Channel blasting neighbor building safety cooperative control method and system based on intelligent sensing

Abstract

The invention provides a channel blasting neighbor building safety cooperative control method and system based on intelligent sensing. Comprising the steps that before blasting operation, parameters are collected, a safety control threshold value is set, a sensing unit is arranged within the range of 100 meters between a blasting operation area and an adjacent building, and rock mass parameters, blasting parameters and building basic parameters are collected through the sensing unit; calculating a stress wave propagation coefficient based on the collected rock mass parameters, and correcting a stress wave propagation error by using the stress wave propagation coefficient; calculating the dynamic rigidity attenuation of the building foundation based on the collected blasting parameters and the building foundation parameters, and updating the anti-interference capability of the building through the dynamic rigidity attenuation of the building foundation; by combining the stress wave propagation coefficient and the dynamic rigidity attenuation of the building foundation, the blasting hole distance, the blasting row distance and the thickness of a buffer layer are optimized; the embodiment can solve the problem that an existing method cannot reliably guarantee the safety of adjacent buildings.

Description

Technical Field

[0001] This invention relates to the field of building safety technology, and in particular to a method and system for collaborative control of safety of neighboring buildings during waterway blasting based on intelligent sensing. Background Technology

[0002] During the upgrading and renovation of canal waterways, widening and dredging often require blasting of the surrounding rock mass. Within a 100-meter radius of such blasting operations, there are often adjacent buildings such as brick and stone houses and concrete ancillary facilities. Precisely controlling blasting disturbance to avoid damage to these structures is a core safety requirement for the project. Current blasting control methods for this scenario generally rely on the assumption of homogeneous rock mass to calculate the propagation law of blasting stress waves, use fixed values ​​to describe the dynamic stiffness of building foundations, and adjust parameters such as blast hole spacing, row spacing, and buffer layer thickness in isolation—that is, determining the value range of each parameter separately based on empirical formulas, without establishing a logical correlation between the parameters. However, in actual engineering, the rock mass of the waterway exhibits significant heterogeneity. Spatial differences in parameters such as porosity and coefficient of variation of elastic modulus can lead to dispersion distortion in stress wave propagation. The prediction error of stress wave amplitude and propagation velocity under the traditional homogeneity assumption can reach more than 25%, failing to reflect the actual wave propagation characteristics. At the same time, the cumulative impact of multiple blasts can cause microscopic damage inside the building foundation, resulting in a gradual decrease in the dynamic stiffness of the foundation with increasing blasting frequency. Fixed stiffness models will underestimate the decline in the foundation's disturbance resistance, making the safety threshold setting too dangerous. Isolated parameter optimization based on this does not consider the dynamic changes in stress wave propagation, nor does it match the decay trend of the foundation's disturbance resistance. This can easily lead to blasting disturbances exceeding the building's safe tolerance range, causing hidden dangers such as wall cracking and foundation settlement, and in severe cases, even affecting the normal use of the building.

[0003] Based on the above problems, there is an urgent need for a technical solution that can accurately characterize the influence of rock mass heterogeneity on wave propagation, quantify the attenuation law of foundation stiffness in real time, and achieve coordinated control of blasting parameters and vibration reduction measures, so as to solve the problem that existing methods cannot reliably guarantee the safety of neighboring buildings. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and proposes a collaborative control method for the safety of neighboring buildings during waterway blasting based on intelligent perception, comprising:

[0005] Before blasting operations, parameter acquisition and safety control threshold setting are carried out. Sensing units are deployed within a 100-meter range between the blasting operation area and adjacent buildings. Rock mass parameters, blasting parameters and building foundation parameters are collected through the sensing units.

[0006] The stress wave propagation coefficient is calculated based on the collected rock mass parameters, and the stress wave propagation error is corrected using the stress wave propagation coefficient.

[0007] The dynamic stiffness attenuation of the building foundation is calculated based on the collected blasting parameters and building foundation parameters, and the building's disturbance resistance is updated based on the dynamic stiffness attenuation of the building foundation.

[0008] By combining the stress wave propagation coefficient with the dynamic stiffness attenuation of the building foundation, the blasting hole spacing, blasting row spacing, and buffer layer thickness are optimized.

[0009] After blasting operations are carried out, actual vibration data are collected. The calculated values ​​of the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation are compared with the actual vibration data to correct the parameter library and form a closed-loop control.

[0010] Preferably, the sensing unit includes a distributed sensing device. The rock mass parameters collected by the distributed sensing device include the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient. The blasting parameters collected include the peak stress wave pressure, cumulative number of blasts, and interval between adjacent blasts. The building foundation parameters collected include the foundation material damping ratio and the foundation deformation used to calculate the foundation material damping ratio. The distributed sensing device synchronously transmits all collected parameters to a calculation unit, which is used to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation.

[0011] More preferably, in the process of calculating the stress wave propagation coefficient, multiple sets of rock mass parameters are used for iterative calculation; in each iteration, the correction coefficient used to calculate the stress wave propagation coefficient is adjusted based on the stress wave propagation coefficient obtained in the previous calculation, until the difference between the stress wave propagation coefficients obtained in two adjacent calculations is less than a preset threshold, then the iteration stops and the final stress wave propagation coefficient is output.

[0012] In a further preferred embodiment, during the optimization of the blasting hole spacing, the blasting row spacing, and the buffer layer thickness, the blasting-damping coordinated control quantity is first calculated. If the blasting-damping coordinated control quantity exceeds the safety control threshold, the blasting hole spacing and the blasting row spacing are first reduced, and then the buffer layer thickness is increased. The blasting-damping coordinated control quantity is repeatedly calculated until it is lower than the safety control threshold, and then the blasting hole spacing, the blasting row spacing, and the buffer layer thickness at this time are output.

[0013] More preferably, the stress wave propagation coefficient is calculated using the following formula:

[0014]

[0015] Where K is the stress wave propagation coefficient of the heterogeneous rock mass, K V The rock mass integrity coefficient. C represents the porosity of the rock mass. E denoted as the coefficient of variation of elastic modulus, f is the dominant frequency of the blasting stress wave, f0 is the natural frequency of the rock mass, α is the correction coefficient for rock mass porosity, and β is the correction coefficient for the coefficient of variation of elastic modulus.

