Dsp-based variable resonant frequency hydraulic vibration control system and method

Abstract

The application discloses a variable resonant frequency hydraulic vibration control system and method based on DSP, relates to the technical field of hydraulic vibration control, and specifically comprises the following steps: analyzing geological dynamic information of each region, evaluating the adaptability of geological materials of each region to the vibration frequency of current vibration equipment, and dividing each region into a high-adaptation region, a medium-adaptation region and a low-adaptation region according to the evaluation result; an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed; in the application process of the adjustment mechanism, vibration feedback information of each region is acquired in real time, and after acquisition, analysis is performed to evaluate whether the adjustment effect of the adjustment mechanism in each region meets the expectation, and the adjustment mechanism is adjusted according to the evaluation result. The application solves the problem of vibration frequency adjustment lag under complex geological conditions, and achieves the technical effect of real-time adjustment of the vibration frequency to ensure the uniformity of foundation ramming.

Description

Technical Field

[0001] This invention relates to the field of hydraulic vibration control technology, specifically to a DSP-based variable resonant frequency hydraulic vibration control system and method. Background Technology

[0002] Hydraulic vibration refers to the mechanical vibration of a hydraulic system during operation caused by factors such as pressure fluctuations, flow rate changes, or external excitations. This vibration can affect the system's stability and efficiency. Variable resonant frequency hydraulic vibration refers to the phenomenon where the resonant frequency of a hydraulic system dynamically changes with variations in external load or operating conditions. The resonant frequency is the vibration frequency at which the hydraulic system responds most strongly at a specific frequency. If the variable resonant frequency is not effectively controlled, the system may operate at an mismatched resonant frequency, leading to excessive vibration, system instability, or increased energy consumption. Therefore, the purpose of controlling variable resonant frequency hydraulic vibration is to adjust the operating parameters of the hydraulic system to match its resonant frequency with the external excitation frequency, thereby achieving optimal vibration control. The unique feature of DSP-based variable resonant frequency hydraulic vibration control is that the DSP can acquire, process, and accurately analyze the vibration signals of the hydraulic system in real time, and dynamically adjust the resonant frequency through advanced control algorithms to ensure that the system always operates in an optimal state. This high-precision, fast-response control method significantly improves the efficiency and stability of hydraulic vibration control.

[0003] Existing DSP-based variable resonant frequency hydraulic vibration control technology operates through the following specific steps: First, the system collects vibration signals from the hydraulic system in real time via sensors, including data such as pressure and displacement, and transmits these signals to the DSP for processing. Next, the DSP uses spectral analysis algorithms (such as Fast Fourier Transform, FFT) to identify the current resonant frequency of the hydraulic system and determine whether it matches the external excitation frequency. If they do not match, the DSP dynamically adjusts the hydraulic system parameters (such as the output of the hydraulic pump or the opening of the control valve) based on the detection results using its built-in control algorithm to change the system's resonant frequency and make it consistent with the external excitation frequency. Throughout this process, the system employs a closed-loop control strategy, providing real-time feedback on the vibration signal and continuously optimizing the control parameters based on the feedback results to ensure optimal vibration control. The high-speed processing capability of the DSP enables it to respond quickly to vibration changes, achieving efficient and precise control.

[0004] The existing technology has the following shortcomings:

[0005] During the foundation construction of high-rise buildings, when hydraulic vibratory compactors are used to compact complex foundations containing various geological materials such as rock, sand, and silt, a lag in vibration frequency adjustment occurs. Because different geological materials (such as rock, sand, and silt) exhibit significantly different absorption and reflection characteristics to vibration, the DSP (Digital Substrate) needs to process vibration feedback signals from multiple materials when the equipment rapidly switches working areas. However, due to the differences in these material feedback signals, existing DSPs struggle to respond to these changes in a timely manner and cannot adjust the vibration frequency in real time to adapt to rapidly changing geological conditions. This lag in frequency adjustment leads to inconsistent compaction effects in different areas of the foundation, with insufficient density in some areas, thus increasing the risk of foundation settlement. In the long term, this may affect the overall structural stability of the building, leading to increased maintenance and repair costs and even jeopardizing the building's safety.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a DSP-based variable resonant frequency hydraulic vibration control system and method to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a DSP-based variable resonant frequency hydraulic vibration control method, specifically comprising the following steps:

[0009] During the foundation construction of high-rise buildings, the foundation area to be compacted is evenly divided into several areas, and a sensor network is deployed in each area to obtain the geological dynamic information of each area in real time.

[0010] The acquired geological dynamic information of each region is analyzed to assess the adaptability of the geological materials in each region to the vibration frequency of the current vibration equipment. Based on the assessment results, each region is divided into high-adaptability, medium-adaptability, and low-adaptability regions.

[0011] Based on the division of the various regions in the foundation area to be compacted, an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed, and then applied to the current vibration equipment after construction.

[0012] During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time, analyzed, and evaluated to determine whether the adjustment effect of the adjustment mechanism in each region meets expectations. Based on the evaluation results, the adjustment mechanism is then adjusted.

[0013] Based on long-term collected geological dynamic information and vibration feedback information, the adjustment mechanism is dynamically optimized and updated to continuously adjust the vibration frequency of the vibration equipment and maintain the uniformity and stability of the foundation compaction.

[0014] Preferably, the acquired geological dynamic information of each region is analyzed to assess the adaptability of the geological materials in each region to the vibration frequency of the current vibration equipment, and each region is divided into high-adaptability regions, medium-adaptability regions, and low-adaptability regions based on the assessment results. This specifically includes the following steps:

[0015] The acquired geological dynamic information of each region is preprocessed;

[0016] Geological material information and vibration response dynamic information are extracted from the preprocessed geological dynamic information of each region, and analyzed after extraction to generate the geological adaptability coefficient and vibration response index of each region.

[0017] An adaptation evaluation model is constructed for the geological adaptation coefficient and vibration response index of each region. The adaptation coefficient of each region is generated and compared with the pre-set adaptation coefficient threshold range. Based on the comparison results, the adaptation degree of the geological materials of each region to the vibration frequency of the current vibration equipment is evaluated. Based on the evaluation results, each region is divided into high adaptation region, medium adaptation region and low adaptation region.

[0018] Preferably, the logic for obtaining the geological adaptability coefficient and vibration response index of each region is as follows:

[0019] Geological material information is extracted from the preprocessed geological dynamic information of each region, specifically including the average material density, average geological layer thickness, and internal damping value of each region at different times over a period of time, and these are calibrated as follows: , and , Indicates the first A region within a certain period of time The average density of the material at that time Indicates the first A region within a certain period of time The average thickness of the geological layer at that time. Indicates the first A region within a certain period of time The internal damping value at time t, , , and All are positive integers;

[0020] The geological adaptability coefficient for each region is calculated using the following formula:

[0021] ;

[0022] In the formula, For the first Geological adaptability coefficient of each region;

[0023] Vibration response dynamic information is extracted from the preprocessed geological dynamic information of each region, specifically including the average internal vibration transmission velocity, elastic modulus of the material, and strain rate of the geological material at different times over a period of time, and calibrated as follows: , and , Indicates the first A region within a certain period of time The average transmission velocity of internal vibration at any given time. Indicates the first A region within a certain period of time The elastic modulus of the material at a given time. Indicates the first A region within a certain period of time The strain rate of geological materials at any given time;

[0024] The vibration response index for each region is calculated using the following formula:

[0025] ;

[0026] In the formula, For the first Vibration response index of each region.

[0027] Preferably, the geological adaptability coefficient for each generated region and vibration response index An adaptation assessment model was constructed, and the adaptation coefficients for each region were generated by weighted summation. And the fitness coefficients of each generated region With the pre-set fitness coefficient threshold range A comparison was conducted, and the compatibility between the geological materials in each region and the vibration frequency of the current vibration equipment was evaluated based on the comparison results. Based on the evaluation results, each region was divided into high-compatibility, medium-compatibility, and low-compatibility regions. The specific comparison analysis and division are as follows:

[0028] like If the geological materials in a region are poorly adapted to the vibration frequency of the current vibration equipment, then that region is classified as a low-adaptability region.

[0029] like If the geological materials in this area are moderately compatible with the vibration frequency of the current vibration equipment, then this area is classified as a moderately compatible area.

[0030] like If the geological materials in a region are highly compatible with the vibration frequency of the current vibration equipment, then that region is classified as a high-compatibility region.

