A dynamic sounding in-situ test automation system and method

Abstract

The application discloses a kind of power sounding in-situ test automation system and method, belong to geotechnical engineering in-situ test technical field.System includes mechanical execution module, data acquisition module, core control module and man-machine interaction module, core control module is connected with other module respectively, overall test process and data processing;Mechanical execution module automatically completes drop hammer lifting, release and sounding rod penetration action;Data acquisition module synchronously collects penetration depth, impact acceleration and formation resistance signal;Man-machine interaction module realizes instruction input and information output.The application solves the problem of poor coordination, low efficiency, unreliable data and other problems caused by lack of integrated architecture in traditional test, realizes test full-process automation and standardization, improves test efficiency and data repeatability, accuracy, meets the demand of modern engineering informatization survey, and has wide application prospect.

Description

Technical Field

[0001] This invention relates to the field of in-situ testing technology in geotechnical engineering, specifically to an automated system and method for dynamic penetration in-situ testing. Background Technology

[0002] In-situ dynamic penetration testing (DPPT) is a core method in geotechnical engineering investigation for assessing foundation bearing capacity, determining soil density, and obtaining pile foundation design parameters. It is widely used in infrastructure construction fields such as highways, railways, water conservancy, and buildings. Especially under complex geological conditions, it can provide continuous and representative in-situ data, compensating for the shortcomings of indoor testing sampling in terms of disturbance and representativeness. It serves as a crucial bridge connecting geological investigation and engineering design. However, traditional dynamic penetration testing has long lacked an integrated automated architecture, relying entirely on manual operation. This results in independent testing stages and a lack of coordination, severely restricting testing efficiency and data reliability. Specifically, the manual operation of mechanical actuators is completely disconnected from the data acquisition process, making it impossible to dynamically adjust test actions based on real-time acquired formation response data. The testing process lacks standardized closed-loop control logic, making it prone to confusion, misoperation, or even test interruption due to differences in operator experience, fatigue, or operational negligence. Data acquisition relies on manual reading and recording, and key parameters such as penetration depth and number of hammer blows are susceptible to visual errors, omissions, or misrecording. Furthermore, multi-channel data cannot be captured synchronously, making it difficult to fully obtain the transient response signal of hammer blows. Data processing requires manual post-processing and analysis, which is not only inefficient but also susceptible to environmental noise interference, leading to insufficient data reliability. Additionally, remote sharing and real-time monitoring of test data are not possible, failing to meet the needs of modern engineering informatization and large-scale exploration. To address the series of problems caused by the lack of an integrated and automated architecture, this invention proposes an automated system and method for in-situ dynamic penetration testing. Through modular integrated design, it achieves automation, precision, and intelligence throughout the entire testing process, providing efficient and reliable technical support for geotechnical engineering exploration. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the present invention aims to provide an automated system and method for in-situ dynamic probing testing, which solves the problems of poor coordination, low efficiency, and unreliable data caused by the lack of integrated architecture in traditional testing, and achieves full automation and standardization of the testing process.

[0004] To achieve the above objectives, the embodiments of this invention provide the following technical solutions:

[0005] This application provides an automated system for in-situ testing of dynamic penetration test, comprising: a mechanical execution module for automatically executing the lifting and releasing of the drop hammer and the penetration action of the penetration rod; a data acquisition module for acquiring the penetration depth, impact acceleration, and formation resistance signals of the penetration rod; a core control module connected to the mechanical execution module and the data acquisition module respectively, for controlling the test process and processing data; and a human-machine interaction module connected to the core control module for receiving instructions and outputting information.

[0006] Furthermore, the mechanical execution module includes a drop hammer drive unit; the drop hammer drive unit includes a lifting mechanism consisting of a ball screw driven by a servo motor and a release mechanism consisting of dual electromagnets; the lifting mechanism integrates a photoelectric encoder for real-time feedback of the drop hammer position; the release mechanism is used to achieve contactless release of the drop hammer after receiving an electrical signal.

[0007] Furthermore, the data acquisition module includes a displacement sensing unit, an acceleration sensing unit, and a force sensing unit; the acceleration sensing unit is mounted on the hammer body, and the impact pulse output by the acceleration sensing unit is designated as a global hardware trigger signal to initiate synchronous sampling of the displacement sensing unit and the force sensing unit; the data acquisition module includes a high-speed acquisition circuit based on FPGA, used to synchronously acquire and latch the data of each sensing unit at a sampling rate of not less than 10KHz when the global hardware trigger signal is valid.

[0008] Furthermore, the core control module includes: a process control unit, the operation logic of which is based on a state machine model including IDLE, RISING, READY, IMPACT, and RECOVERY states; a data processing unit, which integrates a Kalman filter algorithm for online denoising and fusion of multi-channel synchronization signals; and a communication unit, which supports uploading the processed data to a remote server via a wireless network.