[0016] More preferably, the following formula is used to calculate the dynamic stiffness attenuation of the building foundation:

[0017] ΔK f =K×P max ×N γ ×(1-ζ)×exp(-δ×t int );

[0018] Where ΔK f P represents the dynamic stiffness attenuation of the building foundation, K is the stress wave propagation coefficient of the heterogeneous rock mass, and P is the dynamic stiffness attenuation of the building foundation. max ζ is the peak stress wave pressure, N is the cumulative number of explosions, ζ is the damping ratio of the base material, and t is the peak stress wave pressure. int γ is the interval between adjacent blasts, δ is the attenuation coefficient of the number of blasts, and δ is the attenuation coefficient of the interval time.

[0019] Furthermore, the following formula is used to optimize the blasting hole spacing, the blasting row spacing, and the buffer layer thickness:

[0020]

[0021] And U≤U0, where U is the blasting-damping coordinated control quantity, a is the blasting hole spacing, b is the blasting row spacing, h is the buffer layer thickness, η is the porosity of the buffer layer material, K is the stress wave propagation coefficient of the heterogeneous rock mass, and ΔK f The dynamic stiffness attenuation of the building foundation is given by ρ, the density of the rock mass is given by v, and the allowable vibration velocity is given by E. buf denoted as the elastic modulus of the buffer layer, k1 to k4 are weighting coefficients, and U0 is the safety control threshold.

[0022] A collaborative control system for the safety of adjacent buildings during waterway blasting based on intelligent sensing, applied to any of the aforementioned collaborative control methods for the safety of adjacent buildings during waterway blasting based on intelligent sensing, includes an intelligent sensing module, a parameter calculation module, a control decision module, and a feedback correction module. The intelligent sensing module is electrically connected to the parameter calculation module, which is also electrically connected to the control decision module and the feedback correction module. The feedback correction module is further electrically connected to the parameter calculation module. The intelligent sensing module is used to collect rock mass parameters, blasting parameters, and building foundation parameters. The parameter calculation module includes a processor and a memory. The processor executes a program stored in the memory to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation. The control decision module includes a PLC. Based on the calculation results output by the parameter calculation module, the PLC outputs control commands for blasting hole spacing, blasting row spacing, and buffer layer thickness. The feedback correction module includes a communication module and a cloud server. The communication module transmits actual vibration data to the cloud server. The cloud server compares the calculated data with the actual vibration data, corrects the calculated parameters, and feeds back the corrected parameters to the parameter calculation module.

[0023] More preferably, the intelligent sensing module includes a distributed optical fiber sensor, a piezoelectric pressure sensor, a displacement sensor, and a blasting counter; the distributed optical fiber sensor is used to collect the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient; the piezoelectric pressure sensor is used to collect the peak stress pressure; the displacement sensor is used to collect the deformation of the building foundation; and the blasting counter is used to record the cumulative number of blasts and the interval between adjacent blasts; the output terminals of the distributed optical fiber sensor, the piezoelectric pressure sensor, the displacement sensor, and the blasting counter are all electrically connected to the input terminal of the parameter calculation module.

[0024] More preferably, the communication module of the feedback correction module adopts wireless communication, and the cloud server stores historical calculation data and actual vibration data; the cloud server corrects the correction coefficients α and β used for calculating the stress wave propagation coefficient and the attenuation coefficients γ and δ used for calculating the dynamic stiffness attenuation of the building foundation by comparing the calculated blasting-damping coordinated control quantity with the blasting-damping coordinated control quantity corresponding to the actual vibration data; the corrected parameters are transmitted to the memory of the parameter calculation module through the communication module, and the processor of the parameter calculation module calls the updated parameters for the next calculation.

[0025] Technical effects:

[0026] This invention collects multi-dimensional parameters of rock mass, blasting, and building foundations by deploying sensing units. It introduces stress wave propagation coefficient calculations to correct wave propagation prediction errors caused by the homogeneous rock mass assumption. Combined with blasting and foundation parameters, it calculates stiffness attenuation to update the building's disturbance resistance. Furthermore, it collaboratively optimizes blasting hole spacing, row spacing, and buffer layer thickness, and implements closed-loop feedback. This effectively solves the core problems of inaccurate wave propagation prediction, underestimated foundation stiffness, and isolated parameter optimization in existing technologies, ensuring controllable blasting disturbances to neighboring buildings within 100 meters and guaranteeing building structural safety. Attached Figure Description

[0027] Figure 1 This is a flowchart of the intelligent sensing-based collaborative control method for the safety of neighboring buildings during waterway blasting, as described in this application.

[0028] Figure 2 This is a connection block diagram of the intelligent sensing-based waterway blasting neighboring building safety collaborative control system of this application;

[0029] Figure 3 This is a detailed construction diagram of the intelligent sensing-based collaborative control system for the safety of neighboring buildings during waterway blasting, as described in this application. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0031] Traditional waterway blasting control does not consider the heterogeneity of rock mass, resulting in large errors in stress wave propagation prediction; it ignores the cumulative attenuation of building foundation stiffness, and the blasting parameters and vibration reduction measures are optimized in isolation, which cannot guarantee the safety of buildings within 100 meters.

[0032] Based on this, please refer to Figure 1 This embodiment provides a method for collaborative safety control of neighboring buildings during waterway blasting based on intelligent perception, including:

[0033] S1: Parameter acquisition and safety control threshold setting before blasting operation. Sensing units are deployed within a 100-meter range between the blasting operation area and adjacent buildings. Rock mass parameters, blasting parameters and building foundation parameters are acquired through the sensing units.

[0034] S2: Calculate the stress wave propagation coefficient based on the collected rock mass parameters, and use the stress wave propagation coefficient to correct the stress wave propagation error;

[0035] S3: Calculate the dynamic stiffness attenuation of the building foundation based on the collected blasting parameters and building foundation parameters, and update the building's disturbance resistance capability through the dynamic stiffness attenuation of the building foundation.

[0036] S4: Optimize the blasting hole spacing, blasting row spacing and buffer layer thickness by combining the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation.

