A method and system for measuring the thickness of scale deposits in sewage pipes

Abstract

The present invention relates to the technical field of ultrasonic thickness measurement, and in particular to a method and system for measuring the thickness of scale deposited in sewage pipes. The present invention first obtains all similar ultrasonic segment groups between all ultrasonic signals at the same measuring point, and further screens out all stable band groups; then the two ultrasonic signals of each group of preset measuring points are symmetrically fused, and then the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency is obtained; finally, based on all fused ultrasonic signals and corresponding confidence weights, the thickness of scale deposited in the sewage pipe is evaluated. The present invention determines the stable ultrasonic segment through the similar fluctuation characteristics of ultrasonic signals at the same angle and different frequencies, and then fuses the ultrasonic signals at the measuring points at symmetrical angles to evaluate their confidence, thereby accurately evaluating the thickness of scale deposited in the pipeline based on the confidence and the fused ultrasonic signal, reducing the interference of other external factors on the ultrasonic signal, and improving the measurement accuracy of the thickness of scale deposited in the pipeline.

Description

Technical Field

[0001] The invention relates to the technical field of ultrasonic thickness measurement, and in particular to a method and system for measuring the thickness of scale deposits in a sewage pipe. Background Art

[0002] Sewage pipes are an important part of urban infrastructure and are mainly used to collect, transport and discharge sewage. During the sewage discharge process, solid particles, suspended matter or other impurities in the sewage will gradually deposit on the inner wall of the pipe to form scale. Pipeline scale not only affects the smoothness of discharge, but may also cause pipeline corrosion or water pollution. Measuring the thickness of sewage pipe scale can help assess the severity of scale, thereby determining a reasonable cleaning strategy and increasing the service life of the pipe.

[0003] In the prior art, a probe with a camera, i.e., a detection device similar to an endoscope, is usually used to enter the sewage pipe from the sewage outlet to collect real-time images of the inside of the pipe. Although this method can clearly and intuitively observe the inner wall of the sewage pipe and help analyze the thickness and distribution of scale in the pipe, the probe needs to be manually inserted and operated, and the detection length is limited. When the sewage pipe is in a sewage discharge state, the operation difficulty will be further increased, resulting in low efficiency in pipeline scale detection, which in turn affects the measurement effect of scale thickness on the sewage pipe. Summary of the invention

[0004] In order to solve the technical problem that the prior art has poor effect on measuring the scale thickness of sewage pipes, the purpose of the present invention is to provide a method and system for measuring the scale thickness of sewage pipes. The technical solution adopted is as follows:

[0005] The present invention provides a method for measuring the thickness of scale deposits in a sewage pipe, the method comprising:

[0006] Acquire ultrasonic signals at different frequencies from each measuring point in each set of preset measuring points on the sewage pipe, wherein each set of preset measuring points is symmetrical based on the cross-sectional axis of the sewage pipe;

[0007] At the same measuring point, all similar ultrasonic segment groups between all the ultrasonic signals are obtained according to the fluctuation characteristics of the ultrasonic signals at different frequencies; in each of the similar ultrasonic segment groups, the stability coefficient of each similar ultrasonic segment group is obtained according to the corresponding frequency and time duration of each ultrasonic segment and the similar fluctuation between each ultrasonic segment and the other ultrasonic segments; and all stable band groups are screened out from all the similar ultrasonic segment groups according to the stability coefficient;

[0008] In each group of preset measuring points, at the same frequency, according to the corresponding time of each signal point in the ultrasonic signal of each measuring point and the time interval with the corresponding stable ultrasonic segment in each stable band group, the two ultrasonic signals of each group of preset measuring points are symmetrically fused, and all stable ultrasonic segments in the fused ultrasonic signal are obtained;

[0009] According to the time interval between each stable ultrasonic segment in the fused ultrasonic signal of each group of preset measuring points at each frequency and the stable ultrasonic segments in the fused ultrasonic signals of other groups of preset measuring points at the same frequency, the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency is obtained; based on all the fused ultrasonic signals and the corresponding confidence weights, the scale thickness of the sewage pipe is evaluated.

[0010] Furthermore, the method for obtaining the similar ultrasonic segment group includes:

[0011] At the same measuring point, an ultrasonic signal at any frequency is used as a target signal, and the other ultrasonic signals are used as reference signals; a sliding window of a preset size is used to slide from the starting point of each ultrasonic signal based on a preset step length, and each sliding window of the target signal is used as a target window, and each sliding window of the reference signal is used as a reference window;

[0012] According to the fluctuation difference and corresponding time interval between the signal segments in each target window and each reference window, the matching parameters between each target window and each reference window are obtained; the reference window corresponding to the maximum matching parameter is used as the matching window of each target window in the corresponding reference signal;

[0013] Starting from the first target window, a target analysis set is constructed according to a preset number of target windows; between the target signal and each reference signal, a matching reference coefficient of the target analysis set is obtained according to the discrete degree of the time interval between the matching windows corresponding to the adjacent target windows and the matching parameters between the target window and the corresponding matching window in the target analysis set;

[0014] On the target signal, the target analysis set is updated according to the matching reference coefficient, and the signal segment corresponding to the sliding window in the target analysis set that meets the preset conditions after the update is used as the band to be matched; all the ultrasonic signal segments corresponding to the matching windows of each band to be matched in each reference signal are used as the matching ultrasonic segments of each band to be matched in each reference signal; each band to be matched and all its corresponding matching ultrasonic segments are used as a similar ultrasonic segment group.

[0015] Furthermore, the method for obtaining the matching parameters includes:

[0016] Between each target window and the corresponding signal segments in each reference window, the negative correlation mapping result of the amplitude difference between all signal points with the same serial number is used as the fluctuation similarity coefficient, and the negative correlation mapping result of the difference between the corresponding moments of any signal point with the same serial number is used as the time reference weight; the fluctuation similarity coefficient is weighted using the time reference weight, and the weighted result is used as the matching parameter between the corresponding target window and the corresponding reference window.

[0017] Furthermore, the method for obtaining the matching reference coefficient includes:

[0018] Between the target signal and each reference signal, the negative correlation mapping result of the variance of the time intervals between adjacent target windows corresponding to the matching windows is used as a reference weight, and the reference weight is used to accumulate and weight the matching parameters between all target windows and the corresponding matching windows in the target analysis set, and the weighted result is used as the matching sub-parameter of the target analysis set and the corresponding matching window in the corresponding reference signal; the normalized result of the mean of the matching sub-parameters of the target analysis set and the corresponding matching windows in all reference signals is used as the matching reference coefficient of the target analysis set.

