A construction method and system for full-casing cast-in-place piles on the side of a subway line

Abstract

This invention discloses a construction method and system for full-casing cast-in-place piles on the side of a subway, specifically relating to the field of foundation engineering technology for construction near subway protection zones. It addresses the problem that existing full-casing techniques are insufficient to withstand the dynamic pore water pressure coupling caused by subway operation, leading to the risk of borehole instability. By simultaneously monitoring the ground pressure inside the casing and on the tunnel side, the method assesses the disturbance propagation intensity and identifies abnormal fluctuations inside the casing based on the tunnel side pressure. When an anomaly is detected, coupled modal analysis is performed on the data from both to extract dynamic modal parameters, thereby assessing the cumulative disturbance effect of subway loads. Finally, based on the assessment results, active pressure compensation is initiated during borehole formation, and the effect is verified after compensation. This achieves real-time perception, mechanism diagnosis, and active control of dynamic operational disturbances from the subway, improving the safety and reliability of full-casing borehole formation in sensitive environments.

Description

Technical Field

[0001] This invention relates to the field of foundation engineering technology for construction near subway protection zones, and more specifically, to a construction method and system for subway-side full-casing cast-in-place piles. Background Technology

[0002] When constructing pile foundations on the side of subway tunnels or track structures, the full-casing cast-in-place pile process is often used to strictly control soil deformation and ensure the safety of subway operation. The full-casing cast-in-place pile process forms rigid support by pressing the steel casing into the stratum throughout the process. The drilling, cage placement and grouting operations are completed inside the casing. This reduces disturbance to the surrounding soil through physical isolation, thereby effectively preventing the risks of borehole collapse and stratum settlement that are easily caused by conventional drilled piles. It has become an important method for foundation construction in subway protection zones.

[0003] However, in the extremely sensitive environment adjacent to an operating subway line, even with the full casing technology, the construction process still faces complex challenges. The periodic piston wind pressure generated by the high-speed operation of the subway train will cause regular pulsations in the pore water pressure of the strata around the tunnel. This dynamic load effect may penetrate the microscopic boundary between the casing and the soil. When a local negative pressure is formed inside the casing during the drilling stage, the external dynamic pore water pressure fluctuations are easily coupled with it, disrupting the pressure balance inside the casing and inducing instability or even hidden loss of the soil in the borehole wall. This not only directly threatens the safety of the borehole but may also transmit additional stress to the subway structure through the soil, weakening the isolation and protection effect of the full casing technology, thus creating a prominent contradiction between construction risks and subway protection requirements. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a construction method and system for subway-side full-casing cast-in-place piles 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 constructing full-casing cast-in-place piles on the side of a subway line includes the following steps:

[0007] S1. Simultaneously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side of the adjacent subway tunnel area;

[0008] S2. Evaluate the propagation intensity of subway operation pressure disturbance based on tunnel side stratum pressure data, and determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity.

[0009] S3. When abnormal pressure fluctuations are determined to exist, coupled modal analysis is performed on the pressure data inside the cylinder and the pressure data of the strata on the tunnel side to extract dynamic modal parameters that reflect the coupled state of the disturbance.

[0010] S4. Based on dynamic modal parameters, evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing;

[0011] S5. Based on the evaluation results of the cumulative disturbance effect, the pressure compensation device is activated to actively compensate the pressure inside the steel casing during subsequent drilling operations.

[0012] S6. After active pressure compensation, verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state.

[0013] Furthermore, the pressure data inside the steel casing and the ground pressure data on the tunnel side in the adjacent subway tunnel area are acquired simultaneously, including:

[0014] A pore water pressure sensor is installed inside the steel casing to collect pressure data inside the casing.

[0015] A pore water pressure sensor is installed in the stratum adjacent to the sidewall of the subway tunnel to collect stratum pressure data on the side of the tunnel.

[0016] The data acquisition system synchronously receives pressure data from the pore water pressure sensor inside the steel casing and pressure data from the pore water pressure sensor on the tunnel side of the stratum in the adjacent subway tunnel area.

[0017] Furthermore, the propagation intensity of subway operation pressure disturbances is assessed based on tunnel-side ground pressure data, and the presence of abnormal pressure fluctuations in the cylinder pressure data is determined according to the propagation intensity, including:

[0018] Spectral analysis was performed on the ground pressure data on the tunnel side to extract the characteristic frequency band energy corresponding to the subway operation cycle as the propagation intensity;

[0019] Perform the same spectral analysis on the internal pressure data and calculate the energy values ​​of the same characteristic frequency bands;

[0020] A threshold for judging abnormal fluctuations is determined based on the propagation intensity;

[0021] Compare the energy value of the cylinder pressure data in the characteristic frequency band with the abnormal fluctuation judgment threshold;

[0022] If the energy value of the internal pressure data in the characteristic frequency band exceeds the threshold for judging abnormal fluctuations, then it is determined that there are abnormal pressure fluctuations in the internal pressure data.

[0023] Furthermore, when abnormal pressure fluctuations are determined to exist, coupled modal analysis is performed on the pressure data inside the cylinder and the ground pressure data on the tunnel side to extract dynamic modal parameters reflecting the coupled state of the disturbance, including:

[0024] Multiple consecutive time-segment subsequences with equal durations and containing the complete subway operation cycle were extracted from the pressure data inside the cylinder and the ground pressure data on the side of the tunnel.

[0025] For each time period subsequence, the pressure data inside the tube and the pressure data of the formation on the tunnel side are subjected to bandpass filtering of the same frequency band, and the mutual coherence function corresponding to each time period subsequence is calculated.

[0026] The consistency of the mutual coherence function peaks of the subsequences in each time period on the characteristic frequency band is analyzed, and the stability parameter of the phase delay corresponding to the subsequences in each time period is calculated.

[0027] The degree of consistency of the peak values ​​of the mutual coherence spectrum and the stability parameters of the phase delay are used as dynamic mode parameters reflecting the perturbation coupling state.

[0028] Furthermore, based on dynamic modal parameters, the cumulative disturbance effect of subway operating loads on the strata surrounding the steel casing is evaluated, including:

[0029] Based on the degree of consistency of the peak values ​​of the mutual coherence spectrum, it is determined whether the response of subway operation pressure disturbance in the steel casing has temporal continuity.

[0030] Based on the stability parameter of phase delay, it is determined whether the coupling path of subway operation pressure disturbance transmitted through the stratum to the steel casing has spatial stability.

[0031] If the response of the subway operation pressure disturbance within the steel casing is continuous in time and the coupling path is spatially stable, then it is determined that the subway operation load produces a significant cumulative disturbance effect in the strata surrounding the steel casing.

