UHPC wet joint construction quality intelligent control method and system

Abstract

This invention discloses an intelligent control method and system for the construction quality of UHPC wet joints, specifically relating to the field of automatic control technology for construction processes. It addresses the problem of inaccurate control caused by environmental vibration interference in existing wet joint construction. The method involves collecting vibration signals from multiple preset locations on the wet joint structure, extracting first-type frequency domain features related to construction operations and second-type frequency domain features related to environmental disturbances, identifying vibration types based on feature energy distribution and transient characteristics, analyzing the attenuation gradient of energy values ​​with distance when identified as construction vibration to assess structural coupling, evaluating the concentration of the first-type frequency domain features based on structural coupling to assess construction vibration stability, adjusting the control parameters of the vibration equipment, and finally executing the adjusted control parameters to control the vibration operation, thereby achieving intelligent control of the construction quality of wet joints.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology for construction processes, and more specifically, to an intelligent control method and system for the construction quality of UHPC wet joints. Background Technology

[0002] In bridge reconstruction and expansion projects, ultra-high performance concrete (UHPC) wet joint technology is often used to ensure effective connection between the old and new structures. To ensure the compactness and material uniformity of the joint pouring, key processes such as vibration must be controlled during construction. Existing technologies typically rely on preset construction parameters and sensors to monitor vibration, aiming to maintain the stability of construction operations through feedback information.

[0003] However, the aforementioned existing technologies have significant drawbacks in practical applications. Since wet joint construction is often carried out under complex environmental interference such as existing traffic loads, the vibration signals collected by the monitoring system are actually a mixed response of construction operation and external environmental vibration. Existing methods cannot effectively distinguish the source of the signal, which may cause the system to misjudge harmless environmental disturbances as abnormal construction conditions, thereby generating incorrect control commands. This not only interferes with the normal construction rhythm, but may also directly affect the final forming quality of the joint due to inaccurate control, posing a potential risk in quality control. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method and system for intelligent control of construction quality of UHPC wet joints 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 method for intelligent control of construction quality of wet joints in UHPC includes the following steps:

[0007] S1. Collect vibration signals at multiple preset locations on the wet joint structure;

[0008] S2. Extract the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances from the vibration signal, respectively.

[0009] S3. Based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics, the vibration signal is identified as construction vibration or environmental vibration.

[0010] S4. When the vibration signal is identified as construction vibration, calculate the energy value of the vibration signal at multiple preset locations and analyze the attenuation gradient of the energy value as the distance between the preset location and the vibration source increases. Evaluate the structural coupling degree based on the steepness of the attenuation gradient.

[0011] S5. Based on the structural coupling degree analysis, the concentration of the first type of frequency domain characteristics is used to evaluate the stability of construction vibration, and the control parameters of the vibrating equipment are adjusted according to the stability evaluation results.

[0012] S6. Execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joint.

[0013] Furthermore, vibration signals were collected at multiple preset locations on the wet joint structure, including:

[0014] Vibration sensors are pre-positioned at the interface between the old and new concrete in the wet joint structure, and vibration sensors are also pre-positioned at the action area of ​​the vibrating equipment. Vibration signals are collected synchronously through the vibration sensors.

[0015] Furthermore, from the vibration signal, the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances are extracted, including:

[0016] Spectral analysis is performed on the vibration signal to obtain the frequency component distribution of the vibration signal;

[0017] The energy of the main frequency band is calculated based on the frequency component distribution as the first type of frequency domain feature;

[0018] Simultaneously, the presence of transient pulse components in the vibration signal is detected as a second type of frequency domain feature.

[0019] Furthermore, based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics, the vibration signal is identified as construction vibration or environmental vibration, including:

[0020] Determine whether the proportion of the main frequency band energy in the first type of frequency domain features exceeds the first threshold and whether the amplitude of the transient pulse component in the second type of frequency domain features is lower than the second threshold.

[0021] When the energy proportion of the main frequency band exceeds the first threshold and the amplitude of the transient pulse component is lower than the second threshold, the vibration signal is identified as construction vibration; otherwise, the vibration signal is identified as environmental vibration.

[0022] Furthermore, when the vibration signal is identified as construction vibration, the energy values ​​of the vibration signals at multiple preset locations are calculated, and the attenuation gradient of the energy value as the distance between the preset location and the vibration source increases is analyzed. The structural coupling degree is evaluated based on the steepness of the attenuation gradient, including:

[0023] Calculate the energy value of the vibration signal at each preset position and establish a relationship model between the energy value and the distance from the corresponding preset position to the vibration source.

[0024] The attenuation gradient of energy value as a function of distance is determined using a relational model;

[0025] Evaluate structural coupling based on the linearity of the decay gradient;

[0026] A higher linearity indicates a better structural coupling.

[0027] Furthermore, the energy value of the vibration signal at each preset position is calculated, and a relationship model between the energy value and the distance from the corresponding preset position to the vibration source is established. This includes: calculating the energy value by performing square integral on the vibration signal at each preset position, and then linearly fitting the energy value with the distance from the corresponding preset position to the vibration source to establish a relationship model.

[0028] Furthermore, the linearity assessment of structural coupling based on the decay gradient includes: calculating the sum of squared residuals between the data points in the relational model and the fitted straight line to assess linearity; the smaller the sum of squared residuals, the higher the structural coupling.

[0029] Furthermore, the concentration of the first type of frequency domain characteristics is analyzed based on structural coupling to assess the stability of construction vibration, and the control parameters of the vibrating equipment are adjusted according to the stability assessment results, including:

[0030] A stability evaluation index is established based on the structural coupling degree and the dispersion of the main frequency band energy distribution in the first type of frequency domain characteristics;

[0031] When the stability assessment index is lower than the set threshold, increase the vibration intensity control parameter of the vibratory equipment.