[0019] Furthermore, the acquisition of the to-be-matched band includes:

[0020] When the matching reference coefficient of the updated target analysis set is less than a preset threshold, the signal segment corresponding to the sliding window in the target analysis set is used as the band to be matched; when the matching reference coefficient is greater than or equal to the preset threshold, the next adjacent target window of the last target window in the target analysis set on the target signal is added to the target analysis set to obtain an updated target analysis set, and the matching reference coefficient of the updated target analysis set is obtained, and the iteration is continued until the matching reference coefficient is less than the preset threshold, the band to be matched is obtained, and starting from the next adjacent target window of the last target window in the current target analysis set on the target signal, the target analysis set is reconstructed, and the iteration is continued until all the bands to be matched are obtained.

[0021] Furthermore, the method for obtaining the stability coefficient includes:

[0022] Taking an ultrasonic band corresponding to any ultrasonic signal in any of the similar ultrasonic band groups as a target band, adding a frequency corresponding to the target band and a duration of the target band, and taking a negatively correlated normalized result of the sum as a stable weight of the target band;

[0023] In each matching ultrasonic segment of the target band, the sum of the matching parameters between all sliding windows in the target band and the corresponding matching window is multiplied by the duration of each matching ultrasonic segment to obtain a stable matching parameter between the target band and each matching ultrasonic segment;

[0024] The target band and the sum of the stable matching parameters of all matching ultrasonic bands are weighted by using the stable weight of the target band, and the weighted result is used as the stable sub-parameter corresponding to the similar ultrasonic band group under the target band; the stable sub-parameters corresponding to the similar ultrasonic band group under each ultrasonic band in each similar ultrasonic band group are integrated to obtain the stable parameters of the corresponding similar ultrasonic band group.

[0025] Furthermore, the method for acquiring the stable band group includes:

[0026] The similar ultrasonic wave band group whose stability coefficient is greater than a preset coefficient threshold is taken as a stable wave band group.

[0027] Furthermore, the method of symmetrically fusing the two ultrasonic signals of each group of preset measuring points and obtaining all stable ultrasonic segments in the fused ultrasonic signal includes:

[0028] In each group of preset measuring points, at the same frequency, the time interval between each signal point and the nearest stable ultrasonic segment in the ultrasonic signal of each measuring point is added to the corresponding moment of each signal point, and the negative correlation mapping result of the sum value is used as the fusion weight of each signal point;

[0029] In each set of preset measuring points, at the same frequency, the sum of the corresponding time serial numbers of the signal points in the ultrasonic signals of the two measuring points, which is equal to the ultrasonic signal duration plus 1, is taken as a binary group; the fusion weights of the signal points in each binary group are normalized, wherein the sum of the fusion weights of the two signal points in each binary group is 1;

[0030] The corresponding signal points are weightedly fused using the fusion weights of the two signal points in each binary group, and the weighted fusion result is used as the fused signal point at the corresponding moment; a fused ultrasonic signal is constructed based on the fused signal points at all moments; and the union of the stable ultrasonic segments of the two measuring points corresponding to the fused ultrasonic signal is used as all the stable ultrasonic segments of the fused ultrasonic signal.

[0031] Furthermore, the method for obtaining the confidence weight includes:

[0032] Taking any group of preset measuring points as the target group measuring points, taking the adjacent preset measuring points of each group of preset measuring points as the reference group measuring points, taking the fused ultrasonic signals of the target group measuring points at any frequency as the target fused signals, and taking the fused ultrasonic signals of the reference group measuring points at the same frequency as the reference fused signals of the target fused signals;

[0033] In each reference fusion signal, the stable ultrasonic segment closest to each stable ultrasonic segment in the target fusion signal at the corresponding time is used as the reference stable waveband of each stable ultrasonic segment in the target fusion signal; the variance of the time interval between each stable ultrasonic segment in the target fusion signal and the corresponding reference stable segment is negatively correlated and mapped, and the negative correlation mapping result is used as the weight sub-parameter of each stable ultrasonic segment in the target fusion signal;

[0034] The average value of the weight sub-parameters of all stable ultrasonic segments in the target fusion signal is used as the confidence weight of the target fusion signal.

[0035] The present invention also proposes a sewage pipe scale thickness measurement system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the sewage pipe scale thickness measurement method when executing the computer program.

[0036] The present invention has the following beneficial effects:

[0037] The present invention first obtains the ultrasonic signal of each measuring point in each group of preset measuring points on the sewage pipe at different frequencies to provide a data basis for Houxi analysis; then obtains all similar ultrasonic segment groups between all ultrasonic signals, and further screens out all stable band groups from all similar ultrasonic segment groups, wherein the stable band groups reflect the bands with less interference from other factors and higher confidence at different frequencies, so as to prepare for the subsequent accurate analysis of the scale thickness; then symmetrically fuses the two ultrasonic signals of each group of preset measuring points, obtains all stable ultrasonic segments in the fused ultrasonic signal, and comprehensively evaluates the fusion results of the two ultrasonic signals of the comprehensive symmetrical measuring points to improve the confidence of the subsequent analysis; obtains the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency according to the time interval between each stable ultrasonic segment in the fused ultrasonic signal of each group of preset measuring points at each frequency and the stable ultrasonic segments in the fused ultrasonic signal of other groups of preset measuring points at the same frequency; finally, based on all the fused ultrasonic signals and the corresponding confidence weights, the scale thickness of the sewage pipe is evaluated. The present invention determines the stable ultrasonic segment through the similar fluctuation characteristics of ultrasonic signals at the same angle and different frequencies, and then fuses the ultrasonic signals at the measuring points at symmetrical angles to evaluate their confidence levels, thereby accurately evaluating the thickness of pipeline fouling based on the confidence levels and the fused ultrasonic signals, reducing the interference of other external factors on the ultrasonic signals, and improving the measurement accuracy of pipeline fouling thickness. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 A flow chart of a method for measuring the thickness of scale deposits in a sewage pipe provided by one embodiment of the present invention;

[0040] Figure 2 A schematic diagram of the layout of preset measuring points on a sewage pipe provided by an embodiment of the present invention;

[0041] Figure 3 A flow chart of a method for obtaining similar ultrasonic segment groups provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a sewage pipe scale thickness measurement method and system proposed by the present invention, its specific implementation, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0043] 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 invention belongs.

