A method, device and equipment for optimizing impact sound insulation performance of a floating floor and a storage medium

Abstract

The application provides a floating floor slab impact sound insulation performance optimization method, device, equipment and storage medium, keyword extraction is performed on target building space information input by a user through a natural language processing module, semantic similarity matching is performed in a pre-constructed noise source library, a target noise source spectrum corresponding to the target building space and a sound insulation standard limit value are automatically obtained, then a floating floor slab sound insulation performance target is determined based on spectrum analysis, subsequently, floating plate material parameters and elastic cushion layer parameters are substituted into a floating floor slab sound insulation performance prediction model established based on a finite element method, impact sound insulation performance prediction values under candidate material combinations are quantitatively calculated, finally, a multi-objective optimization model is constructed and solved in combination with user design constraint conditions, and an optimal design scheme of the floating floor slab matched with actual requirements of the target building space is output, so that precise matching and global optimal design of the acoustic requirements of the building space and the construction scheme of the floating floor slab are realized.

Description

Technical Field

[0001] This invention relates to the field of architectural acoustics, and in particular to a method, apparatus, equipment, and storage medium for optimizing the impact sound insulation performance of floating floor slabs. Background Technology

[0002] In recent years, with the continuous improvement of living standards, people's requirements for the quality of indoor acoustic environment have been increasing. However, the current sound insulation effect of buildings is still unsatisfactory, especially in residential buildings, where the problem of impact noise from floor slabs is particularly prominent. Long-term exposure to noise environments can not only distract attention and reduce work efficiency, but may also have adverse effects on physical and mental health. To improve the sound insulation performance of impact noise from floor slabs, three main methods are currently used: laying elastic surface layers, installing floating floor slabs, and installing soundproof ceilings. Compared with the other two methods, floating floor slabs have become one of the most widely used solutions due to their high efficiency in isolating impact noise from the propagation path. In the construction of floating floor slabs, the dynamic stiffness of the elastic layer material and the type of floating slab material have a significant impact on the sound insulation performance of the system itself. In addition, the isolation efficiency of floating floor slabs for noise sources with different spectral characteristics (light / heavy) varies—existing studies mostly use standard impactors to simulate light impact noise sources (100-3150Hz), but this method is difficult to effectively evaluate the sound insulation performance of floor slabs against heavy impact noise sources (50-630Hz). Furthermore, current designs for floating floors rely heavily on experience, making it difficult for the sound insulation performance of floating floors to reach its optimal level under complex constraints, resulting in low efficiency in sound insulation against impacts.

[0003] In view of the above, this application is hereby submitted. Summary of the Invention

[0004] This invention discloses a method, apparatus, equipment, and storage medium for optimizing the impact sound insulation performance of floating floor slabs, aiming to solve the problem of poor matching between the sound insulation structure of floor slabs and actual needs due to different building space usage functions.

[0005] The first embodiment of the present invention provides a method for optimizing the impact sound insulation performance of floating floor slabs, comprising: Receive target building space information input by the user, the target building space information including building space type, room function and surrounding environment; extract keywords from the target building space information, and perform semantic similarity matching between the keywords and tags in a pre-built noise source library, and output the target noise source spectrum and corresponding sound insulation standard limit that match the target building space information; Spectral analysis is performed on the spectrum of the target noise source to calculate the energy ratio of the target noise source spectrum in the low-frequency and high-frequency bands, determine the noise source type (light / heavy), and determine the sound insulation performance target of the floating floor of the target building space in combination with the sound insulation standard limit. Based on the standard construction drawings, the basic floor slab structure was selected as the template. The floating slab material parameters and elastic cushion layer parameters were substituted into the pre-established floating floor slab sound insulation performance prediction model to calculate the predicted values ​​of the impact sound insulation performance of the floating floor slab under multiple candidate material combinations. The floating floor slab sound insulation performance prediction model was established based on the finite element method and corrected by measured data. Based on the predicted impact sound insulation performance of the floating floor and the target sound insulation performance of the floating floor, a multi-objective optimization model is constructed and solved in combination with the design constraints input by the user, and a floating floor scheme that satisfies the target sound insulation performance of the floating floor and meets the design constraints is output.

