Construction area vibration zoning control method based on multi-sound source identification

Abstract

This invention discloses a construction area vibration zoning control method based on multi-source sound identification, relating to the field of engineering construction control. The method includes: acquiring the coordinate positions of the target construction area and the railway track, and determining the upper limit of vibration intensity in the target construction area; determining the target set of construction equipment, and based on the construction movement line, determining the fixed positions of the foundation construction equipment set within the target construction area to form a foundation equipment layout scheme, and generating a foundation construction vibration distribution through multi-source sound identification analysis; performing vibration zoning on the foundation construction vibration distribution, and based on the vibration zoning results and the upper limit of vibration intensity, optimizing the equipment layout of the movable construction equipment set based on the foundation equipment layout scheme to generate a target equipment layout scheme. This solves the technical problem in existing technologies where regional vibration load imbalance prevents the optimal allocation of vibration energy in the construction area, leading to both low construction efficiency and potential safety risks.

Description

Technical Field

[0001] This invention relates to the field of engineering construction control, and specifically to a method for vibration zoning control of construction areas based on multi-sound source identification. Background Technology

[0002] The periodic operation of railway tracks has created a pre-existing dynamic stress state in the surrounding soil. When construction work is carried out against this background, if the construction vibration is unevenly distributed in space, it is easy to cause adverse superposition and stress concentration with the existing vibration in local areas, thereby aggravating the attenuation of the foundation bearing capacity, inducing damage to adjacent structures, and even threatening the safety of train operation.

[0003] The current construction equipment layout is often configured based on the convenience of construction without fully considering the rational distribution of vibration in space. This leads to local over-limit risks and incomplete utilization of the overall vibration capacity, resulting in an imbalance of regional vibration load and an inability to achieve optimal allocation of vibration energy in the construction area. Consequently, it results in technical problems such as low construction efficiency and potential safety risks. Summary of the Invention

[0004] This application provides a construction area vibration zoning control method based on multi-sound source identification, which addresses the technical problem in the prior art where regional vibration load imbalance makes it impossible to achieve optimal allocation of vibration energy in the construction area, resulting in both low construction efficiency and potential safety risks.

[0005] In view of the above problems, this application provides a method for vibration zoning control in construction areas based on multi-sound source identification, the method comprising: Obtain the coordinates of the target construction area and the train track, and determine the upper limit of vibration intensity in the target construction area; The target construction equipment set is determined, which includes a foundation construction equipment set and a movable construction equipment set. The fixed positions of the foundation construction equipment set are determined within the target construction area according to the construction movement line, forming a foundation equipment layout scheme. The foundation construction vibration distribution is generated through multi-sound source identification and analysis. The vibration distribution of the foundation construction is divided into vibration zones, and based on the vibration zone results and the upper limit of vibration intensity, the equipment layout of the movable construction equipment set is optimized on the basis of the foundation equipment layout scheme to generate a target equipment layout scheme.

[0006] Optionally, the upper limit of vibration intensity in the target construction area is determined, including: Obtain the coordinates of the target construction area and the train track, and determine the area coordinate range and track coordinate lines; Calculate the distance from each coordinate point within the specified area to the orbital coordinate line to obtain the shortest coordinate distance; The upper limit of vibration intensity in the target construction area is determined based on the shortest coordinate distance, wherein the upper limit of vibration intensity is positively correlated with the shortest coordinate distance.

[0007] Optionally, based on the construction movement line, the fixed positions of the foundation construction equipment set are determined within the target construction area to form a foundation equipment layout scheme, and the foundation construction vibration distribution is generated through multi-source sound identification and analysis, including: Based on the construction flow, determine the construction process and work path; The sequence of procedures for each foundation construction equipment in the foundation construction equipment center is determined according to the construction process described above. Based on the aforementioned sequence of procedures, fixed work positions are assigned to each basic construction equipment within the target construction area; Based on the fixed operating positions of each basic construction equipment, a basic equipment layout plan is formed; The vibration characteristics of each foundation construction equipment are determined by multi-source sound identification and analysis, and the foundation construction vibration distribution is generated.

[0008] Optionally, the vibration characteristics of each foundation construction equipment are determined through multi-source sound identification and analysis, generating the foundation construction vibration distribution, including: Obtain the equipment model of each basic construction equipment, and the equipment location of each basic construction equipment within the target construction area; Based on the location of each basic construction equipment, the geological information of the location of each basic construction equipment is obtained; Historical construction monitoring data is acquired, multi-source sound identification and analysis is performed on the historical construction monitoring data, and a vibration characteristic predictor is constructed based on the analysis results; The equipment model and geological information of each foundation construction equipment are input into the vibration characteristic predictor to obtain the vibration influence range and vibration intensity distribution of each foundation construction equipment, which are used as the vibration characteristics of each foundation construction equipment. Based on the vibration characteristics and location of each foundation construction equipment, the foundation construction vibration distribution is generated.

[0009] Optionally, multi-source sound identification analysis is performed on the historical construction monitoring data, and a vibration characteristic predictor is constructed based on the analysis results, including: The historical construction monitoring data includes historical construction sound data and historical construction vibration data; The historical construction sound data is subjected to sound source separation, the mixed sound signal is separated into the sound source signals of each independent device, the sound source separation results are obtained, and the device model corresponding to each sound source is identified to construct a sample device model set; Obtain geological information on the operation of various equipment during historical construction, and construct a sample geological information set; Based on the sound source separation results, the vibration impact range generated by each piece of equipment when operating individually is separated from historical construction vibration data, and a sample vibration impact range set is constructed. Based on the sound source separation results, the vibration intensity distribution generated by each piece of equipment when operating individually is separated from historical construction vibration data, and a sample vibration intensity distribution set is constructed. Using the sample equipment model set and sample geological information set as input, and the sample vibration influence range set as output, the vibration influence range prediction branch is trained. Using the sample equipment model set and sample geological information set as input, and the sample vibration intensity distribution set as output, the vibration intensity distribution prediction branch is trained. By combining the vibration influence range prediction branch and the vibration intensity distribution prediction branch, a vibration characteristic predictor is constructed.

[0010] Optionally, the vibration distribution of the foundation construction is divided into vibration zones, and based on the vibration zoning results and the upper limit of vibration intensity, the equipment layout of the movable construction equipment set is optimized on the basis of the foundation equipment layout scheme to generate a target equipment layout scheme, including: Set a preset difference value, and set the areas in the foundation construction vibration distribution where the difference from the upper limit of vibration intensity is less than the preset difference value as forbidden areas, and set other areas as arrangeable areas to complete the vibration zoning; Randomly distribute the set of movable construction equipment within the deployable area to generate the first equipment layout scheme; Calculate the fitness of the first scheme of the first equipment layout scheme; The first equipment layout scheme is optimized and iterated, and the corresponding scheme fitness is calculated in the same way as the first scheme fitness of the first equipment layout scheme, to obtain the equipment layout scheme set; The equipment layout scheme with the highest adaptability is selected as the target equipment layout scheme.

