Nondestructive testing method and system for grouting compactness of duct of prefabricated bridge pier

Abstract

The invention discloses a nondestructive testing method and system for grouting compactness of a prefabricated bridge pier duct, particularly relates to the technical field of nondestructive testing of materials, and is used for solving the problem that an existing ultrasonic testing technology is insensitive to microcosmic nonuniformity response of a grouting material. The method comprises the following steps: transmitting a first fundamental frequency ultrasonic incident signal into a prefabricated bridge pier duct, collecting a reflection echo signal, repeatedly executing to obtain a plurality of echo signals, calculating a coherence coefficient, and judging whether the coherence coefficient is higher than a preset threshold value or not to perform macroscopic defect screening. When the coherence coefficient is higher than the threshold value, at least one second fundamental frequency ultrasonic incident signal is emitted, corresponding echo signals are collected, the waveform asymmetry coefficient of each echo signal is calculated, and finally the microcosmic non-uniformity of the grouting material is evaluated based on the variation trend of the waveform asymmetry coefficients under different fundamental frequencies. And comprehensive grouting quality evaluation from macroscopic to microscopic is realized.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology for materials, and more specifically, to a method and system for nondestructive testing of the grout density of precast bridge pier ducts. Background Technology

[0002] In mountainous bridge construction, multi-segment precast piers are widely used due to their advantages such as high construction efficiency and minimal environmental impact. Among these, the "post-reinforcement method" for connecting pier segments is key to achieving rapid construction. This method involves pre-reserving longitudinal reinforcement ducts in precast segments, inserting reinforcing bars after assembly and positioning, and then injecting high-strength grout to form an integral load-bearing structure. To ensure the structural safety and durability of the pier, the density of the grout within the ducts becomes a decisive factor in quality control. Currently, conventional non-destructive testing techniques based on acoustic waves or ultrasound are commonly used in engineering to assess the quality of such concealed works. These methods primarily determine the presence of obvious macroscopic defects within the grout body, such as voids or segregation, by analyzing linear acoustic parameters such as wave velocity and amplitude attenuation of stress waves propagating in the medium.

[0003] However, the aforementioned existing detection technologies have inherent limitations. Due to their dependence on linear acoustic parameters, these methods are not sensitive to microscale non-uniformity caused by factors such as material bleeding, micro-shrinkage, or uneven mixing during the curing process of grout. Although these micro-defects do not develop into macro-voids, they significantly weaken the bond performance between steel bars and concrete, affecting the overall structural integrity. They can be regarded as a kind of hidden non-compactness, making it difficult to effectively identify and assess such defects. This leads to blind spots in quality control and poses potential risks to the long-term service performance of precast bridge piers. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a non-destructive testing method and system for the grouting density of precast bridge pier ducts to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A non-destructive testing method for the grout density of precast bridge pier ducts includes the following steps:

[0007] S1. Transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device.

[0008] S2. Acquire the ultrasonic echo signal reflected from the channel using an ultrasonic receiving device.

[0009] S3. Repeat the process at the same position in the channel to obtain multiple ultrasonic echo signals, and calculate the coherence coefficient between the multiple ultrasonic echo signals.

[0010] S4. Determine whether the coherence coefficient is higher than the preset threshold.

[0011] S5. When the coherence coefficient is higher than the preset threshold, at least one second fundamental frequency ultrasonic incident signal is emitted into the channel through the ultrasonic transmitting device and the corresponding ultrasonic echo signal is collected. The waveform asymmetry coefficient of each ultrasonic echo signal is calculated.

[0012] S6. Evaluate the micro-uniformity of grouting material based on the changing trend of waveform asymmetry coefficient of ultrasonic echo signals with different fundamental frequencies.

[0013] Furthermore, an ultrasonic incident signal of the first fundamental frequency is emitted into the duct of the precast bridge pier via an ultrasonic transmitting device, including:

[0014] The transmitting probe of the ultrasonic transmitter is coupled and fixed to the precast concrete surface at the entrance of the duct.

[0015] An ultrasonic signal generator is set up to produce a sinusoidal pulse modulated by a Hanning window with a specific pulse width as the ultrasonic incident signal with the first fundamental frequency.

[0016] The first fundamental frequency ultrasonic incident signal is transmitted to the transmitting probe through a power amplifier;

[0017] The transmitting probe is controlled to radiate an ultrasonic incident signal of the first fundamental frequency into the channel.

[0018] Furthermore, the ultrasonic echo signal reflected from the channel is acquired by an ultrasonic receiving device, including:

[0019] The receiving probe of the ultrasonic receiver is coupled and fixed to the precast concrete surface at the outlet of the duct.

[0020] The receiving probe receives ultrasonic echo signals reflected from inside the channel;

[0021] The ultrasonic echo signal is bandpass filtered and amplified by a signal conditioning circuit.

[0022] The amplified ultrasonic echo signal is converted into a digital signal and stored via an analog-to-digital converter.

[0023] Furthermore, the process is repeated at the same location in the channel to obtain multiple ultrasonic echo signals. The coherence coefficient between the multiple ultrasonic echo signals is calculated, including:

[0024] The process involves repeatedly transmitting an ultrasonic incident signal of the first fundamental frequency into the duct of the precast bridge pier via an ultrasonic transmitter and collecting ultrasonic echo signals reflected from the duct via an ultrasonic receiver at the same location in the duct.

[0025] The collected ultrasonic echo signals are time-aligned.

[0026] Calculate the cross-correlation function between each pair of time-aligned multiple ultrasonic echo signals;

[0027] The coherence coefficient between multiple ultrasonic echo signals is obtained by normalization calculation based on the maximum value of the cross-correlation function.

[0028] Furthermore, the calculation of the cross-correlation function between each pair of time-aligned ultrasonic echo signals includes: taking any two time-aligned ultrasonic echo signals as the reference signal and the comparison signal, respectively; sliding the comparison signal along the time axis in the time domain and calculating the sum of the products with the reference signal point by point; and recording the sum of the products at all sliding positions to form a sequence of cross-correlation functions.

[0029] Further, determining whether the coherence coefficient is higher than a preset threshold includes:

[0030] Obtain the coherence coefficient threshold calibrated by testing standard dense grout specimens;

[0031] The coherence coefficients among multiple calculated ultrasonic echo signals are compared with a coherence coefficient threshold.

[0032] When the coherence coefficient is greater than or equal to the coherence coefficient threshold, it is determined to pass the linear screening.

[0033] When the coherence coefficient is less than the coherence coefficient threshold, it is determined that there is a macroscopic defect.

[0034] Furthermore, when the coherence coefficient is higher than a preset threshold, at least one incident ultrasonic signal of a second fundamental frequency is emitted into the channel through the ultrasonic transmitting device, and the corresponding ultrasonic echo signal is acquired. The waveform asymmetry coefficient of each ultrasonic echo signal is calculated, including:

[0035] After determining that the linear screening has been passed, an ultrasonic signal generator is set to generate an ultrasonic incident signal with a second fundamental frequency that is an integer multiple of the first fundamental frequency;

[0036] The ultrasonic transmitter radiates a second fundamental frequency ultrasonic incident signal into the channel.