[0044] The specific scheme of a sewage pipe scale thickness measurement method and system provided by the present invention is described in detail below with reference to the accompanying drawings.

[0045] See also Figure 1 , which shows a flow chart of a method for measuring scale thickness in a sewage pipe provided by an embodiment of the present invention, specifically comprising:

[0046] Step S1, obtaining ultrasonic signals at different frequencies from each measuring point in each group of preset measuring points on the sewage pipe, wherein each group of preset measuring points is symmetrical based on the cross-sectional axis of the sewage pipe.

[0047] In one embodiment of the present invention, firstly, a plurality of preset measuring points are set at the sewage pipe to be detected, and it is necessary to ensure that all measuring points are located on the same cross section of the sewage pipe; an ultrasonic transmitting device is installed at each measuring point on the outer wall of the sewage pipe, and a reflecting device is installed on the outer wall of the pipe on the other side of the ultrasonic transmitting direction of each measuring point; the frequency of ultrasonic transmission is set to different frequencies within the range of 0.2MHz-20MHz, such as 0.2MHz, 2MHz, 12MHz, and 20MHz, and an ultrasonic signal of each measuring point at each frequency is obtained;

[0048] Each set of preset measuring points is based on the cross-sectional axis symmetry of the sewage pipe; see Figure 2 , which shows a schematic diagram of the layout of preset measuring points on a sewage pipe provided by an embodiment of the present invention; Figure 2 The largest circle in the figure represents the cross section of the sewage pipe. The black dots are measuring points, and a measuring point is arranged every 45°. The measuring points on the same straight line of the sewage pipe are a group of preset measuring points, and there are 4 groups of preset measuring points in total.

[0049] It should be noted that the analysis method is consistent at each cross section of the sewage pipe, and the number of preset measuring points can be determined according to the specific application situation. The implementer can also set the frequency and number of ultrasonic waves; among them, obtaining ultrasonic signals is an existing technology well known to technicians in this field and will not be repeated here.

[0050] It should be noted that the time interval for collecting ultrasonic signals at different frequencies at different measuring points should not be too long, and should be completed within 1 hour as much as possible to avoid changes in the scale distribution in the sewage pipe, which in turn affects the accuracy of the scale thickness measurement.

[0051] Step S2, at the same measuring point, according to the fluctuation characteristics of ultrasonic signals at different frequencies, all similar ultrasonic segment groups between all ultrasonic signals are obtained; in each similar ultrasonic segment group, according to the corresponding frequency and time duration of each ultrasonic segment, combined with the similar fluctuations between each ultrasonic segment and the remaining ultrasonic segments, the stability coefficient of each similar ultrasonic segment group is obtained; according to the stability coefficient, all stable band groups are screened out from all similar ultrasonic segment groups.

[0052] Considering that the sewage pipe is not completely blocked by scale, there are still a lot of cavities inside it, and the scale is usually deposited at the bottom of the pipe due to factors such as gravity; considering that the propagation speed of ultrasound in the cavity is not consistent with the propagation speed in the complex scale layer, there will be certain losses during the propagation, and at the same time, the propagation speed of ultrasonic signals at different frequencies at the same measuring point in the cavity or in the scale is also inconsistent, and the degree of loss may also be inconsistent, but the propagation environment of ultrasonic signals at the same measuring point is similar, that is, the order and distance of penetrating the pipe wall, cavity and scale are relatively consistent, then the received ultrasonic signals should have similar fluctuation characteristics;

[0053] Therefore, the embodiment of the present invention first obtains all similar ultrasonic segment groups between all ultrasonic signals at the same measuring point according to the fluctuation characteristics of ultrasonic signals at different frequencies; the similar ultrasonic segment groups are ultrasonic signal segments corresponding to ultrasonic waves at different frequencies passing through similar sewage pipe parts such as cavities or scale, and then the similar ultrasonic segment groups are used as analysis objects to prepare for reducing noise interference in ultrasonic signals and improving the accuracy of subsequent ultrasonic signal analysis.

[0054] Preferably, in one embodiment of the present invention, the method for obtaining a similar ultrasonic segment group includes:

[0055] Please participate Figure 3 , which shows a flow chart of a method for obtaining a similar ultrasonic segment group provided by an embodiment of the present invention, specifically comprising:

[0056] Step S201, at the same measuring point, an ultrasonic signal at any frequency is used as a target signal, and the other ultrasonic signals are used as reference signals; a sliding window of a preset size is used, starting from the starting point of each ultrasonic signal and sliding based on a preset step size, and each sliding window of the target signal is used as a target window, and each sliding window of the reference signal is used as a reference window.

[0057] As an example, to facilitate subsequent analysis and description, any ultrasonic signal at each measuring point is taken as the target signal. In this example, the ultrasonic signal with the lowest frequency is selected as the target signal, and the remaining ultrasonic signals at the measuring point are taken as reference signals. The implementer can also select the target signal by himself. The analysis method under all selection methods is the same and will not be repeated here. At the same time, in order to facilitate the analysis of the similar fluctuations between the target signal and each reference signal, a sliding window is constructed for sliding comparison, so as to facilitate the subsequent acquisition of similar ultrasonic segments of the target signal in the remaining reference signals.

[0058] Among them, the method for constructing the sliding window is to take the starting point of each ultrasonic signal as the starting point of the sliding window, set the preset size to 5, that is, the length of the sliding window is 5, and the height changes with the signal amplitude; set the preset step size to 1, for example, the window starts to slide from the starting point, the time of the corresponding signal segment in the first sliding window is 1 to 5, and the time range of the corresponding signal segment in the second window obtained after sliding is 2 to 6, and so on, which will not be repeated; then all target windows and reference windows are obtained to prepare for the analysis and matching of subsequent windows.

[0059] It should be noted that the implementer can also set the size of the sliding window and the sliding step size by himself, which will not be elaborated here.

[0060] Step S202, obtaining matching parameters between each target window and each reference window according to the fluctuation difference and corresponding time interval between the signal segments in each target window and each reference window; taking the reference window corresponding to the maximum matching parameter as the matching window of each target window in the corresponding reference signal.

