Cooling tower group sound insulation blocking system and method based on big data self-adaption

Abstract

The invention discloses a cooling tower group sound insulation blocking system and method based on big data self-adaption, and the system comprises a noise monitoring subsystem, an environmental parameter monitoring subsystem, a sound insulation blocking subsystem and a data center, and the noise monitoring subsystem comprises noise sensors which are distributed around a cooling tower group and at key positions. Acquiring noise data in real time and uploading the noise data to a data center; the environmental parameter monitoring subsystem comprises a wind direction sensor, a wind speed sensor, an air temperature sensor and an air humidity sensor, monitors environmental parameters such as wind direction, wind speed, temperature and humidity, and provides basic data for a noise control strategy. The invention has the advantages that: 1, a sound insulation barrier is arranged, and an air inlet silencer is cancelled, so that the manufacturing cost is reduced; 2, a sound insulation barrier is arranged, so that maintenance is convenient; 3, a sound insulation barrier is arranged, the resistance of the cooling tower is not increased, and the performance of the cooling tower is not influenced; 4, a sound insulation barrier is arranged, so that the tolerance is very good, and the influence of local climate is avoided;

Description

Technical Field

[0001] The present invention relates to the technical field of cooling tower noise reduction, and specifically to a sound insulation and barrier system and method for a cooling tower group based on big data adaptability. Background Technique

[0002] The cooling tower is one of the main equipment in the cooling system of a gas-fired power plant. It maintains the back pressure at the outlet of the steam turbine and enables the thermodynamic system to achieve the Rankine cycle, directly affecting the thermal economy and operation reliability of the unit and the power plant. The commonly used mechanical draft cooling tower in a gas-fired power plant is a double-sided inlet mechanical draft cooling tower, and its structure is as Figure 1 shown. The cooling water is sent into the water distribution system through the water distribution pipe, and exchanges heat with the air in the water distribution area, packing area and rain area in sequence. After passing through the rain area, it falls into the sump at the bottom of the tower to complete the heat exchange process. A fan is installed at the air outlet of the tower top, and the fan is driven by an electric motor. Without a cooling tower, the steam coming out of the steam turbine cannot be cooled into condensate and sent back to the boiler for reuse, the waste heat of the exhaust gas after the steam turbine generates electricity cannot establish a cycle, and the residual heat cannot be recovered, so the thermal economy of the power plant cannot be improved. However, when the cooling tower is close to the plant boundary or a sensitive point, if the noise exceeds the standard by a large amount, generally a sound insulation cover needs to be installed as a whole to enclose the cooling tower to block the noise in the propagation path. The sound insulation cover cuts off the air inlet and exhaust channels of the cooling tower, so the sound insulation cover must be equipped with an air inlet muffler 5 and an exhaust muffler 6, and a sound insulation door is provided for personnel to perform maintenance.

[0003] The current technology has the following disadvantages: 1. The setting of the air inlet muffler increases the construction cost of the project. 2. The setting of the air inlet muffler is not conducive to the maintenance of the cooling tower. 3. The setting of the air inlet muffler increases the wind resistance of the cooling tower and has a certain impact on the thermal performance. 4. In humid areas, the air inlet muffler is prone to corrosion. Summary of the Invention

[0004] (I) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides a sound insulation and barrier system and method for a cooling tower group based on big data adaptability, which has the following advantages: 1) Cancel the air inlet muffler to reduce the construction cost; 2) Set up a sound insulation and barrier for convenient maintenance; 3) Set up a sound insulation and barrier without increasing the resistance of the cooling tower itself and without affecting the performance of the cooling tower; 4) Set up a sound insulation and barrier with very good tolerance and not affected by the local climate, etc., and solves the problems in the above background technique.

