A pile foundation static load test pile-up precision analysis method based on multi-sensor fusion

Abstract

The present application belongs to the field of pile foundation static load test, and relates to multi-sensor fusion technology, which is used to solve the problem that the prior art cannot realize real-time sensing of the load distribution uniformity of a heaped load body, and specifically relates to a pile foundation static load test heaped load precision analysis method based on multi-sensor fusion, which comprises the following steps: sensor arrangement for the pile foundation static load test; data acquisition and preprocessing for the pile foundation static load test; after the pile foundation static load test starts, a collection time point T i is set i , and heaped load parameter collection is performed; the present application realizes multi-dimensional real-time monitoring and dynamic analysis of the heaped load precision of the pile foundation static load test, so that heaped load abnormalities can be found and located in time, load transmission deviation from the design axis is avoided to prevent bearing capacity data distortion, meanwhile, the hidden risks after test interruption are quantitatively evaluated to provide an objective basis for subsequent scheme adjustment, the test precision can be more comprehensively and accurately controlled, and the reliability of the pile foundation bearing capacity test result is improved.

Description

Technical Field

[0001] This invention belongs to the field of static load testing of pile foundations and involves multi-sensor fusion technology. Specifically, it is a method for analyzing the surcharge accuracy of static load testing of pile foundations based on multi-sensor fusion. Background Technology

[0002] The static load test of pile foundation is the most direct and reliable method to determine the vertical compressive bearing capacity of a single pile. Its principle is to apply load to the top of the pile step by step through a reaction system (usually a surcharge platform) and observe the settlement of the pile top to obtain the load-settlement relationship curve of the pile. Surcharge accuracy analysis refers to the evaluation and control of the accuracy and reliability of the entire load application process. It focuses not only on whether the final load value meets the requirements, but also on whether the load is stably, accurately and without eccentricity transferred to the pile during the entire loading process.

[0003] The invention patent with publication number CN115270238B discloses a method for predicting the static behavior of bridges based on dynamic loads. This method uses the prediction results of machine learning and intelligent algorithms to correct the initial structural analysis model; it predicts the static behavior of the bridge based on the corrected structural analysis model; and it introduces an error analysis method to evaluate the prediction results of the bridge static behavior. However, this method cannot perceive the uniformity of load distribution of the load-bearing capacity in real time (such as the tilting of the counterweight block or the eccentric loading of the jack), which makes it difficult to control the error of the measured bearing capacity, and at the same time, it cannot assess and analyze the hidden risks of the test.

[0004] To address the aforementioned technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of this invention is to provide a method for analyzing the load accuracy of pile foundation static load tests based on multi-sensor fusion, which solves the problem that existing technologies cannot perceive the uniformity of load distribution in real time.

[0006] The technical problem to be solved by this invention is: how to provide a pile foundation static load test load accuracy analysis method based on multi-sensor fusion that can perceive the load distribution uniformity of the pile carrier in real time.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A method for analyzing the surcharge accuracy of static load tests on pile foundations based on multi-sensor fusion includes the following steps:

[0009] Step 1: Set up sensors for the static load test of the pile foundation;

[0010] Step 2: Data Acquisition and Preprocessing for Static Load Test of Pile Foundation: After the static load test of pile foundation begins, set the data acquisition time point T. iLet i = 1, 2, ..., n, where n is a positive integer, and the data is collected at time point T. i Collect load parameters;

[0011] Step 3: Data fusion processing of pile foundation static load test: Numerical processing of load parameters to obtain the acquisition time point T i DP load deviation factor i The load deviation coefficient DPi was used to measure the data at time point T. i The surcharge accuracy is judged to meet the requirements, and abnormal surcharge areas are screened when the surcharge accuracy does not meet the requirements.

[0012] Step 4: Conduct implicit risk analysis on the static load test of the pile foundation: Obtain the implicit risk value and determine whether the implicit risk of the static load test of the pile foundation meets the requirements based on the implicit risk value.

[0013] Furthermore, in step one, the specific process of sensor deployment includes: setting pressure diaphragm sensors on the contact surface between counterweights, setting tilt sensors at the four corners of each layer of counterweights, setting displacement sensors on the pile top reference beam, and setting pressure sensors in the hydraulic pipeline of the jack.