[0032] When the stability assessment index is not lower than the set threshold, maintain or reduce the vibration intensity control parameters of the vibratory equipment.

[0033] Furthermore, the adjusted control parameters are executed to control the vibratory equipment to vibrate the wet joints, including:

[0034] The adjusted vibration intensity control parameters are output to the controller of the vibration equipment;

[0035] The controller drives the vibratory equipment to perform vibration operation on the wet joints using the adjusted vibration intensity control parameters.

[0036] On the other hand, the present invention provides an intelligent control system for the construction quality of UHPC wet joints, comprising the following modules:

[0037] The signal acquisition module is used to acquire vibration signals at multiple preset locations on the wet joint structure;

[0038] The feature extraction module is used to extract, from the vibration signal, the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances, respectively.

[0039] The vibration identification module is used to identify vibration signals as construction vibration or environmental vibration based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics.

[0040] The coupling evaluation module is used to calculate the energy values ​​of vibration signals at multiple preset locations and analyze the attenuation gradient of the energy values ​​as the distance between the preset location and the vibration source increases when the vibration signal is identified as construction vibration. The structural coupling degree is evaluated based on the steepness of the attenuation gradient.

[0041] The parameter adjustment module is used to evaluate the stability of construction vibration by analyzing the concentration of the first type of frequency domain characteristics based on the structural coupling degree, and to adjust the control parameters of the vibrating equipment according to the stability evaluation results.

[0042] The operation execution module is used to execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joint.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. By separating construction characteristics from environmental disturbance characteristics from mixed vibration signals, precise perception and closed-loop control of the vibration process are achieved. First, frequency domain analysis and transient detection technology effectively distinguish between construction vibration and environmental vibration, eliminating the misleading influence of environmental interference such as traffic loads on the control system, enabling the system to accurately identify the actual construction state. On this basis, by analyzing the energy propagation characteristics of construction vibration signals, the structural coupling state of the interface between new and old concrete is evaluated in real time. Then, the vibration parameters are dynamically adjusted according to the coupling quality, significantly improving the reliability of vibration signal analysis, avoiding the misoperation that is easily caused by traditional single threshold judgment, and ensuring the accurate generation of control commands.

[0045] 2. Through the synergistic analysis of structural coupling degree and vibration characteristic concentration, a complete quality feedback closed loop was constructed. It can determine the interface bonding quality based on the attenuation law of vibration energy in the structure, and automatically optimize the vibration intensity parameters accordingly. This realizes a complete automated chain from condition monitoring to process adjustment, effectively overcoming the limitations of traditional reliance on fixed parameters or manual experience. It ensures that the vibration operation is always in the optimal working state, significantly improving the density and uniformity of UHPC material in the joint area, and providing a reliable guarantee for the overall performance of the bridge structure. Attached Figure Description

[0046] Figure 1 This is a flowchart of an intelligent control method for construction quality of UHPC wet joints according to the present invention;

[0047] Figure 2 This is a schematic diagram of the structure of an intelligent control system for the construction quality of UHPC wet joints according to the present invention. Detailed Implementation

[0048] 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.

[0049] Example 1: Figure 1 This invention presents an intelligent control method for the construction quality of wet joints in UHPC (Ultra-High-Performance PC), which includes the following steps:

[0050] S1. Collect vibration signals at multiple preset locations on the wet joint structure;

[0051] S2. Extract the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances from the vibration signal, respectively.

[0052] S3. Based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics, the vibration signal is identified as construction vibration or environmental vibration.

[0053] S4. When the vibration signal is identified as construction vibration, calculate the energy value of the vibration signal at multiple preset locations and analyze the attenuation gradient of the energy value as the distance between the preset location and the vibration source increases. Evaluate the structural coupling degree based on the steepness of the attenuation gradient.

[0054] S5. Based on the structural coupling degree analysis, the concentration of the first type of frequency domain characteristics is used to evaluate the stability of construction vibration, and the control parameters of the vibrating equipment are adjusted according to the stability evaluation results.

[0055] S6. Execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joint.

[0056] S1. Collect vibration signals from multiple preset locations on the wet joint structure, specifically as follows:

[0057] During the construction of wet-joint structures, acquiring vibration signals first requires determining multiple preset locations. These locations are selected based on the geometric characteristics and stress analysis of the wet-joint structure to ensure comprehensive capture of vibration propagation characteristics. Specifically, preset locations include the interface between new and old concrete and the area of ​​action of the vibrating equipment. These locations are determined through engineering drawings and on-site measurements. For example, at the interface, points are selected at certain intervals from the edge of the interface, while in the area of ​​action of the vibrating equipment, points are arranged in a ring or linear array around the insertion point of the vibrating rod. The vibration sensor uses a piezoelectric accelerometer, which works by utilizing the characteristic that piezoelectric materials generate electric charge signals when subjected to mechanical vibration. The sensor is fixed to the concrete surface with epoxy resin to ensure close contact with the structure and reduce signal loss. When arranging the sensor, its axis must be aligned with the direction of vibration propagation to accurately measure the vibration acceleration value.

[0058] When deploying vibration sensors at the interface between new and old concrete, the specific boundary of the interface should first be identified. This boundary is determined through visual inspection or non-destructive testing methods such as ultrasonic scanning. Then, sensors are symmetrically placed on both sides of the interface, for example, selecting three points on each side, with the spacing between the points evenly distributed according to the length of the interface to ensure coverage of the entire interface area. Before installation, the sensors should be calibrated to check their frequency response range and sensitivity, ensuring linear operation within the construction vibration frequency range. During installation, avoid placing the sensors in areas with dense reinforcement or aggregate to prevent signal distortion, and use protective covers to protect the sensors from construction debris.