[0006] (II) Technical Solutions

[0007] To achieve the above object, the present invention provides the following technical solution: A sound insulation and barrier system for a cooling tower group based on big data adaptability, including a noise monitoring subsystem, an environmental parameter monitoring subsystem, a sound insulation and barrier subsystem and a data center;

[0008] The noise monitoring subsystem includes noise sensors distributed around the cooling tower group and at key positions, which collect noise data in real time and upload it to the data center;

[0009] The environmental parameter monitoring subsystem includes a wind direction sensor, a wind speed sensor, an air temperature sensor, and an air humidity sensor, which monitor environmental parameters such as wind direction, wind speed, temperature, and humidity, providing basic data for the noise control strategy;

[0010] The sound insulation and barrier subsystem is located between two rows of cooling towers, and a sound insulation and barrier (sound insulation screen + sound insulation muffler) is set between the two rows of cooling towers. The height of the screen and the volume of the muffler need to be set according to the actual situation.

[0011] The structural type of the sound insulation and barrier adopts a galvanized backboard (double-sided plastic spraying treatment) + sound-absorbing cotton + hydrophobic glass cloth + aluminum alloy perforated facing board (double-sided plastic spraying treatment).

[0012] The structural type of the sound insulation muffler adopts a muffler shell and a sound-absorbing sheet (glass wool + sound-absorbing material facing board + glass cloth + skeleton + sound-absorbing sheet flow guide tip);

[0013] The data center collects and analyzes noise monitoring and environmental parameter data, predicts the noise propagation trend through an algorithm model, and generates sound insulation and barrier adjustment data.

[0014] Preferably, in the sound insulation and barrier subsystem, the sound insulation screen

[0015] 1) The backboard of the screen body adopts galvanized sheet + double-sided plastic spraying. The backboard of the screen body adopts galvanized sheet with a thickness of not less than 1.2 mm, and the coating weight is not less than 275 g / m2. At the same time, the surface (double-sided) is plastic sprayed, and the single-sided spraying thickness is not less than 80 μm;

[0016] 2) The skeleton of the backboard of the screen body is folded with galvanized sheet with a thickness of not less than 2.0 mm, and the coating weight is not less than 275 g / m2. At the same time, the surface (double-sided) is plastic sprayed, and the single-sided spraying thickness is not less than 80 μm. The skeleton spacing ≤ 500 mm × 500 mm;

[0017] 3) The sound-absorbing cotton adopts ultra-fine glass wool. The bulk density of the ultra-fine glass wool is not less than 48 kg / m 3 , the moisture content should not be greater than 1%, the mass moisture absorption rate should not be greater than 5%, and the water repellency rate should not be less than 98%. And it should have appropriate flow resistance, uniform pores, high sound absorption performance and chemical stability. The allowable bulk density error of the sound-absorbing cotton should not exceed ±5%, the impurity content is not greater than 3%, the sound absorption coefficient NRC ≥ 0.95, the fiber diameter is less than 6 μm, without slag balls, moisture-proof and non-water-absorbing. The combustion performance of the glass wool is Class A non-combustible, and the glass wool should be wrapped with plain weave non-alkali hydrophobic glass cloth;

[0018] 4) Corrugated perforated aluminum alloy panel for protecting holes, with a thickness of not less than 1.2 mm, a perforation rate of ≥ 23%, a hole diameter of Φ3 mm, and the surface (both sides) of the corrugated perforated aluminum alloy panel is spray-coated, with a single-sided spraying thickness of not less than 80 μm;

[0019] 5) Steel structure, using H-shaped steel as the support structure. The bidder shall design the diagonal bracing support structure according to the requirements of wind load resistance and insert the barrier into the main column structure. The support structure adopts the hot-dip galvanizing process, and the average coating weight is not less than 610 g / m2.

[0020] Preferably, in the sound insulation and isolation subsystem, there is a sound insulation muffler.