[0037] The corresponding second fundamental frequency ultrasonic echo signal is acquired by an ultrasonic receiving device.

[0038] Hilbert transform is performed on the second fundamental frequency ultrasonic echo signal to extract the signal envelope;

[0039] The ratio of the positive half-axis area to the negative half-axis area of ​​the signal envelope is calculated as the waveform asymmetry coefficient.

[0040] Furthermore, performing a Hilbert transform on the second fundamental frequency ultrasonic echo signal to extract the signal envelope includes: performing a Hilbert transform on the second fundamental frequency ultrasonic echo signal to generate an orthogonal analytic signal; combining the original second fundamental frequency ultrasonic echo signal with the Hilbert-transformed signal to form a complex analytic signal; and calculating the modulus of the complex analytic signal to obtain the envelope of the second fundamental frequency ultrasonic echo signal.

[0041] Furthermore, based on the variation trend of the waveform asymmetry coefficient of ultrasonic echo signals at different fundamental frequencies, the micro-uniformity of the grouting material is evaluated, including:

[0042] Obtain the waveform asymmetry coefficients corresponding to multiple second fundamental frequencies;

[0043] Establish the trend curve of waveform asymmetry coefficient as a function of the second fundamental frequency;

[0044] Calculate the slope variation characteristics of the trend curve;

[0045] The slope variation characteristics are compared with the reference slope range of standard dense grout;

[0046] The degree of micro-uniformity of the grouting material is determined based on the comparison results.

[0047] On the other hand, the present invention provides a non-destructive testing system for the grout density of precast bridge pier ducts, comprising the following modules:

[0048] The signal transmitting module is used to transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device.

[0049] The signal acquisition module is used to acquire the ultrasonic echo signal reflected from the channel through an ultrasonic receiving device;

[0050] The coefficient calculation module is used to repeatedly execute the process at the same location in the channel to obtain multiple ultrasonic echo signals and calculate the coherence coefficient between the multiple ultrasonic echo signals.

[0051] The threshold judgment module is used to determine whether the coherence coefficient is higher than a preset threshold.

[0052] The echo calculation module is used to transmit at least one second fundamental frequency ultrasonic incident signal into the channel through the ultrasonic transmitting device and collect the corresponding ultrasonic echo signal when the coherence coefficient is higher than a preset threshold, and to calculate the waveform asymmetry coefficient of each ultrasonic echo signal.

[0053] The microscopic evaluation module is used to evaluate the microscopic non-uniformity of grouting material based on the changing trend of the waveform asymmetry coefficient of ultrasonic echo signals at different fundamental frequencies.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. By introducing a dual mechanism of coherence coefficient screening and multi-frequency nonlinear acoustic response analysis, the depth and accuracy of grout density detection are effectively improved. First, the coherence coefficient is calculated based on repeatedly acquired ultrasonic echo signals and a threshold judgment is made, which can reliably exclude channels with macroscopic defects. This ensures that subsequent analysis focuses on areas that appear intact but may have hidden problems, significantly improving the targeting and efficiency of the detection process and avoiding unnecessary fine-tuning of obviously unqualified areas. More importantly, for channels that pass the linear screening, by emitting multiple ultrasonic signals with different fundamental frequencies and extracting the waveform asymmetry coefficient, the nonlinear acoustic response of the grout at the microscale can be sensitively captured. This response is closely related to the uniformity of the internal microstructure of the material, revealing hidden non-uniform distributions that traditional linear parameters cannot reflect.

[0056] 2. By analyzing the trend characteristics of waveform asymmetry coefficient with frequency, a quantitative assessment of the micro-uniformity of grouting material was achieved. The detection dimension was expanded from the single macroscopic defect identification to the evaluation of micro-structural characteristics, thus enabling a more comprehensive assessment of the internal quality status of the grout body. This assessment mechanism based on multi-frequency nonlinear response has a unique ability to identify microscopic variations in materials caused by factors such as bleeding and micro-shrinkage, effectively making up for the blind spots of traditional methods in the detection of micro-defects. Ultimately, it provides a comprehensive non-destructive assessment method for the grouting quality of precast bridge pier ducts, from macroscopic to microscopic and from qualitative to quantitative, which is of great value in ensuring the long-term structural performance of key stress nodes. Attached Figure Description

[0057] Figure 1 This is a flowchart of a non-destructive testing method for the grout density of precast bridge pier ducts according to the present invention;

[0058] Figure 2 This is a structural schematic diagram of a non-destructive testing system for the grout density of precast bridge pier ducts according to the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0060] Example 1: Figure 1 This invention provides a non-destructive testing method for the grout density of precast bridge pier ducts, comprising the following steps:

[0061] S1. Transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device.

[0062] S2. Acquire the ultrasonic echo signal reflected from the channel using an ultrasonic receiving device.

[0063] S3. Repeat the process at the same position in the channel to obtain multiple ultrasonic echo signals, and calculate the coherence coefficient between the multiple ultrasonic echo signals.

[0064] S4. Determine whether the coherence coefficient is higher than the preset threshold.

[0065] S5. When the coherence coefficient is higher than the preset threshold, at least one second fundamental frequency ultrasonic incident signal is emitted into the channel through the ultrasonic transmitting device and the corresponding ultrasonic echo signal is collected. The waveform asymmetry coefficient of each ultrasonic echo signal is calculated.

[0066] S6. Evaluate the micro-uniformity of grouting material based on the changing trend of waveform asymmetry coefficient of ultrasonic echo signals with different fundamental frequencies.

[0067] S1. Transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device, specifically as follows:

[0068] During the ultrasonic transmission process, the transmitting probe of the ultrasonic transmitter is first coupled and fixed to the precast concrete surface at the entrance of the channel. This coupling and fixing process involves uniformly coating the contact surface of the transmitting probe with an acoustic coupling agent, such as a silicon-based coupling agent, to fill the tiny gaps between the probe and the concrete surface, ensuring efficient transmission of acoustic energy. The fixing is achieved using a mechanical clamp with adjustable clamping force to accommodate channel entrances of different sizes, while ensuring the probe remains stable during testing and preventing signal deviation due to loosening. The precast concrete surface at the channel entrance must be thoroughly cleaned beforehand to remove dust and impurities to optimize the coupling effect. The central axis of the transmitting probe is aligned with the center of the channel to ensure that the ultrasonic incident signal propagates along the channel axis.

