Road section noise control method and system of intelligent guardrail

Abstract

The embodiment of the invention discloses a road section noise control method and system of an intelligent guardrail, relates to the technical field of noise control, and is used for solving the problem that the current road section noise control mode is difficult to provide enough noise reduction in real time. The method comprises the following steps: determining noise high-incidence time by acquiring noise detection frequency spectrums of all road sections in a current area; acquiring environmental data by utilizing guardrail detection equipment, and establishing a digital twin model of noise of each road section in combination with a noise detection frequency spectrum; and determining a noise source and characteristics thereof based on the model so as to determine a to-be-adjusted physical structure of the guardrail, and determining adjustment data and a noise reduction value thereof through simulation adjustment. And in combination with the noise reduction value, the noise source and the characteristics, determining the operation parameters of the sound wave offset device to perform active noise reduction, adjusting the guardrail physical structure according to the adjustment data to realize physical noise reduction, and realizing noise control of each road section in the current area.

Description

Technical Field

[0001] The present invention relates to the technical field of noise control, and in particular to a method and system for controlling road noise with an intelligent guardrail. Background Art

[0002] With the acceleration of global urbanization, urban transportation networks are becoming increasingly complete, but the resulting traffic noise problem is also becoming increasingly prominent. Traffic noise not only affects the quality of life of urban residents, but may also have long-term negative effects on people's physical and mental health. In order to effectively control and reduce traffic noise, noise control measures are currently being adopted, such as setting up sound barriers and planting soundproof forests to alleviate the noise problem.

[0003] Although traditional noise control measures can alleviate the noise problem to a certain extent, they occupy a large area and have high construction costs, and their adaptability to complex and changing traffic environments is limited. Therefore, in this context, smart guardrails, as an innovative traffic facility, have gradually been introduced into the field of road noise control. The current smart guardrails mainly reduce the propagation and reflection of noise by physical means such as changing the material and shape of the guardrail or adding sound insulation materials. This method mainly depends on the design and manufacturing level of the guardrail, as well as the sound insulation performance of the material, and can usually only deal with noise problems passively. However, it is difficult to grasp the high-noise periods of each section of the road, such as the horn noise caused by traffic jams during peak hours, and it is difficult to actively reduce noise during the high-noise period. This means that during the period of high noise, the smart guardrail may not be able to provide sufficient noise reduction effect in real time, thereby affecting the overall noise control effect. Summary of the invention

[0004] In order to solve the above technical problems, one or more embodiments of this specification provide a road section noise control method and system for an intelligent guardrail.

[0005] One or more embodiments of this specification adopt the following technical solutions:

[0006] One or more embodiments of this specification provide a method for controlling road noise of an intelligent guardrail, the method comprising:

[0007] Acquire the noise detection spectrum of each road section in the current area, so as to determine the peak noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area;

[0008] Based on the guardrail detection equipment pre-installed in each road section of the current area, the environmental data of each road section in the current area is obtained, and the digital twin model of the noise of each road section is established based on the environmental data and the noise detection spectrum simulation;

[0009] Determine the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model;

[0010] Determine the physical structure of the guardrail to be adjusted according to the noise source and the noise characteristics, simulate and adjust the physical structure to be adjusted according to the digital twin model, determine adjustment data of the physical structure to be adjusted, and obtain the noise reduction value corresponding to the adjustment data;

[0011] According to the noise reduction value, the noise source and the noise characteristic, the operating parameters of the sound wave cancellation device on each road section are determined to control the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjust the physical structure to be adjusted based on the adjustment data to perform physical noise reduction.

[0012] Optionally, in one or more embodiments of the present specification, the acquiring of the noise detection spectrum of each road section in the current area to determine the noise peak time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area specifically includes:

[0013] Based on the preset measurement equipment of each road section in the current area, the noise of each road section is measured to obtain the noise intensity of each road section in the current area at different frequencies, and the noise detection spectrum of each road section in the current area is determined according to the noise intensity at different frequencies;

[0014] Screening the peak value of the noise detection frequency to determine the main noise frequency components of each road section;

[0015] Comparing each of the main noise frequency components with the noise frequency range of the current area to determine the noise time period of each road section exceeding the noise frequency range;

[0016] Comparing the noise time period with a preset noise time unit, if the noise time period exceeds the preset noise time unit, taking the noise time period as an initial high noise occurrence time;

[0017] The ratio of the number of occurrences of the initial high noise occurrence time to the number of detections within a preset detection period is obtained. If it is determined that the ratio is greater than the preset ratio, the initial high noise occurrence time is used as the high noise occurrence time.

[0018] Optionally, in one or more embodiments of the present specification, before determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, the method further includes:

[0019] Acquiring road network information of the current area to determine a road noise boundary point of the current area, so as to determine a noise impact area range corresponding to the current area according to a preset distance and the road noise boundary point;

[0020] Obtaining map information within the noise impact area to determine the sensitive area within the noise impact area, and obtaining the boundary contour of the sensitive area; wherein the types of the sensitive area include: residential area type, wildlife protection area type, and education area type;

[0021] Based on the type of the sensitive area, determining the allowable range of noise frequency of the boundary contour of the sensitive area; wherein the allowable range of noise frequency is determined based on expert experience or regulations;

[0022] Input the distance between the preset measuring equipment of each road section and the boundary contour and the allowable range of noise frequency of the boundary contour into the noise propagation model to determine the first allowable range of noise frequency;

[0023] According to the map information within the noise impact area, the obstacle between the sensitive area and the preset measurement device is determined, and the first noise frequency allowable range is corrected according to the noise blocking information corresponding to the obstacle to obtain the noise frequency range of the current area.

[0024] Optionally, in one or more embodiments of the present specification, a digital twin model of the noise of each road section is established based on the environmental data and the noise detection spectrum simulation, specifically including:

[0025] Performing data preprocessing on the environmental data to obtain processed environmental data;

[0026] According to the geographical location information of the current area, the environmental data is associated with the road network information of the current area, and the associated environmental data and the road network information of the current area are input into a preset simulation tool to construct a three-dimensional model of the current area;

[0027] According to the noise collection position corresponding to the noise detection spectrum, the noise detection spectrum data is mapped to the three-dimensional model of the current area to obtain an initial digital twin model of the noise of each road section;

[0028] The propagation path corresponding to the noise of each road section is determined according to the noise propagation model, so as to identify the sensitive area corresponding to the noise of each road section according to the propagation path and the sensitive area of ​​the current area, and associate the sensitive area with each road section in the initial digital twin model to establish a digital twin model of the noise of each road section.

