Intelligent leveling and ground pressure self-adaption system of modularized movable laboratory

Abstract

The invention provides an intelligent leveling and ground pressure self-adaption system of a modularized movable laboratory, and relates to the technical field of laboratory leveling, the system realizes high-precision leveling through six-degree-of-freedom hydraulic support legs, is equipped with pressure and displacement sensors, and is combined with spherical hinge universal joints to compensate ground inclination. And the reliability and the safety of the system are improved through the backup design of the double hydraulic pumps and the energy accumulator. The system further has a ground pressure self-adaption function, the pressure of the supporting legs is dynamically adjusted based on the ground type and a bearing capacity model, local overload is prevented, and an anti-sedimentation strategy is set. In addition, the system integrates technologies of Beidou / GNSS positioning assistance, multi-modal data fusion, block chain traceability and the like, and the leveling efficiency, stability and traceability are enhanced. The system is suitable for mobile laboratory deployment under complex terrains, and has the characteristics of high efficiency, accuracy and reliability.

Description

Technical Field

[0001] This invention relates to the field of laboratory leveling technology, specifically to an intelligent leveling and ground pressure adaptive system for modular mobile laboratories. Background Technology

[0002] With the continuous advancement of technology, mobile laboratories have been widely used in numerous fields, such as field research, emergency rescue, and environmental monitoring. However, existing mobile laboratories face many technical challenges when deployed in complex terrains. On the one hand, leveling work mainly relies on manual operation, which is not only inefficient but also difficult to guarantee accuracy, easily leading to tilting of laboratory equipment and affecting the accuracy and reliability of experimental results. On the other hand, uneven ground pressure distribution is also a significant problem, especially in complex environments such as soft soil foundations or uneven ground, which can easily cause ground subsidence, posing a serious threat to the safety of the laboratory.

[0003] Traditional leveling systems fall short in addressing these issues. Their slow response time and inability to adapt to changes in ground hardness make them ill-suited to the rapid and precise leveling needs of mobile laboratories in complex environments. Furthermore, existing systems lack effective redundancy and safety design, often failing to complete leveling tasks in the event of a single point of failure, further reducing the reliability and availability of the laboratory.

[0004] Regarding ground pressure, there is currently a lack of effective adaptive algorithms, making it impossible to adjust the pressure distribution of the outriggers in real time according to different ground types and bearing capacities to prevent localized overload. Simultaneously, the monitoring and response measures for outrigger settlement rates are also relatively insufficient, failing to promptly detect and resolve potential settlement problems, thus affecting the stability and safety of the laboratory.

[0005] In terms of positioning and support point selection, existing technologies mainly rely on manual judgment and experience, lacking accurate elevation data and terrain slope information. This results in the support point selection of the outriggers being less than scientific and reasonable, increasing the difficulty and time cost of leveling, and also making it difficult to avoid safety hazards caused by improper support point selection.

[0006] Furthermore, existing technologies also have many shortcomings in terms of multimodal data fusion, anti-interference capacity, energy efficiency optimization, and traceability. For example, they lack an effective multimodal data fusion mechanism, making it impossible to fully utilize various sensor data for ground type classification and bearing capacity assessment; their anti-interference capability is weak, making them susceptible to external interference that could lead to data transmission errors or sensor malfunctions; their energy utilization efficiency is low, lacking effective energy recovery and renewable energy utilization measures; and their traceability is poor, making it impossible to effectively record and trace the laboratory deployment process, which is detrimental to quality management and accountability.

[0007] In view of the above, this application is hereby submitted. Summary of the Invention

[0008] This invention provides an intelligent leveling and ground pressure adaptive system for a modular, mobile laboratory, which can at least partially improve the above-mentioned problems.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: A modular mobile laboratory intelligent leveling and ground pressure adaptive system includes: a multi-axis hydraulic leveling mechanism, a sensor assembly configured on the legs of the multi-axis hydraulic leveling mechanism, a positioning module, and a control module. The output end of the positioning module and the output end of the sensor assembly are electrically connected to the input end of the control module, and the output end of the control module is electrically connected to the control end of the multi-axis hydraulic leveling mechanism. The control module is configured to perform the following steps by executing a computer program stored internally: The system acquires the positioning data sent by the positioning module, combines the positioning data with a preset GIS database, identifies the ground type, and calculates the optimal support point based on the identified ground type. A multi-axis hydraulic leveling mechanism and the test platform to be adjusted are placed at the optimal support point. The sensor assembly is sent a command through the preset communication module box to obtain the current sensor data collected by the sensor assembly. The final allowable pressure is calculated based on the current sensor data using a ground pressure adaptive algorithm. The multi-axis hydraulic leveling mechanism is adjusted according to the final allowable pressure to level the test platform to be adjusted.

[0010] In summary, the intelligent leveling and ground pressure adaptive system of the modular mobile laboratory achieves precise leveling through six-degree-of-freedom hydraulic outriggers. Each outrigger is equipped with an independent control unit, pressure sensor, and displacement sensor. Combined with a ball joint universal joint, it can compensate for ground tilt, ensuring that the levelness error of the laboratory platform is controlled within an extremely small range, achieving a leveling accuracy of millimeters. Furthermore, based on ground type and bearing capacity models, the system monitors and dynamically adjusts the pressure and extension speed of each outrigger in real time, effectively avoiding local overload. It also features an anti-settlement strategy; when the outrigger settlement rate exceeds a set threshold, it automatically triggers pressure redistribution to ensure the stability of the laboratory. Integrating BeiDou / GNSS positioning assistance, and utilizing elevation data and a GIS database, it quickly determines the optimal support point location for each outrigger, significantly shortening leveling time, reducing the degree of manual intervention, and identifying obstacle coordinates to avoid dangerous support areas.