[0009] This application embodiment also provides an automated method for in-situ dynamic penetrometer testing. The automated method is scheduled and executed by the core control module and includes the following steps: S1, setting the drop hammer height and target depth parameters through the human-machine interface module, and driving the drop hammer to reset to its initial position via the mechanical execution module; S2, the core control module repeatedly executes the following sub-steps until the test termination condition is met: S21, controlling the servo motor to raise the drop hammer to the set height based on feedback from the photoelectric encoder; S22, triggering the electromagnetic release device to allow the drop hammer to... S3. At the moment of each impact, the pulse generated by the acceleration sensing unit triggers the FPGA high-speed acquisition circuit to simultaneously acquire the current penetration depth, impact acceleration, and formation resistance signals of the probe; S4. The core control module processes the penetration depth, impact acceleration, and formation resistance signals of the probe in real time, calculates the current cumulative depth, and compares it with the target depth parameter to decide whether to start the next cycle of step S2 or end the test; S5. After the test, the penetration resistance curve and test report are automatically generated and input.

[0010] Furthermore, in sub-step S21, the core control module dynamically adjusts the operation of the servo motor using a PID control algorithm based on the real-time feedback from the photoelectric encoder, in order to calibrate and lock the lifting height of the drop hammer.

[0011] Furthermore, in sub-step S22, the electromagnetic release device employs a dual electromagnet cooperative control mechanism to perform contactless release.

[0012] Furthermore, in step S3, after receiving the trigger pulse, the FPGA high-speed acquisition circuit adds a unified timestamp to the synchronously acquired acceleration, displacement, and force signals.

[0013] Further, step S4 includes the following sub-steps: S41, the data processing unit uses the Kalman filter algorithm to denoise and fuse the synchronously acquired signal; S42, calculates and accumulates the penetration increment of a single hammer blow based on the processed displacement signal; S43, compares the accumulated penetration depth with the target depth, and if the target depth is not reached, triggers the next round of S2 loop, and if the target depth is reached, terminates the test.

[0014] Furthermore, in step S5, the communication unit uploads the generated test report to the cloud platform, and the core control module can analyze the characteristics of the resistance curve collected in real time based on the adaptive algorithm trained on historical data to assist in soil interface identification.

[0015] The beneficial effects of this invention are as follows: Through the coordinated design of four modules, a complete transformation of dynamic penetration testing from "manual operation" to "automated closed-loop" is achieved. The mechanical execution module replaces manual labor in completing the high-intensity, repetitive hammer lifting and releasing actions, significantly reducing the labor intensity of operators and avoiding the physiological limitations caused by manual operation. The data acquisition module achieves simultaneous capture of multiple parameters such as penetration depth, impact acceleration, and formation resistance, completely eliminating human reading errors and ensuring the authenticity and integrity of the raw data. The core control module coordinates the testing process and data processing, strictly following the preset logical specifications to execute each step of the operation, avoiding process chaos caused by differences in human experience. The human-computer interaction module provides an intuitive interface for parameter input, status display, and result output, allowing operators to quickly get started without professional skills. At the same time, the real-time feedback of test data and curves helps operators to promptly identify anomalies and improve the controllability of the testing process. The seamless integration of the four modules not only greatly improves testing efficiency but also significantly reduces data dispersion, improves the comparability and reliability of test results, and provides more accurate basic data for geotechnical engineering design. Attached Figure Description

[0016] Figure 1 This application provides a schematic diagram of the structure of an automated in-situ dynamic penetration testing system.

[0017] Figure 2 This application provides a flowchart illustrating an automated method for in-situ dynamic penetration testing. Detailed Implementation

[0018] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0019] In this invention, the terms "system" and "network" are used interchangeably. "Multiple" refers to two or more; therefore, in this invention, "multiple" can also be understood as "at least two." "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / ", unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, it should be understood that in the description of this invention, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0020] The inability to link manual operation of mechanical actuators with data acquisition makes it difficult to dynamically adjust test actions based on real-time data. Data processing relies on manual intervention, resulting in the test process failing to form a closed loop. The separation of operation and result output makes it impossible for operators to grasp the test status in real time, which easily leads to misoperation or test interruption. Ultimately, this results in low test efficiency, poor data consistency, and insufficient reliability of results, failing to meet the standardization and efficiency requirements of modern geotechnical engineering investigation.

[0021] like Figures 1-2 As shown in the figure, this application provides an automated system for in-situ testing of dynamic penetrometers, including: a mechanical execution module for automatically executing the lifting and releasing of the drop hammer and the penetration of the penetrometer rod; a data acquisition module for acquiring the penetration depth, impact acceleration, and formation resistance signals of the penetrometer rod; a core control module connected to the mechanical execution module and the data acquisition module respectively, for controlling the testing process and processing data; and a human-machine interaction module connected to the core control module for receiving instructions and outputting information.

[0022] In another possible embodiment, the core control module serves as the central hub, establishing bidirectional signal transmission connections with the mechanical execution module, data acquisition module, and human-machine interaction module via standardized communication interfaces to achieve information exchange and collaborative work among the modules. The mechanical execution module is deployed at a designated location on the test site, with its probe vertically aligned with the test point, responsible for executing mechanical actions such as lifting and releasing the hammer and penetrating the probe. The various sensing units of the data acquisition module are respectively installed on the hammer body, probe, and related force-bearing components to ensure real-time capture of various physical signals during the test. The core control module employs a high-performance embedded processor, pre-programmed with preset control logic and data processing algorithms, serving as the control unit for the entire system. The core control module is located at the field operation terminal or remote monitoring terminal, and is connected to the core control module via wired or wireless means. The operator inputs the relevant parameters required for the test through the human-machine interaction module. After receiving the command, the core control module sends the corresponding action command to the mechanical execution module, driving the drop hammer to complete the lifting and releasing according to the preset parameters. At the same time, the data acquisition module transmits the collected signals such as penetration depth, impact acceleration, and formation resistance to the core control module in real time. After processing and analyzing the received data, the core control module feeds back the test status, data curves, and preliminary results to the human-machine interaction module, forming a closed-loop operation of "command input - action execution - data acquisition - data processing - result output".