[0029] Optionally, in one or more embodiments of the present specification, determining the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model specifically includes:

[0030] Determine the noise distribution of each road section according to the digital twin model, and determine one or more suspected noise source locations according to the noise distribution and the noise propagation model corresponding to each road section;

[0031] Calling a plurality of historical noise detection data corresponding to each suspected noise source position, and performing spectrum analysis on the historical noise detection data to obtain a historical noise detection spectrum;

[0032] Filtering the suspected noise source position according to each of the historical noise detection spectra and the noise frequency range of the current area to obtain a filtered suspected noise source position;

[0033] Based on the historical noise detection spectrum, determine the peak time of the noise source at each of the filtered suspected noise source locations, as well as the frequency components and spectrum characteristics of the noise source;

[0034] According to the correspondence between the peak time of the noise source at the suspected noise source location and the peak time of the noise, the suspected noise source location is filtered to obtain the location of the noise source;

[0035] Classifying the noise sources based on the locations of the noise sources on each road section to determine the noise types of the noise sources; wherein the noise types include: traffic noise, industrial noise, and construction noise;

[0036] The noise attribute corresponding to the noise type of the noise source is obtained, so as to determine the noise characteristic of each noise source based on the noise attribute of the noise source, the frequency component and the spectrum characteristic of the noise source.

[0037] Optionally, in one or more embodiments of the present specification, determining the physical structure to be adjusted of the guardrail according to the noise source and the noise characteristics, performing simulation adjustment on the physical structure to be adjusted according to the digital twin model, determining adjustment data of the physical structure to be adjusted, and obtaining the noise reduction value corresponding to the adjustment data, specifically includes:

[0038] According to the noise source and the guardrail information of each road section, the guardrail of each road section can be adjusted in physical structure based on the guardrail information; wherein the guardrail information includes: guardrail material, guardrail structure components, guardrail thickness, and guardrail height;

[0039] Retrieving historical noise control data corresponding to the adjustable physical structure, and determining historical noise characteristics corresponding to each of the historical noise control data;

[0040] Determining, according to the matching relationship between the historical noise characteristics and the noise characteristics, a physical structure to be adjusted in the adjustable physical structure that can control the noise of each of the road sections;

[0041] Performing noise simulation in the digital twin model based on the location of the noise source and the noise characteristics, adjusting the physical structure to be adjusted in turn, and collecting simulation results;

[0042] Determine the noise reduction value corresponding to each parameter in the adjustment process of the physical structure to be adjusted according to the simulation result, and determine the adjustment data of the physical structure to be adjusted according to the noise reduction value;

[0043] A secondary simulation is performed on the adjustment data based on the digital twin model to determine the noise reduction value corresponding to the adjustment data.

[0044] Optionally, in one or more embodiments of the present specification, determining the operating parameters of the sound wave cancellation device on each road section according to the noise reduction value, the noise source and the noise characteristics specifically includes:

[0045] According to the noise characteristics and the noise source, the parameter adjustment range of each operating parameter corresponding to the sound wave cancellation device on each road section is determined; wherein the operating parameters include: filter parameters, phase parameters, and power parameters;

[0046] Inputting historical operating parameter data and historical evaluation data of the acoustic wave cancellation device into a preset machine learning model such as a random forest to determine the relationship between the noise cancellation result and the operating parameters, and using it as the objective function of the acoustic wave cancellation device;

[0047] Within the parameter adjustment range of each of the operating parameters, traverse according to a preset step length to obtain a parameter combination of the operating parameters;

[0048] Determine the objective function value corresponding to each of the parameter combinations according to the objective function, and determine one or more optimal parameter combinations by comparing the objective function values;

[0049] The adjustment costs corresponding to the parameter adjustments of the one or more optimal parameter combinations are obtained, so as to screen the one or more optimal parameter combinations based on the adjustment costs and obtain the operating parameters of the sound wave canceling device on each road section.

[0050] Optionally, in one or more embodiments of the present specification, after controlling the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjusting the physical structure to be adjusted based on the adjustment data to perform physical noise reduction, the method further includes:

[0051] Based on the pre-installed measurement equipment on each road section in the current area, noise measurement is performed on each road section to obtain the noise detection spectrum after noise reduction;

[0052] Sorting the noise detection spectra after noise reduction based on the time sequence, so as to sequentially compare two adjacent noise detection spectra after noise reduction to obtain the noise reduction trend of each of the road sections;

[0053] If it is determined based on the noise reduction trend that the noise is decreasing or the noise detection spectrum after the noise reduction is within the noise frequency range of the current area, then maintaining the operating parameters of the sound wave cancellation device and the physical structure to be adjusted;

[0054] If it is determined based on the noise reduction trend that the noise is rising and the noise detection spectrum after noise reduction is not within the noise frequency range of the current area, the current noise peak time is determined based on the noise detection spectrum after noise reduction, and the operating parameters of the sound wave cancellation device on each road section and the adjustment data of the physical structure to be adjusted are iteratively updated.

[0055] One or more embodiments of this specification provide a road noise control system for an intelligent guardrail, the system comprising:

[0056] A time determination unit, used to obtain a noise detection spectrum of each road section in the current area, so as to determine a high noise occurrence time of each road section in the current area according to the noise detection spectrum and a noise frequency range of the current area;

[0057] An establishing unit is used to obtain environmental data of each road section in the current area based on guardrail detection equipment preset in each road section in the current area, and establish a digital twin model of noise of each road section based on the environmental data and the noise detection spectrum simulation;

[0058] A characteristic determination unit, used to determine the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model;

[0059] A simulation unit, used to determine the physical structure to be adjusted of the guardrail according to the noise source and the noise characteristics, to simulate and adjust the physical structure to be adjusted according to the digital twin model, to determine adjustment data of the physical structure to be adjusted, and to obtain a noise reduction value corresponding to the adjustment data;

[0060] The noise reduction unit is used to determine the operating parameters of the sound wave cancellation device on each road section according to the noise reduction value, the noise source and the noise characteristics, so as to control the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjust the physical structure to be adjusted based on the adjustment data to perform physical noise reduction.