[0037] S5: After the blasting operation, collect actual vibration data, compare the calculated values ​​of the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation with the actual vibration data, and correct the parameter library to form a closed-loop control.

[0038] It is worth mentioning that this embodiment first clearly defines the deployment range of the sensing unit as a 100-meter range between the blasting operation area and the adjacent building. This range is determined based on the characteristic that blasting disturbance within 100 meters has a significant impact on building safety, ensuring that the collected data can directly reflect blasting-related parameters that affect the building. The rock mass parameters collected by the sensing unit include the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient, which can reflect the heterogeneity characteristics of the rock mass; blasting parameters include peak stress pressure, cumulative number of blasts, and time interval between adjacent blasts, which can reflect the intensity and frequency of blasting action; building foundation parameters include foundation material damping ratio and foundation deformation, used to assess the foundation's resistance to disturbance.

[0039] When calculating the stress wave propagation coefficient, multiple heterogeneous parameters of the rock mass need to be integrated. This coefficient corrects the stress wave propagation error under the traditional homogeneous rock mass assumption, making the stress wave propagation law more consistent with the actual rock mass conditions. When calculating the dynamic stiffness attenuation of building foundations, the cumulative loss of foundation stiffness due to multiple blasts is quantified by combining blasting parameters and foundation parameters, thereby accurately updating the current disturbance resistance of the building and avoiding safety risks caused by underestimation of stiffness. When optimizing blasting hole spacing, blasting row spacing, and buffer layer thickness, single parameters are no longer adjusted in isolation. Instead, the stress wave propagation characteristics and the foundation's disturbance resistance are combined to ensure that the parameter combination can synergistically reduce disturbances. After blasting, actual vibration data is collected, and the calculated stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation are compared with the actual data to correct the calculation model parameters in the parameter library. This forms a closed-loop control logic from acquisition, calculation, optimization, feedback to re-optimization, ensuring that the accuracy of each blasting control is improved based on previous experience.

[0040] The technical effects of the above embodiments include: achieving coordinated control of blasting disturbance and building safety, reducing stress wave prediction errors and foundation stiffness assessment deviations, avoiding safety risks to buildings within 100 meters due to blasting disturbance, and improving the reliability of disturbance control.

[0041] Traditional blasting parameter sensing equipment has a single monitoring dimension and asynchronous parameter transmission, resulting in inaccurate data foundation for subsequent calculations and failing to provide reliable input for blasting control.

[0042] Based on this, the sensing unit includes a distributed sensing device. The rock mass parameters collected by the distributed sensing device include the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient. The blasting parameters collected include the peak stress wave pressure, cumulative number of blasts, and interval between adjacent blasts. The building foundation parameters collected include the foundation material damping ratio and the foundation deformation used to calculate the foundation material damping ratio. The distributed sensing device synchronously transmits all collected parameters to the calculation unit, which is used to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation.

[0043] It is worth mentioning that the core component of the sensing unit in this embodiment is a distributed sensing device. This device differs from traditional single-point sensors and can achieve synchronous acquisition of multi-dimensional parameters. For rock mass parameter acquisition, specific sensing components in the distributed sensing device specifically capture the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient. Among them, the rock mass integrity coefficient reflects the integrity of the rock mass, the rock mass porosity reflects the distribution of pores inside the rock mass, and the elastic modulus variation coefficient characterizes the spatial differences in the elastic properties of the rock mass. These parameters together constitute the quantitative basis of rock mass heterogeneity.

[0044] For blasting parameters, the equipment uses a dedicated sensing module to collect data on peak stress wave pressure, cumulative number of blasts, and interval between adjacent blasts. The combination of these three data points allows for the assessment of the cumulative effect of the blasting. Regarding foundation parameters, the equipment collects data on the foundation material damping ratio and foundation deformation. Foundation deformation is key raw data for calculating the foundation material damping ratio; dynamic monitoring of deformation allows for real-time derivation of changes in the damping ratio, ensuring that foundation parameters dynamically reflect the current state of the foundation.

[0045] The distributed sensing devices feature synchronous transmission capabilities, ensuring that all collected parameters are simultaneously sent to the computing unit via a unified data transmission link. This avoids data asynchrony issues caused by parameter transmission delays. The computing unit is explicitly designed to calculate stress wave propagation coefficients and the dynamic stiffness attenuation of building foundations, ensuring that the accurate collected data can be directly used in core calculation processes, providing reliable data support for subsequent optimization and control.

[0046] The technical effects of this embodiment include: improving the comprehensiveness and synchronicity of blasting-related parameter acquisition, eliminating parameter transmission delay and data loss problems, providing accurate data input for the calculation of stress wave propagation coefficient and foundation stiffness attenuation, and ensuring the reliability of subsequent control logic.

[0047] Traditional stress wave propagation coefficient calculations are performed in a single operation, without considering the differences in multiple sets of rock mass parameters. This results in insufficient accuracy of the calculation results, making it impossible to accurately correct stress wave propagation errors and affecting the accuracy of blasting disturbance assessment.

[0048] Based on this, in the process of calculating the stress wave propagation coefficient, multiple sets of rock mass parameters are used for iterative calculation. In each iteration, the correction coefficient used to calculate the stress wave propagation coefficient is adjusted based on the stress wave propagation coefficient obtained in the previous calculation, until the difference between the stress wave propagation coefficients obtained in two adjacent calculations is less than a preset threshold. Then, the iteration stops and the final stress wave propagation coefficient is output.