[0011] Optionally, calculating the fitness of the first scheme of the first device layout scheme includes: Obtain the equipment model and geological information of each movable construction equipment in the first equipment layout scheme; Activate the vibration characteristic predictor, input the equipment model and geological information of each movable construction equipment into the vibration characteristic predictor, and obtain the vibration influence range and vibration intensity distribution of each movable construction equipment, which are used as the vibration characteristics of each movable construction equipment; By combining the vibration distribution of the foundation construction and the vibration characteristics of each movable construction equipment, the first construction vibration distribution corresponding to the first equipment layout scheme is generated; The adaptability of the first scheme is obtained based on the first construction vibration distribution.

[0012] Optionally, the fitness of the first scheme is obtained based on the first construction vibration distribution, including: The percentage of areas in the first construction vibration distribution that did not exceed the upper limit of vibration intensity was used to obtain the first vibration compliance rate. Calculate the vibration intensity uniformity of the first construction vibration distribution to obtain the first vibration uniformity. The first vibration compliance degree and the first vibration balance degree are weighted and calculated to obtain the first scheme fitness degree.

[0013] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application first determines the upper limit of vibration intensity in the target construction area by acquiring the coordinates of the target construction area and the railway track, thus scientifically quantifying vibration control standards and accurately matching safety constraints with geographical risk levels. Second, by identifying the target set of construction equipment and generating the foundation construction vibration distribution through multi-source identification and analysis, it achieves accurate prediction of the inherent vibrations at the construction site, obtaining an analyzable dynamic data field. This provides unprecedented predictive data support for subsequent refined control, enabling proactive prediction of vibration control. Finally, vibration zoning is performed based on the foundation construction vibration distribution to generate a target equipment layout scheme, achieving intelligent optimization of the decision-making scheme. Dynamic zoning and compliance control ensure that global vibration does not exceed standards and avoids localized risk concentration. Simultaneously, vibration equalization supports more equipment operating efficiently concurrently or higher-intensity construction activities, ultimately outputting a target equipment layout scheme that optimally balances safety and efficiency, achieving refined, collaborative, and intelligent management of construction vibration control. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart illustrating the construction area vibration zoning control method based on multi-sound source identification proposed in this application. Figure 2 This is a flowchart illustrating the process of generating a target equipment layout scheme in the construction area vibration zoning control method based on multi-sound source identification in this application. Detailed Implementation

[0016] This application provides a construction area vibration zoning control method based on multi-sound source identification, which solves the technical problem in the prior art where regional vibration load imbalance makes it impossible to achieve optimal allocation of vibration energy in the construction area, resulting in both low construction efficiency and potential safety risks.

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0019] The present invention will now be described in detail with reference to the accompanying drawings.

[0020] In the embodiments, such as Figure 1 As shown, this application provides a method for vibration zoning control in construction areas based on multi-sound source identification, the method comprising: S10: Obtain the coordinates of the target construction area and the train track, and determine the upper limit of vibration intensity in the target construction area; In this embodiment of the application, the target construction area refers to the physical space range where construction work is planned; the coordinate position refers to the spatial point data sequence that precisely defines the boundary of the construction area and the track line, obtained using a global positioning system or a coordinate system based on construction drawings; the upper limit of vibration intensity refers to the maximum amount of vibration allowed in the construction area to protect the safety of the track structure or ensure the smooth operation of the train.

[0021] Specifically, the geometric information of the construction area and train track is digitized through data acquisition, and then the upper limit of vibration intensity is determined based on spatial information. By calculating the shortest distance from each point within the construction area to the track and mapping it to the corresponding allowable vibration value, the distribution of distance-related vibration constraint upper limits covering the entire area can be determined.

[0022] Step S10 in the method provided in this application embodiment includes: Obtain the coordinates of the target construction area and the train track, and determine the area coordinate range and track coordinate lines; Calculate the distance from each coordinate point within the specified area to the orbital coordinate line to obtain the shortest coordinate distance; The upper limit of vibration intensity in the target construction area is determined based on the shortest coordinate distance, wherein the upper limit of vibration intensity is positively correlated with the shortest coordinate distance.

[0023] In this embodiment, the coordinate positions of the target construction area and the train track are first obtained, and the area coordinate range and track coordinate line are determined. Here, coordinate position refers to point data used to determine the geometric shape of a spatial entity under a specific measurement or design coordinate system; area coordinate range refers to the set of all coordinate points in the coordinate space of the target construction area that satisfy specific inequality constraints; track coordinate line refers to a broken line or a fitted curve formed by connecting ordered coordinate points.

[0024] Specifically, engineering surveying is first conducted using measuring equipment to obtain the coordinates of the target construction area and the train track. The coordinate range of the area is determined by constructing a polygonal region, and the coordinates of the two control points of the centerline of the relevant track are obtained. The straight line segment is then determined as the track coordinate line.

[0025] For example, in an expansion project, the surveying team used RTK-GPS equipment to collect the coordinates of the four corner points of the construction area boundary: A(0,0), B(200,0), C(200,150), D(0,150) (unit: meters). A closed rectangular polygon was constructed, and all (x,y) points covered by the polygon satisfied 0≤x≤200 and 0≤y≤150, thus obtaining the coordinate range of the area. Simultaneously, the coordinates of the two control points of the relevant track centerline were obtained: P1(x1,y1) and P2(x2,y2). The equation of the straight line y is the track coordinate line.

[0026] Secondly, calculate the distance from each coordinate point within the region to the track coordinate line to obtain the shortest coordinate distance. The shortest coordinate distance refers to the minimum calculated distance to the track coordinate line among all coordinate points within the region.

[0027] Specifically, calculate the distance from the point to the infinite line containing the line segment, and then determine whether the foot of the perpendicular falls within the line segment P1 and P2. If so, the distance is the distance from the point to the line segment; otherwise, take the smaller value of the distance from the point to the two endpoints of the line segment to obtain the shortest coordinate distance.

[0028] Ultimately, the upper limit of vibration intensity in the target construction area is determined based on the shortest coordinate distance, where the upper limit of vibration intensity is positively correlated with the shortest coordinate distance. Positive correlation means that the upper limit of vibration intensity increases as the shortest coordinate distance increases and decreases as the shortest coordinate distance decreases.

[0029] Specifically, when vibration waves propagate in soil and rock media, their energy attenuates with distance due to geometric diffusion and internal friction within the material. Therefore, the farther the vibration source is from the protected target, the higher the permissible initial vibration intensity can be; conversely, strict control is required. Based on the calculated shortest coordinate distance, the distance-permissible vibration mapping relationship in a preset mapping table is applied to determine the upper limit of vibration intensity in the target construction area.

[0030] For example, a preset mapping table might specify: for a minimum coordinate distance of 0-10 meters, the upper limit of vibration intensity is 1.5 mm / s; for a minimum coordinate distance of 10-30 meters, the upper limit of vibration intensity is 2.5 mm / s; and for a minimum coordinate distance of more than 30 meters, the upper limit of vibration intensity is 4.0 mm / s. If the calculated minimum coordinate distance is 25 meters, querying the preset mapping table will show an upper limit of vibration intensity of 2.5 mm / s.