[0061] Optionally, in one or more embodiments of the present specification, before determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, the system is further configured to:

[0062] Acquiring road network information of the current area to determine a road noise boundary point of the current area, so as to determine a noise impact area range corresponding to the current area according to a preset distance and the road noise boundary point;

[0063] Obtaining map information within the noise impact area to determine the sensitive area within the noise impact area, and obtaining the boundary contour of the sensitive area; wherein the types of the sensitive area include: residential area type, wildlife protection area type, and education area type;

[0064] Based on the type of the sensitive area, determining the allowable range of noise frequency of the boundary contour of the sensitive area; wherein the allowable range of noise frequency is determined based on expert experience or regulations;

[0065] Input the distance between the preset measuring equipment of each road section and the boundary contour and the allowable range of noise frequency of the boundary contour into the noise propagation model to determine the first allowable range of noise frequency;

[0066] According to the map information within the noise impact area, the obstacle between the sensitive area and the preset measurement device is determined, and the first noise frequency allowable range is corrected according to the noise blocking information corresponding to the obstacle to obtain the noise frequency range of the current area.

[0067] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0068] By obtaining the noise detection spectrum of each section of the current area and combining it with the regional noise frequency range, the peak noise time can be accurately determined, which is helpful for subsequent identification and noise reduction of the peak noise time. The application of the digital twin model enables the noise control process to be simulated and tested in a virtual environment, and by simulating the adjustment of the physical structure of the guardrail to be adjusted, the optimal adjustment plan can be quickly determined, which improves the implementation efficiency of noise reduction measures. And by combining the active noise reduction of the sound wave cancellation device and the physical noise reduction of the physical structure, it can complement each other and achieve a more comprehensive noise reduction effect. Determining the operating parameters of the sound wave cancellation device according to the noise source and noise characteristics can make the noise reduction measures more targeted and effective, and can also avoid unnecessary waste of resources and reduce the implementation cost of noise reduction measures. And according to the noise detection spectrum and environmental data obtained in real time, the physical structure of the guardrail and the operating parameters of the sound wave cancellation device are dynamically adjusted to adapt to the changing noise environment. This dynamic adaptability helps to maintain the continuity and stability of the noise reduction effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0070] Figure 1 A schematic diagram of a road section noise control method for an intelligent guardrail provided in an embodiment of this specification;

[0071] Figure 2 A schematic diagram of the structure of a road noise control system for an intelligent guardrail provided in an embodiment of this specification. DETAILED DESCRIPTION

[0072] The embodiments of this specification provide a road section noise control method and system for an intelligent guardrail.

[0073] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0074] like Figure 1 As shown, the present specification embodiment provides a method flow chart of a method for controlling road noise of an intelligent guardrail. Figure 1 It can be seen that in one or more embodiments of this specification, a road section noise control method of an intelligent guardrail includes the following steps:

[0075] S101: Acquire noise detection spectra of each road section in the current area, and determine the peak noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area.

[0076] In order to be able to identify the noise frequency components of different road sections and determine the high-noise time periods of each road section, so as to effectively suppress noise for the noise frequency components and the high-noise time periods, improve the quality of life of residents, and protect the ecological environment. In the embodiments of this specification, the noise detection spectrum of each road section in the current area will be obtained. Since the spectrum analysis can cover a wide frequency range, by obtaining the noise frequency range from low frequency to high frequency of each road section, it can be ensured that no important noise components are missed, which helps the flexibility and pertinence of subsequent noise control. By comparing the noise detection spectrum with the noise frequency range of the current area, the high-noise time of each road section in the current area can also be quickly determined. For example: the noise caused by honking during traffic congestion will lead to a high concentration of noise and a high-noise time.

[0077] Specifically, in one or more embodiments of the present specification, obtaining the noise detection spectrum of each road section in the current area, and determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, specifically includes the following process:

[0078] First, based on the preset measurement equipment of each road section in the current area, the noise of each road section is measured to obtain the noise intensity of each road section in the current area at different frequencies, and the noise detection spectrum of each road section in the current area is determined according to the noise intensity at different frequencies. Then, the peak of the noise detection frequency is screened out, so that the main noise frequency components of each road section can be determined according to the distribution of the peak in the noise detection frequency. Compare each main noise frequency component with the noise frequency range of the current area to determine the noise time period of each road section that exceeds the noise frequency range. Compare the noise time period with the preset noise time unit. If the noise time period exceeds the preset noise time unit, that is, the noise maintains a certain duration or frequency, the noise time period will be used as the initial noise high-incidence time. Then obtain the ratio of the number of occurrences of the initial noise high-incidence time to the number of detections within the preset detection cycle. If the ratio is greater than the preset ratio, then the initial noise high-incidence time is used as the noise high-incidence time. In this process, by comparing the noise time period with the preset noise time unit, and calculating the ratio of the number of occurrences of the initial noise peak time to the number of detections, this method can efficiently identify the noise peak time, which helps to take more effective noise reduction measures to improve noise reduction efficiency in the subsequent period of severe noise pollution.