[0023] Through the collaborative design of four modules, the dynamic penetration test (DPPT) achieves a complete transformation from "manual operation" to "automated closed-loop." The mechanical execution module replaces manual labor in performing the high-intensity, repetitive hammer lifting and releasing actions, significantly reducing the labor intensity of operators and avoiding the physiological limitations imposed by manual operation. The data acquisition module simultaneously captures multiple parameters such as penetration depth, impact acceleration, and formation resistance, completely eliminating human reading errors and ensuring the authenticity and integrity of the raw data. The core control module coordinates the testing process and data processing, strictly adhering to preset logical specifications to execute each step of the operation, avoiding process chaos caused by differences in human experience. The human-machine interaction module provides an intuitive interface for parameter input, status display, and result output, allowing operators to quickly get started without specialized skills. Simultaneously, real-time feedback of test data and curves helps operators promptly identify anomalies, improving the controllability of the testing process. The seamless integration of these four modules not only significantly improves testing efficiency but also substantially reduces data dispersion, enhancing the comparability and reliability of test results, and providing more accurate basic data for geotechnical engineering design.

[0024] If traditional manual hammer lifting or simple mechanical hammer dropping methods are used, manual hammer lifting cannot guarantee that the drop distance is completely consistent each time. Operator muscle fatigue or operational negligence can lead to deviations in the drop distance, which in turn causes fluctuations in impact energy and affects the repeatability of test results. Mechanical contact release devices suffer from frictional wear, which can lead to release delays and energy loss. Lateral swaying is also prone to occur during hammer dropping, affecting the stability of the probe penetration. The lack of a real-time position feedback mechanism makes it impossible to dynamically correct the hammer drop height. After long-term operation, deviations caused by mechanical wear will continue to accumulate, further reducing the reliability of test data.

[0025] In the embodiments of this application, the mechanical execution module includes a drop hammer drive unit; the drop hammer drive unit includes a lifting mechanism composed of a ball screw driven by a servo motor and a release mechanism composed of dual electromagnets; the lifting mechanism integrates a photoelectric encoder for real-time feedback of the drop hammer position; the release mechanism is used to realize contactless release of the drop hammer after receiving an electrical signal.

[0026] In another possible embodiment, the ball screw is vertically installed inside the guide frame. A servo motor is connected to the input end of the ball screw via a coupling. The drop hammer engages with the ball screw via a slider, enabling the drop hammer to achieve stable vertical lifting and lowering along the guide frame. A photoelectric encoder is installed at the top of the ball screw to collect the rotation angle of the screw in real time. The core control module calculates the actual lifting height of the drop hammer using this rotation angle signal, forming a closed-loop position control. An electromagnetic release device is fixed at a preset height position on the guide frame to ensure that the drop hammer is accurately attracted and fixed when it is lifted to the target height. Before testing, select the appropriate device according to the test type. The corresponding drop hammer mass module is installed and fixed, and the drop distance parameters are preset through the core control module. During the test, the core control module sends a drive command to the servo motor, which drives the ball screw to rotate and drives the drop hammer to rise along the guide frame. The photoelectric encoder feeds back the drop hammer position signal to the core control module in real time. The core control module adjusts the running state of the servo motor according to the feedback signal so that the drop hammer accurately reaches the preset height. When the drop hammer reaches the target height, the electromagnetic release device attracts and fixes the drop hammer. After the core control module issues an impact trigger command, the electromagnetic release device is quickly de-energized, releasing the drop hammer so that it falls freely along the guide frame to impact the probe rod.

[0027] The lifting mechanism, composed of a servo motor and ball screw, boasts high transmission precision and strong stability. Combined with real-time position feedback from a photoelectric encoder, it precisely controls the lifting height of the hammer, ensuring consistent drop distances and thus guaranteeing the stability of each impact energy. This reduces testing errors caused by energy fluctuations at the source. The electromagnetic release device enables contactless release of the hammer, avoiding frictional losses and action delays caused by mechanical contact. It releases the hammer rapidly upon receiving a trigger command, ensuring effective energy transfer. The lifting mechanism, in conjunction with the guide frame, constrains the hammer's trajectory, preventing lateral swaying during lifting and lowering, ensuring the verticality of the penetration rod, and improving testing stability. Multiple hammer mass modules of various specifications can be quickly replaced to adapt to different types of dynamic penetrometer testing requirements, enhancing the system's engineering applicability.

[0028] Traditional testing methods, which rely on manual measurement of penetration depth and visual observation of the impact state, lead to asynchronous acquisition of multiple parameters. Penetration depth, impact acceleration, and formation resistance cannot correspond at the same time point, making it difficult to fully analyze the transient impact response process. The low sampling rate fails to capture high-frequency signals at the moment of impact, resulting in data distortion and an inability to reflect the true mechanical characteristics of the impact process. Furthermore, the lack of a globally unified triggering mechanism makes it easy for acquisition timing to lag, leading to the loss of key transient data and ultimately affecting the accuracy of formation mechanical parameter inversion, thus failing to provide a reliable basis for engineering design.