[0006] The second embodiment of the present invention provides a device for optimizing the impact sound insulation performance of floating floor slabs, comprising: The noise source matching unit is used to receive target building space information input by the user, which includes building space type, room function and surrounding environment; extract keywords from the target building space information, and perform semantic similarity matching between the keywords and tags in a pre-built noise source library, and output the target noise source spectrum and corresponding sound insulation standard limit that match the target building space information; The sound insulation target determination unit is used to perform spectral analysis on the spectrum of the target noise source, calculate the energy ratio of the spectrum of the target noise source in the low-frequency band and the high-frequency band, determine the noise source type (light / heavy), and determine the sound insulation performance target of the floating floor of the target building space in combination with the sound insulation standard limit. The sound insulation performance prediction unit is used to select the basic floor slab structure as a template based on the standard construction atlas, substitute the floating plate material parameters and elastic cushion layer parameters into the pre-established floating floor slab sound insulation performance prediction model, and calculate the predicted values ​​of the impact sound insulation performance of the floating floor slab under multiple candidate material combinations; the floating floor slab sound insulation performance prediction model is established based on the finite element method and corrected by measured data. The multi-objective optimization output unit is used to construct and solve a multi-objective optimization model based on the predicted impact sound insulation performance of the floating floor and the sound insulation performance target of the floating floor, combined with the design constraints input by the user, and output a floating floor scheme that satisfies the sound insulation performance target of the floating floor and meets the design constraints.

[0007] The third embodiment of the present invention provides a device for optimizing the impact sound insulation performance of floating floor slabs, characterized in that it includes a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to realize the method for optimizing the impact sound insulation performance of floating floor slabs as described in any of the above embodiments.

[0008] The fourth embodiment of the present invention provides a computer-readable storage medium, characterized in that it stores a computer program, which can be executed by the processor of the device where the computer-readable storage medium is located, to implement the method for optimizing the impact sound insulation performance of a floating floor as described in any of the above claims.

[0009] Based on the impact sound insulation performance optimization method, device, equipment, and storage medium of the floating floor provided by this invention, the target building space information input by the user is extracted by a natural language processing module, and semantic similarity matching is performed in a pre-constructed noise source library. The target noise source spectrum and sound insulation standard limit corresponding to the target building space are automatically obtained. Then, the sound insulation performance target of the floating floor is determined based on spectrum analysis. Subsequently, the floating board material parameters and elastic cushion layer parameters are substituted into the floating floor sound insulation performance prediction model established based on the finite element method to quantitatively calculate the impact sound insulation performance prediction value under the candidate material combination. Finally, a multi-objective optimization model is constructed and solved in combination with the user design constraints to output the optimal design scheme of the floating floor that matches the actual needs of the target building space. Thus, the precise matching and global optimal design of the acoustic requirements of the building space and the floating floor construction scheme are achieved. Attached Figure Description

[0010] Figure 1 This is a flowchart illustrating a method for optimizing the impact sound insulation performance of a floating floor slab according to the first embodiment of the present invention. Figure 2 These are the time-domain and frequency-domain diagrams of the heavy and light sound sources provided by this invention. Figure 3 This invention provides the sound pressure level under the action of heavy and light sound sources; Figure 4 This is a schematic diagram of the experimental device for the actual measurement and correction of the sound insulation performance prediction model of the floating floor slab provided by the present invention; Figure 5 This is the time-domain acceleration response fitting verification curve between the sound insulation performance prediction model of the floating floor slab provided by this invention and the measured data; Figure 6 This invention provides the predicted spectrum curves of the impact sound insulation performance of floating floor slabs under light excitation under different combinations of material parameters. Figure 7 This is a schematic diagram of a module for optimizing the impact sound insulation performance of a floating floor slab, provided in the second embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0013] This invention discloses a method, device, equipment, and storage medium for optimizing the impact sound insulation performance of floating floor slabs, aiming to solve the problem of poor matching between the sound insulation structure of floor slabs and actual needs due to different building space usage functions.