[0079] For example, in a certain application scenario, a preset measuring device is used to measure the noise of the road for 24 hours continuously, and the noise intensity at different frequencies is recorded. Based on the measurement data, a spectrum of the noise intensity of each road section at different frequencies is drawn, so as to screen out the peak frequency of the noise intensity of each road section in the spectrum. According to the distribution of the peak frequency, the main noise frequency components of each road section are determined. For example, the main noise frequency component of section A may be low-frequency traffic noise, while section B may be medium-high frequency construction noise. Then the main noise frequency components of each road section are compared with the noise frequency range of the current area to find out the noise frequency components that exceed the range. According to the occurrence time of the noise frequency components that exceed the range, the noise time period of each road section that exceeds the noise frequency range is determined. For example, the low-frequency traffic noise of section A exceeds the range between 5 pm and 7 pm, and the medium-high frequency construction noise of section B exceeds the range between 10 am and 12 noon. The noise time period determined for each road section is compared with the preset noise time unit, such as 1 hour. If a noise time period exceeds 1 hour, that is, the noise maintains a certain duration, then this time period is regarded as the initial high noise time. For example, the time period from 5pm to 7pm on section A is determined as the initial high noise time. Within the preset detection cycle, the number of occurrences of the initial high noise time on each section is counted and the ratio is calculated with the number of detections. If the ratio of a section is greater than the preset ratio of 0.5, the initial high noise time is used as the high noise time for the section. For example, if the number of occurrences of the initial high noise time from 5pm to 7pm on section A accounts for 60% of the number of detections in a week, the time period is determined as the high noise time for section A.

[0080] Further, in one or more embodiments of the present specification, before determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, in order to determine the noise frequency range of the current area, so as to determine whether the noise of the road section exceeds the allowable range to cause noise pollution, the method also includes the following process:

[0081] First, the road network information of the current area is obtained and the road noise boundary point of the current area is determined, so as to determine the noise impact area range corresponding to the current area according to the preset distance and the road noise boundary point. The map information within the noise impact area is obtained to determine the sensitive area within the noise impact area, and the boundary contour of the sensitive area is obtained. It should be noted that the types of sensitive areas include: residential area type, wildlife protection area type, and education area type. Then, according to the type of sensitive area, the noise frequency allowable range of the boundary contour of the sensitive area is determined. Among them, the noise frequency allowable range is determined based on expert experience or regulations. Then, the distance between the preset measurement equipment of each section and the boundary contour and the noise frequency allowable range of the boundary contour are input into the noise propagation model to determine the first noise frequency allowable range. Then, according to the map information within the noise impact area, the obstacles between the sensitive area and the preset measurement equipment are determined, and the first noise frequency allowable range is corrected according to the noise blocking information corresponding to the obstacles to obtain the noise frequency range of the current area.

[0082] This process can determine the permissible range of noise frequency of the boundary contours of different types of sensitive areas, such as residential areas, wildlife reserves, educational areas, etc., reflecting the targeted noise control of different types of sensitive areas. In addition, in this process, by inputting the distance between the preset measuring equipment and the boundary contour and the permissible range of noise frequency of the boundary contour into the noise propagation model, the propagation of noise can be simulated and predicted, thereby obtaining a more accurate permissible range of the first noise frequency. By correcting the permissible range of the first noise frequency according to the noise blocking information corresponding to the obstacle, the noise blocking effect in the actual situation can be further considered, so that the final noise frequency range is closer to reality.

[0083] S102: Based on the guardrail detection equipment preset in each road section of the current area, the environmental data of each road section in the current area is obtained, and a digital twin model of the noise of each road section is established based on the environmental data and the noise detection spectrum simulation.

[0084] In order to facilitate the understanding of the distribution of noise in the propagation path, whether there are corresponding impact objects of noise, that is, whether the noise affects the surrounding residents or surrounding protected areas. In the embodiment of this specification, according to the guardrail detection equipment pre-set in each section of the current area, the environmental data of each section of the current area is obtained, so as to establish a digital twin model of the noise of each section according to the environmental data and the noise detection spectrum simulation. In this process, by establishing a digital twin model, it is possible to quantitatively evaluate the noise level of different sections of the road, and provide accurate data support for subsequent governance work. The real-time collection of environmental data by the guardrail detection equipment and the establishment of a digital twin model of the noise of each section of the road according to the environmental data and the noise detection spectrum simulation will help to take into account the blocking and reduction of noise by environmental factors, thereby helping to improve the subsequent noise control effect as early as possible and reduce unnecessary noise reduction costs.

[0085] Specifically, in one or more embodiments of the present specification, a digital twin model of noise in each road section is established based on environmental data and noise detection spectrum simulation, which specifically includes the following processes:

[0086] The environmental data is preprocessed to obtain the processed environmental data. According to the geographical location information of the current area, the environmental data is associated with the road network information of the current area, and the associated environmental data and the road network information of the current area are input into the preset simulation tool to build a three-dimensional model of the current area. The environmental data is associated with the road network information of the current area to ensure that the model can truly reflect the actual road network situation and enhance the practicality and accuracy of the model. Then, according to the noise collection position corresponding to the noise detection spectrum, the noise detection spectrum data is mapped to the three-dimensional model of the current area to obtain the initial digital twin model of the noise of each road section. Mapping the noise detection spectrum data to the three-dimensional model can accurately reflect the intensity and frequency distribution of noise at different locations, which is helpful to identify the key areas and main sources of noise pollution. Then, according to the noise propagation model, the propagation path corresponding to the noise of each road section is determined, so as to identify the sensitive areas corresponding to the noise of each road section according to the propagation path and the sensitive areas of the current area, and associate the sensitive areas with each road section in the initial digital twin model to establish the digital twin model of the noise of each road section. Determining the propagation path of noise on each road section based on the noise propagation model helps predict the diffusion trend and impact range of noise. Identifying the sensitive areas corresponding to the noise on each road section and associating the sensitive areas with each road section in the initial digital twin model helps to formulate targeted noise reduction measures to protect sensitive areas from noise pollution. In addition, the process can dynamically adjust the model as environmental data and noise detection spectrum are updated to maintain the timeliness and accuracy of the model.

[0087] S103: Determine the noise sources during the peak noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model.

[0088] In order to facilitate targeted treatment of high-noise periods and noise characteristics, thereby avoiding the problem of poor noise reduction effects caused by blind noise reduction, the embodiments of this specification will determine the noise sources during high-noise periods of each road section and the noise characteristics of each noise source based on the digital twin model. By obtaining the noise characteristics of each noise source, such as frequency range, sound pressure level, timbre characteristics, etc., it is helpful to select the most matching noise reduction technology. For example, for low-frequency noise, such as the low-frequency roar emitted by the operation of some large mechanical equipment, it may be necessary to use sound-absorbing cotton, low-frequency shock absorbers and other noise reduction materials and equipment specifically for low frequencies; and for high-frequency noise, such as the sharp sound generated when the vehicle brakes, it can be effectively controlled by using mufflers, sound insulation barriers and other methods.