[0032] Furthermore, the statistical dispersion index of the peak values ​​of the mutual interference spectrum corresponding to multiple time period subsequences is calculated, and the statistical dispersion index is compared with a preset persistence threshold. If the statistical dispersion index is lower than the persistence threshold, it is determined that the response of the subway operation pressure disturbance in the steel casing has temporal persistence.

[0033] Furthermore, the statistical discrete index of phase delay corresponding to multiple time period subsequences is calculated, and the statistical discrete index is compared with a preset stability threshold. If the statistical discrete index is lower than the stability threshold, it is determined that the coupling path of subway operation pressure disturbance transmitted through the stratum to the steel casing has spatial stability.

[0034] Furthermore, based on the assessment results of the cumulative disturbance effect, the pressure compensation device is activated during subsequent drilling operations to actively compensate for the pressure inside the steel casing, including:

[0035] When it is determined that the subway operating load has a significant cumulative disturbance effect on the strata surrounding the steel casing, the pressure data inside the casing is monitored in real time during the subsequent drilling operation.

[0036] When a negative pressure drop is detected in the pressure data inside the cylinder, the pressure compensation device is activated to inject fluid into the steel casing.

[0037] The pressure and flow rate of the injected fluid are controlled so that the pressure data inside the cylinder after the fluid is injected is maintained within the preset pressure threshold range.

[0038] Furthermore, after active pressure compensation, it is verified whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state, including:

[0039] After active pressure compensation is completed, obtain the pressure data inside the cylinder and the ground pressure data on the tunnel side after active pressure compensation;

[0040] Spectral analysis was performed on the tunnel-side stratum pressure data after active pressure compensation, and the characteristic frequency band energy corresponding to the subway operation cycle was extracted as the propagation intensity after compensation.

[0041] Based on the propagation intensity after compensation, a threshold for judging normal fluctuations is determined.

[0042] Perform the same spectrum analysis on the cylinder pressure data after active pressure compensation, and calculate the energy values ​​of the same characteristic frequency bands;

[0043] If the energy value of the cylinder pressure data after active pressure compensation is lower than or equal to the normal fluctuation judgment threshold in the characteristic frequency band, then it is verified that the cylinder pressure data has escaped the abnormal fluctuation state.

[0044] On the other hand, the present invention provides a construction system for subway-side full-casing cast-in-place piles, comprising the following modules:

[0045] The data synchronization module is used to synchronously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side in the adjacent subway tunnel area;

[0046] The fluctuation judgment module is used to assess the propagation intensity of subway operation pressure disturbances based on the tunnel side stratum pressure data, and to determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity.

[0047] The modal analysis module is used to perform coupled modal analysis on the pressure data inside the cylinder and the pressure data of the strata on the tunnel side when abnormal pressure fluctuations are detected, and to extract dynamic modal parameters that reflect the coupled state of the disturbance.

[0048] The effect assessment module is used to evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing based on dynamic modal parameters.

[0049] The pressure compensation module is used to activate the pressure compensation device to actively compensate the pressure inside the steel casing during subsequent drilling operations, based on the evaluation results of the cumulative disturbance effect.

[0050] The status verification module is used to verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state after active pressure compensation.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. By constructing a closed-loop control process integrating synchronous monitoring, intelligent diagnosis, proactive regulation, and effect verification, the risk management capability for pile foundation construction on the side of a dynamically operating subway is fundamentally improved. This not only continues the physical isolation advantage of the full casing process but also innovatively places the construction process under real-time perception and proactive response to the special mechanical environment induced by subway operation. By synchronously acquiring pressure data from the tunnel side and inside the casing, direct quantitative monitoring of the dynamic disturbance source of subway piston wind pressure and its propagation effect in the soil layer is achieved. A series of progressive analysis steps, including judging abnormal fluctuations based on propagation intensity, extracting dynamic modal parameters through coupled modal analysis, and evaluating cumulative disturbance effects, enable construction decisions to shift from relying on experience-based judgment to precise judgment based on data and mechanisms. This allows for the deep identification of gradual instability risks caused by the coupling of periodic operating loads and construction activities, which are difficult to detect by traditional methods.

[0053] 2. Through in-depth analysis of the disturbance coupling state and forward-looking assessment of the cumulative effect, the construction party can anticipate risks and initiate active pressure compensation before significant deformation or hidden loss of the borehole wall soil occurs. This transforms traditional post-event remediation into pre-event prevention, reducing the probability of borehole collapse. The active pressure compensation device intervenes based on real-time assessment results, dynamically and accurately offsetting the impact of external dynamic pore water pressure fluctuations, effectively maintaining the pressure balance inside the casing, and ensuring the stability of the borehole formation process. Finally, the effect verification step ensures the effectiveness of each round of control measures, forming a complete quality control closed loop. This significantly enhances the adaptability and reliability of the full casing process in the extremely sensitive environment of the subway side. While strictly ensuring the safety of the subway operation structure, it also ensures the construction quality and efficiency of the pile foundation project itself, providing a systematic technical solution for underground engineering construction in similar sensitive areas. Attached Figure Description

[0054] Figure 1 This is a flowchart of a construction method for a subway-side full-casing cast-in-place pile according to the present invention;

[0055] Figure 2 This is a structural schematic diagram of a subway-side full-casing cast-in-place pile construction system according to the present invention. Detailed Implementation

[0056] 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.

[0057] Example 1: Figure 1 This invention provides a method for constructing fully casing cast-in-place piles on the side of a subway line, which includes the following steps:

[0058] S1. Simultaneously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side of the adjacent subway tunnel area;

[0059] S2. Evaluate the propagation intensity of subway operation pressure disturbance based on tunnel side stratum pressure data, and determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity.

[0060] S3. When abnormal pressure fluctuations are determined to exist, coupled modal analysis is performed on the pressure data inside the cylinder and the pressure data of the strata on the tunnel side to extract dynamic modal parameters that reflect the coupled state of the disturbance.

[0061] S4. Based on dynamic modal parameters, evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing;

[0062] S5. Based on the evaluation results of the cumulative disturbance effect, the pressure compensation device is activated to actively compensate the pressure inside the steel casing during subsequent drilling operations.

[0063] S6. After active pressure compensation, verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state.