[0014] Furthermore, in step two, the process of acquiring the load parameters includes: obtaining the load value of the accumulator by a pressure membrane sensor, and then... i The pressure distribution value YF is obtained by calculating the variance of the load values ​​of the stack carrier acquired by all pressure membrane sensors. i All tilt sensors were collected at time point T. i The obtained maximum tilt angle value is marked as the tilt angle risk value QF. i The displacement sensor was used at the data acquisition time point T. i With the collection time point T i-1 The difference in the obtained settlement values ​​is denoted as the settlement change value CB. i The pressure sensor was used to collect data at time point T. i With the collection time point T i-1 The difference between the obtained applied load values ​​is labeled as the load change value ZB. i .

[0015] Furthermore, in step three, the data collection time point T... i DP load deviation factor i The acquisition process includes: using the entropy method to analyze the YF value from the previous pile foundation static load test. i QF i and CB i / ZB i Numerical standardization, index weight calculation, and entropy calculation are performed to obtain weight coefficients t1, t2, and t3. Then, the weights are calculated using YF... i QFi CB i / ZB i The data collection time point T is obtained by weighted summation of the weighting coefficients. i DP load deviation factor i .

[0016] Furthermore, in step three, the data collection time point T... i The specific process for determining whether the stacking accuracy meets the requirements includes: retrieving the stacking deviation threshold DP. max The collection time point T i DP load deviation factor i Deviation from the stacking threshold DP max Comparison: If the load deviation coefficient DP i Less than the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i If the loading accuracy meets the requirements, the experiment continues, and step four is executed; if the loading deviation coefficient DP i Greater than or equal to the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i The load accuracy did not meet the requirements, and the test was suspended.

[0017] Furthermore, in step three, the screening process for abnormal load areas includes: marking the L1 counterweight blocks with the largest load values ​​as abnormal load areas, generating a counterweight adjustment signal, and sending the counterweight adjustment signal and the abnormal load areas to the mobile terminal of the management personnel.

[0018] Furthermore, in step four, the process of obtaining the implicit risk value includes: [The text abruptly ends here, likely due to an incomplete sentence or a formatting error.] i With QF i-1 The difference is marked as the acquisition time point T. i tilt angle monitoring value QJ i The tilt angle monitoring value QJ i The time point T with the largest value i Deviation coefficient DP from load i The time point T with the largest value i The ratio of the time interval between tests to the duration of the static load test for the pile foundation is marked as the time risk value, and the surcharge deviation coefficient DP is used as the time risk value. i The maximum value of the stacking deviation from the threshold DP max The ratio is marked as the spatial risk value, and the difference between the spatial risk value and the temporal risk value is marked as the implicit risk value.

[0019] Furthermore, in step four, the specific process for determining whether the implicit risks of the static load test of the pile foundation meet the requirements includes: retrieving the implicit risk threshold and comparing the implicit risk value with the implicit risk threshold; if the implicit risk value is less than the implicit risk threshold, the implicit risks of the static load test of the pile foundation meet the requirements; if the implicit risk value is greater than or equal to the implicit risk threshold, the implicit risks of the static load test of the pile foundation do not meet the requirements, a risk warning signal is generated, and the risk warning signal is sent to the mobile terminal of the management personnel.

[0020] The present invention has the following beneficial effects:

[0021] 1. This application realizes multi-dimensional real-time monitoring and dynamic analysis of the load accuracy of static load tests on pile foundations. This allows for timely detection and location of load anomalies, avoiding distortion of bearing capacity data caused by load transfer deviating from the design axis. At the same time, by quantitatively assessing the hidden risks after test interruption, it provides an objective basis for subsequent scheme adjustments. Compared with traditional single-sensor monitoring, this method can more comprehensively and accurately control test accuracy and improve the reliability of pile foundation bearing capacity test results.

[0022] 2. This application achieves comprehensive acquisition of surcharge parameters for static load tests of pile foundations. As a result, key indicators such as pressure distribution, tilt angle change, settlement rate, and load increase rate can be obtained, providing comprehensive data support for subsequent data fusion processing and surcharge accuracy analysis. Furthermore, this multi-parameter acquisition method can promptly capture abnormal situations during the surcharge process, such as uneven pressure distribution, increased tilt risk, and abnormal settlement rate, thereby improving the safety and reliability of static load tests of pile foundations.