[0011] With its innovative design concept, efficient technical means, and strong adaptability, this system provides a strong guarantee for the stable deployment and efficient operation of mobile laboratories in complex environments, and has significant practical value and broad application prospects. Attached Figure Description

[0012] Figure 1 This is a flowchart of the intelligent leveling and ground pressure adaptive system for a modular mobile laboratory provided in this embodiment of the invention. Figure 2 This is a simplified structural diagram of the multi-axis hydraulic leveling mechanism provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the materials used in the intelligent leveling and ground pressure adaptive system of the modular mobile laboratory provided in this embodiment of the invention; Figure 4 This is a schematic diagram of the blockchain security architecture provided in an embodiment of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0014] The first embodiment of the present invention discloses an intelligent leveling and ground pressure adaptive system for a modular mobile laboratory, which includes: a multi-axis hydraulic leveling mechanism, a sensor assembly configured on the legs of the multi-axis hydraulic leveling mechanism, a positioning module, and a control module. The output end of the positioning module and the output end of the sensor assembly are electrically connected to the input end of the control module, and the output end of the control module is electrically connected to the control end of the multi-axis hydraulic leveling mechanism. Preferably, the multi-axis hydraulic leveling mechanism includes six symmetrically distributed hydraulic outriggers with degrees of freedom. Each outrigger includes a ball joint, a hydraulic cylinder, and a main hydraulic pump. The control terminal of the main hydraulic pump is electrically connected to the output terminal of the control module. The main hydraulic pump is connected to the hydraulic cylinder, and the hydraulic cylinder is connected to the test platform to be adjusted via the ball joint. The multi-axis hydraulic leveling mechanism is hexagonal in plan view, and the hydraulic pump is configured to provide the required hydraulic energy to the hydraulic cylinder.

[0015] Specifically, in this embodiment, the multi-axis hydraulic leveling mechanism is a core component of the system, such as... Figure 2 As shown ( Figure 2The ◉ symbol in the diagram represents the core component of the magnetostrictive displacement sensor. It comprises six symmetrically distributed hydraulic outriggers with independent control of each degree of freedom. This hexagonal layout design ensures a more uniform force distribution across the entire leveling mechanism, effectively improving leveling stability and accuracy. Each outrigger is equipped with a ball joint, a hydraulic cylinder, and a main hydraulic pump. The control terminal of the main hydraulic pump is electrically connected to the output terminal of the control module, ensuring that the control module can precisely control the operation of the main hydraulic pump based on real-time monitoring data and preset leveling strategies, thereby providing the necessary hydraulic energy to the hydraulic cylinder. The hydraulic cylinder is connected to the test platform to be adjusted via a ball joint. The ball joint design allows the hydraulic cylinder to flexibly adapt to uneven ground conditions while providing leveling power, avoiding lateral force problems caused by ground tilt, further improving the reliability and safety of leveling.

[0016] The ball joint is made of 40CrNiMoA alloy steel (nitrided surface), with a degree of freedom of ±15° deflection angle, used to compensate for uneven ground and avoid lateral force on the hydraulic cylinder; that is, to compensate for ground tilt (maximum tilt angle ±15°), and after leveling, the horizontal error of the laboratory platform is ≤0.1°, achieving millimeter-level leveling accuracy (error ≤0.5mm) through PID control. The hydraulic cylinder has a cylinder diameter and rod diameter of Ø80mm and Ø45mm, respectively, and a stroke of 500mm (with mechanical hard limit). It is sealed with a stepped polyurethane sealing ring (resistant to -40℃); a pressure sensor interface is integrated at the bottom of the cylinder.

[0017] During operation, the positioning module first acquires elevation data and surrounding terrain information of the laboratory's location. This data is crucial for subsequent leveling operations. Through high-precision positioning data, the system can predict the ground's tilt and the location of potential obstacles, providing a scientific basis for selecting the optimal support points for the outriggers. The sensor assembly monitors the pressure and displacement of each outrigger in real time. This data is fed back to the control module, which dynamically adjusts the output of the main hydraulic pump based on a preset leveling algorithm and ground pressure adaptive strategy, achieving precise extension and retraction control of the hydraulic cylinders. For example, if the ground on one side is softer, the control module will appropriately reduce the extension speed of the outrigger on that side based on the pressure data from the sensors, while increasing the extension of other outriggers to ensure the levelness and stability of the entire test platform. Simultaneously, the system dynamically adjusts the pressure distribution of each outrigger according to the ground type and load-bearing capacity model to prevent localized overload and ensure the stability and safety of the laboratory under different ground conditions.

[0018] This system, through the coordinated operation of a multi-axis hydraulic leveling mechanism, sensor components, positioning module, and control module, achieves rapid and precise leveling of the laboratory. At the same time, it can dynamically adjust the pressure distribution according to ground conditions, effectively solving the leveling problem and uneven ground pressure distribution problem of existing mobile laboratories when deployed in complex terrain. It has significant innovation and practicality, and provides strong support for the stable operation of mobile laboratories in various complex environments.

[0019] Please see Figure 3 The ball joint of the hydraulic outrigger uses shape memory alloy gaskets (SMA) inside, which automatically harden when the temperature is below -20℃ (phase change point -25℃) to prevent jamming caused by low-temperature hydraulic oil viscosity. Furthermore, a magnetorheological fluid damper is installed in the hydraulic cylinder.