[0014] Please see Figure 1 The first embodiment of the present invention provides a method for optimizing the impact sound insulation performance of floating floor slabs, which can be executed by a floating floor slab impact sound insulation performance optimization device (hereinafter referred to as optimization device or system), specifically, by one or more processors within the optimization device, to at least achieve the following steps: S101, Receive target building space information input by the user, the target building space information includes building space type, room function and surrounding environment; Extract keywords from the target building space information, and perform semantic similarity matching between the keywords and tags in a pre-built noise source library, and output the target noise source spectrum and corresponding sound insulation standard limit that match the target building space information; In this embodiment, the user inputs target building space information in natural language through the user interaction module. The target building space information includes building space type, room function and surrounding environment. For example, the user can input descriptive statements such as "a residential bedroom located next to a main urban road", "a primary school classroom in a school building" and "a hospital ward facing the street". After receiving the target building space information, the system calls a pre-built noise source database for matching. The noise source database is a structured database, and its data sources include national standard databases, public documents, and field measurement data. Each record in the database contains at least a sound source identifier, sound source type, sound source active time, and building space type label and room function label associated with the sound source. For example, a typical record can be represented as "Sound source identifier N001; Sound source type: children running and jumping (heavy sound source); Sound source active time: daytime 07:00~22:00; Building space type label: residential; Room function label: bedroom, living room". Each record is associated with a corresponding spectrum data curve and a sound insulation standard limit determined according to relevant standards such as the "Code for Sound Insulation Design of Civil Buildings" GB50118. During matching, the system uses a natural language processing module to segment and extract keywords from the user's input natural language statement, obtaining keywords such as "residential", "bedroom" and "urban main road". Then, the extracted keywords are used to calculate semantic similarity with the building space type label and room function label of each record in the noise source database. Specifically, word vector cosine similarity algorithm or semantic matching algorithm based on pre-trained language model (such as BERT) can be used to calculate the similarity score between each record and the user input. The spectrum data corresponding to one or more records with the highest similarity scores is selected as the target noise source spectrum, and the sound insulation standard limit associated with the record is also output.

[0015] S102, Perform spectrum analysis on the target noise source spectrum, calculate the energy ratio of the target noise source spectrum in the low-frequency band and the high-frequency band, and determine the sound insulation performance target of the floating floor of the target building space in combination with the sound insulation standard limit. In this embodiment, the system receives the spectrum of the target noise source and the sound insulation standard limit, and performs spectral analysis on the spectrum of the target noise source. Specifically, the system first divides the spectrum of the target noise source into frequency bands of 1 / 3 octave, and further divides it into two segments: a low-mid frequency band (50Hz~250Hz) and a high frequency band (250Hz~3150Hz). By integrating the energy of the sound pressure level within each octave, the system calculates the energy of the target noise source spectrum in the low-mid frequency band and the high frequency band, respectively. The ratio of the low-mid frequency energy to the total energy is used as the proportion of the low-mid frequency component, and the ratio of the high frequency energy to the total energy is used as the proportion of the high frequency component. Based on this, the system determines the sound source characteristic type of the target noise source: when the proportion of the low-mid frequency component is significantly higher than the proportion of the high frequency component, the target noise source is identified as a heavy sound source, such as children running and jumping or objects falling; when the proportion of the high frequency component is significantly higher than the proportion of the low-mid frequency component, the target noise source is identified as a light sound source, such as walking in high heels.

[0016] Please combine Figure 2 (Left: Time Domain Graph, Right: Frequency Domain Graph) and 3. Based on the different spectral characteristics of impact sound sources, we can classify them into heavy sound sources and light sound sources. The energy of heavy sound sources is mainly concentrated in the low-to-mid frequency range, while the energy of light sound sources is mainly concentrated in the mid-to-high frequency range. In the time domain graph, it can be clearly seen that the impact time of light sound sources is extremely short, while the impact time of heavy sound sources is relatively long. Different types of buildings produce different types of sound sources. In daily life, the sound of a child running and jumping barefoot in the bedroom is a typical heavy sound source, while the sound of high heels walking in the office is representative of a light sound source. Currently, in China, standard impactors (light sound sources) are mainly used as standard sound sources to measure the sound insulation performance of floor slabs. This can lead to situations where the measurement results meet the standards but sound insulation problems still exist.