[0031] Preferably, based on the division results of each region in the foundation area to be compacted, an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed. Specifically, different vibration frequency adjustment parameters are set according to the division results of high-adaptability region, medium-adaptability region and low-adaptability region to form an adjustment mechanism. This adjustment mechanism automatically determines the adjustment amplitude and method of vibration frequency based on the adaptation coefficient of each region and the current vibration frequency state through pre-set rules.

[0032] Different frequency adjustments are made for the high-adaptation, medium-adaptation, and low-adaptation regions, respectively. Specifically, in the high-adaptation region, the standard vibration frequency parameter in the adjustment mechanism is used to keep the current vibration frequency unchanged; in the medium-adaptation region, the medium vibration frequency parameter in the adjustment mechanism is used to adjust the vibration frequency; and in the low-adaptation region, the low frequency parameter in the adjustment mechanism is used to reduce the vibration frequency.

[0033] Preferably, during the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time, analyzed, and evaluated to determine whether the adjustment effect of the mechanism in each region meets expectations. Based on the evaluation results, the adjustment mechanism is then adjusted. Specifically, this includes the following steps:

[0034] During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time and preprocessed after acquisition.

[0035] Extract the dynamic information of geological stress and strain and the dynamic information of density change from the vibration feedback information of each preprocessed area, and analyze them after extraction to generate the compaction effect coefficient and density change index of each area respectively.

[0036] An adjustment effect evaluation model is constructed based on the compaction effect coefficient and density change index of each generated region. An adjustment coefficient for each region is generated, and the generated adjustment coefficients for each region are compared with the pre-set adjustment coefficient thresholds for each region. Based on the comparison results, the adjustment effect of the adjustment mechanism in each region is evaluated to see if it meets expectations. The adjustment mechanism is then adjusted based on the evaluation results.

[0037] Preferably, the logic for obtaining the compaction effect coefficient and density change index of each region is as follows:

[0038] The dynamic information of geological stress and strain in the vibration feedback information of each preprocessed region is extracted. Specifically, this includes the average vibration acceleration applied by the vibrating equipment to each region at different times during a period of time during the application of the adjustment mechanism, the vibration frequency of the vibrating equipment in each region, the stress and strain of the geological materials in each region under vibration, and the corresponding time points. These are then processed according to the time series using functions... , , and To express, Define the time period as a point in time. , This indicates that during a certain period of time during the application of the adjustment mechanism. The vibration device applied at the moment The average vibration acceleration of each region This indicates that during a certain period of time during the application of the adjustment mechanism. Vibration equipment at the moment The vibration frequency of each region This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first Stress of geological materials in a region under vibration This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first Strain of geological materials in each region under vibration , It is a positive integer;

[0039] The compaction effect coefficient for each area is calculated using the following formula:

[0040] ;

[0041] In the formula, For the first The coefficient of consolidation effect in each region;

[0042] The dynamic information on density changes in each preprocessed region's vibration feedback information is extracted. Specifically, this includes the average density, strain change rate, and corresponding time points of the geological materials in each region under vibration at different times during a period of time during the application of the adjustment mechanism. These are then analyzed using functions according to the time series. and To express, For a point in time, This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first The average density of geological materials in each region under vibration. This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first The strain change rate of geological materials in each region under vibration;

[0043] The density change index for each region is calculated using the following formula:

[0044] ;

[0045] In the formula, For the first The density change index of each region.

[0046] Preferably, the compaction effect coefficient for each generated region and density change index A model for evaluating the adjustment effect was constructed, and adjustment coefficients for each region were generated through weighted summation. And the adjustment coefficients for each generated region Each region is compared with the pre-set adjustment coefficient threshold. A comparison was conducted, and the adjustment mechanism's effectiveness in each region was evaluated based on the comparison results to determine whether it met expectations. The adjustment mechanism was then adjusted according to the evaluation results. The specific comparative analysis is as follows:

[0047] like The adjustment mechanism has achieved the expected results in this region, and no adjustment is needed.

[0048] like The adjustment mechanism did not achieve the expected results in this area, and the adjustment mechanism needs to be adjusted. Specifically, this includes: analyzing whether the current vibration parameters match the geological material characteristics based on the feedback information from each area, dynamically adjusting the vibration frequency and acceleration parameters, monitoring the adjustment effect in real time, and deciding whether to carry out iterative adjustments.

[0049] Preferably, the DSP-based variable resonant frequency hydraulic vibration control system includes a geological information acquisition module, an adaptive assessment module, a dynamic adjustment mechanism construction module, a feedback analysis and adjustment module, and a dynamic optimization and update module.

[0050] The geological information acquisition module divides the foundation area to be compacted into several areas during the construction of the high-rise building foundation, and deploys a sensor network in each area to acquire the geological dynamic information of each area in real time.

[0051] The adaptability assessment module analyzes the acquired geological dynamic information of each region, assesses the degree of adaptability between the geological materials of each region and the vibration frequency of the current vibration equipment, and divides each region into high-adaptability, medium-adaptability, and low-adaptability regions based on the assessment results.

[0052] The dynamic adjustment mechanism construction module constructs an adjustment mechanism for dynamically adjusting the vibration frequency of different regions based on the division results of each region in the foundation area to be compacted, and applies it to the current vibration equipment after construction.

[0053] The feedback analysis and adjustment module acquires vibration feedback information from various regions in real time during the application of the adjustment mechanism, analyzes the acquired information, evaluates whether the adjustment effect of the adjustment mechanism in each region meets expectations, and adjusts the adjustment mechanism based on the evaluation results.

[0054] The dynamic optimization and update module, based on long-term collected geological dynamic information and vibration feedback information, dynamically optimizes and updates the adjustment mechanism, continuously adjusts the vibration frequency of the vibration equipment, and maintains the uniformity and stability of the foundation compaction.

[0055] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0056] 1. This invention effectively solves the problem of vibration frequency adjustment lag caused by the different absorption and reflection characteristics of vibration frequencies of various geological materials (such as rock, sand, and silt) during the construction of high-rise building foundations. By dynamically collecting geological information and real-time vibration feedback from various areas, the system can accurately analyze and process the feedback signals from different geological materials, thereby adjusting the vibration frequency in real time to ensure uniform compaction of the foundation. This enhances the system's responsiveness under complex geological conditions and reduces the risks caused by frequency lag.

[0057] 2. By constructing an adaptive assessment model, this invention enables dynamic adjustments based on the characteristics of different geological regions (such as geological adaptability coefficients and vibration response indices), ensuring that the vibration equipment can flexibly adjust its vibration frequency according to real-time feedback. This automatic adjustment mechanism improves construction efficiency and ensures the consistency of foundation compaction in different areas, reducing the need for manual intervention. Especially in environments where material properties change rapidly, the system's flexible adjustment capability avoids later settlement problems caused by uneven material compaction.

[0058] 3. This invention also constructs an adaptive optimization and update mechanism based on long-term collected geological dynamic information and vibration feedback information, ensuring that the vibration equipment maintains the optimal frequency adjustment state during long-term construction. This not only improves the working efficiency of the equipment but also continuously optimizes construction parameters, ensuring the stability and reliability of foundation construction and effectively avoiding structural safety hazards caused by insufficient compaction. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0060] Figure 1 This is a flowchart illustrating the variable resonant frequency hydraulic vibration control system and method based on DSP of the present invention.

[0061] Figure 2 This is a schematic diagram of the modules of the DSP-based variable resonant frequency hydraulic vibration control system and method of the present invention. Detailed Implementation

[0062] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0063] This invention provides, for example Figure 1 The DSP-based variable resonant frequency hydraulic vibration control method shown includes the following steps:

[0064] During the foundation construction of high-rise buildings, the foundation area to be compacted is evenly divided into several areas, and a sensor network is deployed in each area to obtain the geological dynamic information of each area in real time.

[0065] To uniformly divide the foundation area to be compacted during the construction of high-rise building foundations, a coordinate grid-based method can be adopted. Specifically, firstly, a two-dimensional or three-dimensional model of the foundation can be generated using digital construction planning software based on the total area of ​​the construction area. Then, based on this model, the software divides the entire foundation area into several regions according to a preset grid density. The grid density can be dynamically adjusted according to the complexity of the geological conditions; for example, the grid can be denser in areas with more complex or varied geology, while it can be sparser in areas with relatively uniform geology. This division method ensures that each region has a relatively uniform size, and the vibration feedback signal of each region can be analyzed independently. Through software-based division, construction personnel can intuitively see the number and location of each grid region, which is beneficial for subsequent sensor deployment and data acquisition.