[0029] In an embodiment of this application, the data acquisition module includes a displacement sensing unit, an acceleration sensing unit, and a force sensing unit; the acceleration sensing unit is mounted on the hammer body, and the impact pulse output by the acceleration sensing unit is designated as a global hardware trigger signal to initiate synchronous sampling of the displacement sensing unit and the force sensing unit; the data acquisition module includes a high-speed acquisition circuit based on FPGA, used to synchronously acquire and latch the data of each sensing unit at a sampling rate of not less than 10KHz when the global hardware trigger signal is valid.

[0030] In another possible embodiment, a displacement sensing unit is mounted on the top of the guide rod to monitor the penetration depth change of the probe in real time; an acceleration sensing unit is fixed on the top of the hammer to ensure accurate capture of the acceleration pulse at the moment of hammer impact; a force sensing unit is mounted at the connection between the probe and the probe to measure the resistance signal of the formation to the probe; the FPGA high-speed acquisition circuit is connected to each sensing unit through shielded cables, and the front end of the acquisition circuit is equipped with a low-noise amplifier and an anti-aliasing filter circuit to preprocess the analog signals output by the sensing units; the impact pulse output by the acceleration sensing unit is configured as a global hardware trigger signal, and the sampling rate of the acquisition circuit is preset; when the hammer impacts the probe, the acceleration sensing unit generates an impact pulse, which triggers the FPGA high-speed acquisition circuit to start working, synchronously acquiring the analog signals output by the displacement sensing unit, acceleration sensing unit, and force sensing unit, and converting the analog signals into digital signals and latching them in the buffer; after acquisition, the FPGA high-speed acquisition circuit transmits the latched digital signals to the core control module through the data bus for subsequent data processing.

[0031] By using the impact pulse output from the accelerometer as the global hardware trigger signal, displacement, acceleration, and force signals can be synchronously acquired at the moment of impact, achieving time-dimensional alignment of multiple parameters and providing a foundation for analyzing the dynamic correlation of various parameters during the impact process. The FPGA high-speed acquisition circuit has high sampling rate characteristics, which can completely record the high-frequency dynamic response waveform at the moment of impact, avoiding signal distortion caused by insufficient sampling rate and ensuring the integrity of the original data. Each sensor unit has undergone professional temperature compensation and field calibration, which can adapt to different field working environments and ensure the accuracy and stability of the measurement data. The low-noise amplifier and anti-aliasing filter circuit at the front end of the acquisition circuit can effectively suppress environmental interference and circuit noise, improve the signal-to-noise ratio, and ensure the fidelity of the acquired data.

[0032] Traditional testing processes lack standardized control and rely on the experience and judgment of operators, which can easily lead to omissions or disordered sequences, resulting in test interruptions or incomplete data. Raw data contains a large amount of noise such as mechanical vibration and electromagnetic interference. Without professional filtering, direct use of this data for calculations can lead to large errors in key parameters such as penetration resistance. Data transmission relies on manual copying, making real-time monitoring and remote analysis impossible. Engineering managers cannot keep track of test progress and results in a timely manner, affecting the efficiency of engineering decision-making. At the same time, the scattered storage of data is not conducive to centralized management and sharing.

[0033] In the embodiments of this application, the core control module includes: a process control unit, the operation logic of which is based on a state machine model including IDLE, RISING, READY, IMPACT, and RECOVERY states; a data processing unit, which integrates a Kalman filter algorithm for online denoising and fusion of multi-channel synchronization signals; and a communication unit, which supports uploading the processed data to a remote server via a wireless network.

[0034] In another possible embodiment, after the core control module is powered on and initialized, the process control unit enters the IDLE state, waiting for the start command from the human-machine interface module. Upon receiving the start command, the process control unit switches to the READY state, completing equipment self-test and parameter loading. Subsequently, it sends a lifting command to the mechanical execution module, and the process control unit enters the RISING state, driving the drop hammer to lift to a preset height. After the drop hammer reaches its position, the process control unit switches to the IMPACT state, triggering the electromagnetic release device to release the drop hammer, and simultaneously initiating data acquisition. After the impact is completed, the process control unit enters the RECOVERY state, receiving and processing the acquired data, and determining whether the test termination conditions are met. If the conditions are not met, the system returns to the RISING state and starts the next loop; if the conditions are met, the test terminates. During data processing, the data processing unit calls the Kalman filter algorithm to perform online noise reduction on the multi-channel synchronous signals transmitted by the FPGA high-speed acquisition circuit. After removing noise interference, it calculates key parameters such as penetration depth increment, hammer blow count, and penetration resistance. The communication unit uploads the processed raw data, key parameters, and test status to a remote server or cloud platform via the wireless communication module. It also supports storing data on local storage media to ensure no data loss. Remote terminals can access the cloud platform or server to view the test progress and data results in real time, enabling remote monitoring and collaborative analysis.