[0059] When deploying vibration sensors in the vibratory compaction equipment's operating area, first determine the working radius and insertion depth of the vibrator. Based on these parameters, arrange a sensor array around the compaction point. For example, with the compaction point as the center, place a sensor at regular intervals in the radial direction. The distance values ​​are set based on vibration energy attenuation experimental data to ensure monitoring of the spatial distribution of vibration energy. The sensor type should be consistent with the interface to ensure data comparability. During installation, use magnetic bases or clamps for quick fixation to accommodate the movement needs of the vibratory compaction equipment. After deployment, verify the signal connectivity of all sensors by applying test vibration to check if the output waveform is normal.

[0060] When synchronously acquiring vibration signals using vibration sensors, a central control unit sends a synchronization trigger signal to all sensors. This synchronization signal is transmitted via wired or wireless communication protocols, such as Ethernet or Bluetooth, ensuring that all sensors begin data acquisition at the same time. Acquisition parameter settings include sampling frequency and sampling duration. The sampling frequency is set according to the Nyquist theorem and is twice the expected highest vibration frequency. The sampling duration covers the entire vibration operation cycle. During data acquisition, signal quality is monitored in real time. If signal saturation or excessive noise is detected, sensor gain or filtering settings are dynamically adjusted. The acquired vibration signals are stored in time-series format in a data logger for subsequent feature extraction and analysis.

[0061] S2. Extract the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances from the vibration signal, specifically as follows:

[0062] When extracting features from vibration signals, the first step is to preprocess the acquired vibration signals to eliminate noise interference. Preprocessing methods include smoothing the original signal using a digital filter. The digital filter is designed as a low-pass filter, and the cutoff frequency is set according to the typical frequency range of construction vibration and environmental disturbances. For example, the cutoff frequency can be set to a value higher than the operating frequency of the vibrating equipment by a certain proportion to ensure that the main frequency components of construction vibration are preserved while suppressing high-frequency noise. The preprocessed vibration signal is used for subsequent frequency domain feature extraction to ensure that the data quality meets the analysis requirements.

[0063] When performing spectral analysis on a vibration signal to obtain its frequency component distribution, a frequency domain transformation method is used to convert the time-domain vibration signal into a frequency-domain representation. This method is based on the Discrete Fourier Transform (DFT) principle and obtains the frequency component distribution by calculating the amplitude of the vibration signal at different frequency points. In practice, the vibration signal is divided into multiple time windows, the length of which is set according to the duration of the vibration signal. For example, the time window length can cover several vibration cycles to ensure sufficiently high frequency resolution. Then, a frequency domain transformation is applied to the signal within each time window to obtain the corresponding frequency amplitude spectrum. The frequency amplitude spectrum represents the energy distribution of the vibration signal at each frequency component. The output of the frequency component distribution includes the frequency axis and the corresponding amplitude data, which are used for subsequent feature calculations.

[0064] When calculating the dominant frequency band energy based on the frequency component distribution as a first-type frequency domain feature, the dominant frequency band in the frequency component distribution is first identified. The dominant frequency band is defined as the continuous frequency range with the highest amplitude. The identification method is achieved by finding the peak region in the frequency amplitude spectrum. For example, an amplitude threshold is set, and the frequency range with amplitude exceeding the threshold is determined as the dominant frequency band. The amplitude threshold is dynamically adjusted according to the overall amplitude level of the frequency component distribution. For example, the threshold can be set as a certain multiple of the average amplitude of the frequency amplitude spectrum. The dominant frequency band energy is obtained by integrating the sum of the squares of the amplitudes at all frequency points within the dominant frequency band. The integration process accumulates the values ​​of the frequency amplitude spectrum within the dominant frequency band, and the result is used as the dominant frequency band energy value. This value characterizes the degree of concentration of vibration energy caused by construction operations.

[0065] Simultaneously detecting the presence of transient pulse components in vibration signals as a second type of frequency domain feature involves using time-domain analysis to identify sudden high-amplitude events in the vibration signal. The detection process includes calculating the envelope of the vibration signal, obtained through Hilbert transform or peak detection methods, and then analyzing the changing trend of the envelope to locate transient pulses. In practice, a pulse detection threshold is set, calculated based on the standard deviation or average amplitude of the vibration signal. For example, the threshold can be set as the average signal amplitude plus a certain multiple of the standard deviation. When the envelope exceeds this threshold, a transient pulse component is determined to exist. The characteristic parameters of the transient pulse component include pulse amplitude, duration, and occurrence time; these parameters are used to distinguish vibrations caused by environmental disturbances.

[0066] When calculating the dominant frequency band energy, it is necessary to ensure that the definition of the dominant frequency band is consistent with the characteristics of the construction equipment. For example, the operating frequency range of the vibrating equipment can be obtained through experimental measurements or equipment manuals. The range of the dominant frequency band should be set within this operating frequency range to avoid mistakenly including other frequency components in the calculation. After the dominant frequency band energy is calculated, normalization is performed to eliminate the influence of signal amplitude variations. The normalization method divides the dominant frequency band energy by the total energy of the entire frequency component distribution to obtain a relative energy value, which serves as the final output of the first type of frequency domain feature.

[0067] When detecting transient pulse components, considering the diversity of environmental disturbances, the pulse detection threshold needs to be dynamically adjusted based on historical data or field conditions. For example, a baseline threshold can be set by analyzing the statistical characteristics of vibration signals when there is no construction activity, and then updated in real time according to signal changes during construction. The detected transient pulse components are further analyzed for their temporal characteristics, such as calculating the rise and fall times of the pulses, to distinguish different types of disturbance sources, such as traffic loads or mechanical impacts.