[0017] After completing the spectral analysis, the system uses the standardized impact sound pressure level as the core evaluation target for the sound insulation performance of floating floors, based on the single-value evaluation index for impact sound insulation of floor slabs specified in the "Code for Sound Insulation Design of Civil Buildings" GB 50118. It also supplements this with corresponding refined design targets based on the aforementioned sound source characteristics: For scenarios dominated by heavy sound sources with a high proportion of mid-to-low frequency components (such as residential bedrooms and kindergarten activity rooms), the system automatically adds a spectral correction C or a sound insulation value within a specific frequency band of 100Hz~3150Hz as a refined design target on top of the core evaluation target to strengthen the control of sound insulation performance in the mid-to-low frequency band; for scenarios dominated by light sound sources with a high proportion of high frequency components (such as office spaces), the core evaluation target is used as the main design target. The determined sound insulation performance target of the floating floors will serve as the performance constraint input when constructing a multi-objective optimization model. S103, based on the standard construction drawing set, the basic floor slab structure is selected as the template, and the floating plate material parameters and elastic cushion layer parameters are substituted into the pre-established floating floor slab sound insulation performance prediction model to calculate the predicted values ​​of the impact sound insulation performance of the floating floor slab under multiple candidate material combinations; the floating floor slab sound insulation performance prediction model is established based on the finite element method and corrected by measured data. In this embodiment, the system first selects a floor slab structure that meets the standard requirements as the basic template based on the standard construction drawing set. The floor slab structure of the basic template consists of a floating slab layer L1, an elastic layer L2, and a basic floor slab layer L3 from top to bottom. Then, the floating slab material parameters and the elastic cushion layer parameters are used as input parameters and substituted into the pre-established floating floor sound insulation performance prediction model. The floating slab material parameters include at least the areal density, thickness, elastic modulus, and Poisson's ratio of the floating slab material. The elastic cushion layer parameters include at least the dynamic stiffness, thickness, density, and damping loss factor of the elastic cushion layer. The floating slab material can be selected from cement mortar, lightweight concrete, or C30 fine stone concrete, etc. The dynamic stiffness of the elastic cushion layer can be in the range of 1MN / m³ to 250MN / m³. The sound insulation performance prediction model of the floating floor is a parametric finite element acoustic-vibration response model established based on the time-domain finite element method. The establishment process of the parametric finite element acoustic-vibration response model is as follows: The floating floor is regarded as an overall system composed of a floating layer L1, an elastic layer L2, and a foundation floor layer L3. The overall system is meshed using finite element methods, and the following overall dynamic equilibrium equations are established:

[0018] in, To determine the density of each layer of material A defined quality matrix; The Young's modulus of each layer of material and Poisson's ratio A defined stiffness matrix; The damping matrix is ​​obtained using the Rayleigh damping model. ,in , The Rayleigh damping coefficient is... , The system damping coefficient is... This is the system's fundamental natural frequency; , , These are the acceleration vector, velocity vector, and displacement vector of the global node, respectively. The external time-domain excitation acting on the upper surface of the floating plate layer L1 is obtained by inverse transformation of the spectrum of the target noise source. External excitation during the solution process The solution is obtained by transferring the interlayer force layer by layer after the force is applied to the floating plate layer L1, that is:

[0019]

[0020]

[0021] in , , These are the mass matrices for the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the damping matrices for the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the stiffness matrices for the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the acceleration vectors of nodes in the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the velocity vectors of nodes in the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the displacement vectors of nodes in the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively.

[0022] The interlayer contact force transmitted from the floating plate layer L1 to the elastic layer L2. The inter-story contact force transferred from the elastic layer L2 to the foundation slab L3. It is the reaction force between the foundation floor L3 and the fixed constraint boundary. Among them, the stiffness matrix of the elastic layer L2 The dynamic stiffness of the elastic pad Characterized by the dynamic stiffness Defined as the ratio of the dynamic displacement of the elastic cushion layer to the dynamic load under dynamic load, it is determined by the following formula:

[0023] Where F is the dynamic load acting perpendicularly on the elastic cushion specimen (unit: N), and s is the specimen area (unit: m²). 2 ), The dynamic stiffness is the amount of change in the specimen thickness (unit: m). If the elastic pad is considered as a continuous medium with uniform linear elasticity, and its mechanical behavior follows Hooke's Law, then the dynamic stiffness... Alternatively, the Young's modulus E of the elastic padding material can be determined by the relationship between the thickness d and the elastic padding material. Sure. Solving the above equations yields the global nodal acceleration vector. Then, by selecting the transpose of the matrix L, the acceleration response at the receiving point P on the bottom surface of the foundation slab L3 is extracted. The corresponding frequency domain acceleration amplitude is obtained by performing a fast Fourier transform on the acceleration response. and respectively according to and Calculate the average vibration acceleration level of the foundation slab with and without a covering layer. The frequency domain acceleration amplitude is obtained by FFT of the acceleration response at the receiving point without a cover layer. As the reference acceleration, the final acceleration is calculated according to... Calculate the vibration acceleration level difference The output is the predicted value of the impact sound insulation performance of the floating floor. By changing the input floating board material parameters and elastic cushion layer parameters, the parameterized finite element acoustic vibration response model can output the predicted values ​​of impact sound insulation performance under multiple candidate material combinations, which can be used as performance input data for multi-objective optimization. Please combine Figure 4 and Figure 5 The experiment employed a controlled verification approach, conducted in two phases. In the first phase, a hammer impact test was performed on the cast single-layer slab unit to obtain the time-domain vibration response at the receiving point and calculate the frequency-domain vibration level. Simultaneously, the material parameters of the single-layer slab unit were acquired. The experimental conditions (including excitation, boundary conditions, and material parameters) were input into the acoustic-vibration response model to obtain simulation data. In the second phase, multi-layer slabs, i.e., small-sized floating floor slab components, were assembled and subjected to hammer impact tests to calculate… Simultaneously, experimental conditions (including excitation, boundary conditions, and material parameters) are input into the acoustic-vibration response model to obtain simulation data. Finally, the experimental data and simulation data are compared to verify the effectiveness of the acoustic-vibration response model for floating floor slabs.

[0024] The verification results of single-layer and multi-layer slabs show that the established finite element acoustic-vibration response model exhibits good consistency with experimental measurements in terms of time-domain waveform characteristics and frequency-domain vibration acceleration level distribution. The deviation between the experiment and simulation mainly stems from the difference between the idealized model assumptions and the actual specimens. These deviations are within an acceptable range and do not affect the model's effective prediction of the impact sound insulation performance variation law of floating floor slabs. Therefore, this finite element acoustic-vibration response model possesses good accuracy and versatility and can be used for subsequent multi-objective optimization. Based on orthogonal experimental design (DOE) and analysis of variance (ANOVA), the contribution of each design parameter of the floating floor slab to the impact sound insulation performance is quantified. The dynamic stiffness of the elastic material and the floating slab material are identified as having a significant impact on the impact sound insulation performance of the floor slab. Therefore, 16 parameter optimization combinations are proposed (as shown in Table 1), and different characteristic sound sources are applied to explore the optimal solution for different structural parameter combinations. Based on the simulation results (… Figure 6 The observed pattern, "the lower the dynamic stiffness of the elastic material and the higher the density of the floating board material, the better the sound insulation performance," is only applicable to preliminary estimates of the sound insulation performance of floating floors with different structures. Actual performance still requires specific analysis considering the characteristics of the floating board material, other parameters of the elastic material, and the spectral characteristics of the sound source.

[0025] Table 1

[0026] S104. Based on the predicted impact sound insulation performance of the floating floor and the sound insulation performance target of the floating floor, a multi-objective optimization model is constructed and solved in combination with the design constraints input by the user, and a floating floor scheme that satisfies the sound insulation performance target of the floating floor and meets the design constraints is output.

[0027] In this embodiment, the system first receives design constraints proposed by the user for different functional spaces through the user interaction module. These design constraints include at least one or more of the following: paving preferences, floor height requirements, and cost limits. For example, the user can set specific constraints such as "cement mortar is preferred for floating slab materials, the total thickness of the floor slab does not exceed 150mm, and the comprehensive cost per square meter does not exceed 300 yuan". Subsequently, the system constructs a multi-objective optimization model based on the predicted impact sound insulation performance of the floating floor slab under multiple combinations of candidate materials and the target sound insulation performance of the floating floor slab. The multi-objective optimization model uses the areal density, thickness, elastic modulus, Poisson's ratio of the floating slab material, and the dynamic stiffness, thickness, and damping loss factor of the elastic pad as design variables. It takes maximizing impact sound insulation performance, minimizing structural thickness, and minimizing material cost as three optimization objectives, and the target sound insulation performance of the floating floor slab (i.e., the weighted normalized impact sound pressure level is higher than the standard limit, and the refined design objective is not higher than the corresponding limit) and the design constraints as constraints.