[0069] Next, an ultrasonic signal generator is configured to produce a sinusoidal pulse modulated with a Hanning window of a specific pulse width as the first fundamental frequency ultrasonic incident signal. The ultrasonic signal generator is a digital signal generator, and its parameters include frequency, pulse width, and modulation type. The selection of the first fundamental frequency is based on the acoustic characteristics of the grouting material. For example, the sound wave propagation speed of common grouting materials is in the range of 2000 m / s to 4000 m / s, and the first fundamental frequency is set to a value between 50 kHz and 100 kHz to balance penetration depth and resolution. The specific pulse width is determined based on the channel length and sound wave velocity. For example, for a channel with a length of 1 meter, the round-trip time of the sound wave is approximately 0.5 milliseconds, and the pulse width is set to 10 microseconds to 100 microseconds to ensure that the pulse can cover the entire channel without overlap. Hanning window modulation is implemented through a built-in function of the signal generator. The Hanning window is a window function, mathematically represented as a weighted cosine function, applied to the sinusoidal pulse to reduce spectral leakage and improve signal purity. In the specific settings, select the sine wave mode in the signal generator interface, input the first fundamental frequency value, set the pulse width parameter, and enable the Hanning window modulation option to generate a smooth pulse signal.

[0070] The primary frequency ultrasonic incident signal is then transmitted to the transmitting probe via a power amplifier. The power amplifier is a linear amplifier, and its input interface is connected to the output interface of the ultrasonic signal generator via a coaxial cable. The amplification factor is set based on the impedance of the transmitting probe and the required sound pressure level. For example, if the typical impedance of the transmitting probe is 50 ohms, the amplification factor of the power amplifier is set to 10 to 100 times, corresponding to a gain of 20 to 40 dB, to ensure sufficient signal strength to penetrate the grouting material. During transmission, the power amplifier amplifies the signal in both voltage and current, and has a built-in overload protection circuit to prevent signal distortion. The amplified signal is then transmitted to the transmitting probe via a shielded cable to reduce external electromagnetic interference.

[0071] Finally, the transmitting probe is controlled to radiate a primary frequency ultrasonic incident signal into the duct. This control process is achieved through an external trigger signal generated by the control unit, such as a microcontroller generating digital pulses to trigger the transmitting probe's operating circuitry. The transmitting probe is a piezoelectric transducer, its core being a piezoelectric ceramic element. When an electrical signal is applied, the piezoelectric effect converts electrical energy into mechanical vibration, generating ultrasonic waves that radiate into the duct. The radiation direction is along the duct axis, ensuring that the ultrasonic incident signal uniformly covers the grouting area. The control timing is synchronized with the signal generator; for example, radiation is initiated at the rising edge of the trigger signal, and the duration matches the pulse width, ensuring signal continuity. The radiating surface of the transmitting probe remains parallel to the duct inlet plane to ensure that the ultrasonic incident signal enters the duct perpendicularly, reducing signal reflection loss.

[0072] S2. Acquire the ultrasonic echo signal reflected from the channel using an ultrasonic receiving device, specifically as follows:

[0073] In the ultrasonic receiving process, the receiving probe of the ultrasonic receiving device is first coupled and fixed to the precast concrete surface at the outlet of the channel. This coupling and fixing process involves uniformly coating the contact surface of the receiving probe with an acoustic coupling agent, such as a silicon-based coupling agent, to fill the tiny gaps between the probe and the concrete surface, ensuring efficient transmission of acoustic energy to the receiving probe. The fixing method utilizes a mechanical clamp with adjustable clamping force to accommodate outlets of different sizes, while ensuring the probe remains stable during testing, preventing signal acquisition deviations due to loosening. The precast concrete surface at the outlet of the channel must be thoroughly cleaned beforehand to remove dust and impurities to optimize the coupling effect. The central axis of the receiving probe is aligned with the center of the channel to ensure effective capture of ultrasonic echo signals reflected from inside the channel. The receiving probe is a piezoelectric transducer, with a piezoelectric ceramic element at its core. When mechanical vibration acts on the probe, the piezoelectric effect converts mechanical energy into an electrical signal, achieving signal reception. The amount of coupling agent used is determined experimentally. For example, in typical applications, the coating thickness is controlled between 0.1 mm and 0.5 mm to balance acoustic transmission efficiency and signal attenuation.

[0074] The receiving probe receives ultrasonic echo signals reflected from inside the channel. This reception process is based on the piezoelectric effect; when the ultrasonic echo signal reaches the receiving probe, the piezoelectric ceramic element deforms, generating a corresponding voltage signal. The characteristics of the ultrasonic echo signal depend on the acoustic properties of the grout. For example, in dense grout, the sound wave propagation speed is approximately 3000 meters per second, and the echo signal frequency range is related to a first fundamental frequency. For example, when the first fundamental frequency is 50 kHz, the echo signal frequency is mainly distributed between 40 kHz and 60 kHz. The sensitivity of the receiving probe is determined through calibration, for example, by testing the relationship between the probe's output voltage and sound pressure level under known conditions using a standard sound source to ensure the accuracy of signal acquisition. The operating bandwidth of the receiving probe covers the first fundamental frequency and its harmonic components; for example, the bandwidth is set to 20 kHz to 200 kHz to capture the complete echo signal. During signal reception, the probe's directional pattern ensures that reflected signals are primarily received along the channel axis, reducing lateral interference. The output interface of the receiving probe is connected to the signal conditioning circuit via a shielded cable to reduce the introduction of electromagnetic noise.

[0075] The ultrasonic echo signal undergoes bandpass filtering and amplification via a signal conditioning circuit. The bandpass filtering is implemented using an active filter circuit, with its passband frequency range set based on a primary fundamental frequency and the expected signal characteristics. For example, the lower passband limit is set to 0.8 times the primary fundamental frequency, and the upper passband limit is set to 1.2 times the primary fundamental frequency to retain useful signals and suppress noise. A Butterworth filter of order 4 is used to provide a flat passband response and steep stopband attenuation. The filter design parameters are determined through circuit simulation; for example, resistor and capacitor values ​​are selected based on passband frequency calculations to ensure effective filtering. A programmable gain amplifier is used for amplification. The amplification factor is dynamically adjusted according to the echo signal amplitude. For example, the initial amplification factor is set to 20 dB, and then automatically adjusted to the range of 40 to 60 dB based on the signal peak value to ensure the signal amplitude is at an appropriate level in subsequent processing. The amplification factor adjustment is based on the input range of the analog-to-digital converter (ADC). For example, if the ADC input voltage range is 0 V to 5 V, the amplifier output signal amplitude is controlled between 1 V and 4 V to avoid saturation or distortion. The signal conditioning circuit is powered by a voltage regulator to ensure operational stability. The bandpass filtering and amplification processes are performed in the order of filtering first, followed by amplification, to reduce the impact of noise during the amplification process.