[0064] S1. Simultaneously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side in the adjacent subway tunnel area, implemented as follows:

[0065] A pore water pressure sensor is installed inside the steel casing to collect pressure data within the casing. Specifically, a vibrating wire pore water pressure gauge is selected. Its working principle involves measuring the change in the vibration frequency of the steel wire inside the sensor. This frequency change has a specific functional relationship with the pore water pressure acting on the permeable stone of the sensor, thus sensing changes in pore water pressure. After the steel casing is lowered into place, pore water pressure sensors are installed at certain intervals along the depth direction on sensor mounting brackets pre-welded to the inner wall of the casing. For example, one pore water pressure sensor is installed every 2 to 3 meters to monitor the pressure data inside the casing at different depths. The range of each pore water pressure sensor is selected based on the historical maximum pore water pressure value of the construction area provided in the engineering geological survey report. The selection method is to use a value greater than the historical maximum value as the upper limit of the range. For example, a pressure value 1.5 times greater than the historical maximum value is selected as the upper limit of the sensor range to ensure that the sensor will not be damaged under abnormal construction conditions. The accuracy of the sensor is not less than 0.1% of full scale to ensure the sensitivity of the pressure data. All pore water pressure sensors must be calibrated in the laboratory before deployment. The calibration process involves placing the sensor in a pressure calibration tank, applying a series of known standard pressure values, recording the frequency values ​​output by the sensor, and thus establishing a curve showing the correspondence between the frequency output value and the standard pressure value, i.e., the calibration curve.

[0066] A pore water pressure sensor is installed in the stratum adjacent to the sidewall of the subway tunnel to collect ground pressure data. Specifically, a pre-drilled micro-hole is drilled outside the sidewall of the subway tunnel structure, and a pre-packaged vibrating wire pore water pressure gauge of the same model is buried in the target monitoring stratum. The sensor is buried in the middle area between the steel casing and the subway tunnel sidewall, and the burial depth is approximately the same as the depth of the ongoing drilling operation inside the steel casing; for example, the depth difference with the current drilling face is controlled within ±1 meter to ensure the comparability of the monitored ground pressure with the pressure at the working face inside the casing. The diameter of the micro-hole is slightly larger than the sensor diameter. After drilling, the sensor is pushed to the designed depth, and then the hole is backfilled and sealed using bentonite balls and undisturbed soil slurry to restore the original ground conditions and ensure close contact between the sensor and the soil, thereby accurately sensing the pore water pressure. Similarly, these sensors also need to undergo the same laboratory calibration process as the aforementioned in-casing sensors before burial to obtain their respective frequency-pressure calibration curves.

[0067] The data acquisition system synchronously receives pressure data from pore water pressure sensors inside the steel casing and pressure data from pore water pressure sensors in the adjacent subway tunnel area. Specifically, the system consists of a multi-channel data acquisition unit with multiple independent signal input channels. The signal cables from all pore water pressure sensors inside the steel casing and those in the adjacent subway tunnel area are connected to different input channels of the multi-channel data acquisition unit. To achieve synchronous acquisition, the multi-channel data acquisition unit has a built-in unified clock source and is configured to synchronously trigger sampling for all connected channels. The sampling frequency is set based on the pressure fluctuation characteristics that may be caused by subway operation. The principle is that the sampling frequency should be at least twice the highest fluctuation frequency to be monitored, typically set to 10 Hz, meaning that readings from all sensors are collected every 0.1 seconds. This frequency effectively captures rapid fluctuations in pore water pressure caused by subway trains passing by. At each sampling instant, the multi-channel data acquisition instrument simultaneously reads the frequency signals output by the pore water pressure sensors connected to all channels. Based on the unique calibration curves of each sensor, it converts the frequency signals into corresponding pressure values ​​in real time, expressed in kilopascals (kPa). The converted cylinder pressure data and the tunnel-side ground pressure data are timestamped and stored in the multi-channel data acquisition instrument's storage unit. The timestamp accuracy reaches the millisecond level to ensure strict synchronization of the time series in subsequent analyses. The stored data is in a text file containing the time series and corresponding pressure values, providing a unified time reference and accurate and reliable cylinder pressure data series and tunnel-side ground pressure data series for subsequent steps such as spectrum analysis and coupled modal analysis. This method ensures that pressure data acquired from different spatial locations are completely synchronized in the time dimension, providing a solid foundation for accurately analyzing the spatial propagation and coupling of subway operational disturbances.

[0068] S2. Evaluate the propagation intensity of subway operation pressure disturbances based on tunnel side stratum pressure data, and determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity. This is implemented as follows:

[0069] A continuous pressure data segment is extracted from the stored tunnel-side ground pressure data sequence. The extracted data duration needs to cover multiple complete subway operation cycles, for example, a 10-minute segment of tunnel-side ground pressure data. After extraction, data preprocessing is performed to remove potential DC offset components from the data sequence. This is done by calculating the arithmetic mean of all data points in the segment and then subtracting this arithmetic mean from the pressure value of each data point. The preprocessed tunnel-side ground pressure data is then subjected to spectral analysis using a Fast Fourier Transform (FFT) algorithm. The FFT algorithm takes the time series of the preprocessed tunnel-side ground pressure data and its corresponding equally spaced time points as input, and outputs the amplitude spectrum of the tunnel-side ground pressure data in the frequency domain. By observing and analyzing the amplitude spectrum, characteristic frequency bands associated with the regular passage of subway trains are identified. The identification of a characteristic frequency band is based on a significant spectral peak in the amplitude spectrum. The frequency corresponding to this peak matches the reciprocal of the train departure interval. For example, when a subway train passes by on average every 3 minutes, its characteristic frequency is approximately 0.0056 Hz. In practical analysis, the characteristic frequency band can be defined as a narrow band centered on this characteristic frequency, such as a frequency range with a center frequency within ±0.002 Hz. The propagation intensity is calculated as the energy value of the amplitude spectrum within this characteristic frequency band. The calculation method involves squaring the amplitude spectrum values ​​corresponding to all discrete frequency points within the characteristic frequency band, and then summing all the squared values. This summation represents the energy of the characteristic frequency band and is defined as the propagation intensity. The unit of propagation intensity is related to the square of the original pressure value unit, such as the square of kilopascals.

[0070] The same spectral analysis is performed on the pressure data inside the cylinder to calculate the energy value of the same characteristic frequency band. Specifically, a segment of pressure data inside the cylinder that is completely synchronized in time with the tunnel-side formation pressure data is selected, i.e., a data segment with the same start time and duration, such as a 10-minute segment of pressure data inside the cylinder. This pressure data undergoes the same preprocessing steps as before, namely, removing the DC offset component. Then, using the same Fast Fourier Transform algorithm parameters as described above, a spectral transform is performed on the preprocessed pressure data inside the cylinder to obtain the amplitude spectrum. Based on the amplitude spectrum of the pressure data inside the cylinder, energy is calculated according to the same characteristic frequency band range determined from the analysis of the tunnel-side formation pressure data, such as the same frequency interval with a center frequency of ±0.002 Hz. The energy calculation uses the same method as the propagation intensity calculation, i.e., the squared values ​​of the pressure amplitude spectrum corresponding to all frequency points within the characteristic frequency band are summed; this summation result is the energy value of the pressure data inside the cylinder in the same characteristic frequency band.