[0035] The state machine model clearly defines the switching logic for each stage of the test, ensuring that the test process is executed strictly according to the preset steps, avoiding process chaos caused by human intervention, and ensuring the standardization and normalization of the test process. The Kalman filter algorithm can effectively suppress the impact of noise such as mechanical vibration and electromagnetic interference on the data, improve the smoothness and accuracy of the data, and make the calculated key parameters such as penetration resistance and hammer blow count more reflective of the true characteristics of the formation. The wireless communication unit supports real-time data upload to a remote server or cloud platform, realizing centralized management and remote access to test data. Engineering managers can view the test progress and results at any time, make timely decisions, and facilitate cross-regional collaborative analysis. The multi-unit collaborative work of the core control module realizes the integration of test process control, data processing, and data transmission, improving the system's integration and automation level.

[0036] In traditional manual testing processes, parameter setting relies on manual recording, which is prone to parameter confusion or omission; drop hammer cyclic impact requires manual judgment of lifting height and release timing, which is inefficient and inconsistent; data acquisition and testing decisions are disconnected, making it impossible to dynamically adjust the testing process based on real-time penetration depth; result generation requires manual data processing and curve plotting, which is time-consuming and error-prone, making it difficult to meet the schedule requirements of large-scale exploration projects. At the same time, manual data processing leads to inconsistent result formats, affecting data comparability and sharing.

[0037] This application embodiment also provides an automated method for in-situ dynamic penetrometer testing. The automated method is scheduled and executed by the core control module and includes the following steps: S1, setting the drop hammer height and target depth parameters through the human-machine interface module, and driving the drop hammer to reset to its initial position via the mechanical execution module; S2, the core control module repeatedly executes the following sub-steps until the test termination condition is met: S21, controlling the servo motor to raise the drop hammer to the set height based on feedback from the photoelectric encoder; S22, triggering the electromagnetic release device to allow the drop hammer to... S3. At the moment of each impact, the pulse generated by the acceleration sensing unit triggers the FPGA high-speed acquisition circuit to simultaneously acquire the current penetration depth, impact acceleration, and formation resistance signals of the probe; S4. The core control module processes the penetration depth, impact acceleration, and formation resistance signals of the probe in real time, calculates the current cumulative depth, and compares it with the target depth parameter to decide whether to start the next cycle of step S2 or end the test; S5. After the test, the penetration resistance curve and test report are automatically generated and input.

[0038] In another possible embodiment, the operator inputs test parameters such as the drop hammer height and target penetration depth through the human-machine interface module. After receiving and storing these parameters, the core control module sends a reset command to the mechanical execution module, driving the drop hammer back to its initial position. Simultaneously, it initiates sensor calibration and equipment self-test procedures to ensure that each module is working properly. After the equipment is ready, the core control module initiates the cyclic impact logic. First, it sends a lifting command to the mechanical execution module to control the servo motor to operate. Based on the position signal fed back by the photoelectric encoder, it lifts the drop hammer to a preset height and locks it. Then, the core control module sends a trigger command to the electromagnetic release device. The electromagnet is de-energized, releasing the drop hammer, which falls freely along the guide frame to impact the probe rod. At the moment of impact, the impact pulse generated by the acceleration sensing unit triggers the FPGA high-speed acquisition circuit to synchronously acquire the current moment. The system collects penetration depth, impact acceleration, and ground resistance signals, temporarily stores the collected data, and marks relevant information. The core control module reads the collected data in real time, calculates the penetration increment corresponding to this hammer blow, and accumulates it to obtain the cumulative penetration depth. The cumulative penetration depth is compared with the preset target depth. If the cumulative penetration depth does not reach the target depth, the core control module returns to the cyclic impact logic and starts the next round of hammer drop lifting and release actions. If the cumulative penetration depth reaches the target depth, the core control module triggers a test termination command. After the test, the core control module integrates all collected data and calculated key parameters, automatically plots the penetration resistance curve, and generates a standardized test report containing parameters such as soil layer boundary information, standard penetration blow count, and recommended bearing capacity. The report is displayed through the human-computer interaction module and can also be exported in a preset format for convenient subsequent use.

[0039] By automating the entire testing process—from parameter setting, cyclic impact, data acquisition to result output—requires no manual intervention, significantly shortening single-hole testing time, improving testing efficiency, and meeting the needs of large-scale exploration projects. Based on real-time acquired penetration depth data, the testing progress is dynamically assessed to avoid over-penetration or under-testing, ensuring the scientific rigor and rationality of the test. Standardized penetration resistance curves and test reports are automatically generated, with unified format, traceable data, and compliance with relevant specifications, facilitating data sharing and later review. The testing process strictly follows preset logic, reducing the impact of human factors on test results and improving data repeatability and reliability.

[0040] If the drop hammer height is not dynamically adjusted using a PID control algorithm and only relies on the fixed drive logic of the servo motor, the actual drop hammer height will deviate from the preset height due to mechanical wear, power fluctuations, or changes in environmental resistance. After long-term operation, this deviation will accumulate and directly cause fluctuations in impact energy, leading to errors in the calculation of penetration resistance. This reduces the repeatability and comparability of test results, making it impossible to accurately reflect the true mechanical properties of the formation, and thus affecting the safety and rationality of the engineering design.

[0041] In the embodiments of this application, in sub-step S21, the core control module dynamically adjusts the operation of the servo motor using a PID control algorithm based on the real-time feedback from the photoelectric encoder, so as to calibrate and lock the lifting height of the drop hammer.