[0049] It is worth mentioning that the core of this embodiment lies in the iterative calculation of the stress wave propagation coefficient using multiple sets of rock mass parameters, which differs from the traditional single-calculation mode. First, the acquisition method for multiple sets of rock mass parameters is determined: through distributed sensing devices at different locations within a 100-meter monitoring range, rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient are collected, forming multiple sets of parameter samples with spatial differences. These samples can cover the heterogeneous characteristics of the rock mass within the monitoring range, avoiding the one-sidedness caused by parameters from a single location. The specific logic of the iterative calculation is as follows: In the first calculation, one set of rock mass parameters is used in conjunction with an initially set correction coefficient to obtain the initial stress wave propagation coefficient; in the second calculation, another set of rock mass parameters is selected, and the correction coefficient is adjusted based on the stress wave propagation coefficient obtained in the first calculation. The adjustment direction of the correction coefficient is determined according to the correlation between the stress wave propagation coefficient and the rock mass parameters. After each iteration, the difference between two adjacent stress wave propagation coefficients is calculated. This difference is used to determine whether the calculation result tends to be stable; the preset threshold is set based on the requirements of building safety for the accuracy of stress wave prediction, ensuring that the error of the final output coefficient is within an acceptable range. The iteration stops when the difference is less than the preset threshold. At this time, the output stress wave propagation coefficient integrates the influence of multiple rock mass parameters, which can more accurately reflect the propagation law of actual stress waves in heterogeneous rock masses. This provides a high-precision coefficient basis for subsequent correction of stress wave propagation errors and avoids disturbance assessment deviations caused by inaccurate coefficients.

[0050] The technical effects of the above embodiments include: improving the calculation accuracy of the stress wave propagation coefficient through iterative calculation of multiple sets of parameters, eliminating the one-sidedness of single parameter calculation, ensuring the accuracy of stress wave propagation error correction, and providing a reliable basis for blasting disturbance assessment.

[0051] Traditional blasting parameter optimization lacks clear judgment criteria and the adjustment order is chaotic, which may result in the optimized parameters still exceeding the safety threshold and failing to effectively reduce the risk of blasting disturbance to buildings.

[0052] Based on this, in the process of optimizing the blasting hole spacing, the blasting row spacing, and the buffer layer thickness, the blasting-damping coordinated control quantity is first calculated; if the blasting-damping coordinated control quantity exceeds the safety control threshold, the blasting hole spacing and the blasting row spacing are first reduced, and then the buffer layer thickness is increased; the blasting-damping coordinated control quantity is repeatedly calculated until the blasting-damping coordinated control quantity is lower than the safety control threshold, and then the blasting hole spacing, the blasting row spacing, and the buffer layer thickness at this time are output.

[0053] It is worth mentioning that this embodiment first clarifies that the core judgment index of the optimization process is the blasting-damping coordinated control quantity. This control quantity can comprehensively reflect the coordinated disturbance control effect of blasting hole spacing, blasting row spacing, and buffer layer thickness, avoiding the limitations of traditional methods that use only a single parameter as the judgment standard. When calculating the blasting-damping coordinated control quantity, it is necessary to combine the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation obtained in the early stage to ensure that the control quantity calculation can be correlated with the rock mass propagation characteristics and the building's disturbance resistance. When the control quantity exceeds the safety control threshold, a clear adjustment sequence is determined: first reduce the blasting hole spacing and blasting row spacing, and then increase the buffer layer thickness.

[0054] The order of these parameters is based on the following: hole spacing and row spacing directly affect the intensity of the stress wave generated by blasting; reducing these parameters directly lowers the peak stress wave value. Increasing the thickness of the buffer layer further weakens the stress wave propagating to the building. The logic of controlling the source first and then reducing vibration is more efficient in reducing disturbance. After each adjustment, the blasting-vibration control quantity needs to be recalculated. During recalculation, the stress wave propagation situation needs to be updated based on the adjusted parameters to ensure that the control quantity truly reflects the adjusted disturbance control effect. This adjustment and calculation process is repeated until the control quantity is below the safety control threshold. At this point, the output combination of blasting hole spacing, row spacing, and buffer layer thickness parameters ensures that the disturbance generated by the blast is within the building's tolerance range, avoiding optimization failure due to a chaotic adjustment order or lack of judgment criteria. The technical effect is to standardize the blasting parameter optimization process, clarify the adjustment order and judgment criteria, ensure that the optimized combination of hole spacing, row spacing, and buffer layer thickness parameters meets safety requirements, and effectively reduce the disturbance risk of blasting to nearby buildings.

[0055] Traditional stress wave propagation coefficient calculations fail to quantify the impact of rock mass heterogeneity on propagation, resulting in coefficients that cannot accurately reflect the actual propagation situation and thus cannot provide precise basis for disturbance assessment.

[0056] Based on this, the stress wave propagation coefficient is calculated using the following formula:

[0057]

[0058] It is worth mentioning that, where K is the stress wave propagation coefficient due to rock mass heterogeneity, which is dimensionless and used to quantify the comprehensive impact of rock mass heterogeneity on stress wave propagation; KV φ is the rock mass integrity coefficient, dimensionless, ranging from 0.3 to 0.9, measured by distributed fiber optic sensors, reflecting the integrity of the rock mass; the larger the value, the more intact the rock mass and the less obstruction it provides to stress wave propagation; φ is the rock mass porosity, dimensionless, ranging from 0.02 to 0.15, measured by ultrasonic flaw detector, characterizing the proportion of pores within the rock mass; the larger the porosity, the easier it is to weaken stress wave propagation; C E α is the coefficient of variation of elastic modulus, dimensionless, ranging from 0.05 to 0.3, taken from the coefficient of variation of three sets of borehole core test values, reflecting the spatial differences in the elastic properties of the rock mass; f is the dominant frequency of the blasting stress wave, in Hertz, measured by a piezoelectric sensor, ranging from 5 to 50 Hertz, representing the main vibration frequency of the stress wave; f0 is the natural frequency of the rock mass, in Hertz, calibrated by a vibration tester, ranging from 10 to 30 Hertz, reflecting the inherent vibration characteristics of the rock mass itself; α is the rock mass porosity correction coefficient, dimensionless, ranging from 0.8 to 1.2, fitted with data from 10 field blast tests, used to adjust the weight of porosity on the propagation coefficient; β is the coefficient of variation of elastic modulus correction coefficient, dimensionless, ranging from 0.5 to 0.8, also fitted with blast test data, used to adjust the weight of elastic modulus variation on the propagation coefficient. The calculation logic of the formula is: first, through K... V This reflects the basic integrity of the rock mass, and then through The term quantifies the weakening effect of porosity on propagation; the greater the porosity, the smaller this exponential term. This item reflects the impact of variations in the elastic modulus on propagation; the larger the coefficient of variation, the larger this component's value. The term reflects the degree of matching between the dominant frequency of the stress wave and the natural frequency of the rock mass. When the two are close, the value of the sine term is larger, indicating that there may be a resonance effect.