[0023] 3. This application can monitor the surcharge accuracy in pile foundation static load tests in real time and promptly detect situations where the surcharge accuracy does not meet the requirements. This can prevent test data deviations caused by insufficient surcharge accuracy, improve the accuracy and reliability of pile foundation static load tests, and at the same time, by setting a surcharge deviation threshold and performing real-time comparison, the test can be suspended in time when problems occur with the surcharge accuracy, avoiding potential safety hazards and resource waste that may result from continuing the test. In addition, this method provides test personnel with clear judgment criteria, reduces the subjectivity and uncertainty of human judgment, and helps to improve the standardization and scientific nature of the test.

[0024] 4. This application can comprehensively consider the changes in inclination angle, the degree of load deviation, and the time factor of risk occurrence to quantitatively assess the implicit risks of pile foundation static load tests. As a result, it can more comprehensively reflect the potential risks in the test process, improve the accuracy and timeliness of risk warning. Furthermore, by introducing the time dimension, this method can capture the dynamic characteristics of risk evolution, which helps to identify key time nodes in the test process and provide test management personnel with more accurate decision-making basis. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] In traditional static load tests of pile foundations, the reaction system of the surcharge platform applies the load through the coordinated action of counterweights and jacks. Its precision control relies on human experience and data from a single sensor, making it impossible to perceive the uniformity of load distribution and dynamic risks in real time. Abnormal conditions such as uneven contact pressure distribution between counterweights, deviations in the tilt angle of multiple counterweights, and sudden changes in the settlement rate at the pile top are difficult to capture synchronously. This leads to the load transfer path deviating from the design axis during the test, reducing the reliability of the measured bearing capacity data. Furthermore, the implicit risks after the test is interrupted cannot be quantitatively assessed.

[0029] For example, during a static load test of a cross-sea bridge pile foundation using traditional methods, the counterweights were stacked to a height of 12 meters. During the test, pressure concentration at the contact surfaces of some counterweights caused tilting, but this was not detected in time during manual inspections. The hydraulic pressure sensors in the jacks only monitored the total load value and could not reflect the load eccentricity, resulting in an abnormal displacement data of the pile top reference beam being detected only after a 4-hour delay. After the test was forced to stop, the counterweight layout needed to be recalibrated, but the lack of quantitative indicators to assess the risk of structural damage affected subsequent adjustments to the test plan.

[0030] If the above problems are not addressed, the testing system will be unable to establish a multi-dimensional data correlation model, and abnormal load transfer will not be detected before the critical state, potentially leading to the accumulation of hidden damage to the pile body. The lack of risk quantification after test interruption will result in a lack of data support for repair plans, extending the project cycle. More seriously, the failure to correct uneven load distribution in real time may cause the counterweight platform to become unstable and overturn, threatening the safety of testing personnel and the integrity of the surrounding structure.

[0031] like Figure 1As shown, a method for analyzing the surcharge accuracy of pile foundation static load tests based on multi-sensor fusion includes the following steps:

[0032] Step 1: Grid-based pressure membrane sensor layout for static load test of pile foundation: Set pressure membrane sensors on the contact surface between counterweights, set tilt sensors at the four corners of each layer of counterweights, set displacement sensors on the pile top reference beam, and set pressure sensors on the hydraulic pipeline of the jack.

[0033] Among them, the pressure diaphragm sensor directly measures the load distribution between the counterweights through the contact surface, the tilt sensor monitors the tilt state of the counterweight layer through a four-corner layout, the displacement sensor captures the dynamic settlement of the pile top through the reference beam, and the pressure sensor obtains the changes in the load applied by the jack in real time through the hydraulic pipeline. For example, the pressure diaphragm sensor adopts a diaphragm structure attached to the surface of the counterweight, the tilt sensor is symmetrically distributed at the four corners of each layer, the displacement sensor is installed at the central axis of the reference beam, and the pressure sensor is integrated at the tee interface of the hydraulic pipeline.