[0042] In another possible embodiment, the core control module presets the target height parameter of the falling hammer. During the lifting process, the photoelectric encoder collects the rotation angle of the ball screw in real time, and the core control module converts this rotation angle signal into the actual lifting height of the falling hammer. The core control module compares the actual lifting height with the preset target height and calculates the height deviation value between the two. According to the preset proportional coefficient, integral coefficient, and derivative coefficient, the PID controller of the core control module calculates the height deviation value to obtain the speed adjustment amount of the servo motor. The core control module converts the speed adjustment amount into a corresponding drive signal and sends it to the servo motor to adjust the operating speed and rotation angle of the servo motor. The servo motor changes its operating state according to the drive signal, drives the ball screw to adjust its rotation speed, and then adjusts the lifting speed and position of the falling hammer until the actual height of the falling hammer is consistent with the preset target height. At this point, the core control module controls the servo motor to stop running and locks the position of the falling hammer.

[0043] The PID control algorithm dynamically adjusts the servo motor's operation based on the deviation between the actual and preset drop heights, compensating in real time for errors caused by mechanical wear, power fluctuations, and other factors. This ensures the drop hammer accurately reaches the preset height each time, improving drop distance control accuracy. Precise drop distance control guarantees consistent hammer energy for each impact, reducing the impact of energy fluctuations on test results. This makes the measurement of parameters such as penetration resistance and number of impacts more accurate, improving the repeatability and comparability of test data. The PID control algorithm also possesses good adaptability and stability, capable of handling interference factors in different environments. This ensures the system maintains high control accuracy during long-term operation, enhancing system reliability.

[0044] If a single electromagnet release mechanism is used, contact friction may occur during the release of the hammer due to unbalanced electromagnet adsorption and mechanical jamming. Frictional resistance will consume some impact energy, resulting in a loss of impact energy of the hammer. At the same time, it may cause lateral displacement of the hammer, affecting the verticality of the probe rod. The release response of a single electromagnet is delayed, making it impossible to achieve instantaneous unlocking of the hammer, which further aggravates energy fluctuations and test errors, leading to a decrease in the reliability of test data.

[0045] In the embodiments of this application, in sub-step S22, the electromagnetic release device employs a dual electromagnet cooperative control mechanism to perform contactless release.

[0046] In another possible embodiment, two identical electromagnets are symmetrically installed at a preset height on the guide frame, located on either side of the drop hammer, ensuring that the distance between the two electromagnets and the drop hammer is equal, thus forming a balanced attraction force on the drop hammer. The core control module establishes a signal connection with the two electromagnets, ensuring that control commands can be sent to both electromagnets simultaneously. When the drop hammer is raised to the target height, the core control module sends an attraction command to both electromagnets simultaneously. The electromagnets are energized to generate magnetic force, symmetrically attracting the drop hammer and keeping it stationary. At this time, the drop hammer is in a vertically balanced position. When the core control module issues an impact trigger command, it sends a power-off command to both electromagnets simultaneously. The magnetic force of the two electromagnets disappears instantaneously, and the drop hammer falls vertically and freely along the guide frame under the action of gravity, achieving a non-contact synchronous release and impacting the probe rod.

[0047] The balanced adsorption of the hammer is achieved by symmetrically deploying two electromagnets, avoiding tilting caused by unbalanced adsorption and ensuring that the hammer is vertical before release. The two electromagnets are controlled in tandem, and are simultaneously de-energized upon receiving a release command, enabling contactless synchronous release of the hammer. This eliminates energy loss and lateral deviation caused by mechanical friction, ensuring the integrity and stability of the hammer impact energy. The fast release response of the two electromagnets enables instantaneous unlocking of the hammer, further improving the consistency of hammer impact energy, reducing N-value measurement errors, and making the test data more reflective of the true formation conditions.

[0048] If the synchronously acquired data is not stamped with a unified timestamp, the multi-channel data (acceleration, displacement, force signals) will lack a clear temporal correlation. During later analysis, it will be impossible to determine the correspondence between the parameters at the same moment, making it difficult to accurately calculate key indicators such as impact energy transfer efficiency and transient penetration resistance. This will lead to deviations in the interpretation of formation mechanical properties, affecting the reliability of engineering design, and will also hinder the comparative analysis of multiple sets of data and data traceability.

[0049] In the embodiments of this application, in step S3, after receiving the trigger pulse, the FPGA high-speed acquisition circuit adds a unified timestamp to the synchronously acquired acceleration, displacement and force signals.

[0050] In another possible embodiment, the FPGA high-speed acquisition circuit has a built-in high-precision real-time clock. During system initialization, this real-time clock is synchronized with the clock signal of the core control module to ensure that the time base of the entire system is consistent. The preset trigger condition for the FPGA high-speed acquisition circuit is the impact pulse output by the acceleration sensing unit. When the trigger pulse occurs, the FPGA high-speed acquisition circuit immediately starts multi-channel synchronous sampling. At the same time as the sampling starts, the FPGA high-speed acquisition circuit reads the current time of the built-in real-time clock and uses this time as a unified timestamp. This timestamp is bound to the synchronously acquired acceleration, displacement, and force signal data to form a complete record containing time information and multi-parameter data. The bound complete record is stored in the buffer of the FPGA high-speed acquisition circuit. After sampling is completed, it is transmitted to the core control module along with the data. The core control module sorts and manages the data according to the timestamp for easy subsequent analysis and traceability.

