment, an AMPD algorithm is used to obtain all amplitude peaks in the spectrum diagram of each time period of each measuring point, wherein the AMPD algorithm is a well-known technology and will not be described in detail here.

[0078] The envelope extraction algorithm is used to obtain the number of envelopes of the spectrum diagram of each measuring point in each time period;

[0079] Preferably, in this embodiment, Hilbert transform is used to extract the envelope in the spectrum, wherein Hilbert transform is a well-known technology and will not be described in detail here.

[0080] The mean of the fundamental frequency differences between each time period of each measuring point and all other time periods is taken as the fundamental frequency difference of each time period of each measuring point;

[0081] The mean of the difference in the number of envelopes between each time period of each measuring point and all other time periods is taken as the difference in the number of envelopes of each time period of each measuring point;

[0082] The sum of the fundamental frequency difference and the envelope difference is used as the frequency domain offset coefficient of each time period of each measuring point;

[0083] Preferably, in this embodiment, the average of the differences in fundamental frequency between each time period of each measuring point and all other time periods is taken as the fundamental frequency difference of each time period of each measuring point; the average of the differences in the number of envelope lines between each time period of each measuring point and all other time periods is taken as the envelope difference of each time period of each measuring point.

[0084] In this embodiment, the frequency domain offset coefficient of each time period of each measuring point is calculated as follows: ,in, For the The first The frequency domain offset coefficient of the time period, For the The first The fundamental frequency of the time period, For the The first The fundamental frequency of the time period, For the The first The number of envelopes per time period, For the The first The number of envelopes per time period, For the The number of all time periods for each measurement point, is the fundamental frequency difference, is the envelope difference.

[0085] It should be noted that when the waste incineration power generation equipment continues to operate, more noise will continue to be generated in the collected ultrasonic signal. The more noise there is in each time period, the larger the fundamental frequency, and the greater the difference in the fundamental frequency in the spectrum diagram of different time periods, that is, the greater the difference in the fundamental frequency, the greater the difference in the total number of envelopes, and the larger the obtained frequency domain offset coefficient, indicating that the ultrasonic signal is more interfered by noise.

[0086] Further, the step flow chart of the method for obtaining the frequency domain offset coefficient of each time period of each measuring point provided in the embodiment of the present application is as follows: Figure 3 shown.

[0087] Further, based on the peak variation coefficient and the frequency domain offset coefficient, a noise interference index is determined to reflect the degree of noise interference during signal acquisition in the corresponding time period, specifically:

[0088] The product of the peak variation coefficient and the frequency domain offset coefficient is used as the noise interference index of each time period of each measuring point.

[0089] It should be noted that the greater the degree of peak change in each time period, that is, the larger the peak change coefficient, the more obvious the offset of the fundamental frequency and envelope quantity in the frequency domain, that is, the larger the frequency domain offset coefficient, the more noise generated by the waste incineration power generation equipment at this time, the more obvious the noise interference in this time period, the larger the resulting noise interference index, and the larger the filter window should be in the process of denoising through the filtering algorithm to better remove noise.

[0090] At this point, the noise interference index of each time period at each measuring point is obtained.

[0091] Step 4: Determine the effective information inclusion degree of each time period of each measuring point according to the fluctuation difference of the ultrasonic signal in different time periods of each measuring point and the degree of confusion of the wave crest change of the ultrasonic signal.

[0092] Although the denoising effect can be adjusted by the noise interference index to remove noise in the time period with greater noise interference in the ultrasonic signal, it may also cause the denoising effect to be too strong, which may lead to smoothing and denoising of the reflected ultrasonic signal received by the receiving probe, causing too much effective information to be lost in the ultrasonic signal, thereby affecting the accuracy of density detection. Therefore, it is necessary to analyze the effective information in each time period.

[0093] When collecting ultrasonic signals from steel tube concrete columns, the received ultrasonic signals will generate multiple reflected ultrasonic signals due to different propagation paths, and the energy of these reflected signals will be low due to reflection, but the peak shapes formed are relatively consistent, and the peak amplitudes in the frequency domain are relatively similar. These ultrasonic signals are all valid information, while the peaks formed by noise have more diverse shapes. When there is more noise, the peaks are more chaotic. When there is more valid information, the regularity of the peaks formed is relatively high. The more valid information there is in each time period, the more the filtering window of the filtering algorithm should be appropriately reduced to retain more valid information.

[0094] Based on the above analysis, the changes in the wave crests of the ultrasonic signals in different time periods and the differences in the amplitudes of the envelopes are analyzed, and the consistency coefficient is constructed to reflect the similarity of the wave crest shapes formed by the ultrasonic signals, specifically:

[0095] The sum of the differences between the ultrasonic signals of each time period of each measuring point and all other time periods is taken as the signal fluctuation difference of each time period of each measuring point;

[0096] Preferably, in this embodiment, the DTW distance of the ultrasonic signal at each time period of each measuring point and all moments in the remaining time periods is calculated, and the sum of the DTW distances between each time period of each measuring point and all other time periods is taken as the signal fluctuation difference of each time period of each measuring point.