[0066] The deployment of sensor networks across designated areas can be achieved through a construction management software system combined with sensor placement algorithms. First, based on the previously defined grid areas, the software calculates the sensor deployment locations for each area, ensuring that sensors can cover the entire region and accurately collect data. The sensor network can utilize wireless communication-based sensor nodes, such as seismic sensors, accelerometers, and strain sensors, with each node rationally distributed according to the size and geological complexity of the area. The software dynamically acquires "geological dynamic information" for each area by reading real-time sensor data, such as soil vibration response characteristics, density changes, and pressure data. This data is transmitted back to the central control system via a wireless network for real-time monitoring and feedback analysis, ensuring that the geological conditions of each area can be recorded and analyzed in real time.

[0067] This method of uniformly dividing the foundation and deploying a sensor network is designed to accurately address the core issue of "vibration frequency adjustment lag." Due to significant differences in geological materials within the foundation of high-rise buildings (such as rock, sand, and silt), the vibration feedback signals differ in each area, directly affecting the frequency adjustment of the vibration equipment. By uniformly dividing the foundation to be compacted and deploying a sensor network in each area, real-time monitoring of the geological characteristics of each area can be refined, accurately acquiring the response characteristics of different geological materials and ensuring that vibration feedback information from each area is processed independently. This effectively avoids the frequency adjustment lag problem caused by differences in material properties, ensuring that the system can dynamically adjust the vibration frequency of different areas, thereby improving the uniformity and stability of compaction and ultimately solving the risks of insufficient foundation density and localized settlement.

[0068] The acquired geological dynamic information of each region is analyzed to assess the adaptability of the geological materials in each region to the vibration frequency of the current vibration equipment. Based on the assessment results, each region is divided into high-adaptability, medium-adaptability, and low-adaptability regions.

[0069] In this embodiment, the acquired geological dynamic information of each region is analyzed to assess the adaptability of the geological materials in each region to the vibration frequency of the current vibration equipment. Based on the assessment results, each region is divided into high-adaptability regions, medium-adaptability regions, and low-adaptability regions. The specific steps include:

[0070] The acquired geological dynamic information of each region is preprocessed;

[0071] Acquiring dynamic geological information in various regions can be achieved through a sensor network deployed across different areas. These sensors can include accelerometers, strain sensors, seismic wave sensors, etc., which can monitor the geological response characteristics of each region in real time during vibration. Specifically, data is collected by sensor nodes and transmitted to a central processing system via a wireless communication network. The sensors can detect vibration transmission velocity, stress changes, density changes, etc., forming dynamic geological information for each region. The data acquisition frequency of the sensor network can be dynamically adjusted according to the real-time operation of the vibration equipment, ensuring accurate recording of the feedback response of geological materials at different vibration frequencies.

[0072] The purpose of preprocessing is to improve data quality, eliminate noise and outliers, and ensure the accuracy of subsequent analysis and evaluation. Vibration feedback signals and geological dynamic information may be affected by environmental noise, equipment deviations, and other interferences during the acquisition process, making preprocessing essential. The preprocessing process includes: data denoising, using filtering algorithms such as high-pass or low-pass filters to remove high-frequency noise or low-frequency drift from the signal; data normalization, scaling data collected from different areas to the same range to ensure data comparability; and outlier handling, identifying and removing anomalous data that significantly deviates from normal values ​​by analyzing the data distribution. These operations can be automated using data processing algorithms and statistical analysis methods, implemented through software, thereby ensuring that the preprocessed data accurately reflects the true dynamic characteristics of geological materials and provides a reliable basis for subsequent adaptability assessments.

[0073] Geological material information and vibration response dynamic information are extracted from the preprocessed geological dynamic information of each region, and analyzed after extraction to generate the geological adaptability coefficient and vibration response index of each region respectively.

[0074] An adaptation evaluation model is constructed for the geological adaptation coefficient and vibration response index of each region. The adaptation coefficient of each region is generated and compared with the pre-set adaptation coefficient threshold range. Based on the comparison results, the adaptation degree of the geological materials of each region to the vibration frequency of the current vibration equipment is evaluated. Based on the evaluation results, each region is divided into high adaptation region, medium adaptation region and low adaptation region.

[0075] The "pre-defined adaptation coefficient threshold range" can be determined by analyzing historical construction data, laboratory test data, and simulation experiment results. First, the software system can statistically analyze the operating data of vibration equipment under similar geological conditions in the past to extract the distribution range of geological adaptation coefficients and vibration response indices at different vibration frequencies in different regions. Combined with simulation experiment data from the laboratory, the optimal adaptation coefficient for each material is determined by conducting vibration frequency tests on various geological materials under controlled conditions. Then, data analysis software is used to comprehensively evaluate all collected data, calculate the upper and lower limits of the adaptation coefficient, and determine the threshold range of the adaptation coefficient through regression analysis or other statistical methods. The final threshold range can be iteratively adjusted and verified multiple times to ensure optimal matching between the vibration frequency and the geological materials in the actual construction environment.

[0076] In this embodiment, the logic for obtaining the geological adaptability coefficient and vibration response index of each region is as follows:

[0077] Geological material information is extracted from the preprocessed geological dynamics information of each region, specifically including the average material density, average geological layer thickness, and internal damping value of each region at different times over a period of time, and these are calibrated as follows: , and , Indicates the first A region within a certain period of time The average density of the material at that time Indicates the first A region within a certain period of time The average thickness of the geological layer at that time. Indicates the first A region within a certain period of time The internal damping value at time t, , , and All are positive integers;

[0078] Extracting pre-processed geological material information can be achieved through multi-step analysis and processing of raw geological data collected by sensors. First, sensors deployed in various regions continuously collect material characteristic data (such as density, geological layer thickness, and internal damping) at preset time intervals. This data is then transmitted to a central processing system and automatically pre-processed by data processing software, including noise reduction and outlier filtering. Next, the software extracts geological material information for each region from the pre-processed data according to a preset algorithm. Specifically, the software can automatically extract core data items related to geological adaptability at each time point, including material density, thickness, and internal damping values, and perform a weighted average across multiple time points. The software can automatically identify and label different material characteristic information for each region according to specific rules or models, and store and process the data according to each region, ensuring that the data from different regions are independent and comparable.

[0079] These quantitative data (material density, geological layer thickness, and internal damping value) can be acquired through various sensor devices deployed in each area. For example, material density can be indirectly obtained by calculating the propagation speed of vibration waves in the material using seismic wave sensors; the average thickness of the geological layer can be determined using ground-penetrating radar and other detection equipment; and the internal damping value is estimated by monitoring the attenuation rate of vibration waves using accelerometers and strain sensors. During data acquisition, the software system dynamically adjusts the acquisition frequency according to the operating status of the vibration equipment to ensure that the data reflects the geological conditions at different points in time. The reason for collecting data at different times over a period of time is that the physical properties of the material (such as density and damping value) may change dynamically during vibration compaction. This change may be affected by vibration intensity, geological material structure, and external environment (such as humidity and temperature). Through multiple acquisitions and time-weighted averaging, the software can generate a more stable and accurate material property value, eliminating random errors at a single time point and ensuring that the final geological adaptability coefficient accurately reflects the dynamic changes of the material throughout the compaction process.

[0080] The geological adaptability coefficient for each region is calculated using the following formula:

[0081] ;

[0082] In the formula, For the first Geological adaptability coefficient of each region;

[0083] This calculation formula reflects the dynamic adaptability of materials during vibration by integrating time-weighted averaging and multiple geological parameters. The calculation steps in the formula are designed to comprehensively consider the physical properties of the material over different time periods and to evaluate the adaptability of geological materials based on these properties. Specifically: (Average density of material): This reflects the density change of the material at different points in time. The higher the density, the more difficult it is for the material to transmit vibrations. Therefore, it is necessary to consider the influence of density on vibration adaptability. (Average thickness of geological layer): The thickness of geological layer directly affects the transmission path of vibration. The greater the thickness, the worse the material's ability to adapt to vibration. Therefore, it is multiplied by density in the formula to reflect the degree of material adaptability. (Internal damping value): The internal damping of a material determines the rate attenuation of vibrational energy within the material. The greater the damping, the faster the vibration decays. Therefore, by... To calculate, ensure that the damping effect of the material's internal structure on vibrations is taken into account. Weighted average processing: the summation sign in the formula and the... This method involves averaging data from multiple time points over a period of time to ensure that the adaptability coefficient reflects changes in material properties throughout the entire time period, avoiding the impact of instantaneous fluctuations on the calculation results. This calculation method comprehensively considers the material's density, thickness, and damping characteristics, and combined with time-weighted averaging, provides a more comprehensive adaptability assessment, ensuring that the geological adaptability coefficient accurately reflects the degree of matching between the vibrating equipment and the geological materials.

