Ultrasonic array based method and system for non-destructive testing of early strength of precast components

Abstract

The present application belongs to the technical field of nondestructive testing, and particularly relates to a prefabricated component early strength nondestructive testing method and system based on an ultrasonic array, aiming to solve the technical problem that the existing nondestructive testing technology is difficult to accurately evaluate the early strength of the prefabricated component under the interference of multiple factors. The detection method comprises: S1, identifying the first wave arrival time for each time domain waveform signal, and calculating the average sound velocity in combination with the geometric position of each receiving channel; S2, calculating the average value of the permutation entropy of all receiving channels to obtain the average value of the peak front entropy; S3, calculating the average value of the attenuation coefficient of all receiving channels to obtain the average value of the frequency attenuation coefficient; S4, determining the early strength of the prefabricated component based on the comprehensive strength indicator value through a preset strength mapping relationship. The detection method of the present application constructs a comprehensive strength indicator value, and improves the accuracy of the nondestructive testing of the early strength of the prefabricated component.

Description

Technical Field

[0001] This invention belongs to the technical field of non-destructive testing, specifically relating to a method and system for non-destructive testing of early strength of prefabricated components based on ultrasonic arrays. Background Technology

[0002] The early strength of precast components is related to whether the components can be safely demolded, stacked, transported, and used for subsequent construction. Currently, strength testing methods, such as the test block compressive strength test, are accurate, but they are destructive tests. Moreover, the production and curing of test blocks takes a long time and cannot reflect the strength development of precast components in real time.

[0003] Ultrasonic testing methods are widely used due to their ease of operation, low cost, and harmlessness to humans. The most common method is the ultrasonic pulse velocity method, which indirectly assesses strength by measuring the propagation speed of ultrasonic waves in concrete. The basic principle of this method is that the strength of concrete is positively correlated with its elastic modulus and density, and the sound velocity is also primarily determined by these two parameters. However, the detection of sound velocity parameters also has limitations: sound velocity is not only affected by strength but also by various factors such as aggregate type, gradation, moisture content, microcracks, and curing conditions. Especially in the early hydration stage, the mapping relationship between sound velocity parameters and strength is unstable, often leading to deviations in the test results. Summary of the Invention

[0004] This invention provides a non-destructive testing method and system for the early strength of precast components based on an ultrasonic array, aiming to solve the technical problem that existing non-destructive testing technologies are difficult to accurately assess the early strength of precast components under multiple interference factors.

[0005] In a first aspect, the present invention provides a method for non-destructive testing of the early strength of prefabricated components based on an ultrasonic array, comprising the following steps:

[0006] S1. Acquire the full matrix data of the ultrasonic array of the prefabricated component, and construct a virtual sound source based on the full matrix data using a phased focusing algorithm to obtain the time-domain waveform signal of each receiving channel; for each time-domain waveform signal, identify the arrival time of the first wave, and calculate the average sound velocity in combination with the geometric position of each receiving channel;

[0007] S2, set the pre-peak analysis window before the arrival time of the first wave of each time domain waveform signal, calculate the arrangement entropy of the time domain waveform signal within each pre-peak analysis window, and calculate the average arrangement entropy of all receiving channels to obtain the average pre-peak entropy.

[0008] S3. After the arrival time of the first wave of each time-domain waveform signal, set the post-peak analysis window, perform Hilbert-Huang transform on the time-domain waveform signal within each post-peak analysis window to obtain the time spectrum, calculate the attenuation coefficient of the instantaneous frequency centroid in each time spectrum, and calculate the average attenuation coefficient of all receiving channels to obtain the average frequency attenuation coefficient.

[0009] S4. According to preset weights, the average sound velocity, the average pre-peak entropy, and the average frequency attenuation coefficient are linearly weighted and combined to obtain a comprehensive strength indication value. Based on the comprehensive strength indication value, the early strength of the precast component is determined through a preset strength mapping relationship.

[0010] Furthermore, when acquiring the full matrix data, it will include... An ultrasonic array probe with multiple elements is placed on the surface of a prefabricated component. Each element then emits an ultrasonic pulse as a transmitter, while all elements simultaneously... Each array element acts as a receiver to receive signals, repeating... This process continues until all array elements have been fired once, thus obtaining a... The full matrix data.