[0020] Preferably, the sensor assembly includes a pressure sensor and a displacement sensor, and the output terminals of the pressure sensor and the displacement sensor are electrically connected to the input terminal of the control module. The pressure sensor is a strain gauge thin-film sensor, and the displacement sensor is a magnetostrictive linear displacement sensor.

[0021] Specifically, in this embodiment, the pressure sensor is a strain gauge thin-film sensor (0-15MPa), which features high accuracy and fast response. It can monitor pressure changes within the hydraulic cylinder in real time, providing accurate pressure data to the control module. This data is crucial for the system to determine ground bearing capacity and adjust the outrigger pressure. For example, on soft soil foundations, the pressure sensor can promptly report pressure changes, allowing the control module to adjust the hydraulic cylinder's pressure output accordingly, preventing ground overload and subsequent collapse, thereby effectively protecting the laboratory's safety.

[0022] Please see Figure 3 The pressure sensor uses a self-healing polymer coating (piezoelectric ceramic) to generate a self-powered early warning signal when settlement occurs (>2mm / s settlement triggers 50Hz vibration).

[0023] The displacement sensor employs a magnetostrictive linear displacement sensor with a resolution as high as 0.01 mm, enabling precise measurement of the extension and retraction displacement of the hydraulic cylinder. This high-precision displacement monitoring is crucial for achieving millimeter-level leveling accuracy. Based on the data from the displacement sensor, the control module precisely controls the extension and retraction of the hydraulic cylinder, ensuring that the levelness error of the laboratory platform is kept within an extremely small range. For example, during leveling, if the extension and retraction of the hydraulic cylinder on one side is insufficient, the displacement sensor will feed this information back to the control module, which will then adjust the extension and retraction of the hydraulic cylinder until the ideal level is achieved. Furthermore, both sensors have a resolution of 0.01 mm, enabling non-contact measurement, and a lifespan exceeding 1 million cycles.

[0024] Preferably, the positioning module is a BeiDou / GNSS positioning module.

[0025] In this embodiment, an advanced BeiDou / GNSS positioning module is used, a choice that significantly improves the accuracy and optimizes the efficiency of the system's leveling operation. By receiving satellite signals, the BeiDou / GNSS positioning module provides high-precision positioning data, including the latitude, longitude, elevation, and positioning accuracy of the laboratory's location. This data is crucial for determining the laboratory's initial attitude and terrain slope, providing a scientific basis for subsequent leveling operations.

[0026] In simple terms, the BeiDou / GNSS positioning module combines elevation data (accuracy ±10cm) with a GIS database, pre-loads terrain slope information, and automatically generates the optimal support point location for the outriggers, shortening leveling time and reducing manual intervention. It identifies obstacle coordinates (such as tree stumps, time delays, etc.) in the positioning data and automatically avoids dangerous support areas. This module (such as the UBLOX NEO-M8N) connects to the control module via a UART serial port to transmit positioning data in NMEA-0183 format, including latitude, longitude, elevation, and positioning accuracy.

[0027] Specifically, the output of the BeiDou / GNSS positioning module is electrically connected to the input of the control module, ensuring that positioning data can be transmitted to the control module in real time. After receiving this data, the control module, combined with terrain information from a pre-stored GIS (Geographic Information System) database, can quickly generate the optimal support point locations for the outriggers. This process not only improves the efficiency of leveling but also reduces the need for manual intervention and minimizes errors caused by human factors. For example, when deploying a mobile laboratory in complex terrain, the BeiDou / GNSS positioning module can quickly determine the laboratory's precise location and elevation information. Based on this data, and combined with terrain slope information from the GIS database, the control module automatically calculates the optimal extension length for each outrigger, thus achieving rapid leveling. This process is typically completed within minutes, significantly shortening leveling time and improving work efficiency compared to traditional manual leveling methods.

[0028] Furthermore, the BeiDou / GNSS positioning module also has the ability to identify obstacle coordinates. In actual operation, this function can automatically avoid dangerous support areas, such as tree stumps and rocks, ensuring safer and more reliable selection of support points for the outriggers. This automated obstacle recognition and avoidance function not only improves system safety but also further enhances the reliability of leveling.

[0029] Preferably, it also includes a backup hydraulic pump and a backup accumulator. The backup hydraulic pump is connected to the hydraulic cylinder. The backup hydraulic pump is configured to continue to provide the required hydraulic energy to the hydraulic cylinder when the main hydraulic pump malfunctions. The backup accumulator is configured to store or release hydraulic energy.

[0030] In this embodiment, to further improve the reliability and safety of the system, a backup hydraulic pump and a backup accumulator are specifically designed. This redundancy design ensures that even if the main hydraulic pump malfunctions, the system can continue to operate stably, providing the necessary hydraulic energy to the hydraulic cylinders. This means that leveling can still be completed under a single point of failure, thus guaranteeing the continuity and reliability of the leveling operation. The accumulator capacity is 2L (35MPa).

[0031] Specifically, the backup hydraulic pump is connected to the hydraulic cylinder and configured to automatically start in case of an abnormality in the main hydraulic pump. This automatic switching mechanism is achieved by monitoring the operating status of the main hydraulic pump. Once a fault signal is detected in the main hydraulic pump, the backup hydraulic pump starts immediately and seamlessly takes over the operation of the main hydraulic pump, ensuring the normal operation of the hydraulic cylinder. This design not only improves the reliability of the system but also reduces downtime caused by equipment failure, thereby increasing work efficiency. Meanwhile, the configuration of the backup accumulator further enhances the stability and safety of the system. The backup accumulator can store hydraulic energy and release it quickly when needed, providing instantaneous high pressure to the hydraulic cylinder. This function is particularly important in emergency situations, such as when both the main and backup hydraulic pumps fail simultaneously. The accumulator can release the stored energy, enabling the hydraulic cylinder to perform necessary leveling operations, ensuring the stability and safety of the laboratory.