[0084] No. Geological adaptability coefficient of each region The magnitude of the adaptation coefficient directly reflects the degree of compatibility between the geological materials in the region and the vibration frequency of the current vibration equipment. A larger adaptation coefficient indicates lower material density, thinner geological layers, and lower internal damping in the region. These factors make the material more capable of transmitting and responding to vibrations, thus resulting in a better match with the vibration equipment frequency. Conversely, a smaller adaptation coefficient indicates higher material density, thicker geological layers, and higher internal damping in the region. These factors weaken vibration transmission, making it difficult for the vibration equipment frequency to adapt to the current geological materials. Therefore, by calculating the geological adaptation coefficient, it is possible to assess whether the materials in each region are suitable for the current vibration equipment frequency and determine whether the vibration frequency needs to be adjusted.

[0085] Vibration response dynamic information is extracted from the preprocessed geological dynamic information of each region, specifically including the average internal vibration transmission velocity, elastic modulus of the material, and strain rate of the geological material at different times over a period of time, and calibrated as follows: , and , Indicates the first A region within a certain period of time The average transmission velocity of internal vibration at any given time. Indicates the first A region within a certain period of time The elastic modulus of the material at a given time. Indicates the first A region within a certain period of time The strain rate of geological materials at any given time;

[0086] Extracting dynamic vibration response information from various regions can be achieved through a multi-type sensor network deployed in each region, primarily including accelerometers, strain sensors, and vibration transmission velocity measuring devices. First, the sensors collect data such as vibration transmission velocity, the material's elastic modulus, and strain rate at preset time intervals over a period of time. After preliminary processing, this raw data is transmitted to the central control system for further analysis by software. During extraction, the software performs noise reduction, filtering, and normalization on the data from different time points, and automatically calculates the vibration transmission velocity, elastic modulus, and strain rate for each time point. Then, the software integrates the data from multiple time points for each region and extracts the time-weighted average of these data. This method ensures that the dynamic vibration response information for each region is accurate and reflects the dynamic changes in the material.

[0087] The average propagation velocity of internal vibrations can be measured using accelerometers to determine the speed at which vibration waves propagate through geological materials. These sensors record the time delay of the vibration wave reaching different locations from its source. The elastic modulus of the material can be measured using strain sensors, which monitor the relationship between the stress applied by the vibration wave and the strain generated in the material. Software calculates the elastic modulus based on the stress-to-strain ratio. The strain rate of the geological material is calculated by monitoring the change in the material's deformation rate during vibration, with sensors recording the material's deformation and the duration of vibration in real time. These data need to be collected at different times over a period of time because the intensity and frequency of vibration applied to the geological material by the vibrating equipment may fluctuate at different points in time, and the physical properties of the geological material (such as elastic modulus and strain rate) also change dynamically over time. By collecting data multiple times and performing time-weighted averaging using software, it can be ensured that these quantitative data reflect the true response characteristics of the material throughout the entire vibration process, eliminating data bias caused by instantaneous fluctuations or short-term changes. This approach makes the final calculated vibration response index more accurate and stable.

[0088] The vibration response index for each region is calculated using the following formula:

[0089] ;

[0090] In the formula, For the first Vibration response index of each region.

[0091] This calculation formula uses multiple key physical parameters to calculate the vibration response index, aiming to assess the response capability of geological materials in each region to vibration frequencies applied by vibrating equipment. The vibration transmission velocity in the formula... This reflects the efficiency of vibration propagation within a material; the faster the vibration propagation speed, the easier it is for the material to transmit vibration. Elastic modulus This reflects the material's rigidity; the higher the rigidity, the stronger the material's vibration response capability. Therefore, the product of these two factors, placed in the molecule, represents the material's overall response efficiency to vibration. The strain rate of geological materials... This measures the degree of deformation of a material during vibration. Greater deformation indicates lower material stability and poorer response. Therefore, the strain rate is placed in the denominator and... This weakens the material's responsiveness. The formula also reduces the responsiveness of the material over a period of time. The vibration response index is calculated by weighting and summing multiple data collections (representing a time period) to ensure that the calculated index reflects the comprehensive characteristics of the material over the entire time period, rather than based on instantaneous changes at a single point in time. This effectively captures the dynamic response characteristics of the material, making the index calculation more accurate and helping to optimize the adjustment of vibration equipment.

[0092] No. Vibration response index of each region The magnitude of the vibration response index directly reflects the responsiveness of the geological materials in a given area to the vibration frequency applied by the vibrating equipment. A larger vibration response index indicates a faster vibration transmission speed, higher elastic modulus, and lower strain rate. This means the material can transmit vibration more quickly and effectively, indicating a better match between the geological materials in the area and the frequency of the current vibrating equipment. Conversely, a smaller vibration response index indicates lower vibration transmission efficiency or that the material is more prone to deformation under vibration. This means the material is less responsive to the frequency of the vibrating equipment and has poor adaptability. Therefore, by assessing the magnitude of the vibration response index, the response of materials in each area to vibration frequencies can be evaluated, thereby determining whether the frequency of the vibrating equipment needs to be adjusted.

[0093] In this embodiment, the geological adaptability coefficients of each generated region are... and vibration response index An adaptation assessment model was constructed, and the adaptation coefficients for each region were generated by weighted summation. And the fitness coefficients of each generated region With the pre-set fitness coefficient threshold range A comparison was conducted, and the compatibility between the geological materials in each region and the vibration frequency of the current vibration equipment was evaluated based on the comparison results. Based on the evaluation results, each region was divided into high-compatibility, medium-compatibility, and low-compatibility regions. The specific comparison analysis and division are as follows:

[0094] like If the geological materials in a region are poorly adapted to the vibration frequency of the current vibration equipment, then that region is classified as a low-adaptability region.

[0095] This situation indicates a mismatch between the geological materials in the area and the vibration frequency of the current vibration equipment, resulting in low adaptability. Low adaptability suggests that the materials in the area have high density, thick geological layers, or high internal damping, making it difficult to transmit vibration effectively. Significant adjustments to the vibration equipment frequency may be needed to adapt to the material characteristics. This classification can be automatically identified by software based on a comparison of adaptability coefficients. Specifically, the software automatically acquires the adaptability coefficients for each area. and with the preset A threshold is used for comparison, and areas below that value are automatically marked as low-fit regions. In these regions, the vibration frequency can be reduced via software prompts to improve vibration transmission efficiency.

[0096] like If the geological materials in this area are moderately compatible with the vibration frequency of the current vibration equipment, then this area is classified as a moderately compatible area.

[0097] This indicates that the geological materials in the area are moderately matched to the frequency of the current vibration equipment, basically adapting to the vibration frequency, but there may be some room for optimization. This adaptability suggests that the geological materials have moderate density, thickness, and damping characteristics, capable of transmitting some vibration, but the transmission efficiency is not yet ideal. Software can automatically divide these areas, comparing the adaptability coefficient of each area with a threshold range. Areas falling within this range are marked as medium-adaptability areas. In these areas, minor adjustments to the vibration equipment frequency can be considered to further optimize the compaction effect while reducing excessive stress on the materials.

[0098] like If the geological materials in a region are highly compatible with the vibration frequency of the current vibration equipment, then that region is classified as a high-compatibility region.

[0099] This indicates that the geological materials in the area are highly compatible with the vibration frequency of the current vibration equipment, demonstrating a high degree of adaptability. High adaptability suggests that the material has low density, thinness, and low internal damping, resulting in high vibration transmission efficiency and a rapid response to the vibration equipment's actions. Delineating high-adaptability zones can be automatically accomplished by software based on an upper limit comparison of the adaptability coefficient. When the software identifies... Exceed When this occurs, the area is automatically marked as a high-adaptability zone. For these zones, significant adjustments are typically unnecessary; the current vibration frequency can be maintained to ensure optimal equipment efficiency.