[0021] 1) The muffler shell is made of galvanized sheet with a thickness of not less than 1.5 mm, the coating weight is not less than 275 g / m2, and it is spray-coated on both sides, with a single-sided spraying thickness of not less than 80 μm;

[0022] 2) Sound absorption sheet (unit)

[0023] Glass wool, using ultra-fine glass wool; the bulk density of the ultra-fine glass wool is not less than 48 kg / m 3 , the moisture content should not be greater than 1%, the mass moisture absorption rate should not be greater than 5%, the water repellency rate should not be less than 98%, and it should have appropriate flow resistance, uniform pores, high sound absorption performance and chemical stability. The allowable bulk density error of the sound absorption cotton should not exceed ±5%, the impurity content should not be greater than 3%, the sound absorption coefficient NRC≥0.95, the fiber diameter is less than 6 μm, without slag balls, moisture-proof and non-absorbent. The combustion performance of the glass wool is Class A non-combustible, and the glass wool should be wrapped with plain weave alkali-free water-repellent glass cloth;

[0024] Sound absorption material protection panel, made of highly corrosion-resistant 3003H24 aluminum alloy plate with a thickness of not less than 1.5 mm, a perforation rate of ≥ 23%, a hole diameter of φ3 mm, and the aluminum alloy plate is spray-coated on both sides, with a single-sided spraying thickness of not less than 80 μm;

[0025] The glass cloth for wrapping the sound absorption material should be plain weave alkali-free water-repellent glass cloth;

[0026] Skeleton: The sound absorption sheet skeleton is made of galvanized sheet with a thickness of not less than 2.0 mm, and the coating weight is not less than 275 g / m2.

[0027] It is spray-coated on both sides, with a single-sided spraying thickness of not less than 80 μm.

[0028] Sound absorption sheet flow guide tip: Made of highly corrosion-resistant 3003H24 aluminum alloy plate.

[0029] The core advantages of the present invention are: 1) Set sound insulation and isolation, cancel the inlet muffler, and reduce the construction cost.

[0030] 2) Set sound insulation and isolation, which is convenient for maintenance.

[0031] 3) Set up sound insulation barriers without increasing the resistance of the cooling tower itself and without affecting the performance of the cooling tower.

[0032] 4) Set up sound insulation barriers with very good tolerance and not affected by the local climate.

[0033] Since the splash noise of the cooling tower belongs to medium and high frequency noise; compared with medium and low frequency noise, medium and high frequency noise has the characteristic of short propagation distance. Sound insulation barriers are mainly used to block the direct sound propagation of the noise source. Setting up a sound insulation barrier or a sound insulation and absorption barrier between the noise source and the receiver can effectively control the propagation of medium and high frequency noise of the noise source and obtain a relatively quiet environment in the "sound shadow" area of the sound barrier. The closer the barrier is to the sound source, the larger the sound shadow area, the larger the sound insulation area, and the more obvious the sound insulation effect.

[0034] Based on the characteristics of the cooling tower splash noise source and the mechanism of the sound insulation barrier, considering the air intake requirements of the cooling tower, a sound insulation and muffler is installed in the lower part of the barrier. Placed between two groups of cooling tower clusters, it forms a sound insulation barrier for the two groups of cooling tower clusters. The volume of the air intake muffler of the cooling tower can be adjusted according to needs; the total height of the cooling tower can also be adjusted according to needs. In this way, the inlet noise between the two rows of cooling towers will be blocked between the two barriers; at the same time, the air intake of the cooling tower inlet is not blocked.

[0035] A method for sound insulation barrier of a cooling tower cluster based on big data adaptation includes the following steps:

[0036] 1), Data preprocessing

[0037] Data collection: Receive real-time noise data (such as decibel value, frequency distribution) from the noise monitoring subsystem;

[0038] Receive wind direction, wind speed, temperature, and humidity data from the environmental parameter monitoring subsystem;

[0039] Data cleaning: Remove outliers or incorrect data (such as extreme values generated by sensor failures); interpolate or estimate missing data;

[0040] Data integration:

[0041] Align the noise data and environmental parameter data according to the timestamp to form a unified data set;

[0042] 2), Noise propagation model, basic model establishment:

[0043] Adopt an acoustic propagation model (such as the geometric acoustics method, wave equation method, etc.) as the basic model for noise propagation, considering the influence of fixed factors such as terrain and building distribution on the sound field;