[0011] Furthermore, in S1, when obtaining the time-domain waveform signals of each receiving channel, a virtual sound source point is set within the prefabricated component. ;

[0012] For the Each receiving channel, Time-domain waveform signal at time t The contribution from all transmission channels is synthesized by delay superposition, and the calculation formula is as follows: ,in, For the first The launch array element is launched, the first... The time-domain signal received by each receiving channel For from the first Each transmitting element to the virtual sound source point The sound wave propagation time is delayed.

[0013] Furthermore, in S1, when identifying the arrival time of the first wave, for the time-domain waveform signal of each receiving channel, the ratio of energy in the short time window to energy in the long time window is calculated starting from the starting point of the time-domain waveform signal.

[0014] The moment when the ratio first exceeds the energy ratio threshold is determined as the arrival time of the first wave.

[0015] Furthermore, S2 includes the following steps:

[0016] The length of the pre-peak analysis window is set to 10. The end time of the pre-peak analysis window is 1 minute before the arrival time of the first wave. ;

[0017] When calculating the permutation entropy: the embedding dimension is set to 4 and the time delay is 1, and the phase space reconstruction is performed on the time-domain waveform signal within the pre-peak analysis window;

[0018] The reconstructed vectors in the phase space are mapped to a sequence from 0 to 23;

[0019] Calculate the probability of occurrence of each sequence and then calculate the permutation entropy based on the probability distribution.

[0020] Furthermore, in S3, the start time of the post-peak analysis window is set to the arrival time of the first wave, and the length of the post-peak analysis window is 100. 100 The peak-after-peak analysis window can fully capture the main peak of the time-domain waveform signal and the subsequent attenuation portion.

[0021] Furthermore, in S3, within the post-peak analysis window, with 1 Divide into step sizes A point in time;

[0022] Calculate the instantaneous frequency centroid value of the time-domain waveform signal at each time point. ;

[0023] The least squares method is used to analyze the data point sequence. Perform linear fitting to obtain the fitted line. Among them, slope The attenuation coefficient is... For the first At a certain point in time, The value range is from 1 to , Represents a time variable. This represents the intercept of the fitted line.

[0024] Further, in S4, the average sound velocity, the mean value of the pre-peak entropy, and the mean value of the frequency attenuation coefficient are normalized and converted into dimensionless parameters.

[0025] Using formula Calculations are performed, in which, This is the comprehensive strength indication value. , , These represent the normalized average sound velocity, the mean pre-peak entropy, and the mean frequency attenuation coefficient, respectively. , , Preset weights.

[0026] Furthermore, in S4, when determining the early strength of the precast component, non-destructive testing and standard compressive strength tests are simultaneously performed on pre-made standard curing test blocks at different ages to obtain multiple sets of comprehensive strength indication values. Compressive strength value The corresponding data pairs;

[0027] Using a quadratic polynomial Fit multiple sets of corresponding data pairs to determine the coefficients. , , The intensity mapping relationship is obtained.

[0028] Secondly, the present invention provides a non-destructive testing system for early strength of precast components based on an ultrasonic array, comprising a memory and a processor. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned non-destructive testing method for early strength of precast components based on an ultrasonic array is implemented.

[0029] The beneficial effects are as follows: Compared with existing technologies, this invention not only utilizes the average sound velocity reflecting the material's density, but also represents the random changes in the signal caused by changes in the material's internal microstructure by calculating the arrangement entropy of the pre-peak signal, thus obtaining the average pre-peak entropy value that is sensitive to the early structure formation process; by performing a Hilbert-Huang transform on the post-peak signal to obtain the time spectrum, and calculating the attenuation coefficient of the instantaneous frequency centroid, the average frequency attenuation coefficient that reflects the dispersion and absorption effects of ultrasonic energy in heterogeneous media is extracted. This invention linearly weights and fuses the above three parameters that represent the material state from the perspectives of propagation time, microstructure complexity, and energy attenuation characteristics, respectively, to construct a comprehensive strength indicator value, suppressing the influence of interference factors such as moisture and aggregate on the test results, and improving the accuracy of non-destructive testing of the early strength of precast components. Attached Figure Description

[0030] Figure 1 This is a flowchart of a non-destructive testing method for early strength of precast components based on ultrasonic arrays.