[0034] Specifically, the pressure diaphragm sensor reflects the uniformity of load transfer on the accumulator through pressure distribution data at the contact surface, with the load difference between the contact surfaces of the counterweights directly reflecting the degree of load eccentricity. Tilt sensors, positioned at the four corners, can simultaneously detect the tilt direction and magnitude of the counterweights. For example, when a layer of counterweights tilts, the data from the four corner sensors can calculate the tilt angle and deformation trend. Displacement sensors are installed on the pile top reference beam, obtaining continuous data on pile settlement by measuring the relative displacement change between the reference beam and the pile top. Pressure sensors are integrated into the hydraulic jack's hydraulic pipeline, using hydraulic pressure changes to infer the actual applied load value. The tee interface of the hydraulic pipeline avoids the impact of pressure fluctuations on measurement accuracy. The spatial layout of these sensors forms a three-dimensional monitoring network. The pressure diaphragm sensor and tilt sensor work together to monitor the static stability of the accumulator, while the displacement sensor and pressure sensor synchronously track the matching between the pile response and the applied load, providing multi-dimensional data support for subsequent calculations of the load deviation coefficient.

[0035] The sensor deployment process includes the following steps:

[0036] First, pressure film sensors are placed on the contact surfaces between the counterweights. Specifically, multiple pressure film sensors are evenly arranged on the bottom surface of each layer of counterweights to monitor the contact pressure distribution between the counterweights.

[0037] Secondly, tilt sensors are placed at the four corners of each layer of counterweights. Furthermore, high-precision dual-axis tilt sensors are used, and during installation, it is ensured that the sensor's measuring axis is parallel to the edge of the counterweight.

[0038] Next, displacement sensors are installed on the pile top reference beam. Specifically, four reference points are set around the pile top, and a high-precision displacement sensor is installed at each reference point to measure the vertical displacement of the pile top.

[0039] Finally, pressure sensors are installed in the jack's hydraulic lines. Thus, a pressure sensor is installed at both the jack's inlet and outlet to monitor hydraulic pressure changes in real time.

[0040] Step 2: Data Acquisition and Preprocessing for Static Load Test of Pile Foundation: After the static load test of pile foundation begins, set the data acquisition time point T. i i = 1, 2, ..., n, where n is a positive integer, and the load value of the stack carrier is obtained by a pressure membrane sensor at T i The pressure distribution value YF is obtained by calculating the variance of the load values ​​of the stack carrier acquired by all pressure membrane sensors. i All tilt sensors were collected at time point T. i The obtained maximum tilt angle value is marked as the tilt angle risk value QF. i The displacement sensor was used at the data acquisition time point T. i With the collection time point T i-1 The difference in the obtained settlement values ​​is denoted as the settlement change value CB. i The pressure sensor was used to collect data at time point T. i With the collection time point T i-1 The difference between the obtained applied load values ​​is labeled as the load change value ZB. i ;

[0041] Among them, the load values ​​of the stack carrier collected by the pressure diaphragm sensor are converted into pressure distribution values ​​YF through variance calculation. i Variance calculation is used to quantify the dispersion of load distribution among counterweights; the maximum tilt angle value is selected from the data collected by the tilt sensor as the tilt risk value QF. i It is used to characterize the extreme state of interlayer tilt of the counterweight; the settlement difference between adjacent time points collected by the displacement sensor is used as the settlement change value CB. i This reflects the dynamic trend of pile top settlement; the load difference between adjacent time points collected by the pressure sensor is used as the load change value ZB. i It is used to monitor the incremental stability of the load applied by the jack.

[0042] Specifically, in T i At a given time point, the pressure diaphragm sensor array collects load data from the contact surfaces of each counterweight. Variance calculations are used to eliminate local load fluctuation interference, yielding YF, which reflects the uniformity of the overall load distribution. i Simultaneously, iterate through all tilt sensor data and filter for the maximum tilt angle value QF. iTo capture the critical state of the counterweight tilt; the displacement sensor calculates the settlement difference CB between adjacent time points. i Establish a settlement rate index; the pressure sensor calculates the load difference ZB between adjacent time points. i This generates an index for load increment changes. (Through YF) i QF i CB i With ZB i A combination of these parameters is used to construct a multidimensional parameter system, in which YF i With QF i Reflecting load distribution and structural stability from a spatial perspective, CB i With ZB i By characterizing the dynamic changes in settlement and load over time, these four elements work together to achieve comprehensive quantitative monitoring of the surcharge status. For example, when a layer of counterweights tilts, QF... i The value increased significantly, and at the same time, the YF of the pressure film sensor in this layer increased. i As variance increases, CB should be considered. i With ZB i The changing trend can be used to determine whether the abnormal load accuracy is caused by tilting or sudden load changes.