[0097] The maximum value of all envelope amplitudes in the spectrum diagram of each measuring point in each time period is taken as the maximum envelope amplitude of each measuring point in each time period;

[0098] The sum of the differences between the maximum envelope amplitudes of each time period of each measuring point and all other time periods is taken as the signal amplitude difference of each time period of each measuring point;

[0099] The reciprocal of the sum of the signal fluctuation difference and the signal amplitude difference is used as the consistency coefficient of each time period of each measuring point;

[0100] Preferably, in this embodiment, the absolute value of the difference between the maximum envelope amplitude of each time period of each measuring point and the remaining time periods is recorded as the first difference, and the sum of the first differences between each time period of each measuring point and all the remaining time periods is taken as the signal amplitude difference of each time period of each measuring point.

[0101] In this embodiment, if the ultrasonic signals at all times in each time period of each measuring point are combined to form a signal sequence of each time period of each measuring point, the calculation method of the consistency coefficient of each time period of each measuring point is: ,in, For the The first The consistency coefficient of the time period, For the The first The signal sequence of time periods, For the The first The signal sequence of time periods, For the The first The maximum envelope amplitude of a time period, For the The first The maximum envelope amplitude of a time period, For the The number of all time periods for each measurement point, Indicates the calculation of DTW distance, To preset a value greater than 0 to avoid the denominator being 0, in this embodiment, The value is 0.01. For the first difference, is the signal fluctuation difference, For the second difference, is the signal amplitude difference.

[0102] It should be noted that the greater the difference between the peak shape in each time period and the peak shape formed by noise, the more similar it is to the peak shape formed by the reflected ultrasonic signal between each time period, the smaller the difference in the obtained signal fluctuation, and the smaller the difference in the envelope amplitude between each time period, the larger the obtained consistency coefficient, indicating that there is more valid information in the corresponding time period.

[0103] Furthermore, by analyzing the degree of chaos of the ultrasonic wave crest and the degree of chaos of the amplitude wave crest in the spectrum, the signal chaos degree is determined to reflect the characteristics of the noise signal, specifically:

[0104] Calculate the information entropy of all signal peaks in each time period of each measuring point; take the sum of the variance of all amplitude peaks in each time period of each measuring point and the information entropy as the signal chaos degree in each time period of each measuring point;

[0105] It should be noted that the greater the difference between signal peaks and amplitude peaks, the greater the chaos of the obtained signal, which means that the collected ultrasonic signal is more interfered by noise, the more significant the noise signal characteristics in each time period, and the less effective information contained in the corresponding time period.

[0106] Further, based on the consistency coefficient and the signal confusion, the effective information inclusion degree is determined to reflect the possibility of each time period containing effective information, specifically:

[0107] The ratio of the consistency coefficient to the signal chaos is used as the effective information inclusion degree of each time period of each measuring point;

[0108] It should be noted that the greater the effective information inclusion, the greater the possibility that effective information exists in the corresponding time period, and the window size of the filtering algorithm should be reduced to retain more effective information.

[0109] Furthermore, the flowchart of the steps of the method for obtaining the effective information inclusion degree of each time period of each measuring point provided in the embodiment of the present application is as follows: Figure 4 shown.

[0110] At this point, the effective information inclusion degree of each measuring point in each time period is obtained.

[0111] Step 5: Based on the noise interference index and the effective information inclusion degree, determine the filter window size of each time period of each measuring point; use a filtering algorithm to denoise the ultrasonic signal of each time period of each measuring point, and obtain a binary image of each measuring point through ultrasonic imaging technology to perform density detection on the steel tube concrete column.

[0112] Furthermore, in order to consider the interference degree of noise in the filtering process and retain valid information to the greatest extent, the window adjustment factor is determined based on the noise interference index and the valid information inclusion degree, specifically:

[0113] The normalized result of the ratio of the noise interference index to the effective information inclusion degree is used as the window adjustment factor of each time period of each measuring point;

[0114] Preferably, in this embodiment, a sigmoid function is used for normalization processing, wherein the sigmoid function is a well-known technology and will not be described in detail here.

[0115] It should be noted that when the noise interference in each time period is more and the effective information is less, the filter window size can be appropriately expanded when denoising the ultrasonic signal in the time period to better remove the noise; conversely, when the noise interference in each time period is less and the effective information is more, the filter window size can be appropriately reduced when denoising the ultrasonic signal in the time period to retain more effective information while removing the noise.