[0061] Considering that the closer the time interval between sliding windows is, and the more similar the fluctuation of the signal segments within them is, the more likely they are to correspond to the same fluctuation feature segment, based on this, firstly, the matching parameters between each target window and each reference window are obtained, and then from all the reference windows of each target window, a reference window with the largest matching parameter is selected as the matching window of the target window, in preparation for the subsequent acquisition of similar ultrasonic segments based on continuous sliding windows;

[0062] In a preferred embodiment of the present invention, considering that the closer the interval between the sliding windows is, the smaller the difference between the signal points at the same time between the signal segments in the window is, and the greater the matching confidence is, the logic can be adjusted by negative correlation mapping; based on this, the method for obtaining the matching parameters includes:

[0063] Between each target window and the corresponding signal segment in each reference window, the negative correlation mapping result of the amplitude difference between all signal points with the same sequence number is used as the fluctuation similarity coefficient, and the negative correlation mapping result of the difference between the corresponding moments of any signal point with the same sequence number is used as the time reference weight; the fluctuation similarity coefficient is weighted by using the time reference weight, and the weighted result is used as the matching parameter between the corresponding target window and the corresponding reference window.

[0064] It should be noted that in the embodiment of the present invention, the moment corresponding to the center point of each sliding window is used as the comparison reference point, and the difference between the moments of signal points with the same sequence number corresponding to the center point is used as the time interval between windows. The same is true for the time interval mentioned in the subsequent analysis process, which will not be repeated here.

[0065] As an example, the matching parameters are calculated as:

[0066] ; Where i is the serial number of the target signal; l is the serial number of the reference signal; a is the serial number of the target window; b is the serial number of the reference window; is the ath target window in the target signal; is the bth reference window in the lth reference signal; is the matching parameter between the ath target window in the target signal and the bth reference window in the lth reference signal; is the center moment corresponding to the ath target window in the target signal; is the central time corresponding to the bth reference window in the lth reference signal; z is the signal point sequence number of the signal segment in the window; N is the total number of signal points in the signal segment in the window; is the amplitude of the zth signal point in the ath target window in the target signal; the amplitude of the zth signal point in the bth reference window in the lth reference signal; is an exponential function with the natural constant e as base; is the time reference weight; is the fluctuation similarity coefficient.

[0067] In the formula, the time difference and the amplitude difference are accumulated and negatively correlated and mapped to the exponential function to adjust the logic, so that the signal segments in the two sliding windows that are closer in time and amplitude are more similar, and the corresponding matching parameters are larger; in other examples, the implementer may also adopt other negative correlation mapping means, such as adding a preset minimum parameter and then performing an inverse operation, etc., which are all existing commonly used technical means and will not be elaborated here.

[0068] Step S203, starting from the first target window, construct a target analysis set according to a preset number of target windows; between the target signal and each reference signal, obtain the matching reference coefficient of the target analysis set according to the discrete degree of the time interval between the corresponding matching windows of adjacent target windows, and the matching parameters between the target window and the corresponding matching window in the target analysis set.

[0069] Taking into account that the length of similar ultrasonic segments is not just the size of a sliding window, by sliding and merging partial windows and then matching them, a relatively complete similar ultrasonic segment can be obtained; so as an example, first in the target signal, the preset number is set to 3, that is, starting from the first target window, the first three target windows are taken as a target analysis set, and the matching windows corresponding to all target windows in the target analysis set in each reference signal are obtained. The matching windows in each reference signal can be regarded as a reference matching set; then the matching reference coefficient between the target analysis set and the corresponding reference matching set is evaluated. The matching reference coefficient reflects the degree of similarity between the signal segment corresponding to the target analysis set and the corresponding signal segment in the reference signal, in preparation for the subsequent acquisition of similar ultrasonic segment groups.

[0070] In a preferred embodiment of the present invention, considering that the smaller the time interval between the matching windows corresponding to adjacent target windows is, the more similar the fluctuations of the target signal and the reference signal are; and considering that the larger the matching parameter between the target window and the corresponding matching window in the target analysis set is, the more similar the fluctuations of the target signal and the reference signal are; therefore, the method for obtaining the matching reference coefficient includes:

[0071] Between the target signal and each reference signal, the negative correlation mapping result of the variance of the time intervals between the corresponding matching windows of adjacent target windows is used as the reference weight. The reference weight is used to accumulate and weight the matching parameters between all target windows and the corresponding matching windows in the target analysis set, and the weighted result is used as the matching sub-parameter of the target analysis set and the corresponding matching window in the corresponding reference signal; the normalized result of the mean of the matching sub-parameters of the target analysis set and the corresponding matching windows in all reference signals is used as the matching reference coefficient of the target analysis set.

[0072] As an example, the matching reference coefficient is calculated as: ; Where im is the matching reference coefficient of the mth target analysis set in the target signal; is a linear normalization function; l is the serial number of the reference signal; L is the total number of reference signals; is the variance of the time intervals between the corresponding matching windows in the lth reference signal of all adjacent target windows in the target signal; c is the sequence number of the target window in the mth target analysis set in the target signal; is the total number of target windows in the mth target analysis set in the target signal; is the matching coefficient between the cth target window in the mth target analysis set in the target signal and the corresponding matching window in the lth reference signal; is the reference weight; is the matching sub-parameter of the corresponding matching window between the mth target analysis set in the target signal and the lth reference signal.

[0073] In the calculation formula of the matching reference coefficient, the variance of the time intervals between the corresponding matching windows of adjacent target windows is specifically reciprocally calculated to perform a negative correlation mapping adjustment logic; then the reciprocal is multiplied by the cumulative sum of the matching parameters, so that the smaller the variance and the larger the cumulative sum of the matching parameters, the larger the matching sub-parameters of the matching windows in the target analysis set and the corresponding reference signal are obtained, and then all the matching sub-parameters are combined to evaluate the matching reference coefficient of the target analysis set.

[0074] It should be noted that the possibility of the variance being zero is extremely low, but this situation does exist. Therefore, in other examples, the implementer may also map the negative correlation of the variance to an exponential function, such as x in exp(-x). Other negative correlation mapping methods may also be used, which will not be elaborated here.

[0075] Step S204: on the target signal, the target analysis set is updated according to the matching reference coefficient, and the signal segment corresponding to the sliding window in the target analysis set that meets the preset conditions after the update is used as the band to be matched; all the ultrasonic signal segments corresponding to the matching windows of each band to be matched in each reference signal are used as the matching ultrasonic segments of each band to be matched in each reference signal; each band to be matched and all its corresponding matching ultrasonic segments are used as a similar ultrasonic segment group.