[0031] In this embodiment, by accurately calculating the shortest coordinate distance between the construction area and the sensitive track and mapping the corresponding upper limit of vibration intensity, the safety constraints and spatial risk levels are strictly correlated, providing a data foundation for subsequent improvements in refined control and enhancing the applicability of the solution.

[0032] S20: Determine the target construction equipment set, which includes a foundation construction equipment set and a movable construction equipment set. Determine the fixed position of the foundation construction equipment set within the target construction area according to the construction movement line, form a foundation equipment layout scheme, and generate the foundation construction vibration distribution through multi-sound source identification and analysis. In this embodiment of the application, the target construction equipment set refers to the collection of all construction machinery that will generate significant vibration; the foundation construction equipment set and the movable construction equipment set are classifications of the target equipment set; the foundation construction equipment set refers to equipment whose working position is strictly determined by the core construction process, fixed facilities, or the engineering structure itself; the movable construction equipment set refers to equipment that can be freely moved or redeployed within a certain range while meeting the working function; the construction flow line refers to the process flow diagram or work path determined according to the construction organization design and carried out in sequence.

[0033] The basic equipment layout scheme refers to the layout diagram formed by the set of fixed, unchangeable coordinates of all basic construction equipment according to the construction flow line; the basic construction vibration distribution refers to the spatial distribution diagram of the expected vibration intensity in the entire target construction area when only the basic construction equipment sets are operating simultaneously in their fixed positions; multi-source sound identification analysis is a technology based on acoustic signal processing that separates and identifies the acoustic features of different individual equipment from the mixed construction site sounds, and then combines them with historical data models to predict the vibration characteristics of the equipment.

[0034] Specifically, the fixed locations of the foundation construction equipment set are identified from all the equipment. The fixed locations of all equipment are then compiled to form a foundation equipment layout plan. Subsequently, the vibrations generated by the fixed equipment, i.e., the foundation construction vibration distribution, are predicted. Multi-source sound identification and analysis technology is used to analyze historical construction records of equipment sounds and actual vibration data, which are then used as training data for a vibration characteristic predictor.

[0035] Step S20 in the method provided in this application embodiment includes: Based on the construction flow, determine the construction process and work path; The sequence of procedures for each foundation construction equipment in the foundation construction equipment center is determined according to the construction process described above. Based on the aforementioned sequence of procedures, fixed work positions are assigned to each basic construction equipment within the target construction area; Based on the fixed operating positions of each basic construction equipment, a basic equipment layout plan is formed; The vibration characteristics of each foundation construction equipment are determined by multi-source sound identification and analysis, and the foundation construction vibration distribution is generated.

[0036] In this embodiment, the construction process and work path are first determined based on the construction movement line. The work path is a spatial description of the typical movement trajectory or main work area of ​​the main construction equipment related to key procedures in the construction process on the construction site.

[0037] Specifically, the planning personnel first input or retrieve the project's construction flow line, then analyze the construction flow line, breaking it down into an irreversible and continuous construction process. At the same time, combined with the site layout plan of the construction area, the operation paths traversed or occupied by the large equipment group in each stage of the process are identified.

[0038] For example, if a construction route is to proceed from A to B in layers, the construction process may be: pile foundation construction in area A → earthwork excavation in area A → pile foundation construction in area B → earthwork excavation in area B... At the same time, the corresponding excavator operation path may be an area that starts from the boundary of A and gradually moves towards B.

[0039] Secondly, the sequence of operations for each piece of foundation construction equipment in the foundation construction equipment cluster is determined according to the construction process. The sequence of operations refers to the relative time order in which each piece of equipment is assigned to perform its specific tasks within the construction process.

[0040] Specifically, the equipment constituting the layout is selected from all construction equipment, and time labels are determined. Each process in the construction flow is traversed to determine whether the operation position of the process is determined. Then, all equipment determined to have fixed positions is included in the basic construction equipment set, and the order in which they appear in the process is the process sequence, providing a basis for potential time-domain vibration superposition analysis.

[0041] Secondly, based on the sequence of procedures, fixed working positions are assigned to each foundation construction equipment within the target construction area. These fixed working positions refer to the center point or characteristic point location of the foundation construction equipment during its core operations, within the coordinate system of the target construction area.

[0042] Specifically, the system accesses the set of basic construction equipment related to each process and their process sequence. The process sequence is queried, and then, based on the sequence, a precise coordinate design is bound to each piece of basic construction equipment. These coordinates are assigned to the corresponding equipment as fixed work positions, and the system is then guided to process the equipment list sequentially, ensuring that the position assignments match the construction stages.

[0043] For example, based on the fact that pile drivers P1 and P2 belong to process 1, the system extracts their coordinates from a certain pile location design drawing. The fixed working position assigned to pile driver P1 is coordinates (50, 50), and the fixed working position assigned to pile driver P2 is coordinates (150, 100), and the two foundation equipment are completely anchored in space.

[0044] Simultaneously, a foundation equipment layout plan is formulated based on the fixed operating locations of each foundation construction device. Specifically, information such as the allocation of fixed operating locations is summarized using tables or specific graphic formats to ensure that the equipment is located at coordinate points, forming a foundation equipment layout plan used to predict the vibration field generated by these fixed devices.

[0045] Finally, the vibration characteristics of each foundation construction equipment were determined through multi-source sound identification and analysis, generating the foundation construction vibration distribution. Among them, vibration characteristics refer to the core parameters of the vibration impact when a single construction equipment acts as a vibration source, which usually includes the vibration impact range and vibration intensity distribution.

[0046] Specifically, the process involves acquiring the geological information of the equipment model and its location. Then, vibration characteristics are determined through multi-source sound identification and analysis. This information is input into a pre-trained vibration characteristic predictor. The predictor performs predictive analysis, outputting the individual vibration influence range and vibration intensity distribution model for each piece of equipment. This process is repeated for all foundation equipment. Finally, the predicted vibration intensity distribution for each piece of equipment is superimposed onto the same global grid, with its fixed operating location as the origin. For each point in the grid, the vibration intensities generated by all foundation equipment are superimposed, ultimately resulting in a contour map or numerical matrix of foundation construction vibration distribution covering the entire construction area.

[0047] In step S20 of the method provided in this application embodiment, the vibration characteristics of each foundation construction equipment are determined through multi-source sound identification and analysis, and the foundation construction vibration distribution is generated, including: Obtain the equipment model of each basic construction equipment, and the equipment location of each basic construction equipment within the target construction area; Based on the location of each basic construction equipment, the geological information of the location of each basic construction equipment is obtained; Historical construction monitoring data is acquired, multi-source sound identification and analysis is performed on the historical construction monitoring data, and a vibration characteristic predictor is constructed based on the analysis results; The equipment model and geological information of each foundation construction equipment are input into the vibration characteristic predictor to obtain the vibration influence range and vibration intensity distribution of each foundation construction equipment, which are used as the vibration characteristics of each foundation construction equipment. Based on the vibration characteristics and location of each foundation construction equipment, the foundation construction vibration distribution is generated.