[0032] In practical applications, the benefits of this redundancy design are evident. For example, in complex field environments, mobile laboratories may face various unpredictable equipment failures. With the design of backup hydraulic pumps and backup accumulators, even if the main hydraulic pump fails, the system can continue to operate and complete the leveling operation, ensuring the stability and safety of the laboratory. This design not only improves system reliability but also reduces downtime due to equipment failure, increasing work efficiency. Furthermore, the storage and release functions of the backup accumulator can provide additional energy support during normal system operation. For example, when the hydraulic cylinder needs to extend or retract rapidly, the accumulator can release stored energy to provide instantaneous high pressure, ensuring the hydraulic cylinder can quickly respond to leveling commands. This design not only improves the system's response speed but also further enhances its stability and reliability.

[0033] refer to Figure 1 As shown, the control module is configured to perform the following steps by executing a computer program stored internally: S1, Obtain the positioning data sent by the positioning module, combine the positioning data with the preset GIS database, identify the ground type, and calculate the optimal support point based on the identified ground type; Specifically, step S1 further includes: acquiring the positioning data sent by the positioning module, comparing the positioning data with a preset GIS database, and determining the current ground type; The GIS database is formed by processing multiple historical data collected by the ground information acquisition sensor components through a convolutional neural network. The ground information acquisition sensor components include a camera, a ground penetrating radar, an acoustic sensor, and an NV color center diamond quantum sensor. The camera is configured to identify surface texture, the ground penetrating radar is configured to detect underground structures, the acoustic sensor is configured to analyze soil density, and the NV color center diamond quantum sensor is configured to measure the soil micro-stress field.

[0034] Obtain the latitude and longitude of the laboratory corner point, then query the elevation database based on this latitude and longitude, using the query formula. Calculate the angle of inclination, where θ represents the angle between the inclined plane and the horizontal plane, and Δh represents the height difference (or vertical change), which is the difference in displacement of the object in the vertical direction. Overlay geological maps, avoiding underground pipelines or soft soil areas, and output the outrigger extension / retraction matrix: [Δh_1, Δh_2, Δh_3, Δh_4] to obtain the optimal support point, where Δh_1 represents the extension / retraction height change of the first outrigger, Δh_2 represents the extension / retraction height change of the second outrigger, Δh_3 represents the extension / retraction height change of the third outrigger, and Δh_4 represents the extension / retraction height change of the fourth outrigger.

[0035] In this embodiment, positioning data sent by the positioning module is first acquired. This data includes the laboratory's latitude, longitude, elevation, and other information. By comparing this positioning data with a preset GIS database, the control module can determine the current ground type. The GIS database is generated by processing multiple historical data collected by ground information acquisition sensor components through a convolutional neural network. These sensor components include a camera, ground-penetrating radar, acoustic wave sensor, and NV color center diamond quantum sensor. The camera is used to identify surface texture, the ground-penetrating radar is used to detect underground structures, the acoustic wave sensor is used to analyze soil density, and the NV color center diamond quantum sensor is used to measure the soil's micro-stress field. The NV color center diamond quantum sensor has the advantage of a 1000-fold increase in resolution (detecting stress changes as small as 0.1 Pa) and is immune to electromagnetic interference. The combined use of these sensors, along with a convolutional neural network (CNN), achieves ground type classification (accuracy > 95%). Based on reinforcement learning (RL), the ground bearing capacity model is continuously optimized to adapt to extreme environments (such as permafrost and swamps), enabling the system to accurately identify and analyze various ground conditions, providing a scientific basis for subsequent leveling operations.

[0036] In simple terms, the pre-configured AI processing unit (such as the NVIDIA Jetson Nano) communicates with the main controller via the CAN FD bus to transmit ground type codes (e.g., 0 = concrete, 1 = gravel, 2 = grass), along with confidence parameters (0-100%) and other signals. The ground type recognition AI verification code is as follows: def test_ground_ai(): dataset = load_real_world_data() # Contains 100,000 samples of 20 different terrain types model = QuantumEnhancedCNN() accuracy = cross_val_score(model, dataset) assert accuracy>0.95# Acceptance criterion.

[0037] After determining the ground type, the control module queries the elevation database based on the latitude and longitude of the laboratory corner point and calculates the inclination angle using a formula. This calculation process considers not only the macroscopic topographic features of the ground but also incorporates measurement data of the microscopic stress field, making the inclination angle calculation more accurate. By overlaying geological maps, the system can effectively avoid underground pipelines or soft soil areas, thereby outputting the outrigger extension matrix to obtain the optimal support point. This process fully considers the complexity of the ground, ensuring that the selection of outrigger support points is both scientific and safe.

[0038] This method of ground type identification and optimal support point calculation based on positioning data and GIS databases significantly improves the accuracy and reliability of leveling. By accurately identifying ground types and calculating optimal support points, the system can effectively avoid leveling failures or equipment damage caused by poor ground conditions. For example, in areas with soft soil foundations or underground pipelines, by avoiding these hazardous areas, the system can ensure stable support for the outriggers, thereby guaranteeing the stability and safety of the laboratory. Furthermore, this intelligent calculation method reduces the need for manual intervention, improves leveling efficiency, and enables rapid deployment of the laboratory in various complex environments, providing strong technical support for applications such as scientific research and emergency response.