[0076] Considering that the size of the initially constructed target analysis set is also small, in one embodiment of the present invention, the target analysis set is updated after the matching reference coefficient of the target analysis set is obtained, so that a new target analysis set can be expanded or obtained, thereby obtaining a relatively complete similar ultrasonic segment. Based on this, all the to-be-matched bands on the target signal are first obtained, and then the matching ultrasonic segment on the reference signal can be obtained based on the to-be-matched band, thereby constructing a similar ultrasonic segment group;

[0077] In a preferred embodiment of the present invention, obtaining the to-be-matched band includes:

[0078] When the matching reference coefficient of the updated target analysis set is less than a preset threshold, the signal segment corresponding to the sliding window in the target analysis set is used as the band to be matched; when the matching reference coefficient is greater than or equal to the preset threshold, the next adjacent target window of the last target window in the target analysis set on the target signal is added to the target analysis set to obtain an updated target analysis set, and the matching reference coefficient of the updated target analysis set is obtained. The process is iterated continuously until the matching reference coefficient is less than the preset threshold, then the band to be matched is obtained, and starting from the next adjacent target window of the last target window in the current target analysis set on the target signal, the target analysis set is reconstructed, and the process is iterated continuously until all the bands to be matched are obtained.

[0079] It should be noted that, for the target analysis set obtained by the first construction: when the matching reference coefficient is greater than or equal to the preset threshold, the next adjacent target window of the last target window in the target analysis set on the target signal is added to the target analysis set to obtain an updated target analysis set; when the matching reference coefficient is less than the preset threshold, the first target window in the target analysis set is removed, and the next adjacent target window of the last target window in the target analysis set on the target signal is added to the target analysis set to obtain an updated target analysis set;

[0080] As an example, the target window sequence number corresponding to the initially constructed target analysis set is 123, and the target analysis set is subsequently referred to as 123. Similarly, the matching reference coefficient of the current target analysis set 123 is obtained based on the calculation formula of the matching reference coefficient in step S203; the preset threshold is set to 0.7;

[0081] When the matching reference coefficient of the target analysis set 123 is less than 0.7, the target window with serial number 1 is removed from the target analysis set, and the target window with serial number 4 is added, so that the target window serial number corresponding to the updated target analysis set is 234; continue to calculate the matching reference coefficient corresponding to the new target analysis set 234, when the matching reference coefficient is less than 0.7, take the ultrasonic signal segment corresponding to the target window 234 as a band to be matched, otherwise continue to increase the target window and construct a new target analysis set 2345, when the matching reference coefficient of the target analysis set 2345 is greater than or equal to 0.7, iteratively increase the target window to obtain the target analysis set 23456, otherwise when the matching reference coefficient of the target analysis set 2345 is less than 0.7, take the ultrasonic signal segment corresponding to the target analysis set 2345 as a band to be matched, and reconstruct the target analysis set 678, based on the same iterative analysis method as above, obtain all the bands to be matched in the target signal;

[0082] When the matching reference coefficient of the target analysis set 123 is greater than or equal to 0.7, the target window numbered 4 is added to the target analysis set, so that the target window number corresponding to the updated target analysis set is 1234. The target analysis set is also updated based on the same iterative steps to obtain all the bands to be matched in the target signal.

[0083] At this point, all the bands to be matched in the target signal are obtained; then all the ultrasonic signal segments corresponding to the matching windows of each band to be matched in each reference signal are used as the matching ultrasonic segments of each band to be matched in each reference signal; for example, a band to be matched is the ultrasonic signal segment corresponding to the target analysis set 1234567, and its reference matching set of the matching window corresponding to it in the lth reference signal is 2345677, where 2345677 is the reference window serial number on the reference signal, then the ultrasonic signal segment corresponding to 2345677 on the reference signal is the matching ultrasonic segment of the band to be matched; similarly, the matching ultrasonic segments on all other reference signals are obtained to construct a similar ultrasonic segment group.

[0084] In another embodiment of the present invention, the implementer may also identify similar ultrasonic signal segments based on a DTW algorithm, a sequence comparison algorithm or by clustering ultrasonic signal segments, which are all prior arts well known to those skilled in the art and will not be described in detail herein.

[0085] Considering that during the propagation of ultrasonic waves, they may be affected by other external factors such as changes in sewage discharge materials in sewage pipes, water flow or signal interference factors, resulting in the presence of noise in ultrasonic signals, and the ultrasonic segments with similar fluctuation characteristics in all ultrasonic waves, namely similar ultrasonic segment groups, correspond to bands with similar propagation environments and similar interference levels. Based on similar band groups, the accuracy of subsequent fouling analysis can be improved; considering that the signal loss degree at different ultrasonic frequencies is different, the accuracy of the signal information provided by ultrasonic waves is also different, and high-frequency ultrasonic signals often decay faster, and the loss of ultrasonic segments with longer time is relatively large, so the stability and accuracy of the signal are relatively reduced;

[0086] Therefore, in each similar ultrasonic segment group, according to the embodiment of the present invention, the stability coefficient of each similar ultrasonic segment group is obtained according to the corresponding frequency and duration of each ultrasonic segment and the similar fluctuations between each ultrasonic segment and the other ultrasonic segments. Based on the frequency and duration of the ultrasonic segment, the signal accuracy, that is, the reference value, is accurately evaluated, and then the stability coefficient is evaluated in combination with the fluctuation similarity; then, all stable band groups are further screened out from all similar ultrasonic segment groups according to the stability coefficient; the stable band groups reflect the bands that are less affected by other factors at different frequencies and have higher confidence, which prepares for the subsequent accurate analysis of scale thickness.

[0087] Preferably, in one embodiment of the present invention, the method for obtaining the stability coefficient includes:

[0088] The ultrasonic band corresponding to any ultrasonic signal in any similar ultrasonic band group is taken as the target band, the frequency and duration corresponding to the target band are added, and the negative correlation normalization result of the sum is taken as the stable weight of the target band;

[0089] In each matching ultrasonic segment of the target band, the sum of the matching parameters between all sliding windows in the target band and the corresponding matching window is multiplied by the duration of each matching ultrasonic segment to obtain a stable matching parameter between the target band and each matching ultrasonic segment;

[0090] The target band's stability weight is used to weight the sum of the stable matching parameters of the target band and all matching ultrasonic segments, and the weighted result is used as the stable sub-parameter of the corresponding similar ultrasonic segment group under the target band; the stable sub-parameters of the corresponding similar ultrasonic segment group under each ultrasonic segment in each similar ultrasonic segment group are combined to obtain the stable parameters of the corresponding similar ultrasonic segment group.