[0028] The multi-objective optimization model is solved using the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The specific solution process is as follows: First, the system randomly generates an initial population containing several candidate schemes within the value space of the design variables. The floating plate material parameters and elastic pad parameters corresponding to each candidate scheme in the population are substituted into the calibrated parameterized finite element acoustic vibration response model to calculate the predicted value of the impact sound insulation performance corresponding to the candidate scheme. At the same time, the structural thickness and material cost are calculated based on the structural composition of the candidate scheme. Then, based on the three optimization objectives, the candidate schemes in the population are non-dominated sorted and the crowding distance is calculated. The population is iteratively evolved through genetic operations such as selection, crossover, and mutation. The solution is terminated when the number of iterations reaches a preset threshold or the population converges. Finally, a Pareto optimal solution set that achieves the best balance among impact sound insulation performance, structural thickness, and material cost is obtained. After obtaining the Pareto optimal solution set, the system generates the optimal design scheme for the floating floor according to a preset format and outputs it through the user interaction module. The optimal design scheme for the floating floor includes at least the material specifications (such as the type and thickness of the floating plate material, the dynamic stiffness and thickness of the elastic cushion layer, and other specific parameters) corresponding to each optimization scheme in the Pareto optimal solution set, detailed construction drawings (the stacking relationship and geometric dimensions of each layer of material), predicted sound insulation spectrum (impact sound pressure level curves and single-value evaluation quantities at the center frequency of each 1 / 3 octave band), and performance-cost-thickness comparison chart (intuitively displaying the trade-off relationship of each optimization scheme on the three optimization objectives in the form of Pareto front), so that designers can select the final design scheme to be adopted based on the actual situation of the project.

[0029] Please see Figure 7 The second embodiment of the present invention provides a device for optimizing the impact sound insulation performance of floating floor slabs, comprising: The noise source matching unit 201 is used to receive target building space information input by the user, the target building space information including building space type, room function and surrounding environment; extract keywords from the target building space information, and perform semantic similarity matching between the keywords and tags in the pre-built noise source library, and output the target noise source spectrum and corresponding sound insulation standard limit that match the target building space information; The sound insulation target determination unit 202 is used to perform spectral analysis on the spectrum of the target noise source, calculate the energy ratio of the spectrum of the target noise source in the low-frequency band and the high-frequency band, and determine the sound insulation performance target of the floating floor of the target building space in combination with the sound insulation standard limit. The sound insulation performance prediction unit 203 is used to select the foundation floor structure as a template based on the standard construction atlas, substitute the floating plate material parameters and elastic cushion layer parameters into the pre-established floating floor sound insulation performance prediction model, and calculate the predicted values ​​of the impact sound insulation performance of the floating floor under multiple candidate material combinations; the floating floor sound insulation performance prediction model is established based on the finite element method and corrected by measured data. The multi-objective optimization output unit 204 is used to construct and solve a multi-objective optimization model based on the predicted value of the impact sound insulation performance of the floating floor and the target sound insulation performance of the floating floor, combined with the design constraints input by the user, and output a floating floor scheme that satisfies the target sound insulation performance of the floating floor and meets the design constraints.

[0030] The third embodiment of the present invention provides a device for optimizing the impact sound insulation performance of floating floor slabs, characterized in that it includes a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to realize the method for optimizing the impact sound insulation performance of floating floor slabs as described in any of the above embodiments.

[0031] The fourth embodiment of the present invention provides a computer-readable storage medium, characterized in that it stores a computer program, which can be executed by the processor of the device where the computer-readable storage medium is located, to implement the method for optimizing the impact sound insulation performance of a floating floor as described in any of the above claims.

[0032] Based on the impact sound insulation performance optimization method, device, equipment, and storage medium of the floating floor provided by this invention, the target building space information input by the user is extracted by a natural language processing module, and semantic similarity matching is performed in a pre-constructed noise source library. The target noise source spectrum and sound insulation standard limit corresponding to the target building space are automatically obtained. Then, the sound insulation performance target of the floating floor is determined based on spectrum analysis. Subsequently, the floating board material parameters and elastic cushion layer parameters are substituted into the floating floor sound insulation performance prediction model established based on the finite element method to quantitatively calculate the impact sound insulation performance prediction value under the candidate material combination. Finally, a multi-objective optimization model is constructed and solved in combination with the user design constraints to output the optimal design scheme of the floating floor that matches the actual needs of the target building space. Thus, the precise matching and global optimal design of the acoustic requirements of the building space and the floating floor construction scheme are achieved.