[0076] The amplified ultrasonic echo signal is converted into a digital signal and stored via an analog-to-digital converter (ADC). The ADC's sampling rate is set based on the signal frequency and the Nyquist theorem, typically set to at least 10 times the fundamental frequency, with a typical value of 500 kHz to 1 MHz, to ensure distortion-free signal acquisition. The ADC resolution is chosen to be 16-bit to provide sufficient dynamic range to capture signal details. The conversion process is triggered by an external clock, synchronized with the sampling rate, for example, using a crystal oscillator to generate a stable clock signal. The digital signal is stored in non-volatile memory, such as flash memory or a solid-state drive, in binary file format, containing timestamps and signal data. The storage path is managed through a file system, for example, generating a separate file for each test point, with the filename including the channel identifier and test time. The storage capacity is determined based on the test duration; for example, for a 10-second acquisition, the data volume is approximately 10 megabytes, with a 20% margin reserved for unexpected situations. The ADC's reference voltage source uses a precision voltage reference, such as 2.5 volts, to ensure conversion accuracy. Digital signal transmission is achieved through a serial interface, such as SPI or I2C protocols, to communicate with the host control unit and complete the storage operation. During storage, a data buffering mechanism is used to handle real-time data streams, such as using double buffering technology to avoid data loss.

[0077] S3. Repeat the process at the same location in the channel to obtain multiple ultrasonic echo signals, and calculate the coherence coefficient between the multiple ultrasonic echo signals. The specific implementation is as follows:

[0078] In implementing the signal repetitive acquisition and coherence coefficient calculation steps, the process involves repeatedly transmitting a first-frequency ultrasonic incident signal into the precast bridge pier's duct via an ultrasonic transmitter and acquiring the reflected ultrasonic echo signal via an ultrasonic receiver at the same location within the duct. This repetitive execution process is programmed through a control unit, for example, setting the repetition count to 5 to 10 times to obtain multiple ultrasonic echo signals for subsequent statistical analysis. The interval between repetitions is set based on signal attenuation characteristics, for example, an interval of 1 to 10 milliseconds, ensuring that each transmission and acquisition is independent and avoiding signal superposition interference. Maintaining the same location is achieved by fixing the transmitting and receiving probes with mechanical clamps. The clamps have positioning pins or alignment marks to ensure that the probes do not shift during multiple executions. The control unit synchronously triggers the ultrasonic transmitter and receiver, for example, using digital trigger signals to ensure timing consistency. Each acquired ultrasonic echo signal is stored in a memory and appended with a sequence identifier, for example, numbered sequentially as signal 1 to signal N, where N is the repetition count. The number of repetitions is selected based on the signal-to-noise ratio requirements. For example, preliminary experiments have shown that signal stability reaches over 95% when the number of repetitions is greater than 5. The transmission and acquisition cycle is controlled by a timer in the control unit, with the timer period matched to the interval time. For example, a period of 2 milliseconds corresponds to a repetition frequency of 500 Hz. Multiple stored ultrasonic echo signals retain their original data format, including amplitude and time information, for subsequent processing.

[0079] Multiple acquired ultrasonic echo signals undergo time alignment. Time alignment is based on the signal's starting point or characteristic peaks, for example, using the first zero-crossing point of each ultrasonic echo signal as the alignment reference point. The alignment method employs an interpolation algorithm, such as linear interpolation or spline interpolation, to resample the signals onto a unified time axis. The starting point of the time axis is defined as the trigger time of the first signal, and the ending point is determined based on the signal length, for example, a signal length set to 100 microseconds to 500 microseconds, corresponding to the round-trip time of the acoustic wave in the channel. The parameters of the interpolation algorithm are set through calibration, for example, the interpolation step size is set to 1 / 10 of the sampling interval to improve alignment accuracy. Before time alignment, each ultrasonic echo signal is preprocessed, for example, to remove DC offset and noise. DC offset is achieved by calculating the signal mean and subtracting it, and noise removal uses a moving average filter with a window size set to 5 to 10 sampling points. The aligned signals are stored as an array with a uniform array length of the maximum value, for example, 1000 data points, padded with zeros if necessary. The accuracy of time alignment is verified through cross-correlation, such as calculating the correlation coefficient between the aligned signals to ensure that the correlation coefficient is greater than 0.95. The alignment process is performed by a digital signal processor, which loads the signal data, applies an interpolation function, and outputs multiple time-aligned ultrasonic echo signals.

[0080] The cross-correlation function is calculated between each pair of time-aligned ultrasonic echo signals. The cross-correlation function calculation uses any two time-aligned ultrasonic echo signals as the reference and comparison signals, respectively. For example, signal pairs are selected sequentially from the aligned signal group, such as signal 1 and signal 2, signal 1 and signal 3, etc., until all combinations are covered. The comparison signal is slid along the time axis within the time domain, with the sliding step size set based on the sampling interval. For example, a step size of 1 sampling point corresponds to a time interval of 1 to 10 microseconds. The sum of products with the reference signal is calculated point by point. The product sum is calculated as the sum of the products of each data point of the reference signal and the corresponding data point of the comparison signal at the sliding position. For example, for a signal of length L, the product sum is expressed as the sum of the products of the reference signal data points and the comparison signal data points. The product sum values ​​at all sliding positions are recorded to form a cross-correlation function sequence. The sequence length depends on the sliding range. For example, the sliding range is set to be from the negative maximum delay to the positive maximum delay, where the maximum delay is determined based on the signal length, such as being set to 1 / 2 of the signal length. The cross-correlation function sequence is stored as an array, with the array index corresponding to the sliding position. The calculation process is executed iteratively by the processor, for example, by using a loop structure to traverse all sliding positions and signal pairs. The peak position of the cross-correlation function indicates the time difference between the signals and is used to evaluate signal consistency.

[0081] The coherence coefficient between multiple ultrasonic echo signals is obtained by normalizing the results based on the maximum value of the cross-correlation function. The normalization calculation first extracts the maximum value of each cross-correlation function sequence, for example, by traversing an array to find the maximum value. After maximum value extraction, the average of all cross-correlation function maximum values ​​is calculated as the normalization benchmark, for example, averaging the maximum values ​​of all pairwise cross-correlation functions calculated for N signals. The coherence coefficient is defined as the ratio of each cross-correlation function maximum value to the normalization benchmark, for example, the ratio is calculated by dividing the maximum value by the benchmark value, with the result ranging from 0 to 1. The coherence coefficient calculation covers all signal pairs; for example, for N signals, N×(N-1) / 2 coherence coefficient values ​​are calculated. Finally, the coherence coefficient between multiple ultrasonic echo signals is the average of all ratios, for example, the average coherence coefficient is used as the overall evaluation index. The normalization process ensures that the results are not affected by signal amplitude; for example, even if the signal amplitudes are different, the ratio still reflects consistency. The calculation is performed by a processor, for example, using an arithmetic logic unit for division and averaging operations. The coherence coefficient is output as a scalar value and stored in the results file, along with additional test condition information such as channel identification and test time.

[0082] Calculating the cross-correlation function between pairwise time-aligned ultrasonic echo signals involves using any two time-aligned ultrasonic echo signals as a reference signal and a comparison signal, respectively. The selection order of the reference and comparison signals is based on the signal sequence, for example, selecting them in index order from the time-aligned signal array, such as first taking the signal at index 0 as the reference signal and the signal at index 1 as the comparison signal, and then iterating through all combinations. Within the time domain, the comparison signal is slid along the time axis, from the negative maximum delay to the positive maximum delay; for example, the maximum delay is set to 50% of the signal length to ensure coverage of all possible time differences. The product sum with the reference signal is calculated point-by-point. The product sum is calculated by multiplying the reference signal value at time point i by the comparison signal value at time point i plus k for each sliding position k, where i traverses all valid data points. The product sum values ​​at all sliding positions are recorded to form a cross-correlation function sequence, which is stored as an array, with the array index corresponding to the sliding position offset. This process is implemented by the processor using nested loops; for example, the outer loop traverses the sliding positions, and the inner loop traverses the data points for multiplication and accumulation. The cross-correlation function sequence is used for subsequent analysis, such as peak detection and normalization.