[0043] For example, in a static load test of a pile foundation, the data acquisition time points were set at 10 minutes per hour for a total of 24 hours, i.e., n=144. At each acquisition time point, 20 load values ​​of the pile were obtained through a pressure membrane sensor, and the variance of these 20 values ​​was calculated to obtain the pressure distribution value YF. i Simultaneously, the maximum tilt angle value among the four tilt sensors is recorded as the tilt risk value QF. i The difference in settlement between the displacement sensor readings at the current time point and the previous time point is calculated to obtain the settlement change value CB. i The load change value ZB is obtained by calculating the difference between the applied load value of the pressure sensor at the current time point and the previous time point. i .

[0044] Step 3: Data fusion processing of the pile foundation static load test: The YF values ​​from the previous pile foundation static load test are processed using the entropy method. i QF i and CB i / ZB i The weight coefficients t1, t2, and t3 are obtained by performing numerical standardization, index weight calculation, and entropy calculation. Then, the weights are calculated using the formula DP. i =t1×YF i +t2×QF i +t3×CB i / ZB i Get the collection time point T i DP load deviation factori Retrieve load deviation threshold DP max The collection time point T i DP load deviation factor i Deviation from the stacking threshold DP max Comparison: If the load deviation coefficient DP i Less than the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i If the loading accuracy meets the requirements, the experiment continues, and step four is executed; if the loading deviation coefficient DP i Greater than or equal to the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i The load accuracy does not meet the requirements, so the test is suspended. The L1 counterweight blocks with the largest load values ​​are marked as abnormal load areas. A counterweight adjustment signal is generated and sent to the mobile terminal of the management personnel.

[0045] In this process, numerical standardization employs the range method to eliminate dimensional differences. The weighting of indicators is calculated by dividing each indicator's value by the total value of that indicator. Entropy is calculated using the natural logarithm function to quantify the information entropy of the indicators. Weighting coefficients are determined based on the ratio of information entropy to the number of indicators, and these coefficients are negatively correlated with the information entropy of the indicators. During weighted summation, the ratios of pressure distribution values, tilt risk values, and settlement change values ​​to load change values ​​are multiplied by their respective weighting coefficients and then summed to obtain the load deviation coefficient.

[0046] Specifically, in the previous static load test of the pile foundation, the pressure distribution value, tilt angle risk value, and the ratio of settlement change value to load change value were constructed into data matrices. Range standardization was performed on each indicator to eliminate dimensional differences. The proportion of each indicator's value at each time point to the sum of its values ​​at all time points was calculated as the indicator weight. Based on the indicator weights, the information entropy of each indicator was calculated; a higher information entropy value indicates lower data dispersion. A difference coefficient was calculated based on the information entropy; the difference coefficient is complementary to the information entropy, and a higher difference coefficient results in a higher weighting coefficient. Finally, three weighting coefficients were obtained by normalizing the difference coefficients, corresponding to the pressure distribution value, tilt angle risk value, and the ratio of settlement change value to load change value, respectively. In the current test, the real-time collected values ​​of the three indicators were multiplied by their corresponding weighting coefficients and then linearly superimposed to generate the load deviation coefficient. This process objectively reflects the influence of each indicator on the load deviation using the entropy method, avoiding subjective bias from manual weighting, improving the calculation accuracy of the load deviation coefficient, and thus ensuring the reliability of the load accuracy determination.

[0047] The value of L1 is set proportionally according to the total number of counterweights, and can be taken as 5%-10% of the total number of counterweights in specific implementation; the counterweight adjustment signal includes the three-dimensional coordinate positioning information of the abnormal area and the load exceeding the standard value; the mobile terminal receives data through an encrypted communication protocol, and the managers can view the real-time load distribution heat map through the mobile application.