[0048] In this embodiment of the application, the equipment model of each basic construction equipment and the equipment location of each basic construction equipment in the target construction area are first obtained. The equipment model refers to the specific model identifier of the construction machinery, which is the primary input feature for predicting its vibration characteristics.

[0049] Specifically, the system accesses the basic equipment layout plan to obtain the coordinates of each recorded piece of basic construction equipment. Simultaneously, it queries or links to the equipment management database to obtain the precise model number of each piece of equipment, ensuring that each spatial point is associated with a specific vibration source type.

[0050] Secondly, based on the location of each foundation construction device, the geological information of that location is obtained. Specifically, using the coordinates of each foundation construction device's location as the query point, the equipment management database is accessed to obtain the coordinates of the device's location, which may include attributes describing the local foundation conditions, such as the soil type of the bearing layer and the average shear wave velocity, i.e., geological information.

[0051] For example, based on the location (50,50) of device P1, querying the project's geological digital model reveals a geological borehole near coordinate point (50,50) of P1. The borehole's depth of 0-15 meters is composed of plastic silty clay with an average shear wave velocity of 180 m / s. The resulting geological information for the location of P1 is: {Main soil layer: silty clay; State: plastic; Reference shear wave velocity: 180 m / s}.

[0052] Next, historical construction monitoring data is acquired, and multi-source sound identification analysis is performed on this data. Based on the analysis results, a vibration characteristic predictor is constructed. Historical construction monitoring data refers to historical construction sound and vibration data collected and stored synchronously in various previous construction projects. Multi-source sound identification analysis involves separating and identifying the acoustic signatures of individual devices from mixed on-site recordings. The separated sound source signals are then correlated with the synchronously recorded vibration data to extract the vibration characteristics of each device type under different geological conditions.

[0053] Simultaneously, the equipment model and geological information of each foundation construction device are input into the vibration characteristic predictor to obtain the vibration influence range and vibration intensity distribution of each foundation construction device, which are then used as the vibration characteristics of each device. Specifically, the equipment model and geological information of the foundation construction devices are input into the vibration characteristic predictor. Subsequently, based on the predictor's output, and according to the predicted vibration influence range and vibration intensity distribution of each foundation construction device under the current specific geological conditions, the vibration characteristics of each foundation construction device are output.

[0054] Finally, based on the vibration characteristics and locations of each foundation construction device, a foundation construction vibration distribution is generated. Specifically, the target construction area is discretized into a fine grid, and the distance to each foundation device is calculated for each point Q in the grid. Then, according to the vibration intensity distribution model of the device, the vibration intensity value generated by the device at point Q is calculated. Next, the intensity values ​​generated by all foundation devices at this coordinate point are superimposed. The superposition method needs to be determined according to vibration theory, and the superposition method is different for vibrations of different frequencies and phases. Subsequently, all grid points are traversed, and a two-dimensional array is finally obtained, which is the foundation construction vibration distribution, where each element represents the total predicted vibration intensity at that grid point.

[0055] In step S20 of the method provided in this application embodiment, multi-source sound identification analysis is performed on the historical construction monitoring data, and a vibration characteristic predictor is constructed based on the analysis results, including: The historical construction monitoring data includes historical construction sound data and historical construction vibration data; The historical construction sound data is subjected to sound source separation, the mixed sound signal is separated into the sound source signals of each independent device, the sound source separation results are obtained, and the device model corresponding to each sound source is identified to construct a sample device model set; Obtain geological information on the operation of various equipment during historical construction, and construct a sample geological information set; Based on the sound source separation results, the vibration impact range generated by each piece of equipment when operating individually is separated from historical construction vibration data, and a sample vibration impact range set is constructed. Based on the sound source separation results, the vibration intensity distribution generated by each piece of equipment when operating individually is separated from historical construction vibration data, and a sample vibration intensity distribution set is constructed. Using the sample equipment model set and sample geological information set as input, and the sample vibration influence range set as output, the vibration influence range prediction branch is trained. Using the sample equipment model set and sample geological information set as input, and the sample vibration intensity distribution set as output, the vibration intensity distribution prediction branch is trained. By combining the vibration influence range prediction branch and the vibration intensity distribution prediction branch, a vibration characteristic predictor is constructed.

[0056] In this embodiment, historical construction monitoring data includes historical construction sound data and historical construction vibration data. Specifically, historical construction monitoring data refers to the raw dataset systematically collected from multiple completed construction projects; historical construction sound data refers to time-series data containing composite sound signals generated by multiple devices operating simultaneously, collected using an acoustic sensor array deployed at the historical construction site; and historical construction vibration data refers to ground vibration signals recorded by a vibration sensor network at the historical construction site and surrounding area, collected synchronously with the sound data.

[0057] First, sound source separation is performed on historical construction sound data to separate the mixed sound signal into sound source signals from individual devices, obtaining the sound source separation results. The corresponding device models for each sound source are then identified, constructing a sample device model set. Simultaneously, geological information from the operation of each device during historical construction is acquired, constructing a sample geological information set. Sound source separation refers to the process of estimating the original individual sound source signals using algorithms based solely on the mixed signals received from multiple observation points, without prior information about the source signals.

[0058] Specifically, a microphone array is used to collect sound sources. Based on spatial information, the complex sound field is decoupled, outputting sound source separation results from several relatively clean, independent devices. Then, each separated sound source signal is identified, and by comparing it with a voiceprint feature database, the specific device model is labeled. Anonymous mixed recordings are then converted into several audio segments with clearly identified IDs. Finally, the identified model tags are collected to form a sample device model set. Simultaneously, the geographical location of each device's operation is determined based on its active periods in historical data. Then, based on the geographical location of the equipment's operation, historical geological survey data is queried to extract geological information. Finally, the geological information entries are constructed into a sample geological information set according to their correspondence with the device model.

[0059] Secondly, based on the sound source separation results, the vibration impact range generated by each piece of equipment operating individually was separated from the historical construction vibration data, and a sample vibration impact range set was constructed. Simultaneously, based on the sound source separation results, the vibration intensity distribution generated by each piece of equipment operating individually was separated from the historical construction vibration data, and a sample vibration intensity distribution set was constructed.

[0060] Specifically, a time window is used to extract the sound source signal from a certain device. Within this time window, the vibration intensity recorded by all vibration sensors is analyzed. A spatial contour map of the vibration intensity is plotted using spatial interpolation, a vibration intensity threshold is defined, and the area covered by sensors with vibration intensities exceeding the threshold is defined as the vibration influence range of the device operation. This process is repeated for all isolated devices. Finally, a sample vibration influence range set is obtained. Similarly, based on the active time period of the device provided by sound source separation, the readings of each vibration sensor are analyzed within this time period. Using the estimated device location as the center, the distance from each sensor to the center is calculated, and the average vibration intensity of the sensor during this time period is read, obtaining data points for all devices. Curve fitting is then performed on these data points to obtain the near-field intensity coefficient and attenuation coefficient, describing the vibration attenuation characteristics of the device during operation. A specific vibration intensity distribution model is defined based on these two parameters. The fitting is repeated for all devices, and finally, a sample vibration intensity distribution set is obtained.