[0059] In the formula, C E The power of 1.2 is chosen because the variation in the elastic modulus has a more significant impact on the dispersion of high-frequency stress waves, and this effect needs to be amplified by a higher power; the introduction of 1 is to ensure that even if C E If the value is 0, this part remains 1, without further interfering with the calculation of the K value; β is calculated using 3 different C values. E Core testing calibration ensures accurate matching of the dispersion influence patterns of rock masses with different degrees of variation.

[0060] This study specifically characterizes the resonance effect between the dominant frequency of blast stress waves and the natural frequency of the rock mass. The dominant frequency *f* of the blast stress wave is the main frequency component of the blast energy release, while the natural frequency *f0* of the rock mass is an inherent property of the rock mass's own vibration. When *f* is close to *f0*, the rock mass is prone to resonance, leading to an amplification of the stress wave amplitude and exacerbating disturbances to nearby buildings. When *f* is far from *f0*, the resonance effect weakens, and the wave amplitude becomes relatively stable. A sine function can accurately quantify this periodic resonance effect.

[0061] when Approaching That is, f approaches When the sine value approaches 1, the resonance effect is strongest; when When the value approaches 0 or π, that is, when f is much less than or much greater than f0, the sine value approaches 0, and the resonance effect is the weakest. This design ensures that the formula can cover the risk of wave propagation anomalies in the frequency dimension.

[0062] The K value obtained by multiplying the components can comprehensively quantify the impact of rock mass heterogeneity on stress wave propagation and ensure the accuracy of the coefficients.

[0063] The technical effects of the above embodiments include: quantifying the impact of rock mass heterogeneity on stress wave propagation through formulas, solving the problem that traditional coefficient calculations cannot reflect heterogeneity, improving the accuracy of stress wave propagation coefficient calculations, and providing accurate basis for disturbance assessment.

[0064] Traditional building foundation stiffness calculations do not consider the attenuation caused by the cumulative effect of blasting, thus failing to accurately reflect the actual disturbance resistance of the foundation and easily underestimating building safety risks. Therefore, the following formula is used to calculate the dynamic stiffness attenuation of the building foundation:

[0065] ΔK f =K×P max ×N γ ×(1-ζ)×exp(-δ×t int ).

[0066] The technical solution description must clearly define the physical meaning and dimensions of each parameter in the formula to ensure the feasibility of the calculation logic. Among these, ΔK... f P represents the dynamic stiffness attenuation of the building foundation, expressed in kilonewtons per meter (kN / m). It quantifies the loss of foundation stiffness due to cumulative impact from blasting; a higher value indicates weaker foundation resistance. K is the stress wave propagation coefficient for heterogeneous rock mass, dimensionless, and directly related to stress wave propagation characteristics. maxζ represents the peak stress wave pressure, measured in megapascals (MPa), measured by a piezoelectric pressure sensor, ranging from 0.5 to 2.0 MPa, reflecting the stress intensity of a single blast on the foundation; N represents the cumulative number of blasts, dimensionless, recorded by a blast counter, ranging from 1 to 20 times, reflecting the cumulative frequency of the blasting action; ζ represents the foundation material damping ratio, dimensionless, ranging from 0.02 to 0.05, measured by the free vibration method, reflecting the foundation material's ability to absorb vibration energy; t int The interval between adjacent blasts, in hours (h), is recorded by a timer and ranges from 12 to 72 hours, reflecting the impact of the blasting time interval on foundation recovery; γ is the blast count attenuation coefficient, dimensionless, ranging from 0.3 to 0.6, calibrated using monitoring data from three similar buildings, used to adjust the impact of cumulative blast counts on stiffness attenuation; δ is the interval time attenuation coefficient, dimensionless, ranging from 0.01 to 0.03, also calibrated using building monitoring data, used to adjust the mitigation effect of interval time on stiffness attenuation.

[0067] The formula calculation logic is as follows: first, use K and P... max The product of these values ​​reflects the actual strength of the stress wave acting on the foundation, which is then expressed through N. γ The cumulative number of terms quantifies the continuous weakening of stiffness. The (1-ζ) term reflects the effect of damping ratio on stiffness decay. The larger the damping ratio, the easier it is for the material to absorb energy, and the stiffness decay is relatively slowed down. exp(-δ×t) int The term reflects the mitigating effect of the time interval; the longer the interval, the more time the foundation has to recover, and the smaller the stiffness decay. The multiplication of each part yields ΔK. f It can accurately reflect the actual loss of foundation stiffness.

[0068] The technical effects of the above embodiments include: accurately calculating the cumulative attenuation of the dynamic stiffness of the building foundation, avoiding the underestimation problem of traditional fixed stiffness models, truly reflecting the building's resistance to disturbances, and providing precise safety constraints for the optimization of blasting parameters.

[0069] Traditional optimization of blasting and vibration reduction parameters lacks synergistic quantitative indicators, making it impossible to determine whether the parameter combination meets safety requirements. This can easily lead to improper parameter matching and disturbance control failure.