[0071] An abnormal fluctuation judgment threshold is determined based on the propagation intensity. In practice, the setting of the abnormal fluctuation judgment threshold directly depends on the calculated propagation intensity value. One method for determining the abnormal fluctuation judgment threshold is the proportional coefficient method. The proportional coefficient method requires setting an empirical coefficient greater than 1, multiplying this empirical coefficient by the propagation intensity value, and using the product as the abnormal fluctuation judgment threshold. The value range of the empirical coefficient is determined based on historical data statistics or engineering experience. For example, the value range of the empirical coefficient can be between 1.2 and 2.0. The specific value selection needs to consider the safety level requirements of the project. For projects with high safety level requirements, the empirical coefficient can be a smaller value, such as 1.5, to provide earlier warning of potential risks. Another method for determining the abnormal fluctuation judgment threshold is the benchmark value superposition method. The benchmark value superposition method uses the propagation intensity value as a benchmark, plus a fixed pressure energy margin value as the abnormal fluctuation judgment threshold. The pressure energy margin value is set based on the background energy level that may be generated by normal construction fluctuations inside the tube. The abnormal fluctuation judgment threshold is dynamically updated after each calculation of a new propagation intensity to ensure that the judgment standard is adapted to the current disturbance level of subway operation.

[0072] The energy value of the cylinder pressure data in the characteristic frequency band is compared with the abnormal fluctuation judgment threshold. In practice, this comparison operation is a direct comparison of the numerical values. The calculated energy value of the cylinder pressure data in the characteristic frequency band is used as one input, and the abnormal fluctuation judgment threshold determined based on the propagation intensity is used as another input. The comparison logic is used to determine whether the former input value is greater than the latter input value.

[0073] If the energy value of the internal pressure data in the characteristic frequency band exceeds the abnormal fluctuation judgment threshold, then abnormal pressure fluctuations are determined to exist in the internal pressure data. Specifically, when the comparison operation results in the energy value of the internal pressure data in the characteristic frequency band being greater than the abnormal fluctuation judgment threshold, an anomaly determination is triggered, generating a logical judgment signal. This logical judgment signal indicates the presence of abnormal pressure fluctuations in the internal pressure data. This judgment result directly determines whether subsequent steps require initiating coupled modal analysis. If the energy value of the internal pressure data in the characteristic frequency band does not exceed the abnormal fluctuation judgment threshold, then the internal pressure state is determined to be normal, and subsequent coupled modal analysis is not required.

[0074] S3. When abnormal pressure fluctuations are detected, coupled modal analysis is performed on the pressure data inside the cylinder and the ground pressure data on the tunnel side to extract dynamic modal parameters reflecting the coupled state of the disturbance. This is implemented as follows:

[0075] First, multiple consecutive time-segment subsequences of equal length, encompassing complete subway operating cycles, are extracted from the pressure data inside the tube and the ground pressure data on the tunnel side. The extraction method involves selecting a continuous, unprocessed segment of raw data from the synchronously stored pressure data sequences inside the tube and ground pressure data on the tunnel side after identifying the time points exhibiting abnormal pressure fluctuations. The number of time-segment subsequences is typically selected from 3 to 5, for example, 4, to ensure a sufficient sample size for subsequent statistical analysis. The duration of each time-segment subsequence must ensure it contains an integer number of complete subway operating cycles. For example, if the subway operating cycle is approximately 180 seconds, the duration of the time-segment subsequence can be set to 600 seconds (10 minutes) to ensure it contains at least 3 complete operating cycles. The extraction operation must be performed synchronously with the pressure data inside the tube and the ground pressure data on the tunnel side, meaning all time-segment subsequences must have identical start and end times. This ensures strict temporal alignment between the pressure data inside the tube and the ground pressure data on the tunnel side within different time-segment subsequences, laying the foundation for subsequent synchronous analysis.

[0076] For each time-segment subsequence, the pressure data inside the tube and the ground pressure data on the tunnel side are subjected to bandpass filtering in the same frequency band, and the cross-coherence function corresponding to each time-segment subsequence is calculated. Specifically, for each extracted time-segment subsequence, digital bandpass filtering is performed on its included pressure data segments inside the tube and ground pressure data segments on the tunnel side. The frequency band for bandpass filtering is set based on the characteristic frequency bands corresponding to the subway operating cycle identified in the spectrum analysis step; for example, the passband frequency range of the bandpass filter is set to ±0.002 Hz of the center frequency of the characteristic frequency band. The filtering process is implemented using digital filters, such as finite-length unit impulse response filters, to eliminate frequency interference outside the characteristic frequency band range, thereby extracting the signal components purely dominated by subway operating pressure disturbances. After filtering, for each time-segment subsequence, the cross-coherence function between its filtered pressure data segments inside the tube and ground pressure data segments on the tunnel side is calculated. The method for calculating the cross-coherence function involves performing Fast Fourier Transform (FFT) on each of the two filtered data segments to obtain their respective spectra, then calculating the cross-power spectral density (CPSD) of the two spectra, and finally performing an Inverse Fourier Transform (IFT) on the CPSD to obtain the cross-coherence function corresponding to the subsequence of that time period. The cross-coherence function is a function of time delay, and its value characterizes the degree of correlation between signals at two different locations—inside the tube and on the tunnel side—under different time delays.