[0116] Further, based on the window adjustment factor, the filter window size of the filter algorithm is determined, specifically:

[0117] The filter window size for each time period of each measuring point is: ,in, For the The first The filter window size for each time period, For the The first The window adjustment factor for each time period, To preset the first threshold, To preset the second threshold, Indicates calculating the maximum value. Represents the ceiling function.

[0118] Preferably, in this embodiment, the first threshold is preset The value is 20, and the second threshold is preset The value is 20. The preset second threshold represents the minimum value that the filter window size can take. The implementer can set it according to the actual situation.

[0119] Based on the filter window size of each time period of each measuring point, a filtering algorithm is used to denoise the ultrasonic signals at all times in each time period of each measuring point;

[0120] Preferably, in this embodiment, a Savitzky-Golay filtering algorithm is used to denoise the ultrasonic signals at all times in each time period of each measuring point, and the window size of the Savitzky-Golay filtering algorithm is set to the filtering window size of each time period of each measuring point, wherein the Savitzky-Golay filtering algorithm is a well-known technology and will not be described in detail here.

[0121] The ultrasonic imaging algorithm is used to image the denoised ultrasonic signals in all time periods of each measuring point to obtain the ultrasonic topography of each measuring point;

[0122] Preferably, in this embodiment, a time reversal-multiple signal classification (TR-MUSIC) algorithm is used to obtain the ultrasonic topography image, wherein the TR-MUSIC algorithm is a well-known technology and will not be described in detail here.

[0123] Binarization processing is performed on the ultrasonic topography image of each measuring point to obtain a binary image of each measuring point;

[0124] Preferably, in this embodiment, a histogram construction method is used to perform binarization processing on the ultrasonic topography image to obtain a binary image, wherein the method of constructing a histogram for binarization processing is a well-known technology and will not be described in detail here.

[0125] It should be noted that the TR-MUSIC algorithm is a well-known technology and will not be described in detail here. In the ultrasonic topography of the steel tube concrete column, if the density of the steel tube concrete column is high, the grayscale distribution in the binary image of the ultrasonic topography is relatively uniform, and the overall grayscale value of the image is low. However, when the density of the steel tube concrete column is low and there are defects such as voids, cracks, and holes, bright blocks will appear in its ultrasonic topography, the grayscale distribution in the binary image of the ultrasonic topography is relatively different, and the overall grayscale value of the image is high.

[0126] Obtain a standard binary image from the database, use an image matching algorithm to match the binary image of each measuring point with the standard binary image, and obtain a matching value of the binary image of each measuring point;

[0127] Preferably, a Scale Invariant Feature Transform (SIFT) algorithm is used for image matching, wherein the SIFT algorithm is a well-known technology and will not be described in detail here.

[0128] Using the threshold segmentation algorithm, the segmentation threshold of the matching value of the binary image of all the measuring points is obtained;

[0129] If the matching value is less than or equal to the segmentation threshold, the steel tube concrete column at the corresponding measuring point has defects; if the matching value is greater than the segmentation threshold, the steel tube concrete column at the corresponding measuring point does not have defects.

[0130] Preferably, a cross-validation method is used to obtain the segmentation threshold of the matching value of the binary image of all the measuring points, wherein the cross-validation method is a well-known technology and will not be described in detail here.

[0131] It should be noted that when there are defects inside the steel tube concrete column, it means that there may be voids, cracks, holes, etc. in the steel tube concrete column. The density of the steel tube concrete column at the corresponding measuring point is low and requires certain maintenance and repair.

[0132] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0133] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0134] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the present application. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the content of the technical solution of the present application, shall fall within the protection scope of the technical solution of the present application.