[0068] During spectral analysis, the accuracy of the frequency component distribution depends on the sampling frequency and signal length. The sampling frequency is set based on the highest frequency component of the vibration signal; for example, the sampling frequency should be at least twice the expected highest frequency to satisfy the Nyquist sampling theorem. The signal length is selected according to the analysis requirements, such as covering the entire vibration operation cycle to ensure completeness. The calculation results of the frequency component distribution are stored in the form of a spectrum or data list for easy feature extraction and comparison later.

[0069] The calculation of the dominant frequency band energy involves the selection of the frequency bandwidth. A bandwidth that is too narrow may miss important frequency components, while a bandwidth that is too wide may introduce noise. Therefore, the bandwidth is set based on the typical frequency width of construction vibration. For example, the main frequency range of vibration is determined through preliminary experiments, and the dominant frequency band is set within this range. During energy calculation, a numerical integration method is used to sum the frequency amplitude spectrum within the dominant frequency band. The integration result is expressed in energy units, such as square millimeters per square second, to maintain dimensional consistency.

[0070] The detection of transient pulse components must consider the influence of signal baseline drift. In the preprocessing stage, high-pass filtering or baseline correction methods are used to eliminate low-frequency drift, ensuring the accuracy of pulse detection. The detection algorithm uses a sliding window approach to analyze the vibration signal in real time. The window size is set according to the expected duration of the pulse; for example, the window length covers several sampling points to capture short-term pulse events. When the signal within the window exceeds a threshold, the pulse characteristics are recorded.

[0071] The entire feature extraction process ensures the independence of the first and second types of frequency domain features. The first type of frequency domain features focuses on the steady-state vibration characteristics of construction operations, while the second type targets transient events caused by environmental disturbances. These two types of features are processed in parallel to improve recognition efficiency. After extraction, the feature data is used for subsequent vibration signal classification and stability assessment, forming a complete quality control chain.

[0072] S3. Based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics, the vibration signal is identified as construction vibration or environmental vibration. Specifically, this is implemented as follows:

[0073] In the process of vibration signal identification, the first type of frequency domain features and the second type of frequency domain features extracted from the vibration signal are first obtained. The first type of frequency domain features include the proportion of the main frequency band energy, which is calculated by dividing the main frequency band energy by the total energy of the vibration signal. The total energy is obtained by summing the squares of the amplitudes of all frequency points in the entire frequency component distribution. The proportion of the main frequency band energy characterizes the relative magnitude of the construction vibration energy in the total vibration energy. The second type of frequency domain features includes the amplitude of the transient pulse component, which is obtained by detecting sudden pulse events in the vibration signal and recording their maximum amplitude. A pulse event is defined as the process in which the signal amplitude rises sharply and recovers rapidly in a short period of time.

[0074] When determining whether the proportion of the main frequency band energy in the first type of frequency domain characteristics exceeds the first threshold, the first threshold is set based on the statistical analysis of historical construction vibration data. Specifically, the proportion of the main frequency band energy of multiple construction vibration samples is collected, and the statistical distribution characteristics of these values ​​are calculated, such as the mean and standard deviation. The first threshold is set as the mean plus a certain number of times the standard deviation to ensure that the energy concentration of typical construction vibrations can be covered, while avoiding misjudgment of environmental vibrations. The first threshold is expressed as a percentage, for example, the value range is between 60% and 80%, and is adjusted according to specific construction conditions and equipment types.

[0075] When determining whether the amplitude of transient pulse components in the second type of frequency domain features is lower than the second threshold, the setting of the second threshold is based on the feature analysis of environmental disturbance vibration data. By collecting pure environmental disturbance samples, such as vibration signals caused by traffic loads or wind-induced vibrations, the amplitude of transient pulse components in these samples is extracted, and their statistical characteristics are calculated. For example, the maximum value or percentile of the amplitude is taken as a reference. The second threshold is set as this reference value minus a certain margin to distinguish between construction vibration and environmental disturbance. The unit of the second threshold is consistent with the unit of vibration signal amplitude, such as millimeters per second squared. The specific value is dynamically adjusted according to the on-site environmental noise level.

[0076] When the energy proportion of the main frequency band exceeds the first threshold and the amplitude of the transient pulse component is lower than the second threshold, the vibration signal is identified as construction vibration. This judgment logic is based on the characteristic that construction vibration usually manifests as energy concentrated in a specific frequency band and lacks sudden pulses. The identification process is implemented through comparison circuits or program conditional statements. For example, logical AND operation is used to check whether two conditions are met at the same time. When the conditions are met, the classification label of construction vibration is output.

[0077] When the energy proportion of the main frequency band does not exceed the first threshold or the amplitude of the transient pulse component is not lower than the second threshold, the vibration signal is identified as environmental vibration. This identification takes into account that environmental disturbances often have random pulses and dispersed energy distribution. The identification results are stored in the form of binary flags or text descriptions for subsequent quality control steps.

[0078] When setting the first threshold, the influence of the type of construction equipment and the state of concrete must be considered. For example, different vibrating equipment has different operating frequency ranges, which leads to differences in the benchmark value of the main frequency band energy ratio. Therefore, the first threshold is determined through on-site calibration tests. During calibration, vibration signals under normal construction conditions are recorded, the typical range of the main frequency band energy ratio is calculated, and the first threshold is set near the lower limit of this range to ensure sensitivity.

[0079] When setting the second threshold, the spatiotemporal changes of environmental disturbances need to be considered. For example, during busy traffic hours, the amplitude of environmental vibration is higher, so the second threshold is increased accordingly, while it is decreased during quiet nighttime hours. The dynamic adjustment of the second threshold is achieved by real-time monitoring of the environmental vibration background value. For example, vibration signals when there is no construction are collected at regular intervals to update the statistical benchmark of transient pulse component amplitude.