[0051] A unified timestamp establishes a clear temporal correlation for multi-channel data, enabling precise correspondence between the changing trends of various parameters during transient impact processes. This facilitates the analysis of deeper issues such as the transmission process of impact energy and the instantaneous changes in formation resistance. The timestamp also makes the data traceable, allowing for post-test process reviews to identify the causes of test anomalies. Furthermore, a unified time base facilitates the comparative analysis of multiple sets of test data, enhancing the utilization value of the data and providing a high-quality data foundation for in-depth research such as formation mechanical parameter inversion and energy correction.

[0052] If Kalman filtering is not used for noise reduction and loop decision-making is not performed based on the cumulative penetration depth, noise such as mechanical vibration and electromagnetic interference in the original data will cause significant errors in the calculation of the penetration increment, affecting the accuracy of the test results. Relying on manual observation of the penetration depth to determine whether to continue the loop is prone to misjudgment, resulting in insufficient or excessive penetration. This not only wastes human and material resources but also affects the scientific validity and engineering applicability of the test results. In addition, manual judgment is inefficient and cannot meet the needs of automated testing.

[0053] In the embodiments of this application, step S4 includes the following sub-steps: S41, the data processing unit uses the Kalman filter algorithm to denoise and fuse the synchronously acquired signal; S42, the penetration increment of a single hammer blow is calculated and accumulated based on the processed displacement signal; S43, the accumulated penetration depth is compared with the target depth, and if it is not reached, the next round of S2 cycle is triggered, and if it is reached, the test is terminated.

[0054] In another possible embodiment, the data processing unit of the core control module pre-loads a Kalman filter algorithm. Upon receiving a multi-channel synchronization signal transmitted by the FPGA high-speed acquisition circuit, it immediately calls the algorithm to process the data online. The Kalman filter algorithm removes noise such as mechanical vibration and electromagnetic interference from the signal, resulting in smooth acceleration, displacement, and force signal curves. Based on the denoised displacement signal, the core control module calculates the penetration depth increment corresponding to the current hammer blow, i.e., the difference between the current displacement value and the displacement value after the previous hammer blow. The calculated penetration depth increment is added to the cumulative penetration depth to update the cumulative penetration depth data. The core control module compares the updated cumulative penetration depth with the preset target depth. If the cumulative penetration depth is less than the target depth, the core control module sends a command to the mechanical execution module to start the next round of hammer drop lifting-release cycle. If the cumulative penetration depth reaches or exceeds the target depth, the core control module sends a stop command to the mechanical execution module to terminate the test process and avoid over-penetration.

[0055] The Kalman filter algorithm effectively removes high-frequency noise and random interference from the original data, making the data curve smoother, improving the signal-to-noise ratio, and ensuring the accuracy of incremental calculation. Automating cyclic decision-making based on cumulative penetration depth avoids human experience errors, ensuring that testing is strictly performed according to preset goals and improving the standardization of the testing process. Automated cyclic decision-making reduces human intervention, improves testing efficiency, and allows for timely termination of testing, preventing over-penetration from damaging equipment or under-penetration from resulting in incomplete data. The integration of data processing and cyclic decision-making makes the testing process more coherent, improving the system's automation level and reliability.

[0056] Traditional testing data is stored in local devices, making it difficult to achieve cross-regional collaborative analysis and data sharing. Engineering managers cannot keep track of the survey progress in real time, affecting the efficiency of engineering decision-making. Soil interface identification relies on subjective judgment of data curves by humans, which is prone to misjudgment due to insufficient experience or differences in personal habits, affecting the accuracy of foundation bearing capacity assessment and thus increasing the risk of engineering design. Locally stored data is prone to loss due to equipment failure, which is not conducive to long-term data preservation and traceability.

[0057] In the embodiments of this application, in step S5, the communication unit uploads the generated test report to the cloud platform, and the core control module can analyze the characteristics of the resistance curve collected in real time based on the adaptive algorithm trained on historical data to assist in soil interface identification.

[0058] In another possible embodiment, the core control module pre-installs an adaptive recognition algorithm trained on a large amount of historical test data. This algorithm has learned the penetration resistance curve characteristics corresponding to different soil layers and established a soil layer feature library. After the test, the core control module generates a standardized test report containing data tables, penetration resistance curves, calculation parameters, etc. The communication unit of the core control module encrypts and uploads the generated test report to a preset cloud platform through a wireless communication network. The cloud platform classifies, stores, and backs up the received test reports. At the same time, the core control module calls the built-in adaptive recognition algorithm to extract features from the real-time acquired and processed penetration resistance curves. The extracted curve features are compared and analyzed with the preset soil layer feature library to automatically identify information such as soil layer boundary depth and the location of weak interlayers. The recognition results are integrated into the test report, and the complete test report is displayed through the human-computer interaction module. It also supports users to export reports as needed to assist engineering technicians in decision-making.