Claims

1. A method for detecting the density of a steel tube concrete column for waste incineration power generation, characterized in that: The method comprises the following steps: Obtain the ultrasonic signal at each measuring point in the steel tube concrete column at each time; The ultrasonic signal of each measuring point at all times is divided into multiple time periods; according to the difference in the peak value of the ultrasonic signal in each time period of each measuring point and the difference in the interval time between the peaks, the peak change coefficient of each time period of each measuring point is determined; Analyze the difference in the change of the ultrasonic signal in the frequency domain between different time periods of each measuring point, and determine the frequency domain offset coefficient of each time period of each measuring point; based on the peak variation coefficient and the frequency domain offset coefficient, obtain the noise interference index of each time period of each measuring point; According to the fluctuation difference of the ultrasonic signal in different time periods at each measuring point and the degree of confusion of the wave crest change of the ultrasonic signal, the effective information inclusion degree of each time period at each measuring point is determined; Based on the noise interference index and the effective information inclusion degree, the filter window size of each time period of each measuring point is determined; the ultrasonic signal of each time period of each measuring point is denoised by using a filtering algorithm, and a binary image of each measuring point is obtained by ultrasonic imaging technology to perform density detection on the steel tube concrete column; Obtain the spectrum diagram of each time period at each measuring point, and record the peak of the spectrum diagram as the amplitude peak; Determining the effective information inclusion degree of each time period of each measuring point includes: Analyze the difference in the ultrasonic signal fluctuations between different time periods at each measuring point, as well as the difference in the corresponding amplitude of the envelope line in the spectrum diagram, and determine the consistency coefficient of each time period at each measuring point; Calculate the information entropy of all signal peaks in each time period of each measuring point; take the sum of the variance of all amplitude peaks in each time period of each measuring point and the information entropy as the signal chaos degree in each time period of each measuring point; The ratio of the consistency coefficient to the signal chaos is used as the effective information inclusion degree of each time period of each measuring point; Determining the consistency coefficient of each time period of each measuring point includes: The sum of the differences of the ultrasonic signals between each time period of each measuring point and all other time periods is taken as the signal fluctuation difference of each time period of each measuring point; The maximum value of all envelope amplitudes in the spectrum diagram of each measuring point in each time period is taken as the maximum envelope amplitude of each measuring point in each time period; The sum of the differences between the maximum envelope amplitudes of each time period of each measuring point and all other time periods is taken as the signal amplitude difference of each time period of each measuring point; The reciprocal of the sum of the signal fluctuation difference and the signal amplitude difference is used as the consistency coefficient of each time period of each measuring point; The filter window size of each time period of each measuring point is: ,in, For the The first The filter window size for each time period, For the The first The window adjustment factor for each time period, To preset the first threshold, To preset the second threshold, Indicates calculating the maximum value. is the ceiling function.

2. A method for detecting the density of a steel tube concrete column for waste incineration power generation according to claim 1, characterized in that: Determining the peak variation coefficient of each measuring point in each time period includes: A peak detection algorithm is used to obtain all the peaks of the ultrasonic signal at all times in each time period of each measuring point, and the peaks are recorded as the signal peaks in each time period of each measuring point; Calculate the time interval between each signal peak and the previous signal peak in each time period of each measuring point as the interval time length of each signal peak in each time period of each measuring point; The variance of all signal peaks in each time period of each measuring point is calculated and recorded as the first variance; the product of the variance of the interval duration of all signal peaks in each time period of each measuring point and the first variance is used as the peak variation coefficient of each time period of each measuring point.

3. A method for detecting the density of a steel tube concrete column for waste incineration power generation as claimed in claim 2, characterized in that: Determining the frequency domain offset coefficient of each time period of each measuring point includes: Perform frequency domain analysis on the ultrasonic signals at all times in each time period of each measuring point to obtain the spectrum diagram of each time period of each measuring point; A peak detection algorithm is used to obtain all peaks in the spectrum diagram, which are recorded as the amplitude peaks of each time period at each measuring point; The frequency corresponding to the maximum value of all amplitude peaks in each time period of each measuring point is taken as the fundamental frequency of each time period of each measuring point; Using an envelope extraction algorithm to obtain the number of envelopes of the spectrum diagram in each time period of each measuring point; The mean of the fundamental frequency differences between each time period of each measuring point and all other time periods is taken as the fundamental frequency difference of each time period of each measuring point; The mean of the difference in the number of envelopes between each time period of each measuring point and all other time periods is taken as the difference in the number of envelopes of each time period of each measuring point; The sum of the fundamental frequency difference and the envelope difference is used as the frequency domain offset coefficient of each time period of each measuring point.

4. A method for detecting the density of a steel tube concrete column for waste incineration power generation according to claim 1, characterized in that: The noise interference index of each time period of each measuring point is the product of the peak variation coefficient and the frequency domain offset coefficient.

5. A method for detecting the density of a steel tube concrete column for waste incineration power generation according to claim 1, characterized in that: The window adjustment factor is a normalized result of the ratio of the noise interference index to the effective information inclusion degree.

6. A method for detecting the density of a steel tube concrete column for waste incineration power generation according to claim 1, characterized in that: The step of obtaining a binary image of each measuring point comprises: The ultrasonic imaging algorithm is used to image the denoised ultrasonic signals in all time periods of each measuring point to obtain the ultrasonic topography of each measuring point; The ultrasonic topography of each measuring point is binarized to obtain a binary image of each measuring point.

7. A method for detecting the density of a steel tube concrete column for waste incineration power generation according to claim 1, characterized in that: The density test of the steel tube concrete column includes: Match the binary image of each measuring point with the standard binary image obtained from the database to obtain the matching value of the binary image of each measuring point; obtain the segmentation threshold of the matching value of the binary image of all measuring points; If the matching value is less than or equal to the segmentation threshold, the steel tube concrete column at the corresponding measuring point has defects; otherwise, the steel tube concrete column at the corresponding measuring point does not have defects.

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