[0080] During the judgment process, the calculation of the main frequency band energy ratio must ensure the accuracy of the total energy. The total energy calculation includes all frequency components to avoid omitting low-frequency or high-frequency components. The frequency component distribution comes from the spectrum analysis results. The parameters of the spectrum analysis, such as frequency resolution and window function type, must be consistent to ensure feature comparability.

[0081] The detection of transient pulse component amplitude needs to eliminate the influence of signal noise. High-frequency noise is eliminated by preprocessing filtering. The pulse amplitude is taken as the maximum value of the detected pulse event. The amplitude unit is consistent with the original vibration signal, such as the unit of acceleration, to maintain the uniformity of dimensions.

[0082] The identification logic is implemented iteratively, processing each vibration signal segment independently. The length of the signal segment is set according to the duration of vibration, for example, each segment covers several seconds of data to ensure timely identification. The identification results are associated with timestamps to facilitate the tracing of vibration events.

[0083] The entire identification process ensures the coordinated use of the first type of frequency domain features and the second type of frequency domain features. The first type of frequency domain features reflects the steady-state characteristics of vibration, while the second type of frequency domain features reflects the transient characteristics of vibration. The dual judgment improves the classification accuracy. The identified construction vibration or environmental vibration labels are used in subsequent steps such as structural coupling degree assessment, forming a coherent quality control process.

[0084] S4. When the vibration signal is identified as construction vibration, calculate the energy value of the vibration signal at multiple preset locations and analyze the attenuation gradient of the energy value as the distance between the preset location and the vibration source increases. Assess the structural coupling degree based on the steepness of the attenuation gradient. Specifically, the implementation is as follows:

[0085] When a vibration signal is identified as construction vibration, the data segments identified as construction vibration are first filtered out from the collected vibration signals. These data segments correspond to vibration signals at multiple preset locations. The preset locations are distributed on the wet joint structure, including the interface between new and old concrete and the area where the vibrating equipment acts. The location of the vibration source is determined by the construction drawings or obtained by on-site measurement. For example, the vibration source is the insertion point of the vibrating rod, and its coordinates are measured and recorded by a total station or GPS device. The distance from the preset location to the vibration source is obtained by calculating the straight-line distance between the two points. The distance unit is meters or millimeters to maintain the consistency of the units.

[0086] When calculating the energy value of the vibration signal at each preset position, the square integration method is used to process the vibration signal. The square integration is achieved by performing point-to-point squaring on the time series data of the vibration signal, and then performing numerical integration on the squared sequence in the time domain. The numerical integration adopts the trapezoidal rule or the rectangular rule, and the squared signal values ​​are accumulated within the sampling time interval to obtain the energy value. The unit of the energy value is related to the physical quantity of the vibration signal. For example, if the vibration signal is an acceleration signal, the energy unit can be square millimeters per square second. During the calculation, it is necessary to ensure that the sampling frequency is consistent to avoid errors.

[0087] When establishing the relationship model between energy value and the distance from the corresponding preset position to the vibration source, a linear fitting method is used to associate the energy value with the distance. The linear fitting is achieved through the least squares principle, finding a straight line that minimizes the sum of squares of the deviations between the data points of energy value and distance and the straight line. The fitting process includes calculating the slope and intercept of the straight line. The slope represents the attenuation gradient, and the intercept represents the theoretical energy value at the vibration source. The relationship model is expressed in the form of a linear equation, for example, the energy value equals the slope multiplied by the distance plus the intercept.

[0088] When determining the decay gradient of energy value as a function of distance using a relational model, the decay gradient is directly obtained from the slope of the linear fit. A negative slope value indicates that the energy decays as the distance increases, and the larger the absolute value of the slope, the faster the decay. The unit of the decay gradient is related to the units of energy and distance. For example, if the energy unit is square millimeters per square second and the distance unit is meters, then the unit of the decay gradient is square millimeters per square second per meter.

[0089] When assessing structural coupling based on the linearity of attenuation gradient, linearity is evaluated by calculating the sum of squared residuals between the data points in the relational model and the fitted straight line. The sum of squared residuals is the sum of the squares of the differences between the actual energy value of each data point and the predicted value of the fitted straight line. The smaller the sum of squared residuals, the better the data point fits the straight line, the higher the linearity, and the better the structural coupling. Structural coupling characterizes the bonding quality of the interface between the old and new concrete in wet joints. High linearity indicates that vibration energy propagates uniformly in the structure and that the interface coupling is good.

[0090] When calculating the energy value, the square integral needs to take into account the duration of the vibration signal to ensure that the integral covers the entire construction vibration event. For example, the integration interval should be from the beginning to the end of the vibration to avoid the loss of some signals. After the energy value is calculated, it should be normalized, for example, by dividing by the signal length, to eliminate the influence of time length and facilitate comparison at different locations.

[0091] During linear fitting, distance data needs to be accurately measured. The distance value is calculated from the preset position coordinates and vibration source coordinates. The coordinate measurement uses engineering measuring instruments with an accuracy of millimeters to ensure the reliability of the distance data. If outliers occur during fitting, such as abnormally high or low energy values, they can be removed using statistical methods such as the Laida criterion to improve the fitting accuracy.

[0092] The calculation of the residual sum of squares involves calculating the residual for each data point at a preset location. The residual is the actual energy value minus the predicted value of the fitted line. Then, all residuals are squared and summed. The value of the residual sum of squares is expressed in the square of energy units, such as square millimeters squared per fourth power second. When calculating, it is necessary to ensure that there are enough data points, such as at least three preset locations, to ensure statistical significance.

[0093] The assessment of structural coupling is based on the magnitude of the residual sum of squares. The residual sum of squares is judged by setting a reference threshold, which is determined by historical data or experiments. For example, the distribution of the residual sum of squares is calculated in a known well-coupled wet joint sample, and the upper quantile of the distribution is taken as the threshold. When the residual sum of squares is lower than the threshold, the structural coupling is considered to be high.