[0100] The process of constructing an adaptation assessment model involves using the geological adaptation coefficient of each region. and vibration response index A weighted summation is performed to generate the fitness coefficient for the region. In this process, the weighting coefficients and The setting of these weights is crucial, as they correspond to the relative importance of the geological adaptability coefficient and the vibration response index, respectively. The weighting is typically based on experimental data, historical records, and specific geological conditions. For example, if the vibrating equipment has high requirements for material responsiveness, the vibration response index... weight It could be even greater; and if the material's density and thickness have a greater impact on vibration transmission, then the geological adaptability coefficient... weight It will be higher. During the specific calculation, the software will use a pre-set weighting formula to... and Multiply by the corresponding weights respectively and Then, the weighted results are summed to obtain the fitness coefficient for each region. ,Right now: In this way, the evaluation model can comprehensively consider the material properties and vibration response capabilities, ensuring the generated fitness coefficient. It can accurately reflect the degree of matching between the geological materials in each area and the frequency of the current vibration equipment.

[0101] Based on the division of the various regions in the foundation area to be compacted, an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed, and then applied to the current vibration equipment after construction.

[0102] In this embodiment, based on the division results of each region in the foundation area to be compacted, an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed. Specifically, according to the division results of high-adaptability region, medium-adaptability region and low-adaptability region, different vibration frequency adjustment parameters are set to form an adjustment mechanism. This adjustment mechanism automatically determines the adjustment amplitude and method of vibration frequency based on the adaptation coefficient of each region and the current vibration frequency state through pre-set rules.

[0103] The goal of "constructing an adjustment mechanism for dynamically adjusting the vibration frequency of different areas based on the division of the foundation area to be compacted" can be achieved through a software system based on real-time data acquisition and analysis. First, the software system divides the area into high-adaptability, medium-adaptability, and low-adaptability zones based on the adaptation coefficient and vibration response index of each area. This process is handled and evaluated using real-time geological dynamic information and vibration feedback information collected by a sensor network. Next, based on the adaptation assessment results of each area, the system applies preset rules and adjustment strategies to set different vibration frequency adjustment parameters for each area. Specifically, the software automatically calculates the appropriate frequency adjustment range and method (such as keeping the frequency constant, appropriately increasing or decreasing the vibration frequency) for each area based on the current adaptation coefficient and vibration frequency state. These adjustment parameters are transmitted to the vibration equipment in real time through the software's dynamic adjustment mechanism, enabling independent and precise vibration frequency adjustments for different areas. This is done to ensure that each foundation area uses the most suitable vibration frequency according to its different geological characteristics (such as material density, thickness, damping, etc.), avoiding uneven foundation compaction or material damage caused by excessively high or low frequencies. By dynamically adjusting the frequency of different areas in real time using software, compaction efficiency can be improved, unnecessary energy waste reduced, and construction quality and long-term foundation stability ensured. This method, through automated and intelligent software control, minimizes human intervention and ensures precise and efficient adjustment of vibration frequency.

[0104] Different frequency adjustments are made for the high-adaptability, medium-adaptability, and low-adaptability regions. Specifically, in the high-adaptability region, the standard vibration frequency parameter in the adjustment mechanism is used to keep the current vibration frequency unchanged; in the medium-adaptability region, the medium vibration frequency parameter in the adjustment mechanism is used to adjust the vibration frequency to optimize the vibration effect; and in the low-adaptability region, the low frequency parameter in the adjustment mechanism is used to reduce the vibration frequency to improve the vibration adaptability of the material and enhance the compaction effect.

[0105] To achieve "different frequency adjustments for high-adaptability, medium-adaptability, and low-adaptability areas," a software control system combined with real-time monitoring data can be used. First, the software divides the areas into high-adaptability, medium-adaptability, and low-adaptability zones based on previously collected and analyzed geological adaptability coefficients and vibration response indices. Next, the software invokes preset adjustment mechanisms based on the adaptability results of each zone. For high-adaptability zones, the system sets standard vibration frequency parameters and maintains the current frequency unchanged, as the geological materials and equipment frequencies in these zones are already highly matched and require no adjustment. For medium-adaptability zones, the software automatically selects medium-frequency adjustment parameters, slightly increasing or decreasing the vibration frequency to adapt to the material characteristics of the zone and ensure better compaction efficiency. For low-adaptability zones, the system selects low-frequency parameters and automatically reduces the vibration frequency to decrease the strain pressure on the material under high-frequency vibration, increasing the material's adaptability. All frequency adjustments are based on real-time data, monitored through sensor feedback, and controlled by the software to adjust the vibration equipment's frequency. The purpose of this is to ensure that the vibration frequency of each zone matches its geological conditions through automated vibration frequency adjustment, avoiding uneven foundation compaction or material damage caused by excessively high or low frequencies. This approach reduces energy waste during construction, extends equipment lifespan, and ensures construction quality and foundation stability. Dynamic adjustments via a software control system reduce manual intervention, improve construction efficiency, and guarantee the accuracy and timeliness of the adjustment process, thereby optimizing vibration effects in different areas.

[0106] To achieve the goal of "applying it to the current vibration equipment after construction," the frequency parameters generated by the adjustment mechanism can be transmitted in real time to the control module of the vibration equipment through a software control system. First, in the software system, the dynamic adjustment mechanism has already generated corresponding vibration frequency adjustment parameters based on the adaptability of each region. Next, the software sends these frequency parameters to the main controller of the vibration equipment via wireless or wired communication protocols (such as industrial control standards like Modbus, CAN bus, or wireless transmission protocols). The main controller receives the adjustment instructions for each region and adjusts the equipment's operating parameters accordingly, such as the speed of the vibration motor or the frequency output of the vibrator. Specifically, the software monitors the current state of the vibration equipment and compares it in real time with the preset vibration frequency adjustment mechanism to ensure that the equipment can make timely adjustments according to the needs of different regions. The entire process can be implemented through a closed-loop control system. The software continuously receives sensor data, and the adjusted vibration frequency is fed back to the software system to ensure that the equipment operation is consistent with the adaptability of the regional division. This method enables precise vibration frequency control, ensuring that the vibration equipment can operate with the most suitable parameters in regions with different geological conditions, avoiding uneven foundation compaction or damage caused by unsuitable vibration frequencies. This automated control reduces human intervention, improves the operating efficiency of vibration equipment, and ensures the accuracy and consistency of the frequency adjustment process.

[0107] During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time, analyzed, and evaluated to determine whether the adjustment effect of the adjustment mechanism in each region meets expectations. Based on the evaluation results, the adjustment mechanism is then adjusted.

[0108] In this embodiment, during the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time, analyzed, and evaluated to determine whether the adjustment effect of the adjustment mechanism in each region meets expectations. Based on the evaluation results, the adjustment mechanism is then adjusted. Specifically, the following steps are included:

[0109] During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time and preprocessed after acquisition.

[0110] In the application of the adjustment mechanism, real-time acquisition of vibration feedback information can be achieved through a sensor network deployed in various areas. Specifically, accelerometers, strain sensors, and seismic wave sensors are installed at key locations in each area. These sensors capture data such as acceleration, stress, and strain of the geological materials during vibration in real time. These sensors transmit the real-time acquired data to the central control system via wireless communication protocols (such as Wi-Fi, LoRa, or ZigBee) or wired industrial communication protocols (such as Modbus or CAN bus). The software system periodically reads this data from the sensors to ensure that vibration feedback information from each area is accurately and quickly transmitted to the control center during the operation of the vibration equipment. This data transmission method ensures real-time performance and allows for dynamic adjustment of the vibration equipment parameters.

[0111] The purpose of preprocessing is to ensure that the vibration feedback information acquired from sensors is accurate and suitable for subsequent analysis. Raw sensor data can be affected by environmental noise, equipment errors, or signal distortion, and directly using it for analysis may lead to biased results. Preprocessing typically includes the following steps: noise reduction, which uses filters (such as low-pass filters or Kalman filters) to remove high-frequency noise or low-frequency drift from the data; normalization, which scales data from different regions or different sensors to the same numerical range, ensuring that data from different sources can be compared and comprehensively analyzed; and outlier handling, which uses statistical analysis to identify and remove abnormal data points caused by equipment errors or sudden interference. These preprocessing operations can be automated by data processing software, and real-time calculations ensure the accuracy and stability of the feedback data, providing a high-quality data foundation for subsequent evaluation.

[0112] Extract the dynamic information of geological stress and strain and the dynamic information of density change from the vibration feedback information of each preprocessed area, and analyze them after extraction to generate the compaction effect coefficient and density change index of each area respectively.

[0113] An adjustment effect evaluation model is constructed based on the compaction effect coefficient and density change index of each generated region. An adjustment coefficient for each region is generated, and the generated adjustment coefficients for each region are compared with the pre-set adjustment coefficient thresholds for each region. Based on the comparison results, the adjustment effect of the adjustment mechanism in each region is evaluated to see if it meets expectations. The adjustment mechanism is then adjusted based on the evaluation results.