[0083] S4. Determine whether the coherence coefficient is higher than the preset threshold. The specific implementation is as follows:

[0084] When determining whether the coherence coefficient exceeds a preset threshold, the first step is to obtain the coherence coefficient threshold calibrated through testing standard dense grout specimens. The standard dense grout specimens are prepared based on material proportions and curing specifications used in engineering practice. For example, ordinary silicate cement, standard sand, and distilled water are mixed in a mass ratio of 1:2:0.4, cast into cylindrical specimens with a diameter of 50 mm and a height of 100 mm, and cured for 28 days at 20°C and 95% humidity to achieve the designed density. The calibration process uses ultrasonic transmitters and receivers consistent with those used in field testing. Probes are coupled and fixed to the specimen surface, and the transmission of ultrasonic incident signals and the acquisition of echo signals are repeatedly performed. For example, each specimen is tested 10 times, multiple ultrasonic echo signals are acquired, and the coherence coefficient is calculated. The coherence coefficient threshold is calibrated through statistical analysis, such as calculating the average and standard deviation of the coherence coefficients of all tested specimens. The threshold is set as the average minus twice the standard deviation to cover 95% of the variation range of the dense samples. The threshold is stored in non-volatile memory in floating-point format, with numerical precision retained to four decimal places, and is accompanied by calibration information such as material batch and test date. The threshold is obtained through a calibration procedure executed by a control unit, such as a microcontroller, which reads the stored test data and calculates statistics to ensure that the threshold reflects the acoustic characteristic benchmark of the compacted grout.

[0085] The coherence coefficients of multiple calculated ultrasonic echo signals are compared with a coherence coefficient threshold. The comparison process is implemented using a digital comparator integrated into the processor, for example, using an arithmetic logic unit to perform floating-point comparison operations. Input parameters include the coherence coefficients obtained from step S3 and the coherence coefficient threshold read from threshold storage. The coherence coefficients are scalar values, for example, ranging from 0 to 1, and the threshold is a specific value, for example, 0.85. The comparison logic is based on numerical magnitude relationships, for example, performing a sign judgment on the difference between the coherence coefficient and the threshold; if the difference is greater than or equal to zero, the condition of greater than or equal to is considered true. Comparison accuracy is guaranteed by the data format; for example, both the coherence coefficients and the threshold are represented as 32-bit floating-point numbers, and rounding errors are ignored during comparison. The comparison result is output as a Boolean value, such as true or false, stored in a temporary register, and used in subsequent decision steps. The timing of the comparison process is synchronized by the system clock, for example, executed immediately after the data ready signal is triggered, ensuring real-time performance.

[0086] When the coherence coefficient is greater than or equal to the coherence coefficient threshold, the linear screening is considered passed. The judgment process is based on the comparison result Boolean value; for example, when the Boolean value is true, the control unit sets the status flag to pass. The status flag is stored in the result register, which is 1 bit wide; for example, 0 indicates failure and 1 indicates pass. The judgment output of passing the linear screening is displayed through a user interface, such as displaying "pass" on an LCD screen, or transmitted to a host computer via a communication interface. The judgment logic is integrated into the control software, for example, using conditional branch instructions to jump to the pass processing routine when the condition is met. Passing the linear screening indicates that the grouting material in the duct meets the compaction requirements on a macroscopic scale, allowing for subsequent microscopic non-uniformity assessment steps. The judgment result is stored including a timestamp and test location information, for example, written to a database record for future reference.

[0087] When the coherence coefficient is less than the coherence coefficient threshold, a macroscopic defect is identified. The determination process is also based on a Boolean comparison result; for example, when the Boolean value is false, the control unit sets the status flag to indicate the presence of a macroscopic defect. The status flag is stored in a defect register, which is 1 bit wide; for example, 0 indicates no defect, and 1 indicates a defect. The determination of a macroscopic defect triggers an alarm mechanism, such as activating an audible and visual alarm or generating a defect report file and saving it to memory. The determination logic is implemented by the control unit firmware, for example, using an interrupt service routine to handle defect conditions. The presence of a macroscopic defect indicates that the grouting material in the ducts may contain voids, cracks, or loose areas, requiring further manual inspection or repair. The determination result is recorded, including the defect level and location coordinates, for example, by adding a defect description and recommended measures to the log file.

[0088] S5. When the coherence coefficient is higher than a preset threshold, at least one second fundamental frequency ultrasonic incident signal is emitted into the channel through the ultrasonic transmitting device and the corresponding ultrasonic echo signal is collected. The waveform asymmetry coefficient of each ultrasonic echo signal is calculated. Specifically, the implementation is as follows:

[0089] When calculating the waveform asymmetry coefficient, after determining that the linear screening has passed, the ultrasonic signal generator is set to generate an ultrasonic incident signal with a second fundamental frequency that is an integer multiple of the first fundamental frequency. This setting process is triggered based on the linear screening result; for example, when the control unit detects that the linear screening status flag is true, the second fundamental frequency signal generation program is automatically started. The integer multiple relationship between the second fundamental frequency and the first fundamental frequency is achieved through frequency multiplication. For example, if the first fundamental frequency is 50 kHz, the second fundamental frequency is set to 100 kHz or 150 kHz, i.e., a 2x or 3x relationship, to detect the nonlinear acoustic response of the grouting material at different frequencies. The selection of the integer multiple is determined based on material property experiments. For example, pre-testing has shown that the sensitivity to micro-inhomogeneities is optimal when the multiple is in the range of 2 to 5. The parameters of the ultrasonic signal generator include frequency value, pulse width, and modulation type. For example, the pulse width is set to the same range as the first fundamental frequency signal, from 10 microseconds to 100 microseconds, and the modulation method maintains a Hanning window modulated sine wave pulse to ensure signal consistency. The setup process is completed through control software. For example, users can input a second baseband value or select a preset multiplier on the user interface, and the signal generator generates the corresponding waveform according to the instructions. The generation timing of the second baseband signal is independent of the first baseband signal; for example, it starts 1 millisecond after passing linear screening to avoid signal interference. The generated second baseband ultrasonic incident signal is temporarily stored in a buffer memory, awaiting the transmission command.