[0059] By uploading test reports to the cloud platform, centralized data management and remote access are achieved. Engineering managers can view test reports anytime via multiple terminals, monitor exploration progress in real time, make timely engineering decisions, and improve management efficiency. The adaptive algorithm trained on historical data can automatically identify the characteristics of penetration resistance curves, assist in judging soil interface and density changes, reduce human interpretation errors, and improve the accuracy and objectivity of soil layer identification. The cloud platform has data backup and storage functions, which can effectively avoid data loss due to local equipment failure and ensure long-term data preservation and traceability. Cloud data sharing facilitates cross-regional and cross-departmental collaborative work, enhances the utilization value of data, and supports the establishment of regional geological databases.

[0060] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention.

[0061] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not describe the various possible combinations separately.

[0062] Furthermore, various different implementations of the present invention can be combined arbitrarily, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed in the present invention.

Claims

1. An automated system for in-situ dynamic penetrometer testing, characterized in that, include: The mechanical actuator module is used to automatically perform the lifting and releasing of the drop hammer and the penetration of the probe rod; The data acquisition module is used to collect the penetration depth, impact acceleration, and formation resistance signals of the penetration probe. The core control module is connected to the mechanical execution module and the data acquisition module respectively, and is used to control the test process and process data. The human-computer interaction module is connected to the core control module and is used to receive instructions and output information.

2. The automated in-situ dynamic penetration testing system according to claim 1, characterized in that, The mechanical actuation module includes a drop hammer drive unit; The drop hammer drive unit includes a lifting mechanism consisting of a ball screw driven by a servo motor and a release mechanism consisting of two electromagnets. The lifting mechanism integrates a photoelectric encoder for real-time feedback of the hammer's position. The release mechanism is used to receive an electrical signal to achieve contactless release of the falling hammer.

3. The automated in-situ dynamic penetration testing system according to claim 1, characterized in that, The data acquisition module includes a displacement sensing unit, an acceleration sensing unit, and a force sensing unit. The acceleration sensing unit is mounted on the hammer body, and the impact pulse output by the acceleration sensing unit is set as a global hardware trigger signal to start the displacement sensing unit and the force sensing unit to sample synchronously. The data acquisition module includes a high-speed acquisition circuit based on FPGA, which is used to synchronously acquire and latch the data of each sensing unit at a sampling rate of not less than 10KHz when the global hardware trigger signal is valid.

4. The automated in-situ dynamic penetration testing system according to claim 1, characterized in that, The core control module includes: The process control unit, whose operating logic is based on a state machine model including IDLE, RISING, READY, IMPACT, and RECOVERY states; The data processing unit integrates a Kalman filter algorithm for online denoising and fusion of multi-channel synchronization signals; The communication unit supports uploading processed data to a remote server via a wireless network.

5. An automated method for in-situ dynamic penetrometer testing, employing the automated in-situ dynamic penetrometer testing system as described in any one of claims 1-4, characterized in that, The automated in-situ dynamic penetration test method is scheduled and executed by the core control module, and includes the following steps: S1. The human-machine interaction module sets the drop hammer height and target depth parameters, and the mechanical execution module drives the drop hammer to reset to the initial position; S2. The core control module repeats the following sub-steps until the test termination condition is met: S21. Control the servo motor to raise the drop hammer to the set height based on the feedback from the photoelectric encoder; S22. Trigger the electromagnetic release device to allow the hammer to fall freely and impact the probe rod; S3. At the moment of each hammer impact, the pulse generated by the acceleration sensing unit triggers the FPGA high-speed acquisition circuit to synchronously acquire the current penetration depth, impact acceleration and formation resistance signals of the probe. S4. The core control module processes the penetration depth, impact acceleration and formation resistance signals of the probe in real time, calculates the current cumulative depth and compares it with the target depth parameter to decide whether to start the next cycle of step S2 or end the test. S5. After the test is completed, the penetration resistance curve and test report will be automatically generated and entered.

6. The automated method for in-situ dynamic penetration testing according to claim 5, characterized in that, In sub-step S21, the core control module dynamically adjusts the operation of the servo motor using a PID control algorithm based on the real-time feedback from the photoelectric encoder, in order to calibrate and lock the lifting height of the drop hammer.

7. The automated method for in-situ dynamic penetration testing according to claim 5, characterized in that, In sub-step S22, the electromagnetic release device employs a dual electromagnet cooperative control mechanism to perform contactless release.

8. The automated method for in-situ dynamic penetration testing according to claim 5, characterized in that, In step S3, after receiving the trigger pulse, the FPGA high-speed acquisition circuit adds a unified timestamp to the synchronously acquired acceleration, displacement and force signals.

9. The automated method for in-situ dynamic penetration testing according to claim 5, characterized in that, Step S4 includes the following sub-steps: S41. The data processing unit uses the Kalman filter algorithm to denoise and fuse the synchronously acquired signals. S42. Calculate and accumulate the penetration increment of a single hammer blow based on the processed displacement signal; S43. Compare the cumulative penetration depth with the target depth. If the target depth is not reached, trigger the next S2 loop. If the target depth is reached, terminate the test.

10. The automated method for in-situ dynamic penetration testing according to claim 5, characterized in that, In step S5, the communication unit uploads the generated test report to the cloud platform, and the core control module can analyze the characteristics of the resistance curve collected in real time based on the adaptive algorithm trained on historical data to assist in soil interface identification.

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