[0039] S2, place the multi-axis hydraulic leveling mechanism and the test platform to be adjusted on the optimal support point, and send instructions to the sensor component through the preset communication module box to obtain the current sensor data collected by the sensor component; Specifically, in this embodiment, the multi-axis hydraulic leveling mechanism is placed at the optimal support point and connected to the test platform to be adjusted. The control module outputs a PWM signal to the hydraulic outrigger drive board, with a PWM duty cycle (0-100%) corresponding to the target extension / retraction length of the outrigger (0-500mm) and a frequency of 1kHz. This process ensures that the leveling mechanism can accurately support and level the test platform. To achieve this, the system sends instructions to the sensor components via a preset communication module to obtain the current sensor data collected by the sensor components. This data includes real-time readings from the pressure and displacement sensors, which are crucial for subsequent leveling control.

[0040] Once the multi-axis hydraulic leveling mechanism is in place, the control module sends commands to the sensor assembly via the communication module to activate the sensors and begin data acquisition. The pressure and displacement sensors then begin operating, monitoring the pressure and extension / retraction displacement within the hydraulic cylinders in real time. This sensor data is transmitted back to the control module via the communication module, providing real-time feedback. Based on this data and a pre-set leveling algorithm, the control module precisely controls the extension and retraction movements of the hydraulic cylinders, ensuring the levelness and stability of the test platform.

[0041] S3, calculate the final allowable pressure based on the current sensor data using the ground pressure adaptive algorithm; Specifically, step S3 further includes: based on the ground type and bearing capacity model, performing a simplified applicability conversion process, and converting the total bearing capacity q in the bearing capacity model... u Converted to permissible pressure P max Meanwhile, by introducing a safety factor, we obtain the formula for calculating the allowable pressure: , ,in, (tons per square meter) is a commonly used unit of pressure or stress. For ground cohesion, This is the bearing capacity coefficient. It is a natural constant. To represent the internal friction angle of the soil; The bearing capacity model is based on the Terzaghi bearing capacity theory, and the formula is: , For soil cohesion, , Both are bearing capacity coefficients. For soil capacity, Base width; The allowable pressure is corrected by settling rate feedback to obtain the final allowable pressure. ,in, The real-time settlement rate is expressed in mm / s. At that time, dynamic load reduction is triggered.

[0042] In this embodiment, the hydraulic outrigger is equipped with a pressure sensor (Honeywell 40PC series) and a magnetostrictive displacement sensor (MTS Temposonics). Pressure feedback is a 4-20mA analog signal (range 0-15MPa, accuracy ±0.5%FS), and displacement feedback is an SSI synchronous serial interface digital signal (resolution 0.01mm). Furthermore, sensor data is transmitted to the edge computing node via EtherCAT; the raw data is a JSON-formatted pressure-displacement array (e.g., {"leg1_pressure": 7.2MPa, "leg1_displacement": 320mm}), and the control parameters are a PID coefficient matrix.

[0043] The system employs a simplified applicability conversion based on ground type and bearing capacity model, utilizing the classic Terzaghi bearing capacity theory (the 1943 classical soil mechanics formula) with soil cohesion in kPa. To adapt to the specific needs of the mobile laboratory, this system innovatively simplifies and converts the theory, transforming the total bearing capacity into allowable pressure and introducing a safety factor of 0.5 (higher than the conventional 0.3-0.4) to address the specific safety requirements of the mobile laboratory; this results in the allowable pressure. This conversion not only improves the applicability of the calculation but also further enhances the system's safety and reliability by introducing a safety factor. Dynamic parameter mapping yields the bearing capacity coefficient N. c The established real-time mapping table between ground type and internal friction angle is shown in Table 1.

[0044] Table 1

[0045] In practical applications, the benefits of this calculation process are significant. By simplifying the complex bearing capacity model into the calculation of allowable pressure, the system can more intuitively assess the bearing capacity of the ground, thus providing a scientific basis for the pressure distribution of the hydraulic outriggers. For example, on soft soil foundations, the calculated allowable pressure can effectively prevent collapse caused by ground overload, ensuring the safety of the laboratory. At the same time, the introduced safety factor further reduces risks and ensures stability under extreme conditions.

[0046] Furthermore, step S3 also includes settlement rate feedback correction processing for the allowable pressure. The system monitors the settlement rate v of each outrigger in real time. When the settlement rate exceeds the set threshold v>2mm / s, dynamic unloading is triggered, that is, the pressure of the hydraulic outriggers is automatically adjusted to prevent further settlement. This dynamic correction mechanism greatly improves the system's adaptability and response speed, enabling it to respond to changes in ground conditions in real time and ensuring the stability and safety of the leveling operation.

[0047] For example, during laboratory deployment, if ground subsidence suddenly occurs in a certain area, the subsidence rate feedback correction mechanism can respond quickly by adjusting the pressure of the hydraulic outriggers to prevent the laboratory platform from tilting or becoming unstable. This real-time feedback and dynamic adjustment capability not only improves the reliability of the system but also reduces equipment damage and safety accidents caused by ground instability, providing strong support for the stable operation of mobile laboratories in complex environments.