[0090] A second fundamental frequency ultrasonic incident signal is radiated into the duct using an ultrasonic transmitter. The same ultrasonic transmitter with the same frequency as the first fundamental frequency is used for the radiation process. The transmitter probe is kept coupled and fixed to the precast concrete surface at the duct entrance, with the coupling agent application and clamp fixation methods consistent with previous steps. Radiation control is driven by a power amplifier, the amplification factor of which is adjusted according to the second fundamental frequency. For example, due to the significant attenuation of high-frequency signals, the amplification factor is set 10% to 20% higher than the first fundamental frequency to ensure signal strength. The radiation direction is along the duct axis to ensure the ultrasonic incident signal covers the grouting area. Radiation timing is synchronized by an external trigger, such as a trigger signal generated by a control unit to trigger the transmitter probe's operating circuit; the radiation duration is matched to the pulse width. During radiation, the impedance matching of the transmitter probe is monitored, for example, by adjusting it in real time using an impedance analyzer to optimize energy transmission efficiency. The quality of the radiated signal is detected by backscattering, for example, by collecting a small amount of reflected signal to verify waveform integrity and ensure no distortion.

[0091] The corresponding second fundamental frequency ultrasonic echo signal is acquired using an ultrasonic receiving device. The acquisition process uses the same ultrasonic receiving device as the first fundamental frequency, with the receiving probe fixedly coupled to the precast concrete surface at the channel outlet. This coupling is maintained through periodic checks. The receiving probe captures the second fundamental frequency ultrasonic echo signal reflected from inside the channel. The signal frequency range is related to the second fundamental frequency; for example, when the second fundamental frequency is 100 kHz, the echo signal is mainly distributed between 80 kHz and 120 kHz. The acquisition timing is synchronized with radiation, for example, starting acquisition after a predicted propagation time following radiation triggering to avoid noise. The signal conditioning circuit performs bandpass filtering and amplification on the second fundamental frequency ultrasonic echo signal. The passband range of the bandpass filter is set based on the second fundamental frequency; for example, the lower passband is 0.8 times the second fundamental frequency, and the upper passband is 1.2 times the second fundamental frequency to retain useful components. The amplification process uses a programmable gain amplifier, with the gain value adaptively adjusted according to the signal amplitude. For example, the initial gain is set to 30 dB, and then dynamically adjusted to the range of 50 dB to 70 dB based on the signal peak value. The analog-to-digital converter (ADC) converts the amplified second fundamental frequency ultrasonic echo signal into a digital signal. The sampling rate is set based on the second fundamental frequency and the Nyquist theorem, for example, a sampling rate of more than 10 times the second fundamental frequency, typically 1 MHz to 2 MHz, while maintaining a 16-bit resolution. The converted digital signal is stored in non-volatile memory, with the storage format including time series and amplitude values, and an additional frequency identifier for subsequent processing.

[0092] A Hilbert transform is performed on the second fundamental frequency ultrasonic echo signal to extract the signal envelope. The Hilbert transform is implemented using a digital signal processing algorithm executed in a processor, such as using a finite impulse response filter or a fast convolution method to generate an orthogonal analytic signal. The generation of the orthogonal analytic signal involves applying a Hilbert kernel function to each data point of the second fundamental frequency ultrasonic echo signal. The kernel function is a weighted sequence based on sine and cosine functions; for example, the kernel length is set to 1 / 10 of the signal length to balance computational accuracy and efficiency. The original second fundamental frequency ultrasonic echo signal is used as the real part, and the Hilbert-transformed signal is used as the imaginary part. These are combined to form a complex analytic signal, and the real and imaginary parts of the complex analytic signal are stored in a parallel array. The magnitude of the complex analytic signal is calculated to obtain the envelope of the second fundamental frequency ultrasonic echo signal. The magnitude is calculated by taking the square root of the square of the real part plus the square of the imaginary part at each data point. For example, an iterative algorithm or a lookup table is used to implement the square root operation to ensure numerical stability. After envelope extraction, smoothing is performed to reduce noise, for example, by applying a moving average filter with a window size of 5 to 10 sampling points. The envelope data is stored as a new time series for subsequent waveform asymmetry coefficient calculation, retaining time alignment information during storage.

[0093] The ratio of the positive to negative half-axis area of ​​the signal envelope is calculated as the waveform asymmetry coefficient. The positive half-axis area is calculated as the integral of the envelope over all positive values ​​on the time axis, and the negative half-axis area is calculated as the integral of all negative values. Numerical integration methods, such as the trapezoidal rule or rectangular rule, are used, with the step size consistent with the sampling interval. The calculation of the positive and negative half-axis areas is based on the envelope data points. For example, for each data point, if the value is greater than zero, it is added to the positive half-axis area; if the value is less than zero, it is added to the negative half-axis area. The sum is multiplied by the sampling interval to obtain the area value. The ratio is calculated by dividing the positive half-axis area by the negative half-axis area, and the result is used as the waveform asymmetry coefficient. For example, the ratio ranges from 0 to positive infinity, with a typical value close to 1 for dense grout. The calculation process is executed by the processor, for example, using a floating-point unit for division and accumulation operations. The waveform asymmetry coefficient is output as a scalar value, stored in the results file, and accompanied by test parameters such as the second fundamental frequency value and the acquisition time. Normalization of the ratio is optional, such as by dividing by a reference value to adjust the scale, but in this step the original ratio is used directly to reflect the asymmetry.

[0094] The process of extracting the signal envelope from the second fundamental frequency ultrasonic echo signal involves performing a Hilbert transform on the second fundamental frequency ultrasonic echo signal to generate an orthogonal analytic signal. The Hilbert transform is implemented using discrete-time signal processing techniques, such as converting the signal in the frequency domain using a Fast Fourier Transform (FFT), multiplying it by the Hilbert transfer function, and then inversely transforming it back to the time domain. The transfer function is the imaginary sign function. The generation of the orthogonal analytic signal ensures a 90-degree phase difference with the original signal, for example, through convolution operations, with the convolution kernel being a discrete sequence based on the sampling rate. The original second fundamental frequency ultrasonic echo signal and the Hilbert-transformed signal are combined to form a complex analytic signal. The real part of the complex analytic signal represents the original signal value, and the imaginary part represents the transformed signal value. The data is stored as a complex array. The magnitude of the complex analytic signal is calculated to obtain the envelope of the second fundamental frequency ultrasonic echo signal. The magnitude is calculated as the amplitude at each complex point, for example, using a square root algorithm, with the number of iterations set based on accuracy requirements. After envelope extraction, baseline correction is performed, for example, by subtracting the mean to eliminate DC offset and ensure accurate area calculation. This sub-step is integrated into the signal processing pipeline and executed efficiently by a digital signal processor, for example, by using parallel processing units to accelerate transformation and modulus calculation.