[0114] The "pre-set adjustment coefficient thresholds for each region" can be determined through a comprehensive analysis of historical construction data, laboratory test results, and simulation experiments. Specifically, the software system first collects and analyzes feedback data for each region under different adjustment mechanisms based on past construction records under similar geological conditions, including the compaction effect coefficient and density change index. Next, the software simulates the vibration frequency response and density changes of different geological materials in the laboratory to obtain the feedback parameters of the materials under optimal adjustment conditions. The software system then inputs this historical data and laboratory results into regression analysis or machine learning algorithms to calculate the ideal adjustment coefficient range for each region. The automatically generated thresholds are dynamically optimized based on the specific geological conditions of the region and the application of the adjustment mechanism, ensuring that the preset adjustment coefficient thresholds are adaptable to actual construction conditions.

[0115] In this embodiment, the logic for obtaining the compaction effect coefficient and density change index of each region is as follows:

[0116] The dynamic information of geological stress and strain in the vibration feedback information of each preprocessed region is extracted. Specifically, this includes the average vibration acceleration applied by the vibrating equipment to each region at different times during a period of time during the application of the adjustment mechanism, the vibration frequency of the vibrating equipment in each region, the stress and strain of the geological materials in each region under vibration, and the corresponding time points. These are then processed according to the time series using functions... , , and To express, Define the time period as a point in time. , This indicates that during a certain period of time during the application of the adjustment mechanism. The vibration device applied at the moment The average vibration acceleration of each region This indicates that during a certain period of time during the application of the adjustment mechanism. Vibration equipment at the moment The vibration frequency of each region This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first Stress of geological materials in a region under vibration This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first Strain of geological materials in each region under vibration , It is a positive integer;

[0117] To extract dynamic information on geological stress and strain in various regions, a sensor network can be used. Specifically, accelerometers, strain sensors, and stress sensors are deployed in each region. Accelerometers collect the average vibration acceleration applied by the vibration equipment in real time, while stress and strain sensors collect the stress and strain generated in the geological materials during vibration. Each sensor collects data at preset time intervals to ensure that data at different time points are recorded. This data is transmitted to the central control system via wired or wireless transmission methods (such as Modbus or Zigbee communication protocols). The system software preprocesses this data (such as noise reduction and normalization) and marks the data at each time point to ensure the timeliness and accuracy of the data throughout the application of the vibration adjustment mechanism. The software automatically correlates the acceleration, frequency, stress, and strain at each time point to generate complete dynamic stress and strain information.

[0118] Acceleration data is acquired by accelerometers to monitor the vibration intensity of the vibrating equipment in each area; vibration frequency is obtained through a frequency meter built into the vibrating equipment; and stress and strain of the geological materials are monitored by stress and strain sensors buried underground. Data needs to be collected at different times over a period of time because the response of geological materials to vibration has dynamic characteristics; the frequency, acceleration, stress, and strain of the vibrating equipment change over time. By continuously collecting data, the software can obtain a more complete curve of material property changes, ensuring that the evaluation model accurately reflects the effect of the vibration adjustment mechanism at different times. Data collected over a fixed period can help predict the response state of geological materials at different stages, thereby optimizing the adjustment scheme of the vibrating equipment and ensuring uniform and effective foundation compaction.

[0119] The compaction effect coefficient for each area is calculated using the following formula:

[0120] ;

[0121] In the formula, For the first The coefficient of consolidation effect in each region;

[0122] The coefficient of the consolidation effect The calculation formula integrates the acceleration, vibration frequency, stress, and strain at various time points during the vibration process, reflecting the comprehensive compaction effect of the vibrating equipment on the foundation material. Specifically: vibration acceleration... Acceleration represents the magnitude of the force applied to the geological material by the vibrating equipment. The greater the vibration acceleration, the more significant the compaction effect; therefore, it is considered one of the core parameters in the calculation. Vibration frequency. Frequency represents the number of vibrations. Higher frequencies can promote faster compaction of geological materials; therefore, frequency is used to reflect the intensity of the vibration's effect. Stress and strain Stress reflects the force exerted on geological materials during vibration, while strain represents the degree of deformation of the material. The ratio of stress to strain is... This represents the material's resistance to deformation. The stronger the resistance to deformation, the better the material can maintain its structural stability, resulting in better compaction. By examining these parameters over a time period... The integral is performed over time, taking into account the dynamic changes at different points in time during the vibration process. The integral reflects the cumulative compaction effect over the entire time period, rather than the effect at a single instant, ensuring that the calculation results can comprehensively reflect the compaction state of the material.

[0123] No. The consolidation effect coefficient of each region The magnitude of the compaction effect coefficient directly reflects the compaction effect of the vibrating equipment on the geological materials in that area. A larger compaction effect coefficient indicates that the acceleration and frequency applied by the vibrating equipment match the stress-strain response of the material, and the material density increases significantly with vibration time, meaning the adjustment mechanism has achieved its expected effect. Conversely, a smaller compaction effect coefficient indicates that the vibration frequency or acceleration may not have been sufficiently applied to the geological materials, resulting in an unsatisfactory compaction effect, meaning the adjustment mechanism has not achieved its expected effect in that area. Therefore, by evaluating... The magnitude of the vibration parameters can be used to determine whether the current adjustment mechanism has effectively increased the density of the foundation material in each area, and thus determine whether further adjustments to the vibration parameters are needed.

[0124] The dynamic information on density changes in each preprocessed region's vibration feedback information is extracted. Specifically, this includes the average density, strain change rate, and corresponding time points of the geological materials in each region under vibration at different times during a period of time during the application of the adjustment mechanism. These are then analyzed using functions according to the time series. and To express, For a point in time, This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first The average density of geological materials in each region under vibration. This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first The strain change rate of geological materials in each region under vibration;

[0125] To extract dynamic information on density changes in various regions, high-precision density and strain sensors can be deployed in the construction area. Density sensors measure the average density of the geological material in real time during vibration, while strain sensors monitor the strain rate of the geological material. These sensors periodically collect data at fixed intervals over a certain period and mark the corresponding time points to ensure accurate recording of density and strain rate changes at each time point. The dynamic information collected by the sensors is transmitted to the data processing software in the control system via wireless communication protocols (such as LoRa or ZigBee). The software preprocesses the data, including data denoising and time point synchronization, ensuring that all data is uniformly formatted before being input into the density change analysis model. Through dynamic data processing by the software, density change information at different times throughout the vibration process can be generated.

[0126] Average density is obtained through density sensors, which typically calculate real-time density by measuring the vibration propagation characteristics of the material. Strain change rate is obtained through strain sensors, which record the deformation rate of the material during vibration. These data need to be collected at different times over a period of time because changes in density and strain are dynamic throughout the vibration compaction process; as time progresses, changes in vibration frequency cause fluctuations in material density and strain rate. By collecting data at different time points, the trend of compaction over time can be accurately captured, especially the response of geological materials to changes in vibration intensity. Furthermore, timed data collection helps identify patterns in compaction changes within specific time periods, providing complete time-series data for subsequent evaluation models and facilitating dynamic adjustment of vibration frequency to ensure uniform compaction.

[0127] The density change index for each region is calculated using the following formula:

[0128] ;

[0129] In the formula, For the first The density change index of each region.

[0130] The density change index The calculation formula reflects the cumulative impact of vibrating equipment on the density of geological materials by integrating the dynamic information of the material density change rate and strain rate. The specific explanation is as follows: Density change rate This term represents the rate of density change of geological materials under vibration. Density is a key parameter reflecting the degree of material compaction; a higher rate of density change indicates a more significant compaction effect during vibration, making it a core part of the calculation. (Logarithmic function) The logarithmic function here represents the rate of change of strain. The nonlinear effects. Strain rate reflects the deformation speed of a material during vibration. Taking the logarithm can reduce the excessive influence of the strain change rate on the final calculation result, allowing the formula to better handle nonlinear changes and reflect the material's adaptation to vibration at low strain rates. Integral: The formula applies to the entire adjustment mechanism process (from... arrive Integrating the density change and strain rate of the material reflects the continuous impact of the vibrating equipment on the material's density over the entire time period, rather than just the instantaneous change at a single moment. This captures the cumulative density change of the material and more accurately reflects the overall effect of the adjustment mechanism. By integrating the product of these two main variables, the formula comprehensively considers the effects of time, density, and strain rate on density, yielding the trend of density change throughout the vibration process.