[0048] It should be noted that the sensor assembly connects to the control module via a pre-set communication module, which can be either RS485 or RS422. Hydraulic valve drive information uses differential transmission to suppress common-mode noise. Key sensor data is encrypted (AES-256) to prevent malicious tampering. When the outrigger jams, a high-frequency vibration mode (50Hz) is triggered to release the mechanical lock. After communication is interrupted, it switches to local fuzzy control (based on the last valid data).

[0049] S4. Adjust the multi-axis hydraulic leveling mechanism according to the final allowable pressure to level the test platform to be adjusted.

[0050] Specifically, in this embodiment, based on the calculated final allowable pressure and combined with the real-time pressure and displacement data fed back by the sensor components, a preset leveling algorithm sends precise control commands to each hydraulic outrigger of the multi-axis hydraulic leveling mechanism. These commands include the extension and retraction of the hydraulic cylinders and pressure adjustment values, ensuring that each outrigger can accurately adjust its support height without exceeding the allowable pressure, thereby achieving an ideal level state for the test platform. For example, assuming the ground on one side is softer, causing the pressure on the outrigger on that side to approach the upper limit of the allowable pressure, the control module will appropriately reduce the extension of that outrigger based on sensor data, while increasing the extension of other outriggers to maintain the overall level of the test platform. This process, through real-time monitoring and dynamic adjustment, ensures that the pressure of each outrigger is within a safe range, while also guaranteeing the precise leveling of the test platform.

[0051] By adjusting according to the final allowable pressure, the system effectively avoids localized overload caused by uneven ground conditions, thus protecting the hydraulic outriggers and test platform from damage. Secondly, the real-time monitoring and dynamic adjustment mechanism improves the system's response speed and adaptability, enabling it to complete leveling tasks quickly and accurately under complex and changing ground conditions. Furthermore, this automated leveling control reduces the need for manual intervention, lowers errors caused by human factors, and further improves the system's reliability and stability.

[0052] In practical applications, this leveling control method based on the final allowable pressure provides strong support for the rapid deployment and stable operation of mobile laboratories in complex terrains and harsh environments in the field. For example, during field research or emergency response, laboratories may need to be deployed quickly on uneven or soft ground. With the intelligent leveling system of this invention, the laboratory can complete leveling within minutes, ensuring the stable operation of experimental equipment and thus providing solid technical support for the smooth progress of research and emergency response tasks.

[0053] In short, the modular mobile laboratory's intelligent leveling and ground pressure adaptive system monitors the pressure data of each outrigger in real time (≤8 tons / m²), and dynamically adjusts the outrigger extension speed and pressure distribution based on the ground type (concrete, gravel, grass) to prevent local overload. It also features an anti-settlement strategy; when an outrigger settlement rate >2mm / s is detected, pressure redistribution is automatically triggered.

[0054] Please see Figure 4 Preferably, it also includes: uploading the positioning data, ground type, and leveling parameters of each deployment to the blockchain via Hyperledger Sawtooth to save the results; The system uses Microsoft HoloLens to display a virtual outrigger pressure distribution heat map, showing the leveling results and related data in real time, so that users can observe and fine-tune the process.

[0055] In this embodiment, during each laboratory deployment, the system stores key information such as positioning data, ground type, and leveling parameters on the blockchain using Hyperledger Sawtooth blockchain technology. This data includes the laboratory's specific location (latitude, longitude, and elevation), the identified ground type (e.g., concrete, gravel, grass), and the parameters used during leveling (e.g., outrigger extension and retraction, pressure distribution). Through blockchain technology, this data is recorded in an immutable distributed ledger, ensuring the authenticity and integrity of the data.

[0056] This implementation of data on-chain has significant advantages. First, the immutability of blockchain ensures data credibility, making each deployed record legally valid and facilitating subsequent auditing and verification. Second, the distributed ledger feature makes data storage more secure and less susceptible to single points of failure. Furthermore, blockchain technology allows the system to automatically generate compliance certificates conforming to ISO 1496 standards, further enhancing the system's professionalism and reliability.

[0057] In addition, to enhance user experience and ease of use, the system integrates the Microsoft HoloLens augmented reality device. Through HoloLens, users can observe real-time heatmaps of virtual outrigger pressure distribution. These heatmaps visually display the pressure distribution of each outrigger, along with relevant data on the leveling results. Users can interact with the system using natural language commands (such as "level the southeast corner first"), and the system will perform corresponding fine-tuning operations based on the user's instructions.

[0058] The formula for deep integration of digital twins is as follows: , Energy conversion efficiency >60% (measured value). The density of hydraulic oil is approximately 850-900 kg / m³. 3 (Mineral oil), A represents the effective working area of ​​the piston, which depends on the cylinder design; V represents the piston contraction speed, which is related to the system pressure. Actual measured energy recovery during a single leveling operation is ≥200J.

[0059] The introduction of this augmented reality interface greatly enhances the user experience of the system. Users can not only intuitively see the leveling results, but also make fine adjustments through simple commands, making the leveling process more efficient and convenient. For example, during laboratory deployment, if a user finds that the pressure distribution on one side is not ideal, they can directly issue a command through HoloLens, and the system will respond and adjust immediately. This real-time feedback and interaction mechanism not only improves the accuracy of leveling, but also reduces the learning cost and operational difficulty for users.

[0060] Preferably, the method further includes: during the retraction of the outriggers of the multi-axis hydraulic leveling mechanism, a hydraulic motor-generator is used to recover kinetic energy, and the recovered kinetic energy is stored in a supercapacitor.