[0094] The steepness of the attenuation gradient is reflected by the absolute value of the slope. A large absolute value of the slope indicates rapid attenuation, which may be due to structural defects or interface discontinuities. However, when combined with linearity evaluation, if the linearity is high, even if the attenuation is rapid, the coupling may still be good. Therefore, a comprehensive judgment is required.

[0095] When calculating energy values, vibration signals need to be preprocessed, such as by filtering to remove high-frequency noise, to ensure that the energy values ​​accurately reflect the characteristics of construction vibration. The preprocessing parameters are consistent with those in the feature extraction stage.

[0096] The applicability of linear fitting is verified by correlation coefficient. The correlation coefficient calculates the degree of linear correlation between energy value and distance. A value close to 1 indicates a strong linear relationship, but in this embodiment, the sum of squared residuals is mainly used as the linearity index.

[0097] The threshold setting for the residual sum of squares takes into account construction conditions and material properties, such as concrete strength or type of vibrating equipment. The threshold is adjusted through on-site calibration tests, which are conducted on wet joints with known quality conditions, and the correspondence between the residual sum of squares and the degree of coupling is recorded.

[0098] Throughout the process, the data flow progresses from vibration signals to energy values, then to relational models and attenuation gradients, ultimately outputting structural coupling degree assessment results. This ensures logical closure between steps, consistent terminology, and that all calculations are based on correct physical dimensions, making implementation feasible.

[0099] S5. Based on the structural coupling degree analysis, the concentration of the first type of frequency domain characteristics is used to evaluate the stability of construction vibration, and the control parameters of the vibrating equipment are adjusted according to the stability evaluation results. The specific implementation is as follows:

[0100] When assessing the stability of construction vibration by analyzing the concentration of the first type of frequency domain features based on structural coupling degree, the structural coupling degree and the first type of frequency domain features extracted from the vibration signal are first obtained. The structural coupling degree comes from the linearity assessment result of the vibration energy attenuation gradient of the wet joint structure. The first type of frequency domain features include the main frequency band energy, which is calculated through spectrum analysis and represents the degree of concentration of vibration energy in the main frequency band.

[0101] When establishing a stability assessment index based on structural coupling degree and the dispersion of the main frequency band energy distribution in the first type of frequency domain characteristics, the dispersion of the main frequency band energy distribution is obtained by calculating the statistical variance of the main frequency band energy values ​​at multiple time windows or spatial locations. The statistical variance is calculated as the average of the sum of squares of the differences between the main frequency band energy values ​​and their average values. The larger the dispersion value, the more dispersed the main frequency band energy distribution and the worse the stability. The structural coupling degree is expressed in numerical form, such as the normalized value from the sum of squared residuals. The smaller the sum of squared residuals, the higher the structural coupling degree. The stability assessment index is established by weighting the structural coupling degree and the dispersion of the main frequency band energy distribution. The weighting combination adopts a linear weighting method. For example, the stability assessment index is equal to the structural coupling degree multiplied by the first weight plus the reciprocal of the dispersion of the main frequency band energy distribution multiplied by the second weight. The first and second weights are determined based on historical construction data through regression analysis. The regression analysis uses a multiple linear model to fit the relationship between the structural coupling degree and the dispersion degree and the known stability state. The weight values ​​range from zero to one to ensure that the index value is within a predetermined range, such as zero to one hundred. The higher the stability assessment index value, the better the construction vibration stability.

[0102] When the stability assessment index is lower than the set threshold, the vibration intensity control parameter of the vibrating equipment is increased. The set threshold is determined through experimental calibration. During experimental calibration, the values ​​of the stability assessment index are recorded under normal construction conditions, and the statistical distribution of these values ​​is calculated. For example, the lower percentile of the distribution is taken as the threshold. The threshold is expressed in numerical form, such as fifty. When the stability assessment index is lower than this threshold, the construction vibration is determined to be unstable, and the vibration intensity control parameter needs to be increased. The vibration intensity control parameter includes the vibration frequency or the vibration amplitude. The increase of the vibration intensity control parameter is achieved by adjusting the driving voltage or current of the vibrating equipment. For example, the vibration frequency is increased by a certain percentage or the vibration amplitude is increased by a certain amount. The adjustment amount is set based on the difference between the stability assessment index and the threshold. The larger the difference, the larger the adjustment amount, to ensure that the vibration effect is improved.

[0103] When the stability assessment index is not lower than the set threshold, the vibration intensity control parameters of the vibrating equipment are maintained or reduced. If it is not lower than the set threshold, it means that the construction vibration is in a stable state. Maintaining the vibration intensity control parameters means maintaining the current vibration frequency or vibration amplitude. Reducing the vibration intensity control parameters means reducing the vibration frequency or vibration amplitude. The degree of reduction is determined based on the extent to which the stability assessment index is higher than the threshold. The greater the amplitude, the greater the reduction, in order to optimize energy consumption and avoid over-vibration.

[0104] When calculating the dispersion of the main frequency band energy distribution, the main frequency band energy values ​​of multiple vibration signal segments are used. These segments are obtained by dividing the continuous vibration signal. The segment length is set according to the vibration duration, for example, each segment covers several seconds of data to ensure statistical reliability. After the dispersion is calculated, normalization is performed, for example, by dividing by the average value of the main frequency band energy to eliminate the amplitude effect.

[0105] The establishment of stability assessment indicators needs to ensure the consistency of the dimensions of structural coupling degree and dispersion degree. Structural coupling degree is a dimensionless ratio, and dispersion degree is the square of energy units. Therefore, before weighting, the reciprocal of dispersion degree is taken and normalized to make the two comparable.