[0131] No. Density change index of each region The magnitude of the density change index directly reflects the influence of the vibrating equipment on the density change of geological materials over time. A larger density change index indicates a higher rate of density change under vibration, suggesting a better match between the vibration frequency, acceleration, and strain rate and the material's properties, resulting in effective compaction and indicating that the adjustment mechanism in that area meets expectations. Conversely, if... The relatively small value indicates that the vibration has a limited impact on density, and the change in material compactness is not significant, suggesting that the current adjustment mechanism is not functioning effectively and further optimization of vibration parameters is needed. Therefore, through evaluation... The size of the vibration can indicate whether the adjustment mechanism has effectively improved the density of the area, and help determine whether the frequency or force of the vibrating equipment needs to be adjusted.

[0132] In this embodiment, the compaction effect coefficient of each generated region is... and density change index A model for evaluating the adjustment effect was constructed, and adjustment coefficients for each region were generated through weighted summation. And the adjustment coefficients for each generated region Each region is compared with the pre-set adjustment coefficient threshold. A comparison was conducted, and the adjustment mechanism's effectiveness in each region was evaluated based on the comparison results to determine whether it met expectations. The adjustment mechanism was then adjusted according to the evaluation results. The specific comparative analysis is as follows:

[0133] like The adjustment mechanism has achieved the expected results in this region, and no adjustment is needed.

[0134] This situation indicates that the current vibration frequency, acceleration, and other parameters match the physical properties of the geological materials, and the foundation compaction has achieved the target requirements. In this case, no further adjustments to the vibration equipment parameters are needed, and the current adjustment mechanism can be maintained. This demonstrates that the system has entered a stable state, and the current adjustment scheme has effectively improved foundation density and optimized resource and time allocation during construction. For the software system, in this situation, real-time feedback information can continue to be collected for long-term monitoring, while the current parameters can be saved for subsequent construction optimization in similar areas.

[0135] like The adjustment mechanism did not achieve the expected results in this area, and the adjustment mechanism needs to be adjusted. Specifically, this includes: analyzing whether the current vibration parameters match the geological material characteristics based on the feedback information from each area, dynamically adjusting the vibration frequency and acceleration parameters, monitoring the adjustment effect in real time, and deciding whether to carry out iterative adjustments.

[0136] This situation indicates that current vibration frequency, acceleration, and other parameters are not effectively acting on the geological materials, resulting in poor compaction. In this case, the software system needs to analyze the current parameters through feedback information to identify which parameters are not matching the material properties. Then, the system can dynamically adjust the vibration frequency and acceleration. Specifically, this involves analyzing geological stress-strain data and vibration feedback data to identify the problem area and related parameters. Combining historical data or machine learning models, the system adjusts the vibration frequency to increase the force on the material or reduces the frequency to avoid excessive material deformation. The adjusted parameters are applied to the vibration equipment in real time, and the system continues to monitor the effect of the adjustment to ensure that the dynamic adjustment mechanism effectively optimizes the foundation compaction effect, making iterative adjustments as necessary. This approach ensures the flexibility and adaptability of the adjustment mechanism, solving the problem of poor compaction caused by the complexity of geological materials.

[0137] To "calculate the consolidation effect coefficient of each generated region" and density change index A model for evaluating the adjustment effect was constructed, and adjustment coefficients for each region were generated by weighted summation. First, a suitable weighting factor needs to be assigned to each factor. The weighting factor is usually set based on empirical values ​​from geological conditions, engineering requirements, and historical data. Specifically, the compaction effect factor... This reflects the direct impact of vibrating equipment on the stress-strain response of materials; therefore, its weight can be higher for some harder geological materials. Density Variation Index This reflects changes in the density of the foundation materials, and its weight can be even higher, especially for areas with high moisture content and relatively loose soil. The weighting coefficient is set accordingly. and This reflects these different material properties and is used to calculate the overall adjustment factor for each region. The specific formula is as follows: By using a weighted summation, the effects of compaction and changes in density are comprehensively considered. Weights and The values ​​can be optimized and adjusted based on geological characteristics through data analysis or historical records to ensure that the adjustment coefficients fully reflect the vibration effects in each area. This is how the generated values ​​are optimized. It can effectively assess the adaptability of current vibration parameters in various regions and be used to determine whether further adjustments are needed.

[0138] Based on long-term collected geological dynamic information and vibration feedback information, the adjustment mechanism is dynamically optimized and updated to continuously adjust the vibration frequency of the vibration equipment and maintain the uniformity and stability of the foundation compaction.

[0139] To achieve the goal of "dynamically optimizing and updating the adjustment mechanism based on long-term collected geological dynamic information and vibration feedback information, continuously adjusting the vibration frequency of the vibrating equipment, and maintaining the uniformity and stability of foundation compaction," the following approach can be taken: First, the software system continuously collects geological dynamic information (such as density, stress, and strain) and vibration feedback information (such as acceleration and frequency) from various regions. This data is transmitted in real time to the central control system via a sensor network for storage and analysis. Based on historical data and current feedback data, the software uses machine learning algorithms or regression models to dynamically identify geological change trends and vibration effects in different regions, updating the frequency adjustment parameters accordingly. Simultaneously, the system evaluates the matching between the vibration frequency and geological conditions based on this data, continuously optimizing the operating parameters of the vibrating equipment. By comparing long-term trends and short-term feedback, the software can predict future geological material responses and pre-adjust the vibration frequency based on these predictions. The purpose of this is to ensure that the vibrating equipment can adapt to long-term geological changes, avoiding localized over-compaction or under-compaction, and ensuring uniform and stable compaction of the entire foundation.

[0140] like Figure 2 The DSP-based variable resonant frequency hydraulic vibration control system shown includes a geological information acquisition module, an adaptive assessment module, a dynamic adjustment mechanism construction module, a feedback analysis and adjustment module, and a dynamic optimization and update module.

[0141] The geological information acquisition module divides the foundation area to be compacted into several areas during the construction of the high-rise building foundation, and deploys a sensor network in each area to acquire the geological dynamic information of each area in real time.

[0142] The adaptability assessment module analyzes the acquired geological dynamic information of each region, assesses the degree of adaptability between the geological materials of each region and the vibration frequency of the current vibration equipment, and divides each region into high-adaptability, medium-adaptability, and low-adaptability regions based on the assessment results.

[0143] The dynamic adjustment mechanism construction module constructs an adjustment mechanism for dynamically adjusting the vibration frequency of different regions based on the division results of each region in the foundation area to be compacted, and applies it to the current vibration equipment after construction.

[0144] The feedback analysis and adjustment module acquires vibration feedback information from various regions in real time during the application of the adjustment mechanism, analyzes the acquired information, evaluates whether the adjustment effect of the adjustment mechanism in each region meets expectations, and adjusts the adjustment mechanism based on the evaluation results.

[0145] The dynamic optimization and update module, based on long-term collected geological dynamic information and vibration feedback information, dynamically optimizes and updates the adjustment mechanism, continuously adjusts the vibration frequency of the vibration equipment, and maintains the uniformity and stability of the foundation compaction.

[0146] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0147] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0148] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0149] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0151] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0152] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0153] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A DSP-based variable resonant frequency hydraulic vibration control method, characterized in that, Specifically, the following steps are included: During the foundation construction of high-rise buildings, the foundation area to be compacted is evenly divided into several areas, and a sensor network is deployed in each area to obtain the geological dynamic information of each area in real time. The acquired geological dynamic information of each region is analyzed to assess the adaptability of the geological materials in each region to the vibration frequency of the current vibration equipment. Based on the assessment results, each region is divided into high-adaptability, medium-adaptability, and low-adaptability regions. Specifically, the following steps are included: The acquired geological dynamic information of each region is preprocessed; Geological material information and vibration response dynamic information are extracted from the preprocessed geological dynamic information of each region, and analyzed after extraction to generate the geological adaptability coefficient and vibration response index of each region respectively. The logic for obtaining the geological adaptability coefficient and vibration response index of each region is as follows: Geological material information is extracted from the preprocessed geological dynamics information of each region, specifically including the average material density, average geological layer thickness, and internal damping value of each region at different times over a period of time, and these are calibrated as follows: , and , Indicates the first A region within a certain period of time The average density of the material at that time Indicates the first A region within a certain period of time The average thickness of the geological layer at that time. Indicates the first A region within a certain period of time The internal damping value at time t, , , and All are positive integers; The geological adaptability coefficient for each region is calculated using the following formula: ； In the formula, For the first Geological adaptability coefficient of each region; Vibration response dynamic information is extracted from the preprocessed geological dynamic information of each region, specifically including the average internal vibration transmission velocity, elastic modulus of the material, and strain rate of the geological material at different times over a period of time, and calibrated as follows: , and , Indicates the first A region within a certain period of time The average transmission velocity of internal vibration at any given time. Indicates the first A region within a certain period of time The elastic modulus of the material at a given time. Indicates the first A region within a certain period of time The strain rate of geological materials at any given time; The vibration response index for each region is calculated using the following formula: ； In the formula, For the first Vibration response index of each region; An adaptation evaluation model is constructed for the geological adaptation coefficient and vibration response index of each region. The adaptation coefficient of each region is generated and compared with the pre-set adaptation coefficient threshold range. Based on the comparison results, the adaptation degree of the geological materials of each region to the vibration frequency of the current vibration equipment is evaluated. Based on the evaluation results, each region is divided into high adaptation region, medium adaptation region and low adaptation region. Based on the division of the various regions in the foundation area to be compacted, an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed, and then applied to the current vibration equipment after construction. During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time, analyzed, and evaluated to determine whether the adjustment effect of the adjustment mechanism in each region meets expectations. Based on the evaluation results, the adjustment mechanism is then adjusted. Based on long-term collected geological dynamic information and vibration feedback information, the adjustment mechanism is dynamically optimized and updated to continuously adjust the vibration frequency of the vibration equipment and maintain the uniformity and stability of the foundation compaction.