[0095] S6. Based on the changing trend of the waveform asymmetry coefficient of ultrasonic echo signals at different fundamental frequencies, the micro-uniformity of the grouting material is evaluated. The specific implementation is as follows:

[0096] When evaluating the microscopic non-uniformity of the grouting material, the waveform asymmetry coefficients corresponding to multiple second fundamental frequencies are first acquired. This acquisition process is based on the waveform asymmetry coefficient results calculated and stored in step S5. For example, waveform asymmetry coefficient data at different second fundamental frequency values ​​are read from non-volatile memory. The data storage format is key-value pairs, where the key is the second fundamental frequency value and the value is the corresponding waveform asymmetry coefficient. The range of multiple second fundamental frequencies is experimentally determined. For example, the second fundamental frequency values ​​include 100 kHz, 150 kHz, and 200 kHz, covering integer multiples of the first fundamental frequency from 2 to 4 times, to obtain sufficient frequency points for trend analysis. The waveform asymmetry coefficients are acquired in ascending order of the second fundamental frequency values. For example, starting from 100 kHz, data at 150 kHz and 200 kHz are read sequentially to ensure a continuous data sequence. The acquired data is temporarily stored in the processor's cache. The cache size is set according to the data volume, for example, 4 bytes of floating-point data are used for each frequency point, and the total data volume does not exceed 1 kilobyte. The data validation steps include checking the validity of the waveform asymmetry coefficients, for example, by using range checks to ensure the coefficients are between 0 and 10, and excluding outliers. The acquisition method is implemented through control software, such as using data reading functions to load data from a file or database, and attaching timestamps and test location identifiers for traceability.

[0097] A trend curve is established to show the waveform asymmetry coefficient as a function of the second fundamental frequency. The trend curve is built based on multiple acquired second fundamental frequencies and corresponding waveform asymmetry coefficient data points. For example, a scatter plot is created in a two-dimensional coordinate system with the second fundamental frequency as the x-axis and the waveform asymmetry coefficient as the y-axis. The scale of the coordinate system is set according to the data range, for example, the x-axis range is from 100 kHz to 200 kHz, and the y-axis range is from 0.5 to 2.0, to ensure the curve is displayed completely. The trend curve is fitted using least squares linear regression, for example, calculating the linear relationship between the waveform asymmetry coefficient and the second fundamental frequency to generate a straight line or curve to represent the trend. The fitting process is executed by the processor, for example, using a linear algebra library to calculate the slope and intercept. The goodness of fit is evaluated using the correlation coefficient, with a correlation coefficient threshold set above 0.8 to ensure the reliability of the curve. The data points for the trend curve are stored as an array, with array elements including the second fundamental frequency value and the fitted waveform asymmetry coefficient value. Curve visualization is optional, such as displaying a graph on the user interface, or simply retaining the data for subsequent calculations. The purpose of establishing a trend curve is to quantify the variation of waveform asymmetry coefficient with frequency, providing a basis for slope analysis.

[0098] The slope variation characteristic of the trend curve is calculated. This calculation is based on the fitting result of the trend curve. For example, for a linear trend curve, the slope is the coefficient of the fitted straight line, representing the rate at which the waveform asymmetry coefficient changes with the second fundamental frequency. For nonlinear curves, the slope variation characteristic is achieved through piecewise slope or derivative calculation. For example, the second fundamental frequency range is divided into multiple intervals, and the average slope of each interval is calculated. The slope is calculated by dividing the change in the waveform asymmetry coefficient within the interval by the change in the second fundamental frequency. The derivative calculation uses numerical differentiation methods, such as the central difference method, with a step size set to half the second fundamental frequency interval to ensure accuracy. The output of the slope variation characteristic includes the slope value and the magnitude of change. For example, the slope value is stored as a floating-point array, and the magnitude of change is calculated as the difference between the maximum and minimum slopes. The calculation process is performed by an arithmetic logic unit, for example, using an iterative loop to traverse all data points for differentiation. Normalization of the slope variation characteristic is optional, such as adjusting the scale by dividing by a reference slope, but the original value is retained in this step to reflect the actual change. The calculation result is temporarily stored in a register and used in subsequent comparison steps.

[0099] The slope variation characteristics are compared with the baseline slope range of a standard dense grout. The baseline slope range is obtained through testing and calibration of standard dense grout specimens. The preparation of standard dense grout specimens is consistent with the coherence coefficient threshold calibration in step S4. For example, specimens are prepared using the same material ratio and curing conditions, tested at multiple second fundamental frequencies, and the slope of the trend curve is calculated. The slope value distribution of all specimens is statistically analyzed. The baseline slope range is set as the average slope value plus or minus one standard deviation to cover 68% of the variation in dense samples. The comparison process uses a digital comparator, for example, comparing the calculated slope variation characteristics with the lower and upper limits of the baseline slope range to determine whether the slope value falls within the range. The comparison logic is based on interval checks; for example, if the slope value is greater than or equal to the lower limit and less than or equal to the upper limit, it is determined to meet the baseline; otherwise, it is determined to deviate. The comparison accuracy is guaranteed by the data format; for example, both the slope and the baseline value are represented as 32-bit floating-point numbers. The comparison result is output as a Boolean value or a level indicator, such as 0 indicating within the range, 1 indicating below the range, and 2 indicating above the range. The comparison timing is synchronized with the system clock, for example, it is executed immediately after the slope calculation is completed to ensure real-time performance.

[0100] The degree of micro-uniformity of the grouting material is determined based on comparison results. The determination process is based on Boolean values ​​or level indicators of the comparison results. For example, a result within the baseline slope range is considered micro-uniform; a result below the baseline slope range is considered slightly non-uniform; and a result above the baseline slope range is considered significantly non-uniform. The determination logic is integrated into the control software, for example, using conditional branching statements to jump to the corresponding determination routine based on the comparison result. The degree of micro-uniformity is graded using predefined thresholds; for example, slightly non-uniform corresponds to a slope value below the baseline range but with a difference within 10%, while significantly non-uniform corresponds to a difference exceeding 10%. The determination results are output to the user interface, such as displaying text descriptions or color codes, and simultaneously stored in a results file. The storage format includes the non-uniformity level, test time, and location information. The determination process is calibrated experimentally, for example, using samples with known non-uniformity to test and adjusting the grading thresholds to ensure accuracy. The final determination is used to guide engineering decisions; for example, uniform samples require no treatment, while non-uniform samples are recommended for further testing or repair.

[0101] Example 2: Figure 2 A structural schematic diagram of a non-destructive testing system for the grout density of precast bridge pier ducts is provided. The system includes the following modules:

[0102] The signal transmitting module is used to transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device.

[0103] The signal acquisition module is used to acquire the ultrasonic echo signal reflected from the channel through an ultrasonic receiving device;

[0104] The coefficient calculation module is used to repeatedly execute the process at the same location in the channel to obtain multiple ultrasonic echo signals and calculate the coherence coefficient between the multiple ultrasonic echo signals.

[0105] The threshold judgment module is used to determine whether the coherence coefficient is higher than a preset threshold.

[0106] The echo calculation module is used to transmit at least one second fundamental frequency ultrasonic incident signal into the channel through the ultrasonic transmitting device and collect the corresponding ultrasonic echo signal when the coherence coefficient is higher than a preset threshold, and to calculate the waveform asymmetry coefficient of each ultrasonic echo signal.

[0107] The microscopic evaluation module is used to evaluate the microscopic non-uniformity of grouting material based on the changing trend of the waveform asymmetry coefficient of ultrasonic echo signals at different fundamental frequencies.