[0091] As an example, the stability parameter is calculated as:

[0092] ; Wherein, j is the serial number of the similar ultrasonic segment group; is the stability parameter of the jth similar ultrasonic segment group; n is the serial number of the ultrasonic segment in the jth similar ultrasonic segment group; N is the total number of ultrasonic segments in the jth similar ultrasonic segment group, which is also the number of ultrasonic frequencies; is the frequency of the nth ultrasonic segment in the jth similar ultrasonic segment group; is the duration corresponding to the nth ultrasonic segment in the jth similar ultrasonic segment group; b is the serial number of other ultrasonic signals except the frequency corresponding to the nth ultrasonic segment in the jth similar ultrasonic segment group; B is the total number of other ultrasonic signals except the frequency corresponding to the nth ultrasonic segment in the jth similar ultrasonic segment group, which is also N-1; is the sequence number of the sliding window in the nth ultrasonic segment in the jth similar ultrasonic segment group; is the total number of sliding windows within the nth ultrasonic segment in the jth similar ultrasonic segment group; is the matching parameter between the xth sliding window in the nth ultrasonic segment and the matching window in the matching ultrasonic segment in the bth ultrasonic signal; is the length of the matching ultrasonic segment in the bth ultrasonic signal; is an exponential function with the natural constant e as base; is the stable weight of the nth ultrasonic segment in the jth similar ultrasonic segment group; is the stable matching parameter of the nth ultrasonic segment in the jth similar ultrasonic segment group and the corresponding matching ultrasonic segment in the bth ultrasonic signal; is a linear normalization function; is the stable sub-parameter of the jth similar ultrasonic segment group under the nth ultrasonic segment.

[0093] In the formula, the frequency and duration of the ultrasonic segment are specifically added, and the negative correlation of the sum is mapped to the exponential function to adjust the logic so that the ultrasonic segment with higher frequency and longer duration has a lower stability weight; the stability weight is multiplied and combined with the stability matching parameter to obtain the stability sub-parameter, and then the sum of the stability sub-parameters of the corresponding similar ultrasonic segment group under all ultrasonic segments is taken as the stability parameter of the corresponding similar ultrasonic segment group.

[0094] In other examples, implementers may also adopt other negative correlation mapping methods, which are not described here in detail.

[0095] Preferably, in one embodiment of the present invention, a similar ultrasonic wave band group whose stability coefficient is greater than a preset coefficient threshold is taken as a stable wave band group; wherein the preset coefficient threshold is set to 0.75, and the implementer may also set it by himself to obtain all stable wave band groups.

[0096] Step S3, in each group of preset measuring points, at the same frequency, according to the corresponding moment of each signal point in the ultrasonic signal of each measuring point and the time interval with the corresponding stable ultrasonic segment in each stable band group, the two ultrasonic signals of each group of preset measuring points are symmetrically fused, and all stable ultrasonic segments in the fused ultrasonic signal are obtained.

[0097] Taking into account that the measuring points in each group of preset measuring points are symmetrical based on the cross-sectional axis of the sewage pipe, and the transmission paths of the ultrasonic waves are also roughly similar, the ultrasonic signals corresponding to the two measuring points can be regarded as two signals with opposite starting points, and then the two are weightedly fused to obtain a more accurate fused ultrasonic signal; and considering that the ultrasonic wave will gradually attenuate with the increase of propagation time, and may also be affected by the surrounding noise, that is, the inhomogeneous medium, thereby resulting in a decrease in the accuracy of subsequent signal points; therefore, the embodiment of the present invention firstly, in each group of preset measuring points, at the same frequency, symmetrically fuses the two ultrasonic signals of each group of preset measuring points to further obtain all stable ultrasonic segments in the fused ultrasonic signal.

[0098] Preferably, in one embodiment of the present invention, the method of symmetrically fusing two ultrasonic signals of each group of preset measuring points and obtaining all stable ultrasonic segments in the fused ultrasonic signal includes:

[0099] In each set of preset measuring points, at the same frequency, the time interval between each signal point and the nearest stable ultrasonic segment in the ultrasonic signal of each measuring point is added to the corresponding moment of each signal point, and the negative correlation mapping result of the sum value is used as the fusion weight of each signal point;

[0100] In each set of preset measuring points, at the same frequency, the sum of the corresponding time serial numbers of the signal points in the ultrasonic signals of the two measuring points, which is equal to the ultrasonic signal duration plus 1, is taken as a binary group; the fusion weights of the signal points in each binary group are normalized, wherein the sum of the fusion weights of the two signal points in each binary group is 1;

[0101] The corresponding signal points are weightedly fused using the fusion weights of the two signal points in each binary group, and the weighted fusion result is used as the fused signal point at the corresponding moment; a fused ultrasonic signal is constructed based on the fused signal points at all moments; and the union of the stable ultrasonic segments of the two measuring points corresponding to the fused ultrasonic signal is used as all the stable ultrasonic segments of the fused ultrasonic signal.

[0102] As an example, the sum values ​​are respectively used as x in the exponential function exp(-x) with the natural constant e as the base, so as to perform negative correlation mapping adjustment logic, so that the signal point closer to the stable ultrasonic segment and with the earlier corresponding time has a greater confidence and a greater corresponding fusion weight;

[0103] Then, in each set of preset measuring points, it is assumed that the corresponding time sequence of the ultrasonic signal corresponding to a measuring point at any frequency is expressed as abcdefg, and the corresponding time sequence of the ultrasonic signal corresponding to another measuring point is expressed as gfedcba. Because the corresponding time of a in the first ultrasonic signal is 1, and the corresponding time of a in the second ultrasonic signal is 7, the corresponding time of the two a signal points is the length of the ultrasonic signal plus 1, so the two signal points with the same time sequence number in the two ultrasonic signals, such as a corresponding to two signal points, are grouped into a binary group, and the rest of bcdefg are the same, and all binary groups are obtained;

[0104] Then the fusion weights corresponding to the signal points in each binary group are normalized so that the sum of the fusion weights of the two signal points is 1. Then, the corresponding signal points are weightedly fused using the fusion weights to obtain the corresponding fused signal points at each moment, thereby constructing a fused ultrasonic signal, and then obtaining all stable ultrasonic segments of the fused ultrasonic signal corresponding to each group of preset measuring points.

[0105] Among them, the normalization method is to divide each fusion weight by the sum of all fusion weights to obtain the normalized fusion weight; it should be noted that the timing sequence of the constructed fusion ultrasound signal can be the same as the timing sequence of any measuring point. In other examples, other negative correlation mapping methods can also be used. The acquisition of the union and the method are both existing technologies and will not be repeated here.