[0089] Specifically, in one or more embodiments of the present specification, determining the noise sources of each road section during the high noise occurrence time and the noise characteristics of each noise source based on the digital twin model specifically includes the following processes:

[0090] First, the noise distribution of each road section is determined according to the digital twin model, and one or more suspected noise source locations are determined according to the noise distribution and the noise propagation model corresponding to each road section. The noise distribution is determined by the digital twin model, and then the suspected noise source location is located in combination with the noise propagation model corresponding to each road section. This dual-model combination method makes full use of the high-precision simulation of the actual environment by the digital twin model and the physical laws of the noise propagation model. Compared with a single method, it can more accurately narrow the possible range of noise sources and provide a good foundation for subsequent precise positioning. Then, multiple historical noise detection data corresponding to each suspected noise source location are called, and the historical noise detection data is subjected to spectrum analysis to obtain the historical noise detection spectrum. Then, according to each historical noise detection spectrum and the noise frequency range of the current area, the suspected noise source location is filtered to obtain the filtered suspected noise source location. In this process, the historical noise detection data corresponding to the suspected noise source location is used for spectrum analysis, and the suspected noise source location is filtered according to the historical spectrum and the noise frequency range of the current area. The key factor of the frequency characteristics of the noise is considered, and those interference factors that do not conform to the frequency characteristics can be excluded, further improving the accuracy of locating the noise source location. Then, in order to fully grasp the time and frequency characteristics of the noise source, the peak occurrence time of the noise source at each filtered suspected noise source location, as well as the frequency component and spectrum characteristics of the noise source will be determined based on the historical noise detection spectrum.

[0091] Then, based on the correspondence between the peak time of the noise source at the suspected noise source location and the peak time of noise, the suspected noise source location is filtered to obtain the location of the noise source. In the process of filtering the suspected noise source location, the noise frequency range of the current area is considered so that the entire positioning and characteristic analysis process can be adjusted according to the dynamic changes of the actual environment. The noise source is then classified based on the location of the noise source in each road section to determine the noise type of the noise source. Among them, it can be understood that the noise types include: traffic noise, industrial noise, construction noise, etc. By obtaining the noise attributes corresponding to the noise type of the noise source, the noise characteristics of each noise source can be determined based on the noise attributes of the noise source, the frequency components of the noise source, and the spectrum characteristics.

[0092] S104: Determine the physical structure to be adjusted of the guardrail according to the noise source and the noise characteristics, simulate and adjust the physical structure to be adjusted according to the digital twin model, determine the adjustment data of the physical structure to be adjusted, and obtain the noise reduction value corresponding to the adjustment data.

[0093] After determining the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the above step S103, in order to determine the noise reduction measures that match the current noise characteristics and thus achieve effective noise reduction, the physical structure to be adjusted of the guardrail will be determined based on the noise sources and noise characteristics, and then the physical structure to be adjusted will be simulated and adjusted based on the digital twin model, so as to determine the adjustment data of the physical structure to be adjusted and obtain the noise reduction value corresponding to the adjustment data.

[0094] Specifically, in one or more embodiments of the present specification, the physical structure to be adjusted of the guardrail is determined according to the noise source and the noise characteristics, the physical structure to be adjusted is simulated and adjusted according to the digital twin model, the adjustment data of the physical structure to be adjusted is determined, and the noise reduction value corresponding to the adjustment data is obtained, which specifically includes the following processes:

[0095] First, according to the noise source and the guardrail information of each road section, the guardrail adjustable physical structure of each road section is determined based on the guardrail information; it should be noted that the guardrail information includes: guardrail material, guardrail structure components, guardrail thickness, and guardrail height. It can be understood that different materials have different acoustic properties. For example, metals may have a strong reflection effect on high-frequency noise, while some composite materials may have better sound absorption performance; different arrangements and combinations of guardrail structure components will affect the propagation path and scattering effect of sound waves; changes in guardrail thickness and height will also change its ability to block and absorb noise, so by obtaining these guardrail information, it is possible to determine the physical structure of the guardrail that can be adjusted to achieve the purpose of noise reduction. Then, the historical noise control data corresponding to the adjustable physical structure is called, and the historical noise characteristics corresponding to each historical noise control data are determined. According to the matching relationship between the historical noise characteristics and the noise characteristics, the physical structure to be adjusted in the adjustable physical structure that can control the noise of each road section is determined. In this process, the blindness in the adjustment process is avoided by making adjustments with the help of historical practical experience, and the pertinence and success rate of the adjustment are improved. Then, according to the location of the noise source and the noise characteristics, the noise simulation is performed in the digital twin model, and the physical structure to be adjusted is adjusted in turn, and the simulation results are collected. Then, the noise reduction value corresponding to each parameter in the adjustment process of the physical structure to be adjusted is determined according to the simulation results, so as to determine the adjustment data of the physical structure to be adjusted according to the noise reduction value. The adjustment data is simulated twice according to the digital twin model to determine the noise reduction value corresponding to the adjustment data. The validity of the adjustment data is further verified through the precise simulation of the digital twin model, ensuring that the expected noise reduction effect can be achieved in actual operation. At the same time, the adjustment data can also be fine-tuned, which helps to improve the reliability and stability of the noise reduction solution.

[0096] S105: Determine operating parameters of the sound wave cancellation device on each road section according to the noise reduction value, the noise source and the noise characteristic, so as to control the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjust the physical structure to be adjusted based on the adjustment data to perform physical noise reduction.