[0031] Figure 2 Comprehensive strength indicator value With compressive strength The fitted calibration curve;

[0032] Figure 3 This is a schematic diagram of a non-destructive testing system for the early strength of precast components based on an ultrasonic array. Detailed Implementation

[0033] An embodiment of the non-destructive testing method for early strength of precast components based on ultrasonic array provided by the present invention:

[0034] like Figure 1 As shown, the method for non-destructive testing of early strength of precast components based on ultrasonic arrays includes the following steps:

[0035] S1. Acquire the full matrix data of the ultrasonic array of the prefabricated component, and construct a virtual sound source based on the full matrix data using a phased focusing algorithm to obtain the time-domain waveform signal of each receiving channel; for each time-domain waveform signal, identify the arrival time of the first wave, and calculate the average sound velocity in combination with the geometric position of each receiving channel.

[0036] Specifically, it will include An ultrasonic array probe with multiple elements is placed on the surface of a prefabricated component. Each element then emits an ultrasonic pulse as a transmitter, while all elements simultaneously... Each array element acts as a receiver to receive signals, repeating... This process continues until all array elements have been fired once, thus obtaining a... The full matrix data.

[0037] A virtual sound source point is set inside the prefabricated component for the first... For each receiving channel, calculate the sound wave propagation time delay from the transmitting element to the virtual sound source point and then to the receiving element. Then, perform the corresponding time-domain signal in the full matrix data, shift the time accordingly, and add them together to obtain the time-domain waveform signal of the receiving channel. Repeat this process until the time-domain waveform signals of all receiving channels are obtained.

[0038] Based on the location of the virtual sound source and the coordinates of each receiving channel element, the straight-line distance from the virtual sound source to each receiving channel element is calculated. Dividing this straight-line distance by the corresponding arrival time of the first wave yields the sound velocity value for each receiving channel. The average sound velocity is obtained by arithmetically averaging the sound velocity values ​​of all receiving channels.

[0039] In an optional embodiment, in S1, when obtaining the time-domain waveform signals of each receiving channel, a virtual sound source point is set within the prefabricated component. ;

[0040] For the Each receiving channel, Time-domain waveform signal at time t The contribution from all transmission channels is synthesized by delay superposition, and the calculation formula is as follows: ,in, For the first The launch array element is launched, the first... The time-domain signal received by each receiving channel For from the first Each transmitting element to the virtual sound source point The sound wave propagation time is delayed.

[0041] Specifically, a virtual sound source point F is set 50 mm below the surface of the precast component. The purpose is to concentrate ultrasonic energy at a specific location inside the precast component, thereby improving the signal-to-noise ratio and imaging quality. For each transmitting element m, the time required for the sound wave to propagate from transmitting element m to the virtual sound source point F needs to be calculated. This time is equal to the geometric distance between the transmitting element m and the virtual sound source point F divided by the estimated speed of sound. For the nth receiving channel, the time-domain signal received by this receiving channel from the transmitting element m at time t is... Shift the corresponding time on the time axis. (For example, translate 15) ,get The time-domain signals of all transmitting array elements, after appropriate delay adjustments, are summed to synthesize the focused time-domain waveform signal of receiving channel n. This is equivalent to the receiving channel receiving the sound wave emitted by the virtual sound source point F.

[0042] In an optional embodiment, in S1, when identifying the arrival time of the first wave, for the time-domain waveform signal of each receiving channel, the ratio of energy in the short time window to energy in the long time window is calculated starting from the starting point of the time-domain waveform signal.

[0043] The moment when the ratio first exceeds the energy ratio threshold is determined as the arrival time of the first wave.

[0044] Specifically, this process sets two sliding calculation windows for a time-domain waveform signal: a short window for detecting signal abrupt changes and a long window for estimating the average energy level of background noise. For example, the short window has a length of 1... The length of the long window is 20. The two windows slide synchronously backward from the zero point of the time-domain waveform signal.