[0048] Specifically, when the pressure diaphragm sensor array detects the load values ​​on the contact surfaces of each counterweight, the data processing system sorts the load values ​​in descending order and extracts the first L1 samples. The coordinates of the abnormal area are generated by matching the counterweight installation location database and encapsulated together with the load data into a JSON format data packet. The mobile communication module uses a 4G / 5G dual-mode transmission mechanism to ensure signal stability. After receiving the data, management personnel can overlay the location of the abnormal area onto an AR augmented reality interface, guiding on-site personnel to prioritize adjusting counterweights with excessive loads, thereby quickly restoring the stacking balance.

[0049] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0050] In the static load test of the pile foundation, the data collection time point T i When determining whether the stacking accuracy meets the requirements, the preset stacking deviation threshold DP is first retrieved. max The load deviates from the threshold DP. max It can be determined based on engineering experience and relevant specifications; for example, it can be set to 0.05.

[0051] Next, the data collection time point T will be... i DP load deviation factor i Deviation from the stacking threshold DP max A comparison is made. Specifically, if the overload deviation coefficient DP... i Less than the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i The load accuracy meets the requirements. Under these circumstances, the test continues, and subsequent implicit risk analysis steps are performed.

[0052] Conversely, if the load deviation factor DP i Greater than or equal to the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i The load accuracy does not meet the requirements. At this point, the test will be paused for necessary adjustments and checks.

[0053] For example, suppose that in a static load test of a pile foundation, the calculated load deviation coefficient DP5 at the data collection time point T5 is 0.047, while the preset load deviation threshold DP maxThe value is 0.05. Since 0.047 < 0.05, the load accuracy at this time point is determined to meet the requirements, and the test continues.

[0054] Furthermore, if the calculated load deviation coefficient DP8 is 0.052 at the data acquisition time point T8, which is greater than the preset load deviation threshold of 0.05, then the load accuracy at this time is determined to be unsatisfactory, and the test will be suspended.

[0055] Step 4: Conduct implicit risk analysis on the static load test of the pile foundation: QF i With QF i-1 The difference is marked as the acquisition time point T. i tilt angle monitoring value QJ i The tilt angle monitoring value QJ i The time point T with the largest value i Deviation coefficient DP from load i The time point T with the largest value i The ratio of the time interval between tests to the duration of the static load test for the pile foundation is marked as the time risk value, and the surcharge deviation coefficient DP is used as the time risk value. i The maximum value of the stacking deviation from the threshold DP max The ratio is marked as the spatial risk value, and the difference between the spatial risk value and the temporal risk value is marked as the latent risk value. The latent risk threshold is obtained from the database, and the latent risk value is compared with the latent risk threshold: if the latent risk value is less than the latent risk threshold, it is determined that the latent risk of the pile foundation static load test meets the requirements; if the latent risk value is greater than or equal to the latent risk threshold, it is determined that the latent risk of the pile foundation static load test does not meet the requirements, a risk warning signal is generated, and the risk warning signal is sent to the mobile terminal of the management personnel.

[0056] Among them, the tilt angle monitoring value QJ i The dynamic changes in the tilt state of the counterweight are reflected by calculating the difference between tilt angle sensor data at adjacent time points; the time risk value is calculated by the ratio of the interval between the maximum tilt angle monitoring value and the time point corresponding to the maximum load deviation coefficient, quantifying the temporal correlation between tilt angle mutation and load deviation; the spatial risk value is calculated by the ratio of the peak value of the load deviation coefficient to the threshold value, characterizing the spatial accumulation degree of load deviation; the implicit risk value is calculated by the difference between the spatial risk value and the time risk value, comprehensively assessing the spatiotemporal risk superposition effect.