[0070] Based on this, the following formula is used to optimize the blasting hole spacing, the blasting row spacing, and the buffer layer thickness:

[0071] And U≤U0,

[0072] Wherein, U is the dimensionless blasting-damping synergistic control quantity, used to comprehensively evaluate the synergistic disturbance control effect of hole spacing, row spacing, and buffer layer thickness; a is the blasting hole spacing, in meters (m), a parameter to be optimized, ranging from 0.8 to 3.0 meters, affecting the superposition degree of blasting stress waves; b is the blasting row spacing, in meters (m), a parameter to be optimized, ranging from 0.8 to 3.0 meters, which, together with the hole spacing, determines the blasting energy distribution; h is the buffer layer thickness, in meters (m), a parameter to be optimized, ranging from 0.2 to 1.0 meters, used to weaken stress wave propagation; η is the porosity of the buffer layer material, dimensionless, measured through geotechnical tests, ranging from 0.1 to 0.3, reflecting the energy absorption capacity of the buffer layer; K is the stress wave propagation coefficient of rock mass heterogeneity, dimensionless; ΔK f ρ represents the dynamic stiffness attenuation of the building foundation, expressed in kilonewtons per meter (kN / m); ρ represents the density of the rock mass, expressed in kilograms per cubic meter (kg / m³). 3 The density is measured by a density meter, ranging from 2200 to 2800 kg / m³, reflecting the mass characteristics of the rock mass; v is the allowable vibration velocity, measured in centimeters per second (cm / s), set according to the building safety level, ranging from 0.15 to 0.3 cm / s, and is a key indicator of building safety; E_buf is the elastic modulus of the buffer layer, measured in megapascals (MPa), measured through material testing, ranging from 10 to 50 MPa, reflecting the stiffness characteristics of the buffer layer; k1 to k4 are dimensionless weighting coefficients, k1 = 0.3, k2 = 0.25, k3 = 0.35, k4 = 0.1, determined through a multi-objective optimization algorithm, used to balance the influence of various parameters; U0 is the safety control threshold, dimensionless, ranging from 0.6 to 0.8, calibrated through 100 trial calculations, and is the standard for judging the safety of parameters.

[0073] The formula calculation logic is as follows: the numerator k1×a+k2×b quantifies the comprehensive influence of the blasting hole spacing and row spacing, and the denominator k3×h+k4×η quantifies the comprehensive energy absorption effect of the buffer layer. The ratio of the two reflects the basic balance between blasting and vibration reduction. The relationship between rock mass propagation characteristics and foundation stiffness attenuation increases with the smaller K value. f The larger the value, the larger the index, indicating that the difficulty of controlling interference is reduced; The safety constraints are quantified by combining the rock mass density, allowable vibration velocity, and elastic modulus of the buffer layer; the product of the three is U, and it must be ensured that U≤U0, at which point the parameter combination meets the safety requirements.

[0074] The technical effects of the above embodiments include: providing a quantitative standard for the coordinated optimization of blasting and vibration reduction parameters, ensuring that the combination of hole spacing, row spacing and buffer layer thickness can effectively control blasting disturbance, protect the safety of neighboring buildings, and improve the accuracy of disturbance control.

[0075] Traditional blasting control systems are characterized by dispersed modules, unclear signal interactions between modules, and insufficient hardware and software coordination, making it impossible to achieve closed-loop control and resulting in low control efficiency and poor stability.

[0076] Based on this, please refer to Figure 2 and Figure 3 This embodiment provides a collaborative control system for the safety of adjacent buildings during waterway blasting based on intelligent sensing, including: an intelligent sensing module, a parameter calculation module, a control decision module, and a feedback correction module. The intelligent sensing module is electrically connected to the parameter calculation module, the parameter calculation module is electrically connected to the control decision module, the control decision module is electrically connected to the feedback correction module, and the feedback correction module is also electrically connected to the parameter calculation module. The intelligent sensing module is used to collect rock mass parameters, blasting parameters, and building foundation parameters. The parameter calculation module includes a processor and a memory. The processor executes the program stored in the memory to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation. The control decision module includes a PLC. Based on the calculation results output by the parameter calculation module, the PLC outputs control commands for blasting hole spacing, blasting row spacing, and buffer layer thickness. The feedback correction module includes a communication module and a cloud server. The communication module transmits actual vibration data to the cloud server. The cloud server compares the calculated data with the actual vibration data, corrects the calculated parameters, and feeds back the corrected parameters to the parameter calculation module.

[0077] It is worth mentioning that the intelligent sensing module, as the data acquisition end, incorporates various sensors to collect three types of core parameters. The collected data is transmitted to the parameter calculation module via electrical connection to ensure real-time data transmission. The core hardware of the parameter calculation module consists of a processor and a memory. The processor uses a chip with data processing capabilities, and the memory stores the calculation program and the collected data. When the processor executes the program, it calls the rock mass parameters, blasting parameters, and foundation parameters stored in the memory to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation, respectively. The calculation process requires calling the formulas in claims 5 and 6 to ensure that the calculation logic is consistent with the method claims. The control decision module uses a PLC (Programmable Logic Controller) with industrial control capabilities. It receives the coefficients and attenuation values ​​output by the parameter calculation module via electrical connection, optimizes the blasting hole spacing, row spacing, and buffer layer thickness, and outputs control commands to the execution equipment to achieve actual parameter adjustments. The feedback correction module consists of a communication module and a cloud server. The communication module is responsible for transmitting the actual vibration data after the blast to the cloud server, which stores historical calculated data and actual data. By comparing the calculated coordinated control quantity with the coordinated control quantity corresponding to the actual vibration data, the module analyzes the causes of deviations and corrects the calculation parameters, such as the correction coefficients α and β of the stress wave propagation coefficient and the attenuation coefficients γ and δ of the foundation stiffness attenuation. The corrected parameters are fed back to the memory of the parameter calculation module through the communication module to update the calculation model and form a closed loop.

[0078] Electrical connections between modules ensure stable signal transmission, while hardware-software collaboration is manifested in the processor executing programs to control hardware modules and the cloud server correcting parameters to guide subsequent calculations, achieving intelligent disturbance control of the entire system. The technical effect is to achieve orderly collaboration between system modules and deep integration of hardware and software, ensuring efficient operation of closed-loop control, improving the efficiency and stability of blasting disturbance control, and avoiding disturbance control failures caused by module dispersion or poor interaction.

[0079] Traditional intelligent sensing modules use a single type of sensor, which cannot collect different types of parameters in a targeted manner. This results in inaccurate and incomplete parameter collection, affecting the reliability of subsequent calculations and control.

[0080] Based on this, the intelligent sensing module includes a distributed optical fiber sensor, a piezoelectric pressure sensor, a displacement sensor, and a blasting counter; the distributed optical fiber sensor is used to collect the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient; the piezoelectric pressure sensor is used to collect the peak stress pressure; the displacement sensor is used to collect the deformation of the building foundation; the blasting counter is used to record the cumulative number of blasts and the interval between adjacent blasts; the output terminals of the distributed optical fiber sensor, the piezoelectric pressure sensor, the displacement sensor, and the blasting counter are all electrically connected to the input terminal of the parameter calculation module.