[0077] This study analyzes the consistency of the cross-coherence spectrum peaks of the cross-coherence functions corresponding to each time-segment subsequence in the characteristic frequency bands, and calculates the stability parameters of the phase delay corresponding to each time-segment subsequence. Specifically, firstly, the cross-coherence spectrum peaks in the characteristic frequency bands are extracted from the cross-coherence functions corresponding to each time-segment subsequence. The extraction method involves performing a Fourier transform on the cross-coherence function to obtain its frequency domain representation, i.e., the cross-coherence spectrum. The characteristic frequency band range is located on the cross-coherence spectrum, and the maximum amplitude within that band is identified. This maximum amplitude is the cross-coherence spectrum peak corresponding to that time-segment subsequence. After obtaining the cross-coherence spectrum peaks of all time-segment subsequences, the consistency of these peaks is analyzed. The consistency analysis is achieved by calculating the statistical dispersion index of these cross-coherence spectrum peaks, such as the standard deviation or coefficient of variation. The coefficient of variation is calculated by dividing the standard deviation by the absolute value of the mean. The smaller the value of this statistical dispersion index, the higher the consistency of the cross-coherence spectrum peaks within the continuous time period, indicating a more stable response intensity of subway operation disturbances within the tunnel. Secondly, the stability parameters of the phase delay corresponding to each time-segment subsequence are calculated. Phase delay is obtained by reading the phase angle at the frequency point corresponding to the peak of the cross-coherence spectrum in each time-segment subsequence. This phase angle represents the phase shift corresponding to the time delay of the pressure fluctuation inside the casing relative to the pressure fluctuation in the strata on the tunnel side at that frequency. After obtaining the phase delay values ​​for all time-segment subsequences, the stability parameters of these phase delay values ​​are calculated. The stability parameters are also characterized by calculating statistical dispersion indicators, such as the standard deviation of this set of phase delay values. The smaller the standard deviation of the phase delay, the better the stability parameter of the phase delay, that is, the more stable the spatial characteristics of the coupling path from the subway operation pressure disturbance to the steel casing through the strata.

[0078] The consistency of the peak values ​​of the cross-coherence spectrum and the stability parameter of the phase delay are used as dynamic modal parameters reflecting the disturbance coupling state. In specific implementation, the consistency index of the peak values ​​of the cross-coherence spectrum and the stability parameter of the phase delay, obtained through the above analysis and calculation, are directly output and defined as dynamic modal parameters. These two indices quantify the coupling state between subway operating pressure disturbances and the response within the casing from different dimensions: the consistency index reflects the time-varying characteristics of the coupling strength, while the stability parameter of the phase delay reflects the time-invariant characteristics of the coupling path. As a set of key characteristic quantities, these indices will be passed to subsequent steps to assess whether the subway operating load generates a significant cumulative disturbance effect in the strata surrounding the steel casing, thus providing accurate data support for construction decisions. This analysis can deeply reveal the reliability and path stability of disturbance energy transfer under abnormal pressure fluctuations, going beyond simple threshold judgments and achieving in-depth diagnosis of risk mechanisms.

[0079] S4. Based on dynamic modal parameters, evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing, implemented as follows:

[0080] Based on the consistency of the cross-coherence spectrum peak values, the temporal persistence of the response to subway operational pressure disturbances within the steel casing is determined. The method involves calculating the statistical dispersion index of the cross-coherence spectrum peak values ​​corresponding to multiple time-segment subsequences and comparing this index with a preset persistence threshold. The statistical dispersion index is calculated using the standard deviation formula, where the input is the cross-coherence spectrum peak values ​​corresponding to all time-segment subsequences, and the output is the standard deviation of these peak values. The persistence threshold is set based on the statistical analysis results of a large amount of historical construction data or laboratory model test data. Specifically, data from multiple normal construction phases under similar geological conditions and subway operating environments, without cumulative disturbance risk, are collected. The cross-coherence spectrum peak values ​​are calculated for these normal phase data using the same process, and the statistical dispersion index of these peak values ​​is further calculated. The distribution range of these statistical dispersion indices is then analyzed, and the upper limit of this range is selected. This upper limit is then multiplied by a safety factor, and the resulting value is set as the persistence threshold. The safety factor is typically greater than 1, for example, 1.2, to allow for a certain safety margin. If the calculated statistical dispersion index is lower than the preset persistence threshold, it indicates that the peak value of the mutual interference spectrum fluctuates very little in different time periods, meaning that the response intensity of the subway operation pressure disturbance within the steel casing remains stable, thus determining that the response of the subway operation pressure disturbance within the steel casing has temporal persistence. Conversely, if the statistical dispersion index is higher than or equal to the persistence threshold, it is determined that the response does not have temporal persistence.

[0081] Based on the stability parameter of phase delay, the spatial stability of the coupling path from subway operational pressure disturbances transmitted through the ground to the steel casing is determined. The method involves calculating the statistical discrete index of phase delay for multiple time-segment subsequences and comparing this index with a preset stability threshold. The statistical discrete index of phase delay is also calculated using standard deviation; the input to the standard deviation formula is the phase delay value for all time-segment subsequences, and the output is the standard deviation of these phase delay values. The method for setting the stability threshold is logically similar to that for setting the persistence threshold but applies to different physical quantities. The stability threshold is also based on data analysis from historical normal construction phases. Phase delay values ​​calculated under normal conditions are collected, the statistical discrete index of these phase delay values ​​is calculated, their distribution characteristics are analyzed, and the upper limit of the distribution, considering a safety factor, is determined as the stability threshold. Since phase delay reflects the wave propagation path, its stability threshold is usually expressed in degrees; for example, the stability threshold obtained through analysis might be 10 degrees. If the calculated statistical dispersion index of the phase delay is lower than the preset stability threshold, it indicates that the phase delay changes only slightly over different time periods. This means that the propagation path characteristics of the subway operation pressure disturbance from the tunnel side to the steel casing remain constant, thus indicating that the coupling path of the subway operation pressure disturbance transmitted through the strata to the steel casing has spatial stability. Conversely, if the statistical dispersion index of the phase delay is higher than or equal to the stability threshold, it indicates that the coupling path does not possess spatial stability.

[0082] If the response of the subway operation pressure disturbance within the steel casing exhibits temporal persistence and the coupling path demonstrates spatial stability, then the subway operation load is deemed to have generated a significant cumulative disturbance effect in the strata surrounding the steel casing. In practice, this determination is a logical AND operation. Only when the condition of temporal persistence of the response of the subway operation pressure disturbance within the steel casing based on the consistency of the mutual interference spectrum peak values ​​is met, and the condition of spatial stability of the coupling path of the subway operation pressure disturbance transmitted through the strata to the steel casing based on the stability parameter of phase delay is also met, is the final determination that the subway operation load has generated a significant cumulative disturbance effect in the strata surrounding the steel casing. This determination result is a Boolean logical value. If either of the two conditions is not met, such as lacking temporal persistence or spatial stability, then the subway operation load is determined not to have generated a significant cumulative disturbance effect in the strata surrounding the steel casing. The technical meaning of the concept of significant cumulative disturbance effect refers to the continuous input of disturbance energy from the subway operating load into the limited soil area surrounding the steel casing through a stable and continuous coupling path. This input rate may exceed the soil's energy dissipation or stress relaxation rate, leading to a gradual accumulation of disturbance effects such as increased pore water pressure or decreased effective stress over operating time, thus posing a potential threat to the soil structure and engineering safety. This determination provides a direct and mechanistic-based scientific basis for deciding whether to initiate active pressure compensation in subsequent steps. By jointly judging the two dimensions of continuity and stability, it is possible to effectively identify working conditions that, although the instantaneous intensity may not reach extreme values, have long-term cumulative risks due to continuous and stable energy input, thus enabling the prediction of deep-seated safety hazards.