[0106] Step S4, obtaining the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency according to the time interval between each stable ultrasonic segment in the fused ultrasonic signal of each group of preset measuring points at each frequency and the stable ultrasonic segments in the fused ultrasonic signals of other groups of preset measuring points at the same frequency; based on all the fused ultrasonic signals and the corresponding confidence weights, evaluating the scale thickness of the sewage pipe.

[0107] Taking into account the same frequency, the time position of the stable ultrasonic segment in the fused ultrasonic signal of different groups of preset measuring points should be relatively similar in the ultrasonic signal. Based on this, the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency will be obtained. The larger the confidence weight, the more accurate the fused ultrasonic signal corresponding to the group of preset measuring points at the frequency, which prepares for the subsequent accurate assessment of the scale thickness.

[0108] Preferably, in one embodiment of the present invention, the method for obtaining the confidence weight includes:

[0109] Taking any group of preset measuring points as the target group measuring points, taking the adjacent preset measuring points of each group of preset measuring points as the reference group measuring points, taking the fused ultrasonic signals of the target group measuring points at any frequency as the target fused signals, and taking the fused ultrasonic signals of the reference group measuring points at the same frequency as the reference fused signals of the target fused signals;

[0110] In each reference fusion signal, the stable ultrasonic segment closest to each stable ultrasonic segment in the target fusion signal at the corresponding time is used as the reference stable waveband of each stable ultrasonic segment in the target fusion signal; the variance of the time interval between each stable ultrasonic segment in the target fusion signal and the corresponding reference stable segment is negatively correlated and mapped, and the negative correlation mapping result is used as the weight sub-parameter of each stable ultrasonic segment in the target fusion signal;

[0111] The mean value of the weight sub-parameters of all stable ultrasonic segments in the target fusion signal is taken as the confidence weight of the target fusion signal.

[0112] Please note that Figure 2 , assuming that the measurement points in group A are the target group measurement points, then their reference measurement points are group B and group D respectively; as an example, taking the target group measurement points as an example, the calculation formula of the confidence weight is:

[0113] ; Where a is the serial number of the fused ultrasonic signal in the target group measurement point; is the confidence weight of the ath fused ultrasonic signal in the target group measurement point; v is the serial number of the stable ultrasonic segment in the ath fused ultrasonic signal in the target group measurement point; X is the total number of stable ultrasonic segments in the ath fused ultrasonic signal in the target group measurement point; is the variance of the time interval between the vth stable ultrasonic segment in the ath fused ultrasonic signal in the target group measurement point and all corresponding reference stable segments; is an exponential function with the natural constant e as base; is the weight sub-parameter.

[0114] In the formula, the variance is specifically mapped negatively through an exponential function, so that the smaller the variance of the time interval is, the more likely it is that the corresponding time of the stable ultrasonic segment is consistent, and the higher the confidence weight is; in other examples, the implementer may also adopt other negative correlation mapping methods, which will not be repeated here.

[0115] By changing the target group's measuring points, the confidence weights of the corresponding fused ultrasonic signals of all groups' preset measuring points can be obtained, and then each fused ultrasonic signal can be analyzed to evaluate the initial scale thickness measured in the sewage pipe at the corresponding angle. The initial scale thickness is then multiplied by the confidence weight to obtain the scale thickness measured at the corresponding angle. Finally, based on the scale thickness measured at all angles, the approximate distribution of scale in the sewage pipe can be fitted, thereby evaluating the severity of the scale thickness, thereby assisting relevant personnel in formulating a scale cleaning plan to ensure the smooth discharge of the sewage pipe.

[0116] It should be noted that the evaluation of the initial scale thickness in the sewage pipe based on the fusion ultrasonic signal is an existing technology well known to those skilled in the art and will not be elaborated here.

[0117] The present invention also proposes a sewage pipe scale thickness measurement system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, steps of a sewage pipe scale thickness measurement method are implemented.

[0118] In summary, the ultrasonic signals of each measuring point in each group of preset measuring points on the sewage pipe at different frequencies are obtained, and then all similar ultrasonic segment groups between all ultrasonic signals at the same measuring point are obtained; further all stable band groups are screened out from all similar ultrasonic segment groups; then the two ultrasonic signals of each group of preset measuring points are symmetrically fused, and then the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency is obtained; finally, based on all fused ultrasonic signals and corresponding confidence weights, the scale thickness of the sewage pipe is evaluated. The present invention determines the stable ultrasonic segment through the similar fluctuation characteristics of ultrasonic signals at the same angle and different frequencies, and then fuses the ultrasonic signals at the measuring points at symmetrical angles to evaluate their confidence, thereby accurately evaluating the thickness of pipeline fouling based on the confidence and the fused ultrasonic signal, reducing the interference of other external factors on the ultrasonic signal, and improving the measurement accuracy of pipeline scale thickness.

[0119] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0120] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for measuring the thickness of scale deposits in a sewage pipe, characterized in that: The method comprises: Acquire ultrasonic signals at different frequencies from each measuring point in each set of preset measuring points on the sewage pipe, wherein each set of preset measuring points is symmetrical based on the cross-sectional axis of the sewage pipe; At the same measuring point, all similar ultrasonic segment groups between all the ultrasonic signals are obtained according to the fluctuation characteristics of the ultrasonic signals at different frequencies; in each of the similar ultrasonic segment groups, the stability coefficient of each similar ultrasonic segment group is obtained according to the corresponding frequency and time duration of each ultrasonic segment and the similar fluctuation between each ultrasonic segment and the other ultrasonic segments; and all stable band groups are screened out from all the similar ultrasonic segment groups according to the stability coefficient; In each group of preset measuring points, at the same frequency, according to the corresponding time of each signal point in the ultrasonic signal of each measuring point and the time interval with the corresponding stable ultrasonic segment in each stable band group, the two ultrasonic signals of each group of preset measuring points are symmetrically fused, and all stable ultrasonic segments in the fused ultrasonic signal are obtained; According to each stable ultrasonic segment in the fused ultrasonic signal of each group of preset measuring points at each frequency, and the time interval between the stable ultrasonic segments in the fused ultrasonic signals of other groups of preset measuring points at the same frequency, the confidence weight of the fused ultrasonic signal of each group of preset measuring points at each frequency is obtained; based on all the fused ultrasonic signals and the corresponding confidence weights, the scale thickness of the sewage pipe is evaluated; The method of symmetrically fusing the two ultrasonic signals of each group of preset measuring points and obtaining all stable ultrasonic segments in the fused ultrasonic signal includes: In each group of preset measuring points, at the same frequency, the time interval between each signal point and the nearest stable ultrasonic segment in the ultrasonic signal of each measuring point is added to the corresponding moment of each signal point, and the negative correlation mapping result of the sum value is used as the fusion weight of each signal point; In each set of preset measuring points, at the same frequency, the sum of the corresponding time serial numbers of the signal points in the ultrasonic signals of the two measuring points, which is equal to the ultrasonic signal duration plus 1, is taken as a binary group; the fusion weights of the signal points in each binary group are normalized, wherein the sum of the fusion weights of the two signal points in each binary group is 1; The corresponding signal points are weightedly fused using the fusion weights of the two signal points in each binary group, and the weighted fusion result is used as the fused signal point at the corresponding moment; a fused ultrasonic signal is constructed based on the fused signal points at all moments; and the union of the stable ultrasonic segments of the two measuring points corresponding to the fused ultrasonic signal is used as all the stable ultrasonic segments of the fused ultrasonic signal.

2. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 1, characterized in that: The method for obtaining the similar ultrasonic segment group comprises: At the same measuring point, an ultrasonic signal at any frequency is used as a target signal, and the other ultrasonic signals are used as reference signals; a sliding window of a preset size is used to slide from the starting point of each ultrasonic signal based on a preset step length, and each sliding window of the target signal is used as a target window, and each sliding window of the reference signal is used as a reference window; According to the fluctuation difference and corresponding time interval between the signal segments in each target window and each reference window, the matching parameters between each target window and each reference window are obtained; the reference window corresponding to the maximum matching parameter is used as the matching window of each target window in the corresponding reference signal; Starting from the first target window, a target analysis set is constructed according to a preset number of target windows; between the target signal and each reference signal, a matching reference coefficient of the target analysis set is obtained according to the discrete degree of the time interval between the matching windows corresponding to the adjacent target windows and the matching parameters between the target window and the corresponding matching window in the target analysis set; On the target signal, the target analysis set is updated according to the matching reference coefficient, and the signal segment corresponding to the sliding window in the target analysis set that meets the preset conditions after the update is used as the band to be matched; all the ultrasonic signal segments corresponding to the matching windows of each band to be matched in each reference signal are used as the matching ultrasonic segments of each band to be matched in each reference signal; each band to be matched and all its corresponding matching ultrasonic segments are used as a similar ultrasonic segment group.

3. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 2, characterized in that: The method for obtaining the matching parameters includes: Between each target window and the corresponding signal segments in each reference window, the negative correlation mapping result of the amplitude difference between all signal points with the same serial number is used as the fluctuation similarity coefficient, and the negative correlation mapping result of the difference between the corresponding moments of any signal point with the same serial number is used as the time reference weight; the fluctuation similarity coefficient is weighted using the time reference weight, and the weighted result is used as the matching parameter between the corresponding target window and the corresponding reference window.

4. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 2, characterized in that: The method for obtaining the matching reference coefficient includes: Between the target signal and each reference signal, the negative correlation mapping result of the variance of the time intervals between adjacent target windows corresponding to the matching windows is used as a reference weight, and the reference weight is used to accumulate and weight the matching parameters between all target windows and the corresponding matching windows in the target analysis set, and the weighted result is used as the matching sub-parameter of the target analysis set and the corresponding matching window in the corresponding reference signal; the normalized result of the mean of the matching sub-parameters of the target analysis set and the corresponding matching windows in all reference signals is used as the matching reference coefficient of the target analysis set.

5. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 2, characterized in that: The acquisition of the to-be-matched band includes: When the matching reference coefficient of the updated target analysis set is less than a preset threshold, the signal segment corresponding to the sliding window in the target analysis set is used as the band to be matched; when the matching reference coefficient is greater than or equal to the preset threshold, the next adjacent target window of the last target window in the target analysis set on the target signal is added to the target analysis set to obtain an updated target analysis set, and the matching reference coefficient of the updated target analysis set is obtained, and the iteration is continued until the matching reference coefficient is less than the preset threshold, the band to be matched is obtained, and starting from the next adjacent target window of the last target window in the current target analysis set on the target signal, the target analysis set is reconstructed, and the iteration is continued until all the bands to be matched are obtained.

6. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 2, characterized in that: The method for obtaining the stability coefficient includes: Taking an ultrasonic band corresponding to any ultrasonic signal in any of the similar ultrasonic band groups as a target band, adding a frequency corresponding to the target band and a duration of the target band, and taking a negatively correlated normalized result of the sum as a stable weight of the target band; In each matching ultrasonic segment of the target band, the sum of the matching parameters between all sliding windows in the target band and the corresponding matching window is multiplied by the duration of each matching ultrasonic segment to obtain a stable matching parameter between the target band and each matching ultrasonic segment; The target band and the sum of the stable matching parameters of all matching ultrasonic bands are weighted by using the stable weight of the target band, and the weighted result is used as the stable sub-parameter corresponding to the similar ultrasonic band group under the target band; the stable sub-parameters corresponding to the similar ultrasonic band group under each ultrasonic band in each similar ultrasonic band group are integrated to obtain the stable parameters of the corresponding similar ultrasonic band group.

7. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 1, characterized in that: The method for obtaining the stable band group includes: The similar ultrasonic wave band group whose stability coefficient is greater than a preset coefficient threshold is taken as a stable wave band group.

8. A method for measuring the thickness of scale deposits in a sewage pipe according to claim 1, characterized in that: The method for obtaining the confidence weight includes: Taking any group of preset measuring points as the target group measuring points, taking the adjacent preset measuring points of each group of preset measuring points as the reference group measuring points, taking the fused ultrasonic signals of the target group measuring points at any frequency as the target fused signals, and taking the fused ultrasonic signals of the reference group measuring points at the same frequency as the reference fused signals of the target fused signals; In each reference fusion signal, the stable ultrasonic segment closest to each stable ultrasonic segment in the target fusion signal at the corresponding time is used as the reference stable waveband of each stable ultrasonic segment in the target fusion signal; the variance of the time interval between each stable ultrasonic segment in the target fusion signal and the corresponding reference stable segment is negatively correlated and mapped, and the negative correlation mapping result is used as the weight sub-parameter of each stable ultrasonic segment in the target fusion signal; The average value of the weight sub-parameters of all stable ultrasonic segments in the target fusion signal is used as the confidence weight of the target fusion signal.

9. A sewage pipe scale thickness measurement system, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of a method for measuring the thickness of scale deposits in a sewage pipe as claimed in any one of claims 1 to 8 are implemented.

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