[0081] It is worth mentioning that the distributed fiber optic sensor in this embodiment adopts fiber optic sensing technology. Its arrangement involves embedding the sensor in boreholes along a 100-meter monitoring range within the rock mass, enabling distributed acquisition of rock mass parameters. By leveraging the stress-strain sensitivity of optical fibers, the rock mass integrity coefficient, porosity, and elastic modulus variation coefficient are derived. The advantage of this sensor is its ability to cover a large area and achieve high acquisition accuracy, avoiding the limitations of a single measuring point. Piezoelectric pressure sensors are deployed around the blasting zone, specifically for acquiring the peak pressure of the stress wave generated by the blast. Their working principle utilizes the piezoelectric effect of piezoelectric materials to convert pressure signals into electrical signals, enabling rapid response to the high-pressure changes at the moment of blasting and ensuring the capture of the peak intensity of the stress wave. Displacement sensors are installed at the four corners of the building foundation to acquire foundation deformation data. By monitoring the minute displacements of the foundation under blasting action, dynamic change data of the foundation is obtained. This data is crucial for calculating the damping ratio of the foundation material. The accuracy of the displacement sensors must meet the requirements of foundation deformation monitoring to ensure that the data reflects the true state of the foundation.

[0082] A blasting counter is installed on the blasting control equipment to record the cumulative number of blasts and the interval between adjacent blasts. By linking with the blasting trigger signal, it accurately records the time point and interval of each blast, avoiding errors from manual recording. The outputs of all sensors and counters are electrically connected to the input of the parameter calculation module, ensuring that parameters collected by each sensor can be directly transmitted to the calculation module without data loss or delay, guaranteeing that subsequent calculations are based on comprehensive and accurate raw data. The technical effect is to achieve targeted collection of parameters related to different types of blasting, eliminating the limitations of single-sensor collection, improving the accuracy and comprehensiveness of parameter collection, providing reliable raw data input to the parameter calculation module, and ensuring the accuracy of the calculation results.

[0083] Traditional feedback correction modules have too narrow a communication method, and parameter correction is not associated with specific calculation coefficients, resulting in poor correction effect and low system applicability, making them unable to adapt to different blasting scenarios.

[0084] Based on this, the communication module of the feedback correction module adopts wireless communication; the cloud server stores historical calculation data and actual vibration data; the cloud server corrects the correction coefficients α and β used for calculating the stress wave propagation coefficient and the attenuation coefficients γ and δ used for calculating the dynamic stiffness attenuation of the building foundation by comparing the calculated blasting-damping coordinated control quantity with the blasting-damping coordinated control quantity corresponding to the actual vibration data; the corrected parameters are transmitted to the memory of the parameter calculation module through the communication module; the processor of the parameter calculation module calls the updated parameters for the next calculation.

[0085] It is worth mentioning that the communication module in this embodiment adopts wireless communication, which differs from traditional wired communication. This allows it to adapt to the complex construction environment at the waterway blasting site, avoiding problems such as wiring difficulties or line damage. Simultaneously, wireless communication enables long-distance data transmission, ensuring that the cloud server can receive real-time vibration data from the site. The core function of the cloud server is to store and compare data. The stored historical calculation data includes the stress wave propagation coefficient, the dynamic stiffness attenuation of the building foundation, and the collaborative control parameters for each blast. The actual vibration data includes parameters such as the building vibration velocity monitored after the blast. By comparing the calculated collaborative control parameters with the corresponding collaborative control parameters of the actual vibration data, the source of calculation deviation can be accurately identified. The core of parameter correction is for key calculation coefficients, namely the correction coefficients α and β in the stress wave propagation coefficient and the attenuation coefficients γ and δ in the dynamic stiffness attenuation of the building foundation. These coefficients directly affect the accuracy of the calculation results. The correction logic is as follows: when the calculated collaborative control parameters deviate significantly from the actual values, it is analyzed whether the influence is due to the heterogeneity of the rock mass or the attenuation of the foundation, and then the corresponding coefficients are adjusted accordingly.

[0086] The corrected parameters are transmitted to the memory of the parameter calculation module via the wireless communication module, overwriting the original coefficient values. When performing the next calculation, the processor of the parameter calculation module calls the updated coefficients, ensuring that the calculation model can be optimized according to the actual situation, thus improving the accuracy of subsequent blasting control. This correction logic allows the system to continuously adapt to changes in site conditions, improving its disturbance control capabilities under different rock mass and building scenarios. The technical effect is to improve the environmental adaptability and parameter correction accuracy of the feedback correction module, ensure that the calculation model can be dynamically optimized, guarantee the accuracy of subsequent blasting control, and enhance the applicability and stability of the system in different waterway blasting scenarios.

[0087] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for collaborative safety control of neighboring structures during waterway blasting based on intelligent sensing, characterized in that, include: Before blasting operations, parameter acquisition and safety control threshold setting are carried out. Sensing units are deployed within a 100-meter range between the blasting operation area and adjacent buildings. Rock mass parameters, blasting parameters and building foundation parameters are collected through the sensing units. The stress wave propagation coefficient is calculated based on the collected rock mass parameters, and the stress wave propagation error is corrected using the stress wave propagation coefficient. The dynamic stiffness attenuation of the building foundation is calculated based on the collected blasting parameters and building foundation parameters, and the building's disturbance resistance is updated based on the dynamic stiffness attenuation of the building foundation. By combining the stress wave propagation coefficient with the dynamic stiffness attenuation of the building foundation, the blasting hole spacing, blasting row spacing, and buffer layer thickness are optimized. After blasting operations are carried out, actual vibration data are collected. The calculated values ​​of the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation are compared with the actual vibration data to correct the parameter library and form a closed-loop control.