[0033] Exemplary examples show that the computer program described in the third and fourth embodiments of the present invention can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in implementing a floating floor impact sound insulation performance optimization device. For example, the apparatus described in the second embodiment of the present invention.

[0034] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the aforementioned method for optimizing the impact sound insulation performance of floating floors, and it connects various parts of the method using various interfaces and lines to realize the optimization of the impact sound insulation performance of floating floors.

[0035] The memory can be used to store the computer program and / or modules. The processor, by running or executing the computer program and / or modules stored in the memory, and by calling the data stored in the memory, realizes various functions of a method for optimizing the impact sound insulation performance of a floating floor slab. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, text conversion function, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, text message data, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0036] If the implemented module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0037] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0038] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for optimizing the impact sound insulation performance of floating floor slabs, characterized in that, include: Receive target building space information input by the user, the target building space information including building space type, room function and surrounding environment; Keywords are extracted from the target building space information, and the keywords are semantically similar to the tags in the pre-built noise source library. The target noise source spectrum and corresponding sound insulation standard limit that match the target building space information are output. Spectral analysis is performed on the spectrum of the target noise source to calculate the energy ratio of the target noise source spectrum in the low-frequency and high-frequency bands, and the sound insulation standard limit is combined to determine the sound insulation performance target of the floating floor of the target building space. Based on the standard construction atlas, a floor structure that meets the acoustic performance requirements is selected as a template. The floating plate material parameters and elastic cushion layer parameters are substituted into the pre-established floating floor sound insulation performance prediction model to calculate the predicted values ​​of the impact sound insulation performance of the floating floor under multiple candidate material combinations. The floating floor sound insulation performance prediction model is established based on the finite element method and corrected by measured data. Based on the predicted impact sound insulation performance of the floating floor and the target sound insulation performance of the floating floor, a multi-objective optimization model is constructed and solved in combination with the design constraints input by the user, and a floating floor scheme that satisfies the target sound insulation performance of the floating floor and meets the design constraints is output.

2. The method for optimizing the impact sound insulation performance of a floating floor slab according to claim 1, characterized in that, The noise source database is a structured database. Each record in the structured database includes at least the sound source identifier, sound source type, sound source active time, and building space type label and room function label associated with the sound source. The semantic similarity matching includes: calculating the semantic similarity between the keyword and the building space type label and the room function label, and selecting the spectral data corresponding to the record with the highest similarity as the target noise source spectral output.

3. The method for optimizing the impact sound insulation performance of a floating floor slab according to claim 1, characterized in that, The float material parameters include at least the areal density, thickness, elastic modulus, damping, and Poisson's ratio of the float material; The parameters of the elastic pad layer include at least the dynamic stiffness, thickness, density, and damping loss factor of the elastic pad layer; The sound insulation performance prediction model of the floating floor is a parametric finite element acoustic-vibration response model. The parametric finite element acoustic-vibration response model outputs the impact sound insulation performance prediction value of the floating floor under different characteristic noise sources by changing the material parameters of the floating plate and the parameters of the elastic cushion layer.

4. The method for optimizing the impact sound insulation performance of a floating floor slab according to claim 3, characterized in that, The method for constructing the parametric finite element acoustic vibration response model includes: The floating floor is divided into a three-layer structure: a floating slab layer L1, an elastic layer L2, and a foundation slab layer L3. The overall dynamic equilibrium equation of the three-layer structure is established based on the time-domain finite element method. in, The mass matrix is ​​determined by the density of each layer of material; The damping matrix is ​​determined using the Rayleigh damping model. ,in, , The system damping coefficient is... This is the system's fundamental natural frequency; The stiffness matrix is ​​determined by the Young's modulus and Poisson's ratio of each layer of material. , , These are the acceleration vector, velocity vector, and displacement vector of the global node, respectively. This is an external time-domain excitation acting on the upper surface of the floating plate layer L1; The overall dynamic equilibrium equation is solved by passing the interlayer forces layer by layer, specifically as follows: in, The interlayer contact force transmitted from the floating plate layer L1 to the elastic layer L2. The inter-story contact force transferred from the elastic layer L2 to the foundation slab L3. The reaction force between the fixed constraint boundaries of the foundation floor slab L3. , , These are the mass matrices for the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the damping matrices for the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the stiffness matrices for the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the acceleration vectors of nodes in the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the velocity vectors of nodes in the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively. , , These are the displacement vectors of nodes in the floating slab layer L1, the elastic layer L2, and the foundation slab layer L3, respectively.