[0061] In this embodiment, during the retraction of the outriggers of the multi-axis hydraulic leveling mechanism, the kinetic energy of the hydraulic cylinder is recovered through a hydraulic motor-generator. Specifically, the hydraulic motor-generator converts the mechanical energy of the hydraulic cylinder into electrical energy. This process not only reduces energy waste but also stores the recovered electrical energy through a supercapacitor (Maxwell 48V module), reducing dependence on an external power source. The supercapacitor has the characteristics of rapid charging and discharging, enabling efficient storage and release of recovered kinetic energy, ensuring that the system can respond quickly when needed.

[0062] The introduction of this kinetic energy recovery and storage mechanism significantly improves the system's energy efficiency. For example, after the laboratory platform is leveled, the kinetic energy generated during the retraction of the outriggers is effectively recovered and stored in a supercapacitor. When the system needs to perform another leveling operation, the energy in the supercapacitor can be quickly released to provide the necessary energy for the hydraulic cylinder, reducing dependence on the main power supply. This design not only reduces the system's energy consumption but also improves its response speed and reliability. Furthermore, flexible photovoltaic films (SunPower Maxeon series) can be laid on the laboratory roof, generating ≥20kWh of electricity per day.

[0063] In this embodiment, to demonstrate the beneficial effects of the intelligent leveling and ground pressure adaptive system of the modular mobile laboratory, an ultimate load test was conducted, applying 150% of the design load (12... ); Monitor key deformation points (ball joint / cylinder weld). Its environmental adaptability verification is shown in Table 2.

[0064] Table 2

[0065] In summary, the intelligent leveling and ground pressure adaptive system for modular mobile laboratories aims to solve the problems of leveling difficulties and uneven ground pressure distribution faced by existing mobile laboratories when deployed in complex terrain. The system achieves leveling through six-degree-of-freedom hydraulic outriggers, each equipped with an independent control unit, pressure sensor, and displacement sensor. Combined with ball joints, it can compensate for ground tilt, ensuring that the levelness error of the laboratory platform is controlled within an extremely small range, achieving leveling accuracy down to the millimeter level. The dual hydraulic pump and accumulator backup design significantly enhances the system's reliability, enabling it to successfully complete the leveling task even in the event of a single point of failure.

[0066] Specifically, in terms of ground pressure management, the system monitors and dynamically adjusts the pressure and extension speed of each outrigger in real time based on ground type and bearing capacity model, effectively avoiding local overload. It also features an anti-settlement strategy; when the outrigger settlement rate exceeds a set threshold, it automatically triggers pressure redistribution to ensure the stability of the laboratory. Furthermore, the system integrates BeiDou / GNSS positioning assistance, using elevation data and a GIS database to quickly determine the optimal support point location for the outriggers, significantly shortening leveling time, reducing manual intervention, and identifying obstacle coordinates to avoid dangerous support areas.

[0067] The system also employs multimodal data fusion technology, integrating various devices such as cameras, ground-penetrating radar, and acoustic sensors. It uses convolutional neural networks to classify ground types with an accuracy exceeding 95%, and continuously optimizes the ground bearing capacity model based on reinforcement learning, enabling it to adapt to extreme environments including permafrost and swamps. Regarding anti-interference and energy efficiency, hydraulic valve drive information uses differential transmission, key sensor data is encrypted, and a high-frequency vibration mode can be triggered to unlock the outriggers when they become stuck. After communication interruption, it switches to local fuzzy control. Kinetic energy is recovered and stored in a supercapacitor during outrigger retraction, and a flexible photovoltaic film is laid on the laboratory roof to achieve efficient energy utilization and self-sufficiency.

[0068] The application of blockchain technology further enhances the system's traceability. All relevant data from each deployment is recorded on the chain via Hyperledger Sawtooth, forming an immutable log record. This automatically verifies whether the leveling results comply with the ISO 1496 standard and generates a compliance certificate. The human-machine collaborative interaction interface has been upgraded, displaying a virtual outrigger pressure distribution heatmap via Microsoft HoloLens to assist manual fine-tuning. It also integrates an NLP module, supporting natural language command input, improving the system's usability and interaction efficiency.

[0069] In summary, this system, with its innovative design concept, efficient technical means, and strong adaptability, provides a powerful guarantee for the stable deployment and efficient operation of mobile laboratories in complex environments. Through the coordinated work of the multi-axis hydraulic leveling mechanism, sensor components, positioning module, and control module, the system achieves rapid and precise leveling, while dynamically adjusting the pressure distribution according to ground conditions to effectively prevent local overload and ensure the stability of the laboratory. The application of multimodal data fusion technology, anti-interference design, energy recovery and utilization mechanisms, and blockchain traceability further enhances the system's intelligence and reliability. The upgraded human-machine interface makes the system easier to operate and maintain. These innovative designs and functions not only improve the practicality and market competitiveness of mobile laboratories but also provide strong technical support for rapid deployment and stable operation in fields such as scientific research and emergency response, demonstrating significant practical value and broad application prospects.

[0070] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A modular, mobile laboratory intelligent leveling and ground pressure adaptive system, characterized in that, include: The system includes a multi-axis hydraulic leveling mechanism, a sensor assembly, a positioning module, and a control module mounted on the legs of the multi-axis hydraulic leveling mechanism. The output terminals of the positioning module and the sensor assembly are electrically connected to the input terminal of the control module, and the output terminal of the control module is electrically connected to the control terminal of the multi-axis hydraulic leveling mechanism. The control module is configured to perform the following steps by executing a computer program stored internally: The system acquires the positioning data sent by the positioning module, combines the positioning data with a preset GIS database, identifies the ground type, and calculates the optimal support point based on the identified ground type. A multi-axis hydraulic leveling mechanism and the test platform to be adjusted are placed at the optimal support point. The sensor assembly is sent a command through the preset communication module box to obtain the current sensor data collected by the sensor assembly. The final allowable pressure is calculated based on the current sensor data using a ground pressure adaptive algorithm. The multi-axis hydraulic leveling mechanism is adjusted according to the final allowable pressure to level the test platform to be adjusted.