[0045] At each moment, the sum of squares of the signal amplitude within the immediately following short-time window is calculated as the short-time energy, and the sum of squares of the signal amplitude within the preceding long-time window is calculated as the long-time energy. The ratio of the short-time energy to the long-time energy is obtained. In the initial noise segment of the time-domain waveform signal, this ratio is close to 1. When the first wave of ultrasound arrives, the amplitude of the time-domain waveform signal increases sharply, causing the short-time energy to rise rapidly, and the ratio subsequently shows a steep peak. By comparing this ratio with a preset threshold, the moment when the ratio first changes from below the preset threshold to above the preset threshold is recorded; this moment is the arrival time of the first wave. For example, the preset threshold is 5, and the arrival time of the first wave is 42.5. .

[0046] S2. Before the arrival time of the first wave of each time-domain waveform signal, set the pre-peak analysis window, calculate the arrangement entropy of the time-domain waveform signal within each pre-peak analysis window, and calculate the average arrangement entropy of all receiving channels to obtain the average pre-peak entropy.

[0047] Specifically, a fixed-length segment is extracted as a pre-peak analysis window before the arrival time of the first wave of each time-domain waveform signal. For example, the fixed length is 5. For the time-domain waveform signal within the pre-peak analysis window, with an embedding dimension of 3 and a time delay of 1, the time-domain waveform signal within the pre-peak analysis window is reconstructed into a series of three-dimensional vectors. The magnitude relationship of the three components within each three-dimensional vector is compared to determine its corresponding sorting pattern (e.g., ascending order). The frequency of each of the six possible sorting patterns in all three-dimensional vectors is counted, and the permutation entropy of the time-domain waveform is calculated using the Shannon entropy formula. The permutation entropy calculated from all receiving channels is arithmetically averaged to obtain the mean pre-peak entropy.

[0048] In an optional embodiment, S2 includes the following steps:

[0049] The length of the pre-peak analysis window is set to 10. The end time of the pre-peak analysis window is 1 minute before the arrival time of the first wave. ;

[0050] When calculating the permutation entropy: the embedding dimension is set to 4 and the time delay is 1, and the phase space reconstruction is performed on the time-domain waveform signal within the pre-peak analysis window;

[0051] The reconstructed vectors in the phase space are mapped to a sequence from 0 to 23;

[0052] Calculate the probability of occurrence of each sequence and then calculate the permutation entropy based on the probability distribution.

[0053] If the arrival time of the first wave is determined to be 42.5... Then 42.5 is extracted. The preceding time-domain waveform signal is used for analysis. The end time of the pre-peak analysis window is set to 41.5. That is, the first wave arrived 1 The length of the pre-peak analysis window is 10. Therefore, the data range for analysis is 31.5. Up to 41.5 This time-domain waveform signal primarily reflects the microstructure information and background noise characteristics within the material. With an embedding dimension of 4 and a time delay of 1, the one-dimensional time series signal within the pre-peak analysis window is converted into a four-dimensional vector sequence. For example, the signal point sequence... ...in sequence, they form a vector ( (), For each four-dimensional vector, the magnitudes of its four components are compared, and the permutation pattern is determined based on the ascending index. For example, the original position indices corresponding to the ascending values ​​of the vector (0.1, 0.5, 0.2, 0.8) are 1, 3, 2, 4, which is one permutation pattern. There are a total of 4 factorial (i.e., 24) possible permutations. The frequency of each permutation pattern in all four-dimensional vectors is counted to obtain the probability distribution. The permutation entropy of this time-domain waveform signal segment is calculated using the Shannon entropy formula.

[0054] S3. After the arrival time of the first wave of each time-domain waveform signal, a post-peak analysis window is set. The time-domain waveform signal within each post-peak analysis window is subjected to Hilbert-Huang transform to obtain the time spectrum. The attenuation coefficient of the instantaneous frequency centroid in each time spectrum is calculated, and the mean value of the attenuation coefficient of all receiving channels is calculated to obtain the mean value of the frequency attenuation coefficient.

[0055] Specifically, after the arrival time of the first wave of each time-domain waveform signal, a fixed length is extracted as a post-peak analysis window; for example, the fixed length is 50. Empirical mode decomposition (EMD) is performed on the time-domain waveform signal within the post-peak analysis window to obtain a series of intrinsic mode functions (IMFs). A Hilbert transform is applied to each IMF to calculate its instantaneous frequency and amplitude, thus constructing the time-domain waveform signal's frequency spectrum. On the time-spectrum, the energy-weighted average instantaneous frequency at each moment is calculated, yielding a curve showing the change of the instantaneous frequency centroid over time. This curve is then fitted to an exponential decay model, and the resulting exponent is the attenuation coefficient. The attenuation coefficients of all receiving channels are arithmetically averaged to obtain the mean frequency attenuation coefficient.