[0057] Specifically, during the experiment, pressure membrane sensors, tilt sensors, and displacement sensors collected real-time data on the load on the surcharge, the tilt angle of the counterweight, and the settlement at the top of the pile. After data fusion processing, the surcharge deviation coefficient DP was generated. i By extracting QF i With QF i-1 The difference is worth QJ iIdentify the moment of most dramatic change in tilt angle and correlate it with DP. i The time interval at the peak moment is calculated, and the time risk value is obtained by combining it with the total test duration. Simultaneously, DP... i Maximum value and threshold DP max The ratio of the spatial risk value to the temporal risk value is used as the spatial risk value, reflecting the spatial distribution limit of load deviation. Finally, by calculating the difference between the spatial risk value and the temporal risk value, the single-dimensional error is eliminated, and the implicit risk value is generated.

[0058] The calculation of implicit risk values ​​includes the difference between temporal and spatial risk values. The temporal risk value reflects the rate of risk accumulation by the proportion of the time interval between the extreme point of tilt monitoring and the deviation of the load from the extreme point. The spatial risk value reflects the degree of load distribution anomaly by the ratio of the maximum value of the load deviation coefficient to a threshold. For example, when the tilting trend of the counterweight intensifies, QJ... i The maximum value corresponds to a sampling time point that may be earlier than DP. i The maximum value corresponds to the data collection time point. At this point, the proportion of time intervals increases, and the latent risk value increases accordingly. During the risk assessment process, the latent risk threshold can be set to 0.8 based on historical test data. When the latent risk value exceeds this threshold, an early warning signal is triggered.

[0059] Specifically, during the experiment, the tilt angle monitoring value QJ i The tilting trend of the counterweight is dynamically reflected by the difference in tilt angle data at adjacent time points, when QJ i The maximum value corresponds to the sampling time point and the load deviation coefficient DP. i When the maximum value corresponds to a long interval between data collection points, it indicates a temporal correlation between abnormal load distribution and structural tilt, thus increasing the temporal risk value. The spatial risk value is determined by DP. i Maximum value and DP max The ratio quantifies the severity of load deviation. The latent risk value, calculated by subtracting the temporal risk value from the spatial risk value, eliminates the limitations of a single-dimensional risk indicator. For example, when the spatial risk value is high but the temporal risk value is low, it indicates that the anomaly is concentrated in a local area and has not continued to worsen; in this case, the latent risk value may still be below the threshold. After the risk warning signal is generated, it is transmitted to the management personnel terminal via a mobile communication network, achieving real-time closed-loop management of test risks.

[0060] A method for analyzing the surcharge accuracy of pile foundation static load tests based on multi-sensor fusion is proposed. During operation, sensors are first deployed for the pile foundation static load test, and multiple acquisition time points T are set after the test begins. i Load parameters are collected, and then the collected load parameters are numerically processed to obtain the data at each collection time point T. i DP load deviation factor i By comparing DP iThe system uses a preset threshold to determine if the load accuracy meets the requirements. If not, it identifies abnormal load areas and finally obtains the latent risk value to determine if the requirements are met. Specifically, the sensor deployment step establishes a multi-dimensional real-time monitoring system that can simultaneously capture changes in multiple parameters such as counterweight pressure distribution and tilt angle. The data acquisition and preprocessing step enables dynamic acquisition of key parameters. The data fusion processing step constructs a load deviation coefficient to comprehensively reflect abnormal states such as load eccentricity and counterweight tilt. The latent risk analysis step quantitatively assesses the potential structural damage risk after the test is interrupted. These steps work together to form a complete analysis chain from data acquisition and anomaly detection to risk assessment. The introduction of the load deviation coefficient breaks through the limitations of traditional single-threshold alarms, and the calculation of latent risk values ​​provides data support for subsequent scheme adjustments. This multi-dimensional and dynamically integrated analysis method can more comprehensively and accurately assess load accuracy and test risks.