[0061] Next, using the sample equipment model set and sample geological information set as inputs, and the sample vibration influence range set as outputs, a vibration influence range prediction branch is trained. Simultaneously, using the sample equipment model set and sample geological information set as inputs, and the sample vibration intensity distribution set as outputs, a vibration intensity distribution prediction branch is trained.

[0062] Specifically, the sample equipment model set and sample geological information set are processed for feature data and merged as input features of the model. The sample vibration influence range set is used as the prediction target of the model. The vibration influence range prediction branch is trained to learn the dynamic characteristics of the equipment model and the waveguide characteristics of the geological medium, and to estimate the spatial influence of vibration energy. Simultaneously, the sample equipment model set and sample geological information set are processed for data and merged as input features of the model. Using the same sample library, the vibration intensity distribution prediction branch is trained to learn the vibration energy attenuation law with distance.

[0063] Finally, the vibration influence range prediction branch and the vibration intensity distribution prediction branch are combined to construct a vibration characteristic predictor. Specifically, the two prediction branches are combined after training and encapsulated into a unified vibration characteristic predictor.

[0064] For example, the steps to construct a vibration characteristic predictor based on a BP neural network are as follows: Model Construction: The vibration characteristic predictor includes a vibration influence range prediction branch and a vibration intensity distribution prediction branch. Each branch consists of an input layer, a hidden layer, and an output layer. The input layer of the vibration influence range prediction branch receives a set of sample equipment models and a set of sample geological information. The hidden layer performs a nonlinear transformation on the sample equipment model set and the sample geological information set using an activation function. The output layer then performs a weighted summation using weights and biases, and obtains the output sample vibration influence range set through an activation function. Similarly, the input layer of the vibration intensity distribution prediction branch receives a set of sample equipment models and a set of sample geological information. The hidden layer performs a nonlinear transformation on the sample equipment model set and the sample geological information set using an activation function. The output layer then performs a weighted summation using weights and biases, and obtains the output sample vibration intensity distribution set through an activation function.

[0065] Model Training: The sample dataset was divided into a 7:2:1 ratio, and both the vibration impact range prediction branch and the vibration intensity distribution prediction branch were trained simultaneously. Initial learning rates and weights were set and weights were assigned. The mean squared error (MSE) function was used to calculate the error between the predicted and actual results. Weight adjustments were made and calculations were repeated iteratively until the error was minimized. Parameters were generated through forward propagation and updated through backpropagation. Performance was evaluated using a validation set after each training epoch to avoid overfitting. The model was considered successful when the MSE loss decreased by less than 1e over five consecutive training epochs. -5 When the MSE loss on the validation set stabilizes below 0.01, the model is considered converged, and the vibration influence range prediction branch and the vibration intensity distribution prediction branch are obtained. Finally, the vibration influence range prediction branch and the vibration intensity distribution prediction branch are combined to obtain the vibration characteristic predictor.

[0066] In this embodiment, a vibration characteristic database of various construction equipment under specific geological conditions is established from the acoustic and vibration data of the construction site based on multi-source sound identification and analysis. This reduces the roughness of empirical formulas and the errors of general models, enabling personalized prediction of vibration characteristics and providing reliable input data for the entire optimization process. By combining the basic equipment layout scheme determined by the process flow with the vibration characteristic predictor, the vibration distribution of the foundation construction is generated, and the vibration area to be generated by the equipment is obtained. This is beneficial for proactively avoiding vibration risks, taking timely countermeasures, and solving the problem of passive response after vibration exceeds the standard. Subsequently, based on the vibration distribution of the foundation construction, forbidden areas and feasible areas are divided, providing an optimization basis for subsequent intelligent layout optimization.

[0067] S30: The vibration distribution of the foundation construction is divided into vibration zones, and based on the vibration zone results and the upper limit of vibration intensity, the equipment layout of the movable construction equipment set is optimized on the basis of the foundation equipment layout scheme to generate the target equipment layout scheme.

[0068] In this embodiment of the application, vibration zoning refers to the process of dividing the target construction area into different types of sub-regions based on the intensity of vibration distribution during foundation construction; equipment layout optimization refers to the process of using mathematical optimization algorithms to search for and determine the optimal spatial coordinates of each piece of equipment in the movable construction equipment set, under the premise of meeting vibration constraints and process requirements; target equipment layout scheme refers to the final complete spatial configuration diagram of all equipment.

[0069] Specifically, based on the vibration distribution of the foundation construction, dynamic vibration zoning is performed in conjunction with the upper limit of vibration intensity. Then, based on the foundation equipment layout scheme, equipment layout optimization is performed for the set of movable construction equipment. Specifically, within the deployable area, the optimization algorithm tries different position combinations for each movable piece of equipment. Subsequently, for each candidate layout, a vibration characteristic predictor is invoked to calculate the vibration field generated by the movable equipment at the new position, which is then superimposed with the foundation construction vibration distribution to obtain the full-field predicted vibration distribution under that candidate layout.

[0070] Step S30 in the method provided in this application embodiment includes: Set a preset difference value, and set the areas in the foundation construction vibration distribution where the difference from the upper limit of vibration intensity is less than the preset difference value as forbidden areas, and set other areas as arrangeable areas to complete the vibration zoning; Randomly distribute the set of movable construction equipment within the deployable area to generate the first equipment layout scheme; Calculate the fitness of the first scheme of the first equipment layout scheme; The first equipment layout scheme is optimized and iterated, and the corresponding scheme fitness is calculated in the same way as the first scheme fitness of the first equipment layout scheme, to obtain the equipment layout scheme set; The equipment layout scheme with the highest adaptability is selected as the target equipment layout scheme.

[0071] like Figure 2 As shown in the embodiment of this application, a preset difference is first set. Areas in the foundation construction vibration distribution where the difference from the upper limit of vibration intensity is less than the preset difference are designated as forbidden areas, while other areas are designated as arrangeable areas, thus completing the vibration zoning. The preset difference is defined as: areas in the foundation construction vibration distribution where the difference from the upper limit of vibration intensity is less than the preset difference are designated as forbidden areas, while other areas are designated as arrangeable areas; forbidden areas refer to spatial regions in the foundation construction vibration distribution where the predicted vibration intensity value is very close to the upper limit of vibration intensity, and the remaining vibration capacity is extremely small or negative.

[0072] Specifically, a preset difference is set based on engineering experience or safety standard assessments. Then, each location (grid point) in the foundation construction vibration distribution data is traversed. For each location, the difference between the vibration intensity value and the upper limit of vibration intensity is calculated, where the difference = vibration intensity value - upper limit of vibration intensity. If the difference is less than the preset difference, the location is classified as a prohibited area; otherwise, it is classified as a deployable area. After zoning, the entire construction area is clearly divided into two categories: prohibited areas typically form several zones around each foundation piece of equipment, while deployable areas are safe passageways connecting these isolated zones.