[0083] S5. Based on the assessment results of the cumulative disturbance effect, the pressure compensation device is activated during subsequent drilling operations to provide active pressure compensation to the steel casing. The implementation is as follows:

[0084] When it is determined that the subway operating load has a significant cumulative disturbance effect on the strata surrounding the steel casing, the pressure data inside the casing is monitored in real time during subsequent drilling operations. Specifically, during continuous drilling operations, the data acquisition system continuously acquires data from a designated channel connected to the pore water pressure sensor inside the steel casing, maintaining an acquisition frequency of, for example, 10 Hz. The logic for real-time monitoring of the casing pressure data involves continuously reading and processing the latest acquired pressure data. This processing includes converting the frequency signal output by the pore water pressure sensor into a real-time pressure value based on the sensor's unique calibration curve, and then displaying and recording this pressure value in real time.

[0085] When a negative pressure downward trend is detected in the cylinder pressure data, the pressure compensation device is activated to inject fluid into the steel casing. The method for determining if a negative pressure downward trend is present is to set up a real-time trend analysis algorithm. This algorithm uses the current moment as a baseline and extracts a short time segment of cylinder pressure data, such as the most recent 10 seconds. This data segment is then linearly fitted or its pressure change rate per unit time is calculated. The pressure change rate is calculated by subtracting the cylinder pressure data value at the beginning and end of the time segment, obtaining the pressure difference, and then dividing the pressure difference by the duration of the time segment. If the calculated pressure change rate is negative and its absolute value is greater than a preset negative pressure change rate threshold, then a negative pressure downward trend is determined to be present in the cylinder pressure data. The threshold for the negative pressure change rate is set based on engineering experience and formation characteristics. It distinguishes between normal small pressure fluctuations and dangerous rapid pressure loss. The setting process can refer to historical data on normal pressure fluctuations during construction where borehole collapse did not occur, analyze the maximum rate of pressure drop, and add a safety margin to this rate. For example, the threshold can be set to a drop of 0.5 kPa per second. Once the algorithm output is true, a start signal is generated and transmitted to the control unit of the pressure compensation device, triggering the device to start working. The pressure compensation device typically includes a grouting pump, delivery pipeline, pressure regulating valve, and flow meter. The injected fluid is usually bentonite slurry or clean water. The start-up process includes starting the grouting pump and opening the valve on the grouting pipeline leading to the bottom of the steel casing.

[0086] The pressure and flow rate of the injected fluid are controlled to maintain the pressure data inside the casing within a preset pressure threshold range after fluid injection. This preset pressure threshold range is a pressure interval with lower and upper limits pre-set based on geological conditions and engineering requirements. The lower limit is set to prevent excessively low pressure inside the casing from causing a decrease in the effective stress of the soil in the borehole wall, leading to plastic or seepage failure. This lower limit is typically set slightly higher than the hydrostatic pressure at that depth, for example, 5 to 10 kPa higher. The upper limit is set to prevent excessive pressure from causing splitting effects on the steel casing structure or surrounding soil. This upper limit is typically set lower than the effective vertical stress of the soil at that depth, for example, 20 kPa lower. Controlling the pressure and flow rate of the injected fluid is a closed-loop feedback control process. In practice, after the pressure compensation device is activated, the real-time monitored pressure data inside the casing is continuously input to the control unit as a feedback signal. The midpoint of the preset pressure threshold range within the control unit is used as the control target value. The control unit calculates and outputs control commands based on the deviation between the real-time cylinder pressure data and the target value using a proportional-integral-derivative (PID) control algorithm. The PID algorithm involves setting three parameters: proportional coefficient, integral coefficient, and derivative coefficient. The initial values ​​of these parameters can be determined using engineering tuning methods based on the dynamic characteristics of the grouting system and fine-tuned during actual control. The control commands simultaneously adjust the motor speed of the grouting pump to change the output pressure and the opening of the electric regulating valve on the pipeline to change the flow rate. The goal of the adjustment is to bring the real-time cylinder pressure data into and stabilize within the preset pressure threshold range as quickly as possible. For example, when the real-time cylinder pressure data is below the lower limit of the pressure threshold range, the control algorithm will increase the grouting pump speed and open the electric regulating valve wider to increase the grouting pressure and flow rate, thereby raising the cylinder pressure data. When the real-time cylinder pressure data approaches or reaches the pressure threshold range, the control algorithm will decrease the grouting pump speed and close the electric regulating valve to maintain pressure stability. Flow data monitored in real-time by the flow meter also serves as auxiliary feedback to prevent excessive instantaneous flow. The entire control process continues until the borehole operation is completed or the conditions for determining the cumulative disturbance effect disappear, thereby ensuring that the pressure data inside the borehole remains within a safe and controllable range during the sensitive construction phase, effectively offsetting the disturbance energy input by the subway operating load through the coupling path, and maintaining the stability of the borehole wall.

[0087] S6. After active pressure compensation, verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state, implemented as follows:

[0088] After active pressure compensation is completed, the pressure data inside the casing and the ground pressure data on the tunnel side are acquired. The method for acquiring these data involves retrieving from the data acquisition system's storage unit the pressure data inside the casing, collected and converted by a pore water pressure sensor inside the casing, and the ground pressure data on the tunnel side, collected and converted by a pore water pressure sensor in the adjacent subway tunnel area, within a certain period after the active pressure compensation operation ceases. The data time period begins at the moment when pressure compensation control reaches stability and stops adjusting, and the duration must encompass multiple complete subway operation cycles. For example, a 10-minute data segment after compensation is completed represents the pressure data inside the casing and the ground pressure data on the tunnel side after active pressure compensation.