[0097] In order to avoid the problem that the noise reduction effect of a single noise reduction method is not obvious, the operating parameters of the sound wave cancellation device are determined according to the noise reduction value, noise source and noise characteristics in the embodiment of this specification, and combined with the adjustment data of the physical structure to be adjusted, a personalized noise reduction scheme for the specific noise conditions of each road section is realized. At the same time, active noise reduction can accurately cancel noise of specific frequency and phase, and passive noise reduction after physical structure adjustment can change the noise propagation path, absorption and reflection noise from a macro perspective. This comprehensive noise reduction method can effectively reduce noise in a wider frequency range and a larger spatial range. Compared with a single noise reduction method, it can significantly improve the noise reduction effect. In addition, the physical structure to be adjusted is adjusted based on the adjustment data to ensure the accuracy of the physical noise reduction measures. This avoids blindly changing the physical structure, reduces unnecessary material and labor costs, and also ensures that the noise reduction effect after the physical structure is adjusted can cooperate with the active noise reduction measures to achieve the best comprehensive noise reduction effect.

[0098] Specifically, in one or more embodiments of the present specification, the operating parameters of the sound wave cancellation device on each road section are determined according to the noise reduction value, the noise source and the noise characteristics, which specifically includes the following process:

[0099] First, according to the noise characteristics and the noise source, the parameter adjustment range of each operating parameter corresponding to the sound wave cancellation device on each road section is determined; wherein the operating parameters include: filter parameters, phase parameters, power parameters, and this process can be customized for a specific noise environment, thereby improving the adaptability and accuracy of the sound wave cancellation device. Then, the historical operating parameter data and historical evaluation data of the sound wave cancellation device are input into a preset random forest or other machine learning model to determine the relationship between the noise cancellation result and the operating parameters, and use it as the objective function of the sound wave cancellation device. In this process, the machine learning model is used to determine the relationship between the noise cancellation result and the operating parameters, which can capture the nonlinear relationship between the complex noise characteristics and the operation of the device, and further improve the noise reduction effect. In order to obtain the optimal parameter combination, the parameter adjustment range of each operating parameter is traversed according to the preset step size to obtain the parameter combination of the operating parameters, and then the objective function value corresponding to each parameter combination is determined according to the objective function, and one or more optimal parameter combinations are determined by comparing the objective function values, which can systematically search for the optimal parameter configuration and avoid the tediousness and subjectivity of manual adjustment. The adjustment cost corresponding to the parameter adjustment of the one or more optimal parameter combinations is obtained, so as to screen the one or more optimal parameter combinations based on the adjustment cost, and obtain the operating parameters of the sound wave cancellation device on each road section. It should be noted that the adjustment cost may include information such as time cost and technical difficulty, which can be quantified by evaluating the feasibility of technical implementation and the required technical resources, and for example, technical difficulty can be quantified by evaluating the feasibility of technical implementation and the required technical resources. Therefore, after determining the optimal parameter combination, this step further considers the adjustment cost corresponding to the parameter adjustment, which helps to find a balance between noise reduction effect and cost and maximize cost-effectiveness. And by screening the optimal parameter combination with a lower adjustment cost, it can be ensured that in practical applications, a good noise reduction effect can be achieved without losing economic feasibility due to excessively high adjustment costs.

[0100] Further, in one or more embodiments of the present specification, after the sound wave cancellation device is controlled to perform active noise reduction based on the operating parameters and the physical structure to be adjusted is adjusted based on the adjustment data to perform physical noise reduction, the method further includes the following process:

[0101] Based on the preset measurement equipment of each road section in the current area, noise measurement is performed on each road section to obtain the noise detection spectrum after noise reduction. Then the noise detection spectrum after noise reduction is sorted according to the time sequence to compare the two adjacent noise detection spectra after noise reduction in sequence to obtain the noise reduction trend of each road section. Sorting and comparing the noise detection spectrum after noise reduction according to the time sequence can intuitively show the noise reduction trend, which is convenient for timely discovery of changes in noise reduction effect. If it is determined according to the noise reduction trend that the noise is reduced or the noise detection spectrum after noise reduction is within the noise frequency range of the current area, it means that the noise reduction means are effective and can maintain the operating parameters and physical structure to be adjusted of the sound wave cancellation device. For example, on a certain road section, the noise detection spectrum at 10 am shows that the noise level is 65 decibels, while the spectrum at 11 am shows that the noise level is 60 decibels, which indicates that the noise is on a downward trend. If the noise reduction trend shows that the noise is reduced, or the noise detection spectrum after noise reduction is within the noise frequency range of the current area, for example, the noise level allowed in the area is below 60 decibels, it means that the noise reduction means are effective. If the noise is rising according to the noise reduction trend and the noise detection spectrum after noise reduction is not within the noise frequency range of the current area, it means that the current noise reduction means have not achieved the expected effect on noise control. Therefore, the current high-incidence time of noise is determined based on the noise detection spectrum after noise reduction, and the operating parameters of the sound wave cancellation device on each road section and the adjustment data of the physical structure to be adjusted are iteratively updated. By iteratively updating the operating parameters of the sound wave cancellation device on each road section and the adjustment data of the physical structure to be adjusted, the noise reduction effect can be continuously optimized to ensure that the noise reduction means are always kept in the best state. This dynamic adjustment process helps to adapt to the ever-changing noise environment and improve the robustness and adaptability of the noise reduction system.

[0102] like Figure 2 As shown, one or more embodiments of this specification provide a road noise control system for an intelligent guardrail. Figure 2 It can be seen that in one or more embodiments of the present invention, a road noise control system of an intelligent guardrail includes:

[0103] The time determination unit 201 is used to obtain the noise detection spectrum of each road section in the current area, so as to determine the noise peak time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area;

[0104] An establishing unit 202 is used to obtain environmental data of each road section in the current area based on guardrail detection equipment preset in each road section in the current area, and establish a digital twin model of noise of each road section based on the environmental data and the noise detection spectrum simulation;

[0105] A characteristic determination unit 203 is used to determine the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model;

[0106] A simulation unit 204 is used to determine the physical structure to be adjusted of the guardrail according to the noise source and the noise characteristics, simulate and adjust the physical structure to be adjusted according to the digital twin model, determine adjustment data of the physical structure to be adjusted, and obtain a noise reduction value corresponding to the adjustment data;

[0107] The noise reduction unit 205 is used to determine the operating parameters of the sound wave cancellation device on each road section according to the noise reduction value, the noise source and the noise characteristics, so as to control the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjust the physical structure to be adjusted based on the adjustment data to perform physical noise reduction.