5. The method for optimizing the impact sound insulation performance of a floating floor slab according to claim 4, characterized in that, The stiffness matrix of the elastic layer L2 The dynamic stiffness of the elastic pad Characterization, When the elastic pad is considered as a uniform linear elastic continuous medium, and its mechanical behavior follows Hooke's law, the dynamic stiffness is... The alternative is determined by the following formula: Where E is the Young's modulus of the elastic pad material, and d is the thickness of the elastic pad specimen.

6. The method for optimizing the impact sound insulation performance of a floating floor slab according to claim 4, characterized in that, The predicted value of the impact sound insulation performance of the floating floor slab is calculated in the following way: Using the global nodal displacement vector U(t) obtained by solving the overall dynamic equilibrium equation, calculate the acceleration response at the receiving point P on the bottom surface of the foundation slab L3. : Where L is the node selection matrix; For the acceleration response The spectral data was obtained by performing a fast Fourier transform, and the vibration acceleration level difference was calculated. As the predicted value for the impact sound insulation performance of the floating floor slab: in, The average vibration acceleration level of the foundation slab without a covering layer. To set the average vibration acceleration level when the cover layer is applied, As the reference acceleration, The frequency domain acceleration amplitude is obtained by fast Fourier transform of the acceleration response at the receiving point P on the bottom surface of the foundation floor slab L3 without the covering layer consisting of the floating slab layer L1 and the elastic layer L2.

7. The method for optimizing the impact sound insulation performance of a floating floor slab according to claim 1, characterized in that, The design constraints include at least one or more of the following: paving preferences, floor height requirements, and cost restrictions; The multi-objective optimization model takes the predicted sound insulation performance of the floating floor impact sound, the structural thickness and the material cost as optimization objectives, and uses a non-dominated sorting genetic algorithm to solve it, and obtains the Pareto optimal solution set. The floating floor scheme includes at least the material specifications, detailed construction drawings, predicted sound insulation spectrum, and performance, cost, and thickness comparison charts corresponding to the optimal design scheme.

8. A device for optimizing the impact sound insulation performance of floating floor slabs, characterized in that, include: A noise source matching unit is used to receive target building space information input by the user, the target building space information including building space type, room function and surrounding environment; Keywords are extracted from the target building space information, and the keywords are semantically similar to the tags in the pre-built noise source library. The target noise source spectrum and corresponding sound insulation standard limit that match the target building space information are output. The sound insulation target determination unit is used to perform spectral analysis on the spectrum of the target noise source, calculate the energy ratio of the spectrum of the target noise source in the low-frequency band and the high-frequency band, and determine the sound insulation performance target of the floating floor of the target building space in combination with the sound insulation standard limit. The sound insulation performance prediction unit is used to select a floor structure that meets the acoustic performance requirements based on a standard construction atlas as a template, substitute the floating board material parameters and elastic cushion layer parameters into a pre-established floating floor sound insulation performance prediction model, and calculate the predicted values ​​of the impact sound insulation performance of the floating floor under multiple candidate material combinations; the floating floor sound insulation performance prediction model is established based on the finite element method and corrected by measured data. The multi-objective optimization output unit is used to construct and solve a multi-objective optimization model based on the predicted impact sound insulation performance of the floating floor and the sound insulation performance target of the floating floor, combined with the design constraints input by the user, and output a floating floor scheme that satisfies the sound insulation performance target of the floating floor and meets the design constraints.

9. A device for optimizing the impact sound insulation performance of floating floor slabs, characterized in that, The system includes a memory and a processor. The memory stores a computer program that can be executed by the processor to implement a method for optimizing the impact sound insulation performance of a floating floor as described in any one of claims 1 to 6.

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