[0061] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0062] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0063] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for analyzing the surcharge accuracy of static load tests on pile foundations based on multi-sensor fusion, characterized in that, Includes the following steps: Step 1: Set up sensors for the static load test of the pile foundation; Step 2: Data Acquisition and Preprocessing for Static Load Test of Pile Foundation: After the static load test of pile foundation begins, set the data acquisition time point T. i Let i = 1, 2, ..., n, where n is a positive integer, and the data is collected at time point T. i Collect load parameters; Step 3: Data fusion processing of pile foundation static load test: Numerical processing of load parameters to obtain the acquisition time point T i DP load deviation factor i Through the load deviation coefficient DP i For the data collection time point T i The surcharge accuracy is judged to meet the requirements, and abnormal surcharge areas are screened when the surcharge accuracy does not meet the requirements. Step 4: Conduct implicit risk analysis on the static load test of the pile foundation: obtain implicit risk values, and determine whether the implicit risks of the static load test of the pile foundation meet the requirements based on the implicit risk values; In step two, the process of acquiring the load parameters includes: obtaining the load value of the accretion mass using a pressure membrane sensor, and then... i The pressure distribution value YF is obtained by calculating the variance of the load values ​​of the stack carrier acquired by all pressure membrane sensors. i All tilt sensors were collected at time point T. i The obtained maximum tilt angle value is marked as the tilt angle risk value QF. i The displacement sensor was used at the data acquisition time point T. i With the collection time point T i-1 The difference in the obtained settlement values ​​is denoted as the settlement change value CB. i The pressure sensor was used to collect data at time point T. i With the collection time point T i-1 The difference between the obtained applied load values ​​is labeled as the load change value ZB. i ; In step three, the data collection time point T i DP load deviation factor i The acquisition process includes: using the entropy method to analyze the YF value from the previous pile foundation static load test. i QF i and CB i / ZB i Numerical standardization, index weight calculation, and entropy calculation are performed to obtain weight coefficients t1, t2, and t3. Then, the weights are calculated using YF... i QF i CB i / ZB i The data collection time point T is obtained by weighted summation of the weighting coefficients. i DP load deviation factor i ; In step three, the data collection time point T is... i The specific process for determining whether the stacking accuracy meets the requirements includes: retrieving the stacking deviation threshold DP. max The collection time point T i DP load deviation factor i Deviation from the stacking threshold DP max Comparison: If the load deviation coefficient DP i Less than the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i If the loading accuracy meets the requirements, the experiment continues, and step four is executed; if the loading deviation coefficient DP i Greater than or equal to the stacking deviation threshold DP max Then it is determined that the static load test of the pile foundation was conducted at the data collection time point T. i The load accuracy did not meet the requirements, and the test was suspended. In step four, the process of obtaining the latent risk value includes: [The text abruptly ends here, likely due to an incomplete sentence or a formatting error.] i With QF i-1 The difference is marked as the acquisition time point T. i tilt angle monitoring value QJ i The tilt angle monitoring value QJ i The time point T with the largest value i Deviation coefficient DP from load i The time point T with the largest value i The ratio of the time interval between tests to the duration of the static load test for the pile foundation is marked as the time risk value, and the surcharge deviation coefficient DP is used as the time risk value. i The maximum value of the stacking deviation from the threshold DP max The ratio is marked as the spatial risk value, and the difference between the spatial risk value and the temporal risk value is marked as the implicit risk value.

2. The method for analyzing the surcharge accuracy of pile foundation static load tests based on multi-sensor fusion according to claim 1, characterized in that, In step one, the specific process of sensor deployment includes: setting pressure diaphragm sensors on the contact surface between counterweights, setting tilt sensors at the four corners of each layer of counterweights, setting displacement sensors on the pile top reference beam, and setting pressure sensors in the hydraulic pipeline of the jack.

3. The method for analyzing the surcharge accuracy of pile foundation static load tests based on multi-sensor fusion according to claim 2, characterized in that, In step three, the screening process for abnormal load areas includes: marking the L1 counterweight blocks with the largest load values ​​as abnormal load areas, generating a counterweight adjustment signal, and sending the counterweight adjustment signal and the abnormal load areas to the mobile terminal of the management personnel.

4. The method for analyzing the surcharge accuracy of pile foundation static load tests based on multi-sensor fusion according to claim 3, characterized in that, In step four, the specific process for determining whether the implicit risks of the static load test of the pile foundation meet the requirements includes: retrieving the implicit risk threshold and comparing the implicit risk value with the implicit risk threshold; if the implicit risk value is less than the implicit risk threshold, the implicit risks of the static load test of the pile foundation meet the requirements; if the implicit risk value is greater than or equal to the implicit risk threshold, the implicit risks of the static load test of the pile foundation do not meet the requirements, a risk warning signal is generated, and the risk warning signal is sent to the mobile terminal of the management personnel.

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