2. The method for collaborative safety control of neighboring structures during waterway blasting based on intelligent perception as described in claim 1, characterized in that, The sensing unit includes a distributed sensing device. The rock mass parameters collected by the distributed sensing device include the rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient. The blasting parameters collected include the peak stress wave pressure, cumulative number of blasts, and interval between adjacent blasts. The building foundation parameters collected include the foundation material damping ratio and the foundation deformation used to calculate the foundation material damping ratio. The distributed sensing device synchronously transmits all collected parameters to the calculation unit, which is used to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation.

3. The method for collaborative safety control of neighboring buildings during waterway blasting based on intelligent perception as described in claim 1, characterized in that, In the process of calculating the stress wave propagation coefficient, multiple sets of rock mass parameters are used for iterative calculation. In each iteration, the correction coefficient used to calculate the stress wave propagation coefficient is adjusted based on the stress wave propagation coefficient obtained in the previous calculation until the difference between the stress wave propagation coefficients obtained in two adjacent calculations is less than a preset threshold. Then, the iteration stops and the final stress wave propagation coefficient is output.

4. The method for collaborative safety control of neighboring buildings during waterway blasting based on intelligent perception according to claim 1, characterized in that, In optimizing the blasting hole spacing, blasting row spacing, and buffer layer thickness, the blasting-damping coordinated control quantity is first calculated. If the blasting-damping coordinated control quantity exceeds the safety control threshold, the blasting hole spacing and blasting row spacing are first reduced, and then the buffer layer thickness is increased. The blasting-damping coordinated control quantity is repeatedly calculated until it is lower than the safety control threshold. The blasting hole spacing, blasting row spacing, and buffer layer thickness at this point are then output.

5. The method for collaborative safety control of neighboring buildings during waterway blasting based on intelligent perception according to claim 1, characterized in that, The stress wave propagation coefficient is calculated using the following formula: Where K is the stress wave propagation coefficient of the heterogeneous rock mass, K V The rock mass integrity coefficient. C represents the porosity of the rock mass. E denoted as the coefficient of variation of elastic modulus, f is the dominant frequency of the blasting stress wave, f0 is the natural frequency of the rock mass, α is the correction coefficient for rock mass porosity, and β is the correction coefficient for the coefficient of variation of elastic modulus.

6. The method for collaborative safety control of neighboring structures during waterway blasting based on intelligent perception according to claim 1, characterized in that, The following formula is used to calculate the dynamic stiffness attenuation of the building foundation: DK f =K×P max ×N γ ×(1-ζ)×exp(-δ×t int ); Where ΔK f P represents the dynamic stiffness attenuation of the building foundation, K is the stress wave propagation coefficient of the heterogeneous rock mass, and P is the dynamic stiffness attenuation of the building foundation. max ζ is the peak stress wave pressure, N is the cumulative number of explosions, ζ is the damping ratio of the base material, and t is the peak stress wave pressure. int γ is the interval between adjacent blasts, δ is the attenuation coefficient of the number of blasts, and δ is the attenuation coefficient of the interval time.

7. The method for collaborative safety control of neighboring buildings during waterway blasting based on intelligent perception according to claim 1, characterized in that, The following formula is used to optimize the blasting hole spacing, the blasting row spacing, and the buffer layer thickness: And U≤U0, Where: U is the blasting-damping coordinated control quantity, a is the blasting hole spacing, b is the blasting row spacing, h is the buffer layer thickness, η is the porosity of the buffer layer material, K is the stress wave propagation coefficient of the heterogeneous rock mass, and ΔK f The dynamic stiffness attenuation of the building foundation is given by ρ, the density of the rock mass is given by v, and the allowable vibration velocity is given by E. buf denoted as the elastic modulus of the buffer layer, k1 to k4 are weighting coefficients, and U0 is the safety control threshold.

8. A smart sensing-based collaborative control system for the safety of neighboring buildings during waterway blasting, applied to the smart sensing-based collaborative control method for the safety of neighboring buildings during waterway blasting as described in any one of claims 1-7, characterized in that, The system includes an intelligent sensing module, a parameter calculation module, a control decision module, and a feedback correction module. The intelligent sensing module is electrically connected to the parameter calculation module, which in turn is electrically connected to the control decision module, which is also electrically connected to the feedback correction module. The intelligent sensing module collects rock mass parameters, blasting parameters, and building foundation parameters. The parameter calculation module includes a processor and a memory. The processor executes programs stored in the memory to calculate the stress wave propagation coefficient and the dynamic stiffness attenuation of the building foundation. The control decision module includes a PLC, which outputs control commands for blasting hole spacing, blasting row spacing, and buffer layer thickness based on the calculation results output by the parameter calculation module. The feedback correction module includes a communication module and a cloud server. The communication module transmits actual vibration data to the cloud server, which compares the calculated data with the actual vibration data, corrects the calculated parameters, and feeds the corrected parameters back to the parameter calculation module.

9. The intelligent sensing-based collaborative control system for the safety of neighboring buildings during waterway blasting, as described in claim 8, is characterized in that... The intelligent sensing module includes a distributed optical fiber sensor, a piezoelectric pressure sensor, a displacement sensor, and a blasting counter. The distributed optical fiber sensor is used to collect rock mass integrity coefficient, rock mass porosity, and elastic modulus variation coefficient. The piezoelectric pressure sensor is used to collect stress wave peak pressure. The displacement sensor is used to collect building foundation deformation. The blasting counter is used to record the cumulative number of blasts and the interval between adjacent blasts. The output terminals of the distributed optical fiber sensor, the piezoelectric pressure sensor, the displacement sensor, and the blasting counter are all electrically connected to the input terminal of the parameter calculation module.

10. The intelligent sensing-based collaborative control system for the safety of neighboring buildings during waterway blasting, as described in claim 8, is characterized in that... The communication module of the feedback correction module adopts wireless communication, and the cloud server stores historical calculation data and actual vibration data. The cloud server corrects the correction coefficients α and β used for calculating the stress wave propagation coefficient and the attenuation coefficients γ and δ used for calculating the dynamic stiffness attenuation of the building foundation by comparing the calculated blasting-shock reduction coordinated control quantity with the blasting-shock reduction coordinated control quantity corresponding to the actual vibration data. The corrected parameters are transmitted to the memory of the parameter calculation module through the communication module, and the processor of the parameter calculation module calls the updated parameters for the next calculation.

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