[0044] Environmental parameter integration, taking wind direction and wind speed as dynamic input parameters to adjust the noise propagation direction and attenuation coefficient;

[0045] Consider the influence of temperature and humidity on the sound speed and acoustic wave attenuation, and correct the model parameters;

[0046] 3), Prediction and optimization, Noise prediction:

[0047] Based on the current environmental parameters and noise source data, use the noise propagation model to predict the noise distribution in the future for a period of time; consider the superposition effect of noise and complex phenomena such as reflection and diffraction;

[0048] Optimization strategy generation:

[0049] According to the prediction results, evaluate the noise reduction effects under different sound insulation barriers and sound insulation muffler configurations; consider the normal air intake requirements of the cooling tower to ensure that the optimization strategy will not significantly affect the cooling efficiency; use optimization algorithms (such as genetic algorithms, particle swarm optimization, etc.) to search for the best configuration plan;

[0050] 4), Instruction generation and feedback: Instruction generation: Convert the optimized sound insulation barrier and sound insulation muffler configuration plan into specific adjustment instructions; the instructions include detailed information such as position, height, angle, material type, etc.

[0051] Instruction execution and feedback: Send the adjustment instructions to the sound insulation and isolation subsystem for execution; monitor the changed noise after adjustment, and collect feedback data for model verification and optimization;

[0052] 5), Model verification and update, Model verification: Compare the noise data before and after adjustment, and evaluate the accuracy of the model prediction; analyze the error sources, and adjust the model parameters or algorithms.

[0053] Model update: Regularly collect new environmental parameters and noise data, update the model database, and continuously optimize the noise propagation model and optimization algorithm according to the feedback data.

[0054] (III) Beneficial effects

[0055] Compared with the prior art, the present invention provides a sound insulation and isolation system and method for a group of cooling towers based on big data adaptability, and has the following beneficial effects:

[0056] 1. The sound insulation and barrier system and method for cooling tower groups based on big data adaptation. The system includes a noise monitoring subsystem, an environmental parameter monitoring subsystem, a sound insulation and barrier subsystem, and a data center. The method includes data preprocessing, establishment of a noise propagation model and a basic model, prediction and optimization, noise prediction, instruction generation and feedback, model verification and update, and model verification steps. According to big data (noise data, environmental parameters), the configuration of the sound insulation and barrier subsystem for cooling tower groups can be adjusted. Based on the characteristics of the cooling tower water spraying noise source and the mechanism of the sound insulation barrier, considering the air intake requirements of the cooling tower, a sound insulation and muffler is installed in the lower part of the barrier. Placed between two groups of cooling tower groups, two sound insulation and barriers for cooling tower groups are formed. The volume of the air intake muffler of the cooling tower can be adjusted as needed; the total height of the cooling tower can also be adjusted as needed. In this way, the air intake noise between two rows of cooling towers will be blocked between the two barriers; at the same time, the air intake of the cooling tower air inlet is unobstructed;

[0057] Meanwhile, by using big data (environmental parameters such as noise monitoring, wind direction, wind speed, temperature, humidity, etc.), the sound insulation and barrier system for cooling tower groups is made adaptive, and its position, height, angle, and material are adjusted adaptively to match different usage scenarios.

[0058] 2. The sound insulation and barrier system and method for cooling tower groups based on big data adaptation. 1) Set up a sound insulation and barrier, cancel the air intake muffler, and reduce the construction cost; 2) Set up a sound insulation and barrier, which is convenient for maintenance; 3) Set up a sound insulation and barrier, which does not increase the resistance of the cooling tower itself and does not affect the performance of the cooling tower; 4) Set up a sound insulation and barrier, which has very good tolerance and is not affected by the local climate. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a schematic structural diagram of a sound insulation and barrier system for cooling tower groups based on big data adaptation proposed by the present invention;

[0060] Figure 2 It is a schematic diagram of a sound insulation and barrier method for cooling tower groups based on big data adaptation proposed by the present invention;

[0061] Figure 3 It is an elevation view of the sound insulation and barrier of the mechanical draft cooling tower in the present invention;

[0062] Figure 4 It is a plan view of the sound insulation and barrier of the mechanical draft cooling tower in the present invention;

[0063] Figure 5 It is a simulated diagram of the cooling tower noise after using the sound insulation and barrier in the present invention.