2. The DSP-based variable resonant frequency hydraulic vibration control method according to claim 1, characterized in that, Geological adaptability coefficients for each generated region and vibration response index An adaptation assessment model was constructed, and the adaptation coefficients for each region were generated by weighted summation. And the fitness coefficients of each generated region With the pre-set fitness coefficient threshold range A comparison was conducted, and the compatibility between the geological materials in each region and the vibration frequency of the current vibration equipment was evaluated based on the comparison results. Based on the evaluation results, each region was divided into high-compatibility, medium-compatibility, and low-compatibility regions. The specific comparison analysis and division are as follows: like If the geological materials in a region are poorly adapted to the vibration frequency of the current vibration equipment, then that region is classified as a low-adaptability region. like If the geological materials in this area are moderately compatible with the vibration frequency of the current vibration equipment, then this area is classified as a moderately compatible area. like If the geological materials in a region are highly compatible with the vibration frequency of the current vibration equipment, then that region is classified as a high-compatibility region.

3. The DSP-based variable resonant frequency hydraulic vibration control method according to claim 2, characterized in that, Based on the division of the foundation area into different regions, an adjustment mechanism for dynamically adjusting the vibration frequency of different regions is constructed. Specifically, different vibration frequency adjustment parameters are set according to the division of high-adaptability, medium-adaptability, and low-adaptability regions to form an adjustment mechanism. This adjustment mechanism automatically determines the adjustment amplitude and method of vibration frequency based on the adaptation coefficient and current vibration frequency state of each region through pre-set rules. Different frequency adjustments are made for the high-adaptation, medium-adaptation, and low-adaptation regions, respectively. Specifically, in the high-adaptation region, the standard vibration frequency parameter in the adjustment mechanism is used to keep the current vibration frequency unchanged; in the medium-adaptation region, the medium vibration frequency parameter in the adjustment mechanism is used to adjust the vibration frequency; and in the low-adaptation region, the low frequency parameter in the adjustment mechanism is used to reduce the vibration frequency.

4. The DSP-based variable resonant frequency hydraulic vibration control method according to claim 3, characterized in that, During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time, analyzed, and evaluated to determine whether the adjustment effect of the mechanism in each region meets expectations. Based on the evaluation results, the adjustment mechanism is then adjusted, specifically including the following steps: During the application of the adjustment mechanism, vibration feedback information from each region is acquired in real time and preprocessed after acquisition. Extract the dynamic information of geological stress and strain and the dynamic information of density change from the vibration feedback information of each preprocessed area, and analyze them after extraction to generate the compaction effect coefficient and density change index of each area respectively. An adjustment effect evaluation model is constructed based on the compaction effect coefficient and density change index of each generated region. An adjustment coefficient for each region is generated, and the generated adjustment coefficients for each region are compared with the pre-set adjustment coefficient thresholds for each region. Based on the comparison results, the adjustment effect of the adjustment mechanism in each region is evaluated to see if it meets expectations. The adjustment mechanism is then adjusted based on the evaluation results.

5. The DSP-based variable resonant frequency hydraulic vibration control method according to claim 4, characterized in that, The logic for obtaining the compaction effect coefficient and density change index of each region is as follows: The dynamic information of geological stress and strain in the vibration feedback information of each preprocessed region is extracted. Specifically, this includes the average vibration acceleration applied by the vibrating equipment to each region at different times during a period of time during the application of the adjustment mechanism, the vibration frequency of the vibrating equipment in each region, the stress and strain of the geological materials in each region under vibration, and the corresponding time points. These are then processed according to the time series using functions... , , and To express, Define the time period as a point in time. , This indicates that during a certain period of time during the application of the adjustment mechanism. The vibration device applied at the moment The average vibration acceleration of each region This indicates that during a certain period of time during the application of the adjustment mechanism. Vibration equipment at the moment The vibration frequency of each region This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first Stress of geological materials in a region under vibration This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first Strain of geological materials in each region under vibration , It is a positive integer; The compaction effect coefficient for each area is calculated using the following formula: ； In the formula, For the first The coefficient of consolidation effect in each region; The dynamic information on density changes in each preprocessed region's vibration feedback information is extracted. Specifically, this includes the average density, strain change rate, and corresponding time points of the geological materials in each region under vibration at different times during a period of time during the application of the adjustment mechanism. These are then analyzed using functions according to the time series. and To express, For a point in time, This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first The average density of geological materials in each region under vibration. This indicates that during a certain period of time during the application of the adjustment mechanism. Time of the first The strain change rate of geological materials in each region under vibration; The density change index for each region is calculated using the following formula: ； In the formula, For the first The density change index of each region.

6. The DSP-based variable resonant frequency hydraulic vibration control method according to claim 5, characterized in that, The compaction effect coefficient of each generated area and density change index A model for evaluating the adjustment effect was constructed, and adjustment coefficients for each region were generated through weighted summation. And the adjustment coefficients for each generated region Each region is compared with the pre-set adjustment coefficient threshold. A comparison was conducted, and the adjustment mechanism's effectiveness in each region was evaluated based on the comparison results to determine whether it met expectations. The adjustment mechanism was then adjusted according to the evaluation results. The specific comparative analysis is as follows: like The adjustment mechanism has achieved the expected results in this region, and no adjustment is needed. like The adjustment mechanism did not achieve the expected results in this area, and the adjustment mechanism needs to be adjusted. Specifically, this includes: analyzing whether the current vibration parameters match the geological material characteristics based on the feedback information from each area, dynamically adjusting the vibration frequency and acceleration parameters, monitoring the adjustment effect in real time, and deciding whether to carry out iterative adjustments.

7. A DSP-based variable resonant frequency hydraulic vibration control system, used to implement the DSP-based variable resonant frequency hydraulic vibration control method according to any one of claims 1-6, characterized in that, It includes a geological information acquisition module, an adaptability assessment module, a dynamic adjustment mechanism construction module, a feedback analysis and adjustment module, and a dynamic optimization and update module; The geological information acquisition module divides the foundation area to be compacted into several areas during the construction of the high-rise building foundation, and deploys a sensor network in each area to acquire the geological dynamic information of each area in real time. The adaptability assessment module analyzes the acquired geological dynamic information of each region, assesses the degree of adaptability between the geological materials of each region and the vibration frequency of the current vibration equipment, and divides each region into high-adaptability, medium-adaptability, and low-adaptability regions based on the assessment results. The dynamic adjustment mechanism construction module constructs an adjustment mechanism for dynamically adjusting the vibration frequency of different regions based on the division results of each region in the foundation area to be compacted, and applies it to the current vibration equipment after construction. The feedback analysis and adjustment module acquires vibration feedback information from various regions in real time during the application of the adjustment mechanism, analyzes the acquired information, evaluates whether the adjustment effect of the adjustment mechanism in each region meets expectations, and adjusts the adjustment mechanism based on the evaluation results. The dynamic optimization and update module, based on long-term collected geological dynamic information and vibration feedback information, dynamically optimizes and updates the adjustment mechanism, continuously adjusts the vibration frequency of the vibration equipment, and maintains the uniformity and stability of the foundation compaction.

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