[0056] In an optional embodiment, in S3, the start time of the post-peak analysis window is set to the arrival time of the first wave, and the length of the post-peak analysis window is 100. 100 The peak-after-peak analysis window can fully capture the main peak of the time-domain waveform signal and the subsequent attenuation portion.

[0057] Specifically, at the determined arrival time of the first wave, 42.5... As the starting point of the analysis, a segment of time-domain waveform signal is selected for analysis from the starting point. The corresponding analysis window is called the post-peak analysis window, and the starting point of the post-peak analysis window is strictly aligned with the starting point of the first wave.

[0058] Preferably, the length of the post-peak analysis window is 100. The analysis time interval is from 42.5 Up to 142.5 Select 100 This is to ensure the complete detection of the main energy components of the time-domain waveform signal, including the first main peak of the time-domain waveform and the subsequent tail portion formed by scattering and multiple reflections, i.e., the coda wave. Analyzing this part of the time-domain waveform signal allows for the extraction of characteristics such as attenuation and dispersion of sound waves as they propagate in the medium. These characteristics are closely related to the density and strength of concrete.

[0059] In an optional embodiment, in S3, within the post-peak analysis window, at 1 Divide into step sizes A point in time;

[0060] Calculate the instantaneous frequency centroid value of the time-domain waveform signal at each time point. ;

[0061] The least squares method is used to analyze the data point sequence. Perform linear fitting to obtain the fitted line. Among them, slope The attenuation coefficient is... For the first At a certain point in time, The value range is from 1 to , Represents a time variable. This represents the intercept of the fitted line.

[0062] Specifically, for 100 Time-frequency analysis is performed on the time-domain waveform signal within the post-peak analysis window of a certain length, for example, using short-time Fourier transform, to obtain a two-dimensional spectrum of the time-domain waveform signal as a function of time. The two-dimensional spectrum shows which frequency components and their respective energy intensities are contained in the time-domain waveform signal within each tiny time interval.

[0063] With 1 Using a time step, sampling is performed on the time axis of the two-dimensional spectrum: at each time step, the centroid of the frequency spectrum corresponding to that time step is calculated, i.e., the instantaneous frequency centroid. The instantaneous frequency centroid is the energy-weighted average frequency of all frequency components at that moment, with higher-energy frequency components contributing more to the instantaneous frequency centroid. For example, at 45.5... The instantaneous frequency centroid is 150kHz, at 90.5 Because high frequencies decay faster, the instantaneous frequency centroid may drop to 120kHz, resulting in a series of data point pairs (time, instantaneous frequency centroid). Linear regression analysis is performed on these data point pairs to fit a straight line, and the slope of the line is... This is the frequency attenuation coefficient, which represents the rate at which the center of gravity of the signal frequency decreases over time.

[0064] S4. According to preset weights, the average sound velocity, the average pre-peak entropy, and the average frequency attenuation coefficient are linearly weighted and combined to obtain a comprehensive strength indication value. Based on the comprehensive strength indication value, the early strength of the precast component is determined through a preset strength mapping relationship.

[0065] Specifically, using data obtained from non-destructive testing and compressive strength destructive tests on standard cured specimens of different ages and mix proportions in the laboratory, a one-to-one correspondence between the comprehensive strength indication value and the compressive strength value is established, and a calibration curve is fitted, such as... Figure 2 As shown, for example, the standard curve is a second-order polynomial function. Substituting the comprehensive strength indicator value obtained from field testing into the second-order polynomial function, the calculated function value is the predicted early strength of the precast component, in MPa.

[0066] In an optional embodiment, in S4, the average sound velocity, the mean pre-peak entropy, and the mean frequency attenuation coefficient are normalized and converted into dimensionless parameters.

[0067] Using formula Calculations are performed, in which, This is the comprehensive strength indication value. , , These represent the normalized average sound velocity, the mean pre-peak entropy, and the mean frequency attenuation coefficient, respectively. , , Preset weights.