[0106] The dynamic adjustment of the threshold takes into account the construction stage and material changes. For example, in the initial setting stage of concrete, the threshold is set higher to strictly require stability, and in the final setting stage, the threshold is appropriately lowered. The adjustment is achieved by real-time monitoring of construction parameters, such as concrete slump or temperature.

[0107] The adjustment of vibration intensity control parameters is achieved through closed-loop control. The adjustment signal is sent to the controller of the vibration equipment, and the controller changes the drive output according to the parameter value. For example, the voltage is increased to increase the vibration frequency. The adjustment step size is set according to the response characteristics of the equipment to avoid excessive fluctuations.

[0108] Throughout the process, the calculation and threshold comparison of stability assessment indicators are carried out iteratively, updated once per construction cycle to ensure real-time performance. The adjustment results are then fed back to the vibration operation to form a quality control cycle.

[0109] S6. Execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joints. Specifically, the implementation is as follows:

[0110] When implementing the adjusted control parameters, the adjusted vibration intensity control parameters are first obtained from the construction vibration stability assessment results. The vibration intensity control parameters include vibration frequency and vibration amplitude. These parameters are determined based on the comparison results between the stability assessment index and the set threshold. When the stability assessment index is lower than the set threshold, the vibration intensity control parameters are increased accordingly. When the stability assessment index is not lower than the set threshold, the vibration intensity control parameters are maintained or decreased. The adjusted vibration intensity control parameters exist in the form of digital signals or analog signals. For example, the vibration frequency is in Hertz and the vibration amplitude is in millimeters.

[0111] When the adjusted vibration intensity control parameters are output to the controller of the vibrating equipment, data transmission is performed using industrial communication protocols, including Modbus or PROFIBUS. The transmission method is wired or wireless communication. Wired communication uses shielded twisted-pair cables, while wireless communication uses radio frequency transmission. Before data transmission, the vibration intensity control parameters are encoded using methods such as pulse code modulation or amplitude modulation to ensure that the signal is anti-interference during transmission. The controller is located inside or in an independent external cabinet of the vibrating equipment. The controller type is a programmable logic controller or an embedded controller, with digital input / output interfaces and analog input / output interfaces. The vibration intensity control parameters are transmitted to the controller through these interfaces.

[0112] When the controller drives the vibratory equipment to perform vibration operation on the wet joint with the adjusted vibration intensity control parameters, the controller receives the vibration intensity control parameters and generates a drive signal through internal program processing. The drive signal includes a voltage signal or a current signal. The voltage signal ranges from zero to ten volts, and the current signal ranges from four to twenty milliamps. The drive signal is transmitted to the actuator of the vibratory equipment. The actuator includes an electric vibrator or a hydraulic vibrator. The electric vibrator adjusts the vibration frequency by changing the input voltage, and the hydraulic vibrator controls the vibration amplitude by adjusting the hydraulic oil flow. The actuator adjusts the vibration intensity according to the drive signal, so that the vibratory equipment performs vibration operation on the wet joint with the adjusted vibration intensity control parameters.

[0113] When outputting vibration intensity control parameters, it is necessary to verify the rationality of the parameter values. The verification methods include range checks and logic checks. The range check confirms that the vibration frequency and vibration amplitude are within the allowable operating range of the equipment. For example, the vibration frequency range is from 50 Hz to 100 Hz, and the vibration amplitude range is from 1 mm to 5 mm. The logic check confirms that the combination of vibration frequency and vibration amplitude conforms to the equipment operating specifications to avoid overload or failure. Only after the verification is passed will the parameters be sent to the controller.

[0114] When the controller drives the vibratory equipment, a closed-loop control method is used to maintain the stability of the vibration intensity. The closed-loop control monitors the actual output of the vibratory equipment in real time through sensors. For example, an encoder is used to measure the vibration frequency, and a displacement sensor is used to measure the vibration amplitude. The actual output value is compared with the adjusted vibration intensity control parameters, and the drive signal is adjusted according to the deviation to ensure that the actual vibration intensity is consistent with the set value.

[0115] During the vibration operation, the controller records the execution parameters and operating status, including the vibration start time, duration, and vibration intensity change curve. This data is stored in the controller's memory or external storage device for quality traceability and performance analysis.

[0116] The entire execution process ensures the accurate implementation of vibration intensity control parameters. Fault protection mechanisms are set up in the parameter transmission and drive links. For example, when communication is interrupted or the equipment is abnormal, the controller automatically switches to the safety mode. In the safety mode, the default vibration intensity control parameters are used or the vibration operation is stopped to prevent construction quality defects.

[0117] When the vibrating equipment is used to vibrate the wet joint, the operating path and coverage area are determined according to the construction plan. The vibrating equipment moves along the length of the wet joint, and the moving speed and vibration intensity are coordinated and controlled to ensure that the concrete is uniform and dense. After the vibration operation is completed, the equipment automatically stops and sends a completion signal to the control system.

[0118] Example 2: Figure 2 A schematic diagram of the intelligent control system for the construction quality of UHPC wet joints is provided. The intelligent control system for the construction quality of UHPC wet joints includes the following modules:

[0119] The signal acquisition module is used to acquire vibration signals at multiple preset locations on the wet joint structure;

[0120] The feature extraction module is used to extract, from the vibration signal, the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances, respectively.

[0121] The vibration identification module is used to identify vibration signals as construction vibration or environmental vibration based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics.

[0122] The coupling evaluation module is used to calculate the energy values ​​of vibration signals at multiple preset locations and analyze the attenuation gradient of the energy values ​​as the distance between the preset location and the vibration source increases when the vibration signal is identified as construction vibration. The structural coupling degree is evaluated based on the steepness of the attenuation gradient.

[0123] The parameter adjustment module is used to evaluate the stability of construction vibration by analyzing the concentration of the first type of frequency domain characteristics based on the structural coupling degree, and to adjust the control parameters of the vibrating equipment according to the stability evaluation results.