[0073] Secondly, the set of movable construction equipment is randomly distributed within the deployable area to generate a first equipment layout scheme. Here, random distribution refers to the initialization strategy, which assigns coordinates to each piece of equipment by random number generation without considering optimization objectives when allocating positions to movable equipment, based solely on partition constraints and other possible simple rules; the first equipment layout scheme refers to the movable equipment position configuration scheme generated through the random distribution process.

[0074] Specifically, the list of movable construction equipment is identified. Then, a random distribution is performed, accessing the spatial database of deployable areas. For each movable piece of equipment, a coordinate point is randomly selected from the spatial database list as a candidate location. Similarly, random locations are assigned to all movable pieces of equipment to generate a complete first equipment layout scheme, which serves as the starting point for optimization iterations or part of the initial population.

[0075] Next, the fitness of the first equipment layout scheme is calculated. The fitness of the first scheme refers to the numerical result obtained after applying fitness calculation to the first equipment layout scheme. Specifically, the geological information corresponding to the model and location of each movable piece of equipment in the first equipment layout scheme is obtained; then, the constructed vibration characteristic predictor is invoked to predict the individual vibration field of each movable piece of equipment; next, the vibration field generated by the movable equipment is spatially superimposed with the previously calculated foundation construction vibration distribution to obtain the overall predicted vibration distribution under the first equipment layout scheme; finally, the vibration compliance rate and vibration uniformity are calculated, and the scheme fitness is calculated based on these two indicators.

[0076] Simultaneously, the first equipment layout scheme is optimized and iterated, and the fitness of the corresponding scheme is calculated in the same way as the fitness of the first scheme, resulting in a set of equipment layout schemes. Here, optimization iteration refers to the computational process of using a metaheuristic intelligent optimization algorithm, starting from an initial solution, and repeatedly generating, evaluating, and screening new candidate schemes by simulating natural evolution or swarm intelligence, in order to gradually approach the optimal solution; the set of equipment layout schemes is the collection of all candidate equipment layout schemes generated and evaluated during the optimization iteration process.

[0077] For example, a genetic algorithm is used, starting with a first device layout scheme and its fitness, for iterative optimization. First, initialization is performed by replicating multiple variants of the first device layout scheme to form an initial population. Next, based on fitness, some individuals are selected as parents from the current population. Then, crossover and recombination are performed, randomly pairing parent individuals and exchanging the position codes of some devices to generate new offspring schemes. Mutation is then performed, randomly changing the position of a device in the offspring scheme with a small probability. For each new candidate scheme generated through crossover and mutation in each iteration, the corresponding scheme fitness is calculated in the same way as the first scheme fitness is calculated. Then, based on the fitness of the new scheme, it is decided whether to include it in the next generation population. This process is repeated multiple times. Finally, a set of device layout schemes is obtained.

[0078] Finally, the device layout scheme with the highest adaptability is selected as the target device layout scheme. Specifically, the entire set of device layout schemes is traversed, the adaptability of each scheme is compared, and the scheme with the highest adaptability is found. Among all the explored layouts, the scheme with the highest adaptability has the highest overall score and best meets the preset optimization goal, and is finally selected as the target device layout scheme.

[0079] For example, in the set of device layout schemes containing approximately 500 schemes obtained at the end of the iteration, the system sorts and searches. Suppose a scheme is found whose movable device layout is: {E1:(190,35),E2:(20,110),E3:(110,30),E4:(170,120),R1:(60,130)}. The calculated first vibration compliance degree is 0.98, the first vibration balance degree is 0.88, and the weighted fitness degree is 0.98×0.6+0.88×0.4=0.94, which is the highest value. The scheme corresponding to this is taken as the target device layout scheme.

[0080] In step S30 of the method provided in this application embodiment, calculating the first scheme fitness of the first device layout scheme includes: Obtain the equipment model and geological information of each movable construction equipment in the first equipment layout scheme; Activate the vibration characteristic predictor, input the equipment model and geological information of each movable construction equipment into the vibration characteristic predictor, and obtain the vibration influence range and vibration intensity distribution of each movable construction equipment, which are used as the vibration characteristics of each movable construction equipment; By combining the vibration distribution of the foundation construction and the vibration characteristics of each movable construction equipment, the first construction vibration distribution corresponding to the first equipment layout scheme is generated; The adaptability of the first scheme is obtained based on the first construction vibration distribution.

[0081] In this embodiment, the equipment model and geological information of each movable construction device in the first equipment layout scheme are first obtained. Specifically, the movable devices included in the first equipment layout scheme and the specific environment of the vibration source are first identified. Then, the data structure of the first equipment layout scheme is read to obtain the unique identifier and coordinates of each movable device. Based on the device identifier, the equipment database is queried to obtain its precise device model. At the same time, the project's geological digital model is accessed based on the coordinates, and the geological information of the location is obtained through spatial query, thus establishing complete information for each movable device existing in the first equipment layout.

[0082] Secondly, the vibration characteristic predictor is activated. The equipment model and geological information of each movable construction equipment are input into the vibration characteristic predictor to obtain the vibration influence range and vibration intensity distribution of each movable construction equipment, which are used as the vibration characteristics of each movable construction equipment.

[0083] Specifically, the pre-trained and deployed vibration characteristic predictor is first activated. Then, each movable device is sequentially input, including its model number, geological information, and coordinates. After internal calculations, the predictor outputs the predicted vibration influence range and intensity distribution under the current specific geological conditions, which serve as the device's vibration characteristics. This process is repeated to predict the vibration characteristics of all movable devices.

[0084] Next, combining the foundation construction vibration distribution and the vibration characteristics of each movable construction device, a first construction vibration distribution corresponding to the first equipment layout scheme is generated. Specifically, the target construction area is discretized into a fine grid. For each target point Q in the grid, the contribution value from the foundation distribution is calculated. Then, for each movable device i, the distance from point Q to the device is calculated and substituted into the vibration intensity distribution model of the device to obtain the contribution value generated by device i at point Q. Next, the contribution values ​​generated by all foundation equipment and all movable equipment at point Q are synthesized according to the vibration superposition principle to generate the first construction vibration distribution.

[0085] Finally, based on the first construction vibration distribution, the fitness of the first scheme is obtained. The fitness of the first scheme is a comprehensive score obtained through weighted calculation, used for the final comparison and selection of different layout schemes. Specifically, firstly, based on the first construction vibration distribution, the degree of vibration compliance and the degree of vibration uniformity are evaluated. The degree of vibration compliance is the vibration intensity value of all grid points in the first construction vibration distribution, used to reflect the overall safety of the scheme. The degree of vibration uniformity is a statistical uniformity index of the vibration intensity distribution across the entire field, used to reflect the rationality of capacity utilization in the target area, and to obtain the potential collaborative operation space in the target area.