[0068] Specifically, assume that the average values ​​of the three parameters obtained from a single measurement are: average sound velocity 4100 m / s, average peak entropy 0.85, and average frequency attenuation coefficient -0.45. Since the units and numerical ranges of the three parameters are different, they need to be normalized first. For example, based on experience, the typical range of sound speed is set to 3500 to 4500 m / s, then 4100 m / s is normalized to 0.6. Similarly, the entropy value and attenuation coefficient are also converted to dimensionless values ​​between 0 and 1.

[0069] For example, after normalization, suppose the three values ​​obtained are as follows: =0.6、 =0.5、 =0.58. Using preset weights. =0.5、 =0.3、 =0.2, and perform a linear weighted summation of the three normalized parameters. Calculate the comprehensive intensity indicator value. Its value is 0.566. (Comprehensive indicator value) The information from the three physical parameters reflects the current state of the prefabricated components.

[0070] In an optional embodiment, in S4, when determining the early strength of the precast component, non-destructive testing and standard compressive strength tests are simultaneously performed on pre-made standard curing test blocks at different ages to obtain multiple sets of comprehensive strength indication values. Compressive strength value The corresponding data pairs;

[0071] Using a quadratic polynomial Fit multiple sets of corresponding data pairs to determine the coefficients. , , The intensity mapping relationship is obtained.

[0072] Specifically, a calibration model is established, and a batch of standard curing test blocks, identical to those used in actual components, are produced and cured under standard conditions. The standard curing test blocks are then tested at different curing ages, such as day 1, day 3, and day 7. At each curing age, non-destructive testing is performed using this method, and a comprehensive strength indication value is calculated. For example, the comprehensive intensity indicator value measured on the 3rd day. The value is 0.45; the standard cured specimen is placed in a compression testing machine for destructive testing to obtain the true compressive strength value. For example, 15 MPa. Repeat this process to obtain a series of data pairs (I value, S value).

[0073] After collecting enough data pairs, the data points are plotted on a coordinate system, and mathematical methods are used to find patterns among them. A quadratic polynomial is chosen. As a fitting model, regression analysis techniques such as the least squares method are used to calculate coefficients representing the trend of the data points. , , The value of this quadratic polynomial represents the preset strength mapping relationship. When it is necessary to evaluate the strength of precast components on site, only non-destructive testing is required to obtain the comprehensive strength indication value. For example, 0.566. Substituting this value into the established strength mapping relationship, the corresponding predicted compressive strength S can be calculated, which is approximately 29.32 MPa.

[0074] An embodiment of the prefabricated component early strength non-destructive testing system based on ultrasonic array provided by the present invention:

[0075] like Figure 3As shown, the precast component early strength non-destructive testing system based on ultrasonic array includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the aforementioned precast component early strength non-destructive testing method based on ultrasonic array.

[0076] The prefabricated component early strength non-destructive testing system based on ultrasonic array also includes other components well known to those skilled in the art, such as communication interfaces. Their setup and functions are known in the art and will not be described in detail here.

[0077] In addition, in the description of this specification, "multiple" means at least two, such as two, three or more, etc., unless otherwise expressly and specifically defined.

Claims

1. A method for non-destructive testing of the early strength of a precast element based on an ultrasonic array, characterized in that, The method comprises the following steps: S1, acquiring an ultrasonic array full-matrix data of a prefabricated component, and constructing a virtual sound source based on the full-matrix data through a phased focusing algorithm to obtain a time-domain waveform signal of each receiving channel; identifying a first wave arrival time for each time-domain waveform signal, and calculating an average sound speed in combination with a geometric position of each receiving channel; S2, setting a pre-peak analysis window before the first wave arrival time of each time-domain waveform signal, calculating an arrangement entropy of the time-domain waveform signal in each pre-peak analysis window, and calculating a mean value of the arrangement entropies of all receiving channels to obtain a pre-peak entropy mean value; S3, setting a post-peak analysis window after the first wave arrival time of each time-domain waveform signal, performing a Hilbert-Huang transform on the time-domain waveform signal in each post-peak analysis window to obtain a time-frequency spectrum, calculating an attenuation coefficient of an instantaneous frequency centroid in each time-frequency spectrum, and calculating a mean value of the attenuation coefficients of all receiving channels to obtain a frequency attenuation coefficient mean value; S4, linearly weighting and combining the average sound speed, the pre-peak entropy mean value, and the frequency attenuation coefficient mean value according to a preset weight to obtain a comprehensive intensity indication value; Based on the comprehensive intensity indication value, determining the early strength of the prefabricated component through a preset intensity mapping relationship.