[0064] In the figure: 1 - sound insulation barrier, 2 - sound insulation and muffler, 3 - cooling tower, 4 - noise reduction between tower groups, 5 - air intake muffler, 6 - exhaust muffler. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0066] Please refer to Figures 1-4 , a sound insulation and barrier system for a cooling tower group based on big data adaptability, including a noise monitoring subsystem, an environmental parameter monitoring subsystem, a sound insulation and barrier subsystem, and a data center;

[0067] The noise monitoring subsystem includes noise sensors distributed around the cooling tower group 3 and at key positions, which collect noise data in real time and upload it to the data center;

[0068] The environmental parameter monitoring subsystem includes a wind direction sensor, a wind speed sensor, an air temperature sensor, and an air humidity sensor, which monitor environmental parameters such as wind direction, wind speed, temperature, and humidity, and provide basic data for noise control strategies;

[0069] The sound insulation and barrier subsystem is located between two rows of cooling towers 3, and a sound insulation and barrier is set between the two rows of cooling towers 3, including a sound insulation barrier 1 on the upper part and a sound insulation muffler 2 on the lower part. The height of the barrier and the volume of the muffler need to be set according to the actual situation.

[0070] The structural type of the sound insulation and barrier adopts a galvanized backboard (double-sided plastic spraying treatment) + sound-absorbing cotton + hydrophobic glass cloth + aluminum alloy perforated facing board (double-sided plastic spraying treatment).

[0071] The structural type of the sound insulation muffler adopts a muffler housing, a sound-absorbing sheet (glass wool + sound-absorbing material facing board + glass cloth + skeleton + sound-absorbing sheet flow guide tip);

[0072] The data center collects and analyzes noise monitoring and environmental parameter data, predicts the noise propagation trend through an algorithm model, and generates sound insulation and barrier adjustment data.

[0073] Preferably, in the sound insulation and barrier subsystem, the sound insulation barrier

[0074] 1) The backboard of the screen body adopts galvanized sheet + double-sided plastic spraying. The backboard of the screen body adopts galvanized sheet with a thickness of not less than 1.2 mm, and the coating weight is not less than 275 g / m2. At the same time, the surface (double-sided) is plastic sprayed, and the single-sided spraying thickness is not less than 80 μm;

[0075] 2) The screen backplane framework is folded from galvanized steel sheets with a thickness of not less than 2.0 mm, a coating weight of not less than 275 g / m2, and is spray-coated on the surface (both sides) with a single-sided spraying thickness of not less than 80 μm. The framework spacing is ≤ 500 mm × 500 mm;

[0076] 3) Sound-absorbing cotton, made of ultra-fine glass wool, with a bulk density of ultra-fine glass wool of not less than 48 kg / m 3 , the moisture content should not be greater than 1%, the mass moisture absorption rate should not be greater than 5%, and the water repellency rate should not be less than 98%. And it should have an appropriate flow resistance, uniform pores, high sound absorption performance and chemical stability. The allowable bulk density error of the sound-absorbing cotton should not exceed ±5%, the impurity content should not be greater than 3%, the sound absorption coefficient NRC ≥ 0.95, the fiber diameter is less than 6 μm, without slag balls, moisture-proof and non-absorbent. The glass wool has a combustion performance of Class A non-combustible, and the glass wool should be wrapped with plain weave alkali-free water-repellent glass cloth;

[0077] 4) Profiled perforated faceplate made of aluminum alloy, with a thickness of not less than 1.2 mm, a perforation rate of ≥ 23%, a hole diameter of Φ3 mm, and the profiled perforated faceplate is spray-coated on the surface (both sides) with a single-sided spraying thickness of not less than 80 μm;

[0078] 5) Steel structure, using H-shaped steel as the support structure. The tenderer should design the diagonal bracing structure according to the wind load requirements and insert the barrier into the main column structure. The support structure adopts the hot-dip galvanizing process, and the average coating amount is not less than 610 g / m2.