[0108] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0109] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0110] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0111] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0113] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0114] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A non-destructive testing method for the grout density of precast bridge pier ducts, characterized in that, Includes the following steps: S1. Transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device. S2. Acquire the ultrasonic echo signal reflected from the channel using an ultrasonic receiving device. S3. Repeat the process at the same position in the channel to obtain multiple ultrasonic echo signals, and calculate the coherence coefficient between the multiple ultrasonic echo signals. S4. Determine whether the coherence coefficient is higher than the preset threshold. S5. When the coherence coefficient is higher than the preset threshold, at least one second fundamental frequency ultrasonic incident signal is emitted into the channel through the ultrasonic transmitting device and the corresponding ultrasonic echo signal is collected. The waveform asymmetry coefficient of each ultrasonic echo signal is calculated. S6. Evaluate the micro-uniformity of grouting material based on the changing trend of waveform asymmetry coefficient of ultrasonic echo signals with different fundamental frequencies.

2. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 1, characterized in that, An ultrasonic incident signal of the first fundamental frequency is emitted into the duct of the precast bridge pier through an ultrasonic transmitting device, including: The transmitting probe of the ultrasonic transmitter is coupled and fixed to the precast concrete surface at the entrance of the duct. An ultrasonic signal generator is set up to produce a sinusoidal pulse modulated by a Hanning window with a specific pulse width as the ultrasonic incident signal with the first fundamental frequency. The first fundamental frequency ultrasonic incident signal is transmitted to the transmitting probe through a power amplifier; The transmitting probe is controlled to radiate an ultrasonic incident signal of the first fundamental frequency into the channel.

3. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 2, characterized in that, The ultrasonic echo signal reflected from the channel is acquired by an ultrasonic receiving device, including: The receiving probe of the ultrasonic receiver is coupled and fixed to the precast concrete surface at the outlet of the duct. The receiving probe receives ultrasonic echo signals reflected from inside the channel; The ultrasonic echo signal is bandpass filtered and amplified by a signal conditioning circuit. The amplified ultrasonic echo signal is converted into a digital signal and stored via an analog-to-digital converter.

4. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 3, characterized in that, The process is repeated at the same location in the channel to obtain multiple ultrasonic echo signals. The coherence coefficient between the multiple ultrasonic echo signals is calculated, including: The process involves repeatedly transmitting an ultrasonic incident signal of the first fundamental frequency into the duct of the precast bridge pier via an ultrasonic transmitter and collecting ultrasonic echo signals reflected from the duct via an ultrasonic receiver at the same location in the duct. The collected ultrasonic echo signals are time-aligned. Calculate the cross-correlation function between each pair of time-aligned multiple ultrasonic echo signals; The coherence coefficient between multiple ultrasonic echo signals is obtained by normalization calculation based on the maximum value of the cross-correlation function.

5. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 4, characterized in that, The calculation of the cross-correlation function between multiple time-aligned ultrasonic echo signals includes: taking any two time-aligned ultrasonic echo signals as the reference signal and the comparison signal, respectively; sliding the comparison signal along the time axis in the time domain and calculating the sum of the products with the reference signal point by point; and recording the sum of the products at all sliding positions to form a sequence of cross-correlation functions.

6. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 4, characterized in that, Determining whether the coherence coefficient is higher than a preset threshold includes: Obtain the coherence coefficient threshold calibrated by testing standard dense grout specimens; The coherence coefficients among multiple calculated ultrasonic echo signals are compared with a coherence coefficient threshold. When the coherence coefficient is greater than or equal to the coherence coefficient threshold, it is determined to pass the linear screening. When the coherence coefficient is less than the coherence coefficient threshold, it is determined that there is a macroscopic defect.

7. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 6, characterized in that, When the coherence coefficient is higher than a preset threshold, at least one second fundamental frequency ultrasonic incident signal is emitted into the channel through the ultrasonic transmitting device, and the corresponding ultrasonic echo signal is acquired. The waveform asymmetry coefficient of each ultrasonic echo signal is calculated, including: After determining that the linear screening has been passed, an ultrasonic signal generator is set to generate an ultrasonic incident signal with a second fundamental frequency that is an integer multiple of the first fundamental frequency; The ultrasonic transmitter radiates a second fundamental frequency ultrasonic incident signal into the channel. The corresponding second fundamental frequency ultrasonic echo signal is acquired by an ultrasonic receiving device. Hilbert transform is performed on the second fundamental frequency ultrasonic echo signal to extract the signal envelope; The ratio of the positive half-axis area to the negative half-axis area of ​​the signal envelope is calculated as the waveform asymmetry coefficient.

8. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 7, characterized in that, The process of extracting the signal envelope by performing a Hilbert transform on the second fundamental frequency ultrasonic echo signal includes: performing a Hilbert transform on the second fundamental frequency ultrasonic echo signal to generate an orthogonal analytic signal; combining the original second fundamental frequency ultrasonic echo signal with the Hilbert-transformed signal to form a complex analytic signal; and calculating the modulus of the complex analytic signal to obtain the envelope of the second fundamental frequency ultrasonic echo signal.

9. The non-destructive testing method for the grout density of precast bridge pier ducts according to claim 7, characterized in that, The micro-uniformity of grouting material is evaluated based on the variation trend of waveform asymmetry coefficient of ultrasonic echo signals at different fundamental frequencies, including: Obtain the waveform asymmetry coefficients corresponding to multiple second fundamental frequencies; Establish the trend curve of waveform asymmetry coefficient as a function of the second fundamental frequency; Calculate the slope variation characteristics of the trend curve; The slope variation characteristics are compared with the reference slope range of standard dense grout; The degree of micro-uniformity of the grouting material is determined based on the comparison results.

10. A non-destructive testing system for the grout density of precast bridge pier ducts, used to implement the non-destructive testing method for the grout density of precast bridge pier ducts as described in any one of claims 1-9, characterized in that, Includes the following modules: The signal transmitting module is used to transmit a first fundamental frequency ultrasonic incident signal into the duct of the precast bridge pier through an ultrasonic transmitting device. The signal acquisition module is used to acquire the ultrasonic echo signal reflected from the channel through an ultrasonic receiving device; The coefficient calculation module is used to repeatedly execute the process at the same location in the channel to obtain multiple ultrasonic echo signals and calculate the coherence coefficient between the multiple ultrasonic echo signals. The threshold judgment module is used to determine whether the coherence coefficient is higher than a preset threshold. The echo calculation module is used to transmit at least one second fundamental frequency ultrasonic incident signal into the channel through the ultrasonic transmitting device and collect the corresponding ultrasonic echo signal when the coherence coefficient is higher than a preset threshold, and to calculate the waveform asymmetry coefficient of each ultrasonic echo signal. The microscopic evaluation module is used to evaluate the microscopic non-uniformity of grouting material based on the changing trend of the waveform asymmetry coefficient of ultrasonic echo signals at different fundamental frequencies.

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