2. The intelligent leveling and ground pressure adaptive system for the modular mobile laboratory according to claim 1, characterized in that, The multi-axis hydraulic leveling mechanism includes six symmetrically distributed hydraulic outriggers with degrees of freedom. Each outrigger includes a ball joint, a hydraulic cylinder, and a main hydraulic pump. The control terminal of the main hydraulic pump is electrically connected to the output terminal of the control module. The main hydraulic pump is connected to the hydraulic cylinder, and the hydraulic cylinder is connected to the test platform to be adjusted via the ball joint. The multi-axis hydraulic leveling mechanism is hexagonal in plan view, and the hydraulic pump is configured to provide the required hydraulic energy to the hydraulic cylinder.

3. The intelligent leveling and ground pressure adaptive system for the modular mobile laboratory according to claim 1, characterized in that, The sensor assembly includes a pressure sensor and a displacement sensor. The output terminals of the pressure sensor and the displacement sensor are electrically connected to the input terminal of the control module. The pressure sensor is a strain gauge thin-film sensor, and the displacement sensor is a magnetostrictive linear displacement sensor.

4. The intelligent leveling and ground pressure adaptive system for the modular mobile laboratory according to claim 1, characterized in that, The positioning module is a BeiDou / GNSS positioning module.

5. The intelligent leveling and ground pressure adaptive system for a modular mobile laboratory according to claim 2, characterized in that, It also includes a backup hydraulic pump and a backup accumulator. The backup hydraulic pump is connected to the hydraulic cylinder. The backup hydraulic pump is configured to continue to provide the hydraulic cylinder with the required hydraulic energy when the main hydraulic pump malfunctions. The backup accumulator is configured to store or release hydraulic energy.

6. The intelligent leveling and ground pressure adaptive system for a modular mobile laboratory according to claim 1, characterized in that, The positioning data sent by the positioning module is acquired, and combined with the positioning data and a preset GIS database to identify the ground type, specifically: The positioning data sent by the positioning module is obtained, and the positioning data is compared with a preset GIS database to determine the current ground type; The GIS database is formed by processing multiple historical data collected by the ground information acquisition sensor components through a convolutional neural network. The ground information acquisition sensor components include a camera, a ground penetrating radar, an acoustic sensor, and an NV color center diamond quantum sensor. The camera is configured to identify surface texture, the ground penetrating radar is configured to detect underground structures, the acoustic sensor is configured to analyze soil density, and the NV color center diamond quantum sensor is configured to measure the soil micro-stress field.

7. The intelligent leveling and ground pressure adaptive system for a modular mobile laboratory according to claim 1, characterized in that, The optimal support point is calculated based on the identified ground type, specifically as follows: Obtain the latitude and longitude of the laboratory corner point, then query the elevation database based on this latitude and longitude, using the query formula. Calculate the inclination angle, where θ represents the inclination angle and Δh represents the height difference; Overlay geological maps, avoiding underground pipelines or soft soil areas, and output the outrigger extension / retraction matrix: [Δh_1, Δh_2, Δh_3, Δh_4] to obtain the optimal support point. Here, Δh_1 represents the extension / retraction height change of the first outrigger, Δh_2 represents the extension / retraction height change of the second outrigger, Δh_3 represents the extension / retraction height change of the third outrigger, and Δh_4 represents the extension / retraction height change of the fourth outrigger.

8. The intelligent leveling and ground pressure adaptive system for a modular mobile laboratory according to claim 1, characterized in that, The final permissible pressure is calculated based on the current sensor data using a ground pressure adaptive algorithm, specifically: Based on the ground type and bearing capacity model, a simplified applicability conversion process is performed, transforming the total bearing capacity q in the bearing capacity model. u Converted to permissible pressure P max Meanwhile, by introducing a safety factor, we obtain the formula for calculating the allowable pressure: , ,in, It is a commonly used unit of pressure or stress. For ground cohesion, This is the bearing capacity coefficient. It is a natural constant. To represent the internal friction angle of the soil; The bearing capacity model is based on the Terzaghi bearing capacity theory, and the formula is: , For soil cohesion, , Both are bearing capacity coefficients. For soil capacity, Base width; The allowable pressure is corrected by settling rate feedback to obtain the final allowable pressure. ,in, For real-time settling rate, when At that time, dynamic load reduction is triggered.

9. The intelligent leveling and ground pressure adaptive system for a modular mobile laboratory according to claim 1, characterized in that, Also includes: The positioning data, ground type, and leveling parameters for each deployment are uploaded to the blockchain via Hyperledger Sawtooth to save the results; The system uses Microsoft HoloLens to display a virtual outrigger pressure distribution heat map, showing the leveling results and related data in real time, so that users can observe and fine-tune the process.

10. The intelligent leveling and ground pressure adaptive system for a modular mobile laboratory according to claim 1, characterized in that, Also includes: During the retraction of the outriggers of the multi-axis hydraulic leveling mechanism, a hydraulic motor-generator is used to recover kinetic energy, which is then stored in a supercapacitor.

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