[0089] Spectral analysis is performed on the tunnel-side formation pressure data after active pressure compensation to extract the energy of characteristic frequency bands corresponding to the subway operating cycle as the post-compensation propagation intensity. Specifically, the acquired tunnel-side formation pressure data segment after active pressure compensation is preprocessed to remove the DC offset component. This is done by calculating the arithmetic mean of all pressure values ​​in the data segment and then subtracting this arithmetic mean from each pressure value. The preprocessed tunnel-side formation pressure data after active pressure compensation is then subjected to spectral analysis using a Fast Fourier Transform (FFT) algorithm. The FFT input is the time series of the preprocessed tunnel-side formation pressure data after active pressure compensation, and the output is its amplitude spectrum. Energy is calculated on the amplitude spectrum based on the same characteristic frequency band range identified in the previous anomaly detection step. This characteristic frequency band range corresponds to the subway operating cycle. The specific method for energy calculation is to square the amplitude spectrum values ​​corresponding to all discrete frequency points within the characteristic frequency band interval, and then sum all the squared values. This summation result is defined as the post-compensation propagation intensity. The unit of the compensated propagation intensity is related to the square of the original pressure value unit, such as the square of kilopascals.

[0090] Based on the compensated propagation intensity, a normal fluctuation judgment threshold is determined. In practice, the setting of the normal fluctuation judgment threshold directly depends on the calculated compensated propagation intensity value. A common method for determining the normal fluctuation judgment threshold is the proportional coefficient method. The proportional coefficient method requires setting an empirical coefficient less than 1, multiplying this empirical coefficient by the compensated propagation intensity value, and using the product as the normal fluctuation judgment threshold. The range of the empirical coefficient is determined based on historical data statistics or engineering experience, and is used to characterize the range within which the pressure fluctuation energy in the cylinder can be considered normal. For example, the range of the empirical coefficient can be between 0.3 and 0.8. The specific value selection needs to consider the attenuation characteristics of the strata to disturbances and the engineering safety margin requirements. For cases with strong anti-disturbance capabilities or slightly lower safety margin requirements, the empirical coefficient can be taken as a larger value, such as 0.6. Another method for determining the normal fluctuation judgment threshold is the benchmark value reduction method. The benchmark value reduction method uses the compensated propagation intensity value as a benchmark, and then subtracts a fixed pressure energy margin value to obtain the normal fluctuation judgment threshold. The setting of this pressure energy margin value is based on the background noise energy level when the cylinder is completely unaffected by subway operation disturbances. The threshold for judging normal fluctuations is dynamically updated after each calculation to ensure that the verification standard is adapted to the residual disturbance level of the current subway operation.

[0091] The same spectral analysis is performed on the pressure data inside the cylinder after active pressure compensation to calculate the energy value of the same characteristic frequency band. Specifically, the acquired pressure data segment inside the cylinder after active pressure compensation undergoes the same preprocessing steps as the tunnel-side data, namely, removing the DC offset component. Then, using the same Fast Fourier Transform algorithm parameters as described above, a spectral transform is performed on the preprocessed pressure data inside the cylinder after active pressure compensation to obtain the amplitude spectrum of the pressure data inside the cylinder after active pressure compensation. Energy is calculated on the amplitude spectrum of the pressure data inside the cylinder after active pressure compensation, based on the same characteristic frequency band range, such as the same frequency interval within ±0.002 Hz of the center frequency. The energy calculation uses the same method as the calculation of the propagation intensity after compensation, that is, the amplitude spectrum values ​​of the pressure data inside the cylinder after active pressure compensation corresponding to all frequency points within the characteristic frequency band are squared and summed. This summation result is the energy value of the pressure data inside the cylinder after active pressure compensation in the same characteristic frequency band.

[0092] If the energy value of the pressure data inside the cylinder after active pressure compensation in the characteristic frequency band is lower than or equal to the normal fluctuation judgment threshold, then the pressure data inside the cylinder has been verified to have escaped the abnormal fluctuation state. In practice, this verification is a numerical comparison and logical judgment process. The calculated energy value of the pressure data inside the cylinder after active pressure compensation in the characteristic frequency band is used as one input, and the normal fluctuation judgment threshold determined based on the compensated propagation intensity is used as another input. Comparison logic is used to determine whether the former input value is less than or equal to the latter input value. When the comparison result is that the energy value of the pressure data inside the cylinder after active pressure compensation in the characteristic frequency band is lower than or equal to the normal fluctuation judgment threshold, a verification pass signal is generated. This signal indicates that the active pressure compensation measures are effective, and the pressure state inside the cylinder has recovered to a normal range commensurate with the current subway operation disturbance level, i.e., it has escaped the abnormal fluctuation state. If the energy value of the pressure data inside the cylinder after active pressure compensation in the characteristic frequency band is higher than the normal fluctuation judgment threshold, then the verification fails, indicating that the compensation effect has not met expectations, and the pressure inside the cylinder may still be affected by abnormal coupling, requiring further analysis or other measures. The entire verification process provides an objective and quantitative closed-loop test for the effectiveness of active pressure compensation construction, ensuring that construction control achieves the expected goals and guaranteeing the ultimate safety of pile foundation drilling operations under the continuous operation of the subway.

[0093] Example 2: Figure 2 A structural schematic diagram of a subway-side full-casing cast-in-place pile construction system is provided according to the present invention. The subway-side full-casing cast-in-place pile construction system includes the following modules:

[0094] The data synchronization module is used to synchronously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side in the adjacent subway tunnel area;

[0095] The fluctuation judgment module is used to assess the propagation intensity of subway operation pressure disturbances based on the tunnel side stratum pressure data, and to determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity.

[0096] The modal analysis module is used to perform coupled modal analysis on the pressure data inside the cylinder and the pressure data of the strata on the tunnel side when abnormal pressure fluctuations are detected, and to extract dynamic modal parameters that reflect the coupled state of the disturbance.

[0097] The effect assessment module is used to evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing based on dynamic modal parameters.

[0098] The pressure compensation module is used to activate the pressure compensation device to actively compensate the pressure inside the steel casing during subsequent drilling operations, based on the evaluation results of the cumulative disturbance effect.

[0099] The status verification module is used to verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state after active pressure compensation.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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 constructing full-casing cast-in-place piles on the side of a subway line, characterized in that, Includes the following steps: S1. Simultaneously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side of the adjacent subway tunnel area; S2. Evaluate the propagation intensity of subway operation pressure disturbance based on tunnel side stratum pressure data, and determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity. S3. When abnormal pressure fluctuations are determined to exist, coupled modal analysis is performed on the pressure data inside the cylinder and the ground pressure data on the tunnel side to extract dynamic modal parameters reflecting the coupled state of the disturbance, including: Multiple consecutive time-segment subsequences with equal durations and containing the complete subway operation cycle were extracted from the pressure data inside the cylinder and the ground pressure data on the side of the tunnel. For each time period subsequence, the pressure data inside the tube and the pressure data of the formation on the tunnel side are subjected to bandpass filtering of the same frequency band, and the mutual coherence function corresponding to each time period subsequence is calculated. The consistency of the mutual coherence function peaks of the subsequences in each time period on the characteristic frequency band is analyzed, and the stability parameter of the phase delay corresponding to the subsequences in each time period is calculated. The degree of consistency of the peak values ​​of the mutual coherence spectrum and the stability parameters of the phase delay are used as dynamic mode parameters reflecting the perturbation coupling state. S4. Based on dynamic modal parameters, evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing; S5. Based on the evaluation results of the cumulative disturbance effect, the pressure compensation device is activated to actively compensate the pressure inside the steel casing during subsequent drilling operations. S6. After active pressure compensation, verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state.