[0086] In step S30 of the method provided in this application embodiment, obtaining the first scheme adaptability based on the first construction vibration distribution includes: The percentage of areas in the first construction vibration distribution that did not exceed the upper limit of vibration intensity was used to obtain the first vibration compliance rate. Calculate the vibration intensity uniformity of the first construction vibration distribution to obtain the first vibration uniformity. The fitness of the first scheme is obtained by weighting the first vibration compliance degree and the first vibration uniformity degree. Simultaneously, the percentage of areas in the first construction vibration distribution that did not exceed the upper limit of vibration intensity was statistically analyzed to obtain the first vibration compliance rate. Here, the area percentage refers to the ratio of the number of grid points that did not exceed the limit to the total number of grid points within the construction area; the first vibration compliance rate is a scalar value between 0 and 1, quantitatively representing the performance of the layout scheme in meeting vibration safety constraints. A higher value indicates a larger area of ​​safe and compliant operation, and a better overall safety of the scheme.

[0087] Specifically, the target construction area is first divided into grid cells. For each grid point, its predicted vibration intensity value is compared with the upper limit of vibration intensity. If the predicted vibration intensity value is less than or equal to the upper limit of vibration intensity, the grid point is considered to meet the standard; otherwise, it is considered to exceed the standard. Then, the vibration intensity value of each grid cell is counted, and the number of grid cells that do not exceed the upper limit of vibration intensity is calculated. The first vibration compliance rate is calculated as the number of grid cells that do not exceed the standard divided by the total number of grid cells.

[0088] For example, if the upper limit of vibration intensity is 2.0 mm / s, the 3000 grid points of the first construction vibration distribution are statistically analyzed. After comparing them one by one, it was found that the predicted vibration values ​​of 2760 points are ≤2.0 mm / s, and the remaining 240 points are >2.0 mm / s. The area ratio is 27600 / 3000 = 0.92, resulting in a first vibration compliance rate of 0.92. This indicates that under this layout, 92% of the construction area is a vibration-safe zone.

[0089] In addition, the vibration intensity uniformity of the first construction vibration distribution is calculated to obtain the first vibration uniformity. The vibration intensity uniformity describes the degree of dispersion or uniformity of the vibration intensity values ​​in the first construction vibration distribution across the entire spatial area. The higher the uniformity, the more uniform the vibration energy is distributed in space, without any localized severe fluctuations; the lower the uniformity, the more uneven the vibration energy distribution.

[0090] Specifically, vibration intensity values ​​are uniformly collected from multiple grid points in the first construction vibration distribution, and the standard deviation is calculated. The standard deviation is the sum of the squares of the differences between the vibration intensity value of each grid point and its mean, resulting in the standard deviation σ of the vibration intensity of all grid units. Subsequently, the mean μ of the vibration intensity of all grid units is calculated, and the uniformity is calculated as 1 - (σ / μ). A high uniformity indicates that the vibration energy is released more evenly in space, resulting in higher equipment safety, the ability to accommodate more equipment operating simultaneously, or more efficient equipment distribution, thus improving overall construction efficiency.

[0091] Finally, the first vibration compliance rate and the first vibration balance rate are weighted and calculated to obtain the fitness of the first scheme. Specifically, corresponding weights are set according to the influence of the first vibration compliance rate and the first vibration balance rate on the scheme's vibration, and technicians can dynamically configure them according to the actual scenario. Then, a weighted calculation is performed based on the weights: first scheme fitness = first vibration compliance rate × w1 + first vibration balance rate × w2, where a higher fitness value indicates better overall performance of the scheme.

[0092] For example, if the first vibration compliance rate is 0.92 and the first vibration balance rate is 0.75, according to the engineering management strategy, a safety weight w1 is set to 0.6 and a balance weight w2 to 0.4. After weighted calculation, the fitness of the first scheme is 0.6 × 0.92 + 0.4 × 0.75 = 0.852.

[0093] In this embodiment, intelligent and efficient allocation of construction space resources is achieved through dynamic vibration zoning and an optimization iteration mechanism. Dynamic vibration zoning divides the site into prohibited and deployable areas based on precise foundation vibration background, ensuring the safety of the search process while reducing the search space of the optimization algorithm and improving computational efficiency. Simultaneously, a fitness function is calculated to balance the objectives of safety compliance and spatial equilibrium. Vibration compliance and vibration equilibrium are used for bidirectional measurement. These two objectives are combined into a fitness score through weighted calculation, guiding the optimization algorithm to find the comprehensive optimal solution. Finally, an intelligent optimization algorithm iteratively searches within the deployable area to find the optimal layout.

[0094] The embodiments of this application, through the specific implementation methods described above, achieve the following technical effects: In this embodiment, the shortest coordinate distance between the construction area and the sensitive track is first calculated precisely, and the corresponding upper limit of vibration intensity is mapped, so that the safety constraints and spatial risk levels are strictly correlated, which provides a data foundation for subsequent improvement of refined control and enhances the applicability of the solution.

[0095] Based on multi-source sound identification and analysis, a database of vibration characteristics of various construction equipment under specific geological conditions is established from acoustic and vibration data at the construction site. This reduces the roughness of empirical formulas and the errors of general models, enabling personalized prediction of vibration characteristics and providing reliable input data for the entire optimization process. By combining the foundation equipment layout scheme determined by the process flow with the vibration characteristic predictor, a foundation construction vibration distribution is generated, revealing the vibration areas that equipment will generate. This facilitates proactive vibration risk avoidance and timely countermeasures, addressing the issue of passive response after vibration exceeds limits. Subsequently, based on the foundation construction vibration distribution, prohibited and feasible zones are delineated, providing an optimization foundation for subsequent intelligent layout optimization. Ultimately, through dynamic vibration zoning and an iterative optimization mechanism, intelligent and efficient allocation of construction space resources was achieved. Dynamic vibration zoning, based on precise foundation vibration background, divides the area into prohibited and feasible zones, ensuring the safety of the search process while simultaneously reducing the search space of the optimization algorithm and improving computational efficiency. Simultaneously, a fitness function is calculated to balance the objectives of safety compliance and spatial equilibrium. Vibration compliance and vibration equilibrium are used for bidirectional measurement. These two objectives are combined into a fitness score through weighted calculation, guiding the optimization algorithm to find the comprehensive optimal solution. Finally, an intelligent optimization algorithm iteratively searches within the feasible zones to find the optimal layout.

[0096] Compared to existing technologies, this application firstly changes the traditional crude approach of using a single threshold by establishing a differentiated upper limit for vibration intensity based on spatial distance, thus enabling a precise match between safety constraints and geographical risks. Secondly, by introducing a vibration characteristic predictor based on multi-source identification and analysis, it solves the key problem that traditional methods cannot predict vibration sources and superposition effects. Utilizing historical acoustic and vibration data, it constructs a high-precision data-driven mapping relationship between equipment model, geological conditions, and vibration characteristics, enabling personalized prediction of the vibration impact of any equipment at a specific location before construction. Simultaneously, dynamic zoning delineates prohibited and feasible areas based on real-time predicted vibration backgrounds, overcoming the shortcomings of traditional static zoning based on fixed geological maps, which cannot adapt to the dynamic construction process. Based on this, an intelligent optimization algorithm performs a global search within the feasible areas, ensuring that the overall vibration of the found layout scheme does not exceed the limit, meeting hard safety constraints, while also ensuring uniform spatial distribution of vibration energy. Under the premise of absolute safety, it maximizes the accommodation of concurrent equipment operation or allows for higher-intensity construction activities, directly and effectively improving construction efficiency.