[0108] Furthermore, in one or more embodiments of the present specification, before determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, the system is further configured to:

[0109] Acquiring road network information of the current area to determine a road noise boundary point of the current area, so as to determine a noise impact area range corresponding to the current area according to a preset distance and the road noise boundary point;

[0110] Obtaining map information within the noise impact area to determine the sensitive area within the noise impact area, and obtaining the boundary contour of the sensitive area; wherein the types of the sensitive area include: residential area type, wildlife protection area type, and education area type;

[0111] Based on the type of the sensitive area, determining the allowable range of noise frequency of the boundary contour of the sensitive area; wherein the allowable range of noise frequency is determined based on expert experience or regulations;

[0112] Input the distance between the preset measuring equipment of each road section and the boundary contour and the allowable range of noise frequency of the boundary contour into the noise propagation model to determine the first allowable range of noise frequency;

[0113] According to the map information within the noise impact area, the obstacle between the sensitive area and the preset measurement device is determined, and the first noise frequency allowable range is corrected according to the noise blocking information corresponding to the obstacle to obtain the noise frequency range of the current area.

[0114] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0115] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0116] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A road section noise control method for an intelligent guardrail, characterized in that: The method comprises: Acquire the noise detection spectrum of each road section in the current area, so as to determine the peak noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area; Based on the guardrail detection equipment pre-installed in each road section of the current area, the environmental data of each road section in the current area is obtained, and the digital twin model of the noise of each road section is established based on the environmental data and the noise detection spectrum simulation; Determine the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model; Determine the physical structure of the guardrail to be adjusted according to the noise source and the noise characteristics, simulate and adjust the physical structure to be adjusted according to the digital twin model, determine adjustment data of the physical structure to be adjusted, and obtain the noise reduction value corresponding to the adjustment data; According to the noise reduction value, the noise source and the noise characteristic, the operating parameters of the sound wave cancellation device on each road section are determined to control the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjust the physical structure to be adjusted based on the adjustment data to perform physical noise reduction.

2. The road section noise control method of a smart guardrail according to claim 1 is characterized in that: The acquiring of the noise detection spectrum of each road section in the current area to determine the peak noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area specifically includes: Based on the preset measurement equipment of each road section in the current area, the noise of each road section is measured to obtain the noise intensity of each road section in the current area at different frequencies, and the noise detection spectrum of each road section in the current area is determined according to the noise intensity at different frequencies; Screening the peak value of the noise detection frequency to determine the main noise frequency components of each road section; Comparing each of the main noise frequency components with the noise frequency range of the current area to determine the noise time period of each road section exceeding the noise frequency range; Comparing the noise time period with a preset noise time unit, if the noise time period exceeds the preset noise time unit, taking the noise time period as an initial high noise occurrence time; The ratio of the number of occurrences of the initial high noise occurrence time to the number of detections within a preset detection period is obtained. If it is determined that the ratio is greater than the preset ratio, the initial high noise occurrence time is used as the high noise occurrence time.

3. The road section noise control method of a smart guardrail according to claim 1 is characterized in that: Before determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, the method further includes: Acquiring road network information of the current area to determine a road noise boundary point of the current area, so as to determine a noise impact area range corresponding to the current area according to a preset distance and the road noise boundary point; Obtaining map information within the noise impact area to determine the sensitive area within the noise impact area, and obtaining the boundary contour of the sensitive area; wherein the types of the sensitive area include: residential area type, wildlife protection area type, and education area type; Based on the type of the sensitive area, determining the allowable range of noise frequency of the boundary contour of the sensitive area; wherein the allowable range of noise frequency is determined based on expert experience or regulations; Input the distance between the preset measuring equipment of each road section and the boundary contour and the allowable range of noise frequency of the boundary contour into the noise propagation model to determine the first allowable range of noise frequency; According to the map information within the noise impact area, the obstacle between the sensitive area and the preset measurement device is determined, and the first noise frequency allowable range is corrected according to the noise blocking information corresponding to the obstacle to obtain the noise frequency range of the current area.

4. The road section noise control method of a smart guardrail according to claim 3 is characterized in that: A digital twin model of the noise of each road section is established based on the environmental data and the noise detection spectrum simulation, specifically including: Performing data preprocessing on the environmental data to obtain processed environmental data; According to the geographical location information of the current area, the environmental data is associated with the road network information of the current area, and the associated environmental data and the road network information of the current area are input into a preset simulation tool to construct a three-dimensional model of the current area; According to the noise collection position corresponding to the noise detection spectrum, the noise detection spectrum data is mapped to the three-dimensional model of the current area to obtain an initial digital twin model of the noise of each road section; The propagation path corresponding to the noise of each road section is determined according to the noise propagation model, so as to identify the sensitive area corresponding to the noise of each road section according to the propagation path and the sensitive area of ​​the current area, and associate the sensitive area with each road section in the initial digital twin model to establish a digital twin model of the noise of each road section.

5. The road section noise control method of a smart guardrail according to claim 1 is characterized in that: Based on the digital twin model, the noise sources during the peak noise occurrence time of each road section and the noise characteristics of each noise source are determined, including: Determine the noise distribution of each road section according to the digital twin model, and determine one or more suspected noise source locations according to the noise distribution and the noise propagation model corresponding to each road section; Calling a plurality of historical noise detection data corresponding to each suspected noise source position, and performing spectrum analysis on the historical noise detection data to obtain a historical noise detection spectrum; Filtering the suspected noise source position according to each of the historical noise detection spectra and the noise frequency range of the current area to obtain a filtered suspected noise source position; Based on the historical noise detection spectrum, determine the peak time of the noise source at each of the filtered suspected noise source locations, as well as the frequency components and spectrum characteristics of the noise source; According to the correspondence between the peak time of the noise source at the suspected noise source location and the peak time of the noise, the suspected noise source location is filtered to obtain the location of the noise source; Classifying the noise sources based on the locations of the noise sources on each road section to determine the noise types of the noise sources; wherein the noise types include: traffic noise, industrial noise, and construction noise; The noise attribute corresponding to the noise type of the noise source is obtained, so as to determine the noise characteristic of each noise source based on the noise attribute of the noise source, the frequency component and the spectrum characteristic of the noise source.