2. The ultrasonic array-based preform early strength non-destructive testing method of claim 1, wherein, In acquiring full matrix data, an ultrasonic array probe containing elements is placed on the surface of a preform, each element is sequentially used as a transmitter to transmit an ultrasonic pulse, while all elements are used as receivers to receive signals, and the process is repeated times until all elements have been transmitted once, thereby obtaining a full matrix of data.

3. The ultrasonic array-based preform early strength non-destructive testing method of claim 1, wherein, In S1, when obtaining the time-domain waveform signals of each receiving channel, a virtual sound source point is set in the prefabricated component ; For the jth receiving channel, the time-domain waveform signal at the instant of time t is synthesized by delay superposition of the contributions of all transmitting channels, the calculation formula being: wherein is the time-domain signal transmitted by the ith transmitting array element and received by the jth receiving channel, is the time-domain signal transmitted by the ith transmitting array element and received by the jth receiving channel, is the sound wave propagation time delay from the ith transmitting array element to the virtual sound source point 4. The ultrasonic array-based preform early strength non-destructive testing method of claim 3, wherein, In S1, when identifying the first wave arrival time, for the time-domain waveform signal of each receiving channel, a ratio of an energy in a short-time window to an energy in a long-time window is calculated from a starting point of the time-domain waveform signal; The time when the ratio first exceeds an energy ratio threshold is determined as the first wave arrival time.

5. The ultrasonic array-based preform early strength non-destructive testing method of claim 1, wherein, S2 comprises the following steps: The length of the pre-peak analysis window is set to 10 ; the end time of the pre-peak analysis window is 1 second before the first wave arrival time. When calculating the arrangement entropy: setting an embedding dimension as 4 and a time delay as 1, and reconstructing a phase space for the time-domain waveform signal in the pre-peak analysis window; Mapping the vector after the phase space reconstruction into a sequence of 0 to 23; Statistically analyzing the occurrence probability of each sequence, and calculating the arrangement entropy according to the probability distribution.

6. The ultrasonic array-based preform early strength non-destructive testing method of claim 1, wherein, In S3, the start time of the post-peak analysis window is set as the first-peak arrival time, and the length of the post-peak analysis window is 100 , 100 The post-peak analysis window of 100 can completely contain the main peak and the subsequent decay part of the time-domain waveform signal.

7. The ultrasonic array-based preform early strength non-destructive testing method of claim 6, wherein, In S3, within the post-peak analysis window, the time points are divided by 1 as a step size. ​ Computing an instantaneous frequency centroid value of a time domain waveform signal at each time point ; The least squares method is used to analyze the data point sequence. Perform linear fitting to obtain the fitted line. Among them, slope The attenuation coefficient is... For the first At a certain point in time, The value range is from 1 to , Represents a time variable. This represents the intercept of the fitted line.

8. The ultrasonic array-based preform early strength non-destructive testing method of any of claims 1-7, wherein, In S4, the average sound speed, the pre-peak entropy mean value, and the frequency attenuation coefficient mean value are normalized to convert into dimensionless parameters. Using formula Calculations are performed, in which, This is the comprehensive strength indication value. , , These represent the normalized average sound velocity, the mean pre-peak entropy, and the mean frequency attenuation coefficient, respectively. , , Preset weights.

9. The ultrasonic array-based preform early strength non-destructive testing method of claim 8, wherein, In S4, when determining the early strength of the prefabricated component, through the standard curing test block prepared in advance, the nondestructive testing and standard compressive strength test are simultaneously performed at different ages to obtain multiple sets of comprehensive strength indicating values corresponding data pairs of the compressive strength value ​ using a quadratic polynomial fitting a plurality of corresponding data pairs to determine coefficients 、 、 obtaining the intensity mapping relationship.

10. A system for non-destructive testing of the early strength of a precast element based on an ultrasonic array, characterized in that The device comprises a memory and a processor, and the memory stores computer program instructions, which, when executed by the processor, implement the ultrasonic array-based early strength nondestructive testing method for a prefabricated component according to any one of claims 1-9.

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