[0097] Ultimately, this method optimizes construction vibration control from a passive process relying on post-event response, experience-based judgment, and extensive management into a proactive, refined, and intelligent decision-making process based on data-driven approaches, model prediction, and algorithm optimization. In the end, it achieves a dynamic balance between ensuring reliable track vibration safety and maximizing on-site operational efficiency in complex construction environments.

[0098] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0099] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0100] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for vibration zoning control in construction areas based on multi-source sound identification, characterized in that, include: Obtain the coordinates of the target construction area and the train track, and determine the upper limit of vibration intensity in the target construction area; The target construction equipment set is determined, which includes a foundation construction equipment set and a movable construction equipment set. The fixed positions of the foundation construction equipment set are determined within the target construction area according to the construction movement line, forming a foundation equipment layout scheme. The foundation construction vibration distribution is generated through multi-sound source identification and analysis. The vibration distribution of the foundation construction is divided into vibration zones, and based on the vibration zone results and the upper limit of vibration intensity, the equipment layout of the movable construction equipment set is optimized on the basis of the foundation equipment layout scheme to generate a target equipment layout scheme.

2. The method according to claim 1, characterized in that, Obtain the coordinates of the target construction area and the train track, and determine the upper limit of vibration intensity in the target construction area, including: Obtain the coordinates of the target construction area and the train track, and determine the area coordinate range and track coordinate lines; Calculate the distance from each coordinate point within the specified area to the orbital coordinate line to obtain the shortest coordinate distance; The upper limit of vibration intensity in the target construction area is determined based on the shortest coordinate distance, wherein the upper limit of vibration intensity is positively correlated with the shortest coordinate distance.

3. The method according to claim 1, characterized in that, Based on the construction movement line, the fixed locations of the foundation construction equipment set are determined within the target construction area, forming a foundation equipment layout scheme. Furthermore, multi-source sound identification and analysis are used to generate the foundation construction vibration distribution, including: Based on the construction flow, determine the construction process and work path; The sequence of procedures for each foundation construction equipment in the foundation construction equipment center is determined according to the construction process described above. Based on the aforementioned sequence of procedures, fixed work positions are assigned to each basic construction equipment within the target construction area; Based on the fixed operating positions of each basic construction equipment, a basic equipment layout plan is formed; The vibration characteristics of each foundation construction equipment are determined by multi-source sound identification and analysis, and the foundation construction vibration distribution is generated.

4. The method according to claim 3, characterized in that, The vibration characteristics of each foundation construction equipment are determined through multi-source sound identification and analysis, and the foundation construction vibration distribution is generated, including: Obtain the equipment model of each basic construction equipment, and the equipment location of each basic construction equipment within the target construction area; Based on the location of each basic construction equipment, the geological information of the location of each basic construction equipment is obtained; Historical construction monitoring data is acquired, multi-source sound identification and analysis is performed on the historical construction monitoring data, and a vibration characteristic predictor is constructed based on the analysis results; The equipment model and geological information of each foundation construction equipment are input into the vibration characteristic predictor to obtain the vibration influence range and vibration intensity distribution of each foundation construction equipment, which are used as the vibration characteristics of each foundation construction equipment. Based on the vibration characteristics and location of each foundation construction equipment, the foundation construction vibration distribution is generated.

5. The method according to claim 4, characterized in that, The historical construction monitoring data is subjected to multi-source identification and analysis, and a vibration characteristic predictor is constructed based on the analysis results, including: The historical construction monitoring data includes historical construction sound data and historical construction vibration data; The historical construction sound data is subjected to sound source separation, the mixed sound signal is separated into the sound source signals of each independent device, the sound source separation results are obtained, and the device model corresponding to each sound source is identified to construct a sample device model set; Obtain geological information on the operation of various equipment during historical construction, and construct a sample geological information set; Based on the sound source separation results, the vibration impact range generated by each piece of equipment when operating individually is separated from historical construction vibration data, and a sample vibration impact range set is constructed. Based on the sound source separation results, the vibration intensity distribution generated by each piece of equipment when operating individually is separated from historical construction vibration data, and a sample vibration intensity distribution set is constructed. Using the sample equipment model set and sample geological information set as input, and the sample vibration influence range set as output, the vibration influence range prediction branch is trained. Using the sample equipment model set and sample geological information set as input, and the sample vibration intensity distribution set as output, the vibration intensity distribution prediction branch is trained. By combining the vibration influence range prediction branch and the vibration intensity distribution prediction branch, a vibration characteristic predictor is constructed.

6. The method according to claim 1, characterized in that, The vibration distribution of the foundation construction is divided into vibration zones. Based on the vibration zoning results and the upper limit of vibration intensity, the layout of the movable construction equipment set is optimized according to the foundation equipment layout scheme to generate a target equipment layout scheme, including: Set a preset difference value, and set the areas in the foundation construction vibration distribution where the difference from the upper limit of vibration intensity is less than the preset difference value as forbidden areas, and set other areas as arrangeable areas to complete the vibration zoning; Randomly distribute the set of movable construction equipment within the deployable area to generate the first equipment layout scheme; Calculate the fitness of the first scheme of the first equipment layout scheme; The first equipment layout scheme is optimized and iterated, and the corresponding scheme fitness is calculated in the same way as the first scheme fitness of the first equipment layout scheme, to obtain the equipment layout scheme set; The equipment layout scheme with the highest adaptability is selected as the target equipment layout scheme.

7. The method according to claim 6, characterized in that, Calculating the fitness of the first scheme of the first equipment layout scheme includes: Obtain the equipment model and geological information of each movable construction equipment in the first equipment layout scheme; Activate the vibration characteristic predictor, input the equipment model and geological information of each movable construction equipment into the vibration characteristic predictor, and obtain the vibration influence range and vibration intensity distribution of each movable construction equipment, which are used as the vibration characteristics of each movable construction equipment; By combining the vibration distribution of the foundation construction and the vibration characteristics of each movable construction equipment, the first construction vibration distribution corresponding to the first equipment layout scheme is generated; The adaptability of the first scheme is obtained based on the first construction vibration distribution.

8. The method according to claim 7, characterized in that, Based on the first construction vibration distribution, the fitness of the first scheme is obtained, including: The percentage of areas in the first construction vibration distribution that did not exceed the upper limit of vibration intensity was used to obtain the first vibration compliance rate. Calculate the vibration intensity uniformity of the first construction vibration distribution to obtain the first vibration uniformity. The first vibration compliance degree and the first vibration balance degree are weighted and calculated to obtain the first scheme fitness degree.

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