6. The road section noise control method of a smart guardrail according to claim 1 is characterized in that: Determining the physical structure to be adjusted of the guardrail according to the noise source and the noise characteristics, simulating and adjusting the physical structure to be adjusted according to the digital twin model, determining adjustment data of the physical structure to be adjusted, and obtaining the noise reduction value corresponding to the adjustment data, specifically includes: According to the noise source and the guardrail information of each road section, the guardrail of each road section can be adjusted in physical structure based on the guardrail information; wherein the guardrail information includes: guardrail material, guardrail structure components, guardrail thickness, and guardrail height; Retrieving historical noise control data corresponding to the adjustable physical structure, and determining historical noise characteristics corresponding to each of the historical noise control data; Determining, according to the matching relationship between the historical noise characteristics and the noise characteristics, a physical structure to be adjusted in the adjustable physical structure that can control the noise of each of the road sections; Performing noise simulation in the digital twin model based on the location of the noise source and the noise characteristics, adjusting the physical structure to be adjusted in turn, and collecting simulation results; Determine the noise reduction value corresponding to each parameter in the adjustment process of the physical structure to be adjusted according to the simulation result, and determine the adjustment data of the physical structure to be adjusted according to the noise reduction value; A secondary simulation is performed on the adjustment data based on the digital twin model to determine the noise reduction value corresponding to the adjustment data.

7. The road section noise control method of a smart guardrail according to claim 1 is characterized in that: Determining the operating parameters of the sound wave cancellation device on each road section according to the noise reduction value, the noise source and the noise characteristics, specifically including: According to the noise characteristics and the noise source, the parameter adjustment range of each operating parameter corresponding to the sound wave cancellation device on each road section is determined; wherein the operating parameters include: filter parameters, phase parameters, and power parameters; Inputting historical operating parameter data and historical evaluation data of the acoustic wave cancellation device into a preset machine learning model such as a random forest to determine the relationship between the noise cancellation result and the operating parameters, and using it as the objective function of the acoustic wave cancellation device; Within the parameter adjustment range of each of the operating parameters, traverse according to a preset step length to obtain a parameter combination of the operating parameters; Determine the objective function value corresponding to each of the parameter combinations according to the objective function, and determine one or more optimal parameter combinations by comparing the objective function values; The adjustment costs corresponding to the parameter adjustments of the one or more optimal parameter combinations are obtained, so as to screen the one or more optimal parameter combinations based on the adjustment costs and obtain the operating parameters of the sound wave canceling device on each road section.

8. The road section noise control method of a smart guardrail according to claim 1, characterized in that: After controlling the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjusting the physical structure to be adjusted to perform physical noise reduction based on the adjustment data, the method further includes: Based on the pre-installed measurement equipment on each road section in the current area, noise measurement is performed on each road section to obtain the noise detection spectrum after noise reduction; Sorting the noise detection spectra after noise reduction based on the time sequence, so as to sequentially compare two adjacent noise detection spectra after noise reduction to obtain the noise reduction trend of each of the road sections; If it is determined based on the noise reduction trend that the noise is decreasing or the noise detection spectrum after the noise reduction is within the noise frequency range of the current area, then maintaining the operating parameters of the sound wave cancellation device and the physical structure to be adjusted; If it is determined based on the noise reduction trend that the noise is rising and the noise detection spectrum after noise reduction is not within the noise frequency range of the current area, the current noise peak time is determined based on the noise detection spectrum after noise reduction, and the operating parameters of the sound wave cancellation device on each road section and the adjustment data of the physical structure to be adjusted are iteratively updated.

9. A road noise control system for an intelligent guardrail, characterized in that: The system comprises: A time determination unit, used to obtain a noise detection spectrum of each road section in the current area, so as to determine a high noise occurrence time of each road section in the current area according to the noise detection spectrum and a noise frequency range of the current area; An establishing unit is used to obtain environmental data of each road section in the current area based on guardrail detection equipment preset in each road section in the current area, and establish a digital twin model of noise of each road section based on the environmental data and the noise detection spectrum simulation; A characteristic determination unit, used to determine the noise sources during the high noise occurrence time of each road section and the noise characteristics of each noise source based on the digital twin model; A simulation unit, used to determine the physical structure to be adjusted of the guardrail according to the noise source and the noise characteristics, to simulate and adjust the physical structure to be adjusted according to the digital twin model, to determine adjustment data of the physical structure to be adjusted, and to obtain a noise reduction value corresponding to the adjustment data; The noise reduction unit is used to determine the operating parameters of the sound wave cancellation device on each road section according to the noise reduction value, the noise source and the noise characteristics, so as to control the sound wave cancellation device to perform active noise reduction based on the operating parameters, and adjust the physical structure to be adjusted based on the adjustment data to perform physical noise reduction.

10. The road section noise control system of the intelligent guardrail according to claim 9, characterized in that: Before determining the high noise occurrence time of each road section in the current area according to the noise detection spectrum and the noise frequency range of the current area, the system is further used to: Acquiring road network information of the current area to determine a road noise boundary point of the current area, so as to determine a noise impact area range corresponding to the current area according to a preset distance and the road noise boundary point; Obtaining map information within the noise impact area to determine the sensitive area within the noise impact area, and obtaining the boundary contour of the sensitive area; wherein the types of the sensitive area include: residential area type, wildlife protection area type, and education area type; Based on the type of the sensitive area, determining the allowable range of noise frequency of the boundary contour of the sensitive area; wherein the allowable range of noise frequency is determined based on expert experience or regulations; Input the distance between the preset measuring equipment of each road section and the boundary contour and the allowable range of noise frequency of the boundary contour into the noise propagation model to determine the first allowable range of noise frequency; According to the map information within the noise impact area, the obstacle between the sensitive area and the preset measurement device is determined, and the first noise frequency allowable range is corrected according to the noise blocking information corresponding to the obstacle to obtain the noise frequency range of the current area.

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