2. The construction method for a subway-side full-casing cast-in-place pile according to claim 1, characterized in that, Simultaneously acquire internal pressure data within the steel casing and ground pressure data on the tunnel side in the adjacent subway tunnel area, including: A pore water pressure sensor is installed inside the steel casing to collect pressure data inside the casing. A pore water pressure sensor is installed in the stratum adjacent to the sidewall of the subway tunnel to collect stratum pressure data on the side of the tunnel. The data acquisition system synchronously receives pressure data from the pore water pressure sensor inside the steel casing and pressure data from the pore water pressure sensor on the tunnel side of the stratum in the adjacent subway tunnel area.

3. The construction method for a subway-side full-casing cast-in-place pile according to claim 1, characterized in that, The propagation intensity of subway operation pressure disturbances is assessed based on tunnel side stratum pressure data, and the presence of abnormal pressure fluctuations in the cylinder pressure data is determined based on the propagation intensity, including: Spectral analysis was performed on the ground pressure data on the tunnel side to extract the characteristic frequency band energy corresponding to the subway operation cycle as the propagation intensity; Perform the same spectral analysis on the internal pressure data and calculate the energy values ​​of the same characteristic frequency bands; A threshold for judging abnormal fluctuations is determined based on the propagation intensity; Compare the energy value of the cylinder pressure data in the characteristic frequency band with the abnormal fluctuation judgment threshold; If the energy value of the internal pressure data in the characteristic frequency band exceeds the threshold for judging abnormal fluctuations, then it is determined that there are abnormal pressure fluctuations in the internal pressure data.

4. The construction method for a subway-side full-casing cast-in-place pile according to claim 1, characterized in that, Based on dynamic modal parameters, the cumulative disturbance effect of subway operating loads on the strata surrounding the steel casing is evaluated, including: Based on the degree of consistency of the peak values ​​of the mutual coherence spectrum, it is determined whether the response of subway operation pressure disturbance in the steel casing has temporal continuity. Based on the stability parameter of phase delay, it is determined whether the coupling path of subway operation pressure disturbance transmitted through the stratum to the steel casing has spatial stability. If the response of the subway operation pressure disturbance within the steel casing is continuous in time and the coupling path is spatially stable, then it is determined that the subway operation load produces a significant cumulative disturbance effect in the strata surrounding the steel casing.

5. The construction method for a subway-side full-casing cast-in-place pile according to claim 4, characterized in that, Calculate the statistical dispersion index of the peak values ​​of the mutual interference spectrum corresponding to multiple time period subsequences, and compare the statistical dispersion index with a preset persistence threshold. If the statistical dispersion index is lower than the persistence threshold, it is determined that the response of the subway operation pressure disturbance in the steel casing has time persistence.

6. The construction method for a subway-side full-casing cast-in-place pile according to claim 4, characterized in that, Calculate the statistical discrete index of phase delay corresponding to multiple time period subsequences, compare the statistical discrete index with the preset stability threshold, and if the statistical discrete index is lower than the stability threshold, it is determined that the coupling path of subway operation pressure disturbance transmitted through the stratum to the steel casing has spatial stability.

7. The construction method for a subway-side full-casing cast-in-place pile according to claim 1, characterized in that, Based on the assessment results of the cumulative disturbance effect, the pressure compensation device is activated during subsequent drilling operations to provide active pressure compensation to the steel casing, including: When it is determined that the subway operating load has a significant cumulative disturbance effect on the strata surrounding the steel casing, the pressure data inside the casing is monitored in real time during the subsequent drilling operation. When a negative pressure drop is detected in the pressure data inside the cylinder, the pressure compensation device is activated to inject fluid into the steel casing. The pressure and flow rate of the injected fluid are controlled so that the pressure data inside the cylinder after the fluid is injected is maintained within the preset pressure threshold range.

8. The construction method for a subway-side full-casing cast-in-place pile according to claim 1, characterized in that, After active pressure compensation, verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state, including: After active pressure compensation is completed, obtain the pressure data inside the cylinder and the ground pressure data on the tunnel side after active pressure compensation; Spectral analysis was performed on the tunnel-side stratum pressure data after active pressure compensation, and the characteristic frequency band energy corresponding to the subway operation cycle was extracted as the propagation intensity after compensation. Based on the propagation intensity after compensation, a threshold for judging normal fluctuations is determined. Perform the same spectrum analysis on the cylinder pressure data after active pressure compensation, and calculate the energy values ​​of the same characteristic frequency bands; If the energy value of the cylinder pressure data after active pressure compensation is lower than or equal to the normal fluctuation judgment threshold in the characteristic frequency band, then it is verified that the cylinder pressure data has escaped the abnormal fluctuation state.

9. A construction system for subway-side full-casing cast-in-place piles, used to implement the construction method for subway-side full-casing cast-in-place piles as described in any one of claims 1-8, characterized in that, Includes the following modules: The data synchronization module is used to synchronously acquire the pressure data inside the steel casing and the ground pressure data on the tunnel side in the adjacent subway tunnel area; The fluctuation judgment module is used to assess the propagation intensity of subway operation pressure disturbances based on the tunnel side stratum pressure data, and to determine whether there are abnormal pressure fluctuations in the cylinder pressure data based on the propagation intensity. The modal analysis module is used to perform coupled modal analysis on the pressure data inside the cylinder and the pressure data of the strata on the tunnel side when abnormal pressure fluctuations are detected, and to extract dynamic modal parameters that reflect the coupled state of the disturbance. The effect assessment module is used to evaluate the cumulative disturbance effect of subway operating load on the strata surrounding the steel casing based on dynamic modal parameters. The pressure compensation module is used to activate the pressure compensation device to actively compensate the pressure inside the steel casing during subsequent drilling operations, based on the evaluation results of the cumulative disturbance effect. The status verification module is used to verify whether the pressure data inside the cylinder has escaped the abnormal pressure fluctuation state after active pressure compensation.

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