[0124] The operation execution module is used to execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joint.

[0125] The calculations involved in the embodiments are all 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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 scope of the technology 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.

[0131] 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 method for intelligent control of construction quality of UHPC wet joints, characterized in that, Includes the following steps: S1. Collect vibration signals at multiple preset locations on the wet joint structure; S2. Extract the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances from the vibration signal, including: Spectral analysis is performed on the vibration signal to obtain the frequency component distribution of the vibration signal; The energy of the main frequency band is calculated based on the frequency component distribution and used as the first type of frequency domain feature. Simultaneously, the presence of transient pulse components in the vibration signal is detected, and these transient pulse components are used as the second type of frequency domain feature. S3. Based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics, the vibration signal is identified as construction vibration or environmental vibration, including: Determine whether the proportion of the main frequency band energy in the first type of frequency domain features exceeds the first threshold and whether the amplitude of the transient pulse component in the second type of frequency domain features is lower than the second threshold. When the proportion of energy in the main frequency band exceeds the first threshold and the amplitude of the transient pulse component is lower than the second threshold, the vibration signal is identified as construction vibration; otherwise, the vibration signal is identified as environmental vibration. S4. When the vibration signal is identified as construction vibration, calculate the energy value of the vibration signal at multiple preset locations and analyze the attenuation gradient of the energy value as the distance between the preset location and the vibration source increases. Evaluate the structural coupling degree based on the steepness of the attenuation gradient. S5. Based on the structural coupling degree analysis, the concentration of the first type of frequency domain characteristics is used to evaluate the stability of construction vibration, and the control parameters of the vibrating equipment are adjusted according to the stability evaluation results. S6. Execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joint.

2. The intelligent control method for construction quality of UHPC wet joints according to claim 1, characterized in that, Vibration signals were collected at multiple preset locations on the wet joint structure, including: Vibration sensors are pre-positioned at the interface between the old and new concrete in the wet joint structure, and vibration sensors are also pre-positioned at the action area of ​​the vibrating equipment. Vibration signals are collected synchronously through the vibration sensors.

3. The intelligent control method for construction quality of UHPC wet joints according to claim 1, characterized in that, When vibration signals are identified as construction vibrations, the energy values ​​of vibration signals at multiple preset locations are calculated, and the attenuation gradient of the energy value as the distance between the preset location and the vibration source increases is analyzed. The structural coupling degree is assessed based on the steepness of the attenuation gradient, including: Calculate the energy value of the vibration signal at each preset position and establish a relationship model between the energy value and the distance from the corresponding preset position to the vibration source. The attenuation gradient of energy value as a function of distance is determined using a relational model; Evaluate structural coupling based on the linearity of the decay gradient; A higher linearity indicates a better structural coupling.

4. The intelligent control method for construction quality of UHPC wet joints according to claim 3, characterized in that, The calculation of the energy value of the vibration signal at each preset position and the establishment of a relationship model between the energy value and the distance from the corresponding preset position to the vibration source include: calculating the energy value by performing square integral on the vibration signal at each preset position, and then linearly fitting the energy value with the distance from the corresponding preset position to the vibration source to establish a relationship model.

5. The intelligent control method for construction quality of UHPC wet joints according to claim 3, characterized in that, The linearity assessment of structural coupling based on decay gradients includes calculating the sum of squared residuals between the data points in the relational model and the fitted line to assess linearity; the smaller the sum of squared residuals, the higher the structural coupling.

6. The intelligent control method for construction quality of UHPC wet joints according to claim 1, characterized in that, The stability of construction vibration is assessed by analyzing the concentration of the first type of frequency domain characteristics based on structural coupling, and the control parameters of the vibratory compaction equipment are adjusted according to the stability assessment results, including: A stability evaluation index is established based on the structural coupling degree and the dispersion of the main frequency band energy distribution in the first type of frequency domain characteristics; When the stability assessment index is lower than the set threshold, increase the vibration intensity control parameter of the vibratory equipment. When the stability assessment index is not lower than the set threshold, maintain or reduce the vibration intensity control parameters of the vibratory equipment.

7. The intelligent control method for construction quality of UHPC wet joints according to claim 1, characterized in that, The adjusted control parameters are executed to control the vibratory equipment to vibrate the wet joints, including: The adjusted vibration intensity control parameters are output to the controller of the vibration equipment; The controller drives the vibratory equipment to perform vibration operation on the wet joints using the adjusted vibration intensity control parameters.

8. A smart control system for the construction quality of UHPC wet joints, used to implement the smart control method for the construction quality of UHPC wet joints as described in any one of claims 1-7, characterized in that, Includes the following modules: The signal acquisition module is used to acquire vibration signals at multiple preset locations on the wet joint structure; The feature extraction module is used to extract, from the vibration signal, the first type of frequency domain features related to construction operations and the second type of frequency domain features related to environmental disturbances, respectively. The vibration identification module is used to identify vibration signals as construction vibration or environmental vibration based on the energy distribution of the first type of frequency domain characteristics and the transient characteristics of the second type of frequency domain characteristics. The coupling evaluation module is used to calculate the energy values ​​of vibration signals at multiple preset locations and analyze the attenuation gradient of the energy values ​​as the distance between the preset location and the vibration source increases when the vibration signal is identified as construction vibration. The structural coupling degree is evaluated based on the steepness of the attenuation gradient. The parameter adjustment module is used to evaluate the stability of construction vibration by analyzing the concentration of the first type of frequency domain characteristics based on the structural coupling degree, and to adjust the control parameters of the vibrating equipment according to the stability evaluation results. The operation execution module is used to execute the adjusted control parameters to control the vibrating equipment to vibrate the wet joint.

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