[0079] Example 1: In the sound insulation and isolation subsystem, the sound insulation muffler,

[0080] 1) The muffler shell is made of galvanized steel sheets with a thickness of not less than 1.5 mm, a coating weight of not less than 275 g / m2, and is spray-coated on both sides with a single-sided spraying thickness of not less than 80 μm;

[0081] 2) Sound-absorbing sheet (unit)

[0082] Glass wool, made of ultra-fine glass wool,; the bulk density of ultra-fine glass wool is not less than 48 kg / m 3 , the moisture content should not be greater than 1%, the mass moisture absorption rate should not be greater than 5%, the water repellency rate should not be less than 98%, and it should have an appropriate flow resistance, uniform pores, high sound absorption performance and chemical stability. The allowable bulk density error of the sound-absorbing cotton should not exceed ±5%, the impurity content should not be greater than 3%, the sound absorption coefficient NRC ≥ 0.95, the fiber diameter is less than 6 μm, without slag balls, moisture-proof and non-absorbent. The glass wool has a combustion performance of Class A non-combustible, and the glass wool should be wrapped with plain weave alkali-free water-repellent glass cloth;

[0083] The sound-absorbing material faceplate is made of high-corrosion-resistant 3003H24 aluminum alloy sheets with a thickness of not less than 1.5 mm, a perforation rate of ≥ 23%, a hole diameter of φ3 mm, and the aluminum alloy sheets are spray-coated on both sides with a single-sided spraying thickness of not less than 80 μm;

[0084] The glass cloth wrapping the sound-absorbing material shall be plain weave non-alkali water-repellent glass cloth;

[0085] Skeleton: The skeleton of the sound-absorbing panel is made of galvanized sheet with a thickness of not less than 2.0 mm, and the coating weight is not less than 275 g / m2.

[0086] It is double-sided sprayed with plastic, and the thickness of single-sided spraying is not less than 80 μm.

[0087] Flow guiding tips of the sound-absorbing panel: It is made of highly corrosion-resistant 3003H24 aluminum alloy plate.

[0088] In the sound insulation barrier subsystem, the sound insulation barrier

[0089] 1) The back panel of the screen body is made of galvanized sheet + double-sided sprayed with plastic. The back panel of the screen body uses galvanized sheet with a thickness of not less than 1.2 mm, and the coating weight is not less than 275 g / m2. At the same time, the surface (double-sided) is sprayed with plastic, and the thickness of single-sided spraying is not less than 80 μm;

[0090] 2) The skeleton of the back panel of the screen body is folded with galvanized sheet with a thickness of not less than 2.0 mm, and the coating weight is not less than 275 g / m2. At the same time, the surface (double-sided) is sprayed with plastic, and the thickness of single-sided spraying is not less than 80 μm. The distance between the skeletons ≤ 500 mm × 500 mm;

[0091] 3) Sound-absorbing cotton, made of ultra-fine glass wool. The bulk density of the ultra-fine glass wool is not less than 48 kg / m 3 , the moisture content should not be greater than 1%, the mass moisture absorption rate should not be greater than 5%, and the water-repellent rate should not be less than 98%. And it should have appropriate flow resistance, uniform pores, high sound-absorbing performance and chemical stability. The allowable bulk density error of the sound-absorbing cotton should not exceed ±5%, the impurity content should not be greater than 3%, the sound-absorbing coefficient NRC ≥ 0.95, the fiber diameter is less than 6 μm, without slag balls, moisture-proof and non-absorbent. The combustion performance of the glass wool is Class A non-combustible, and the glass wool should be wrapped with plain weave non-alkali water-repellent glass cloth;

[0092] 4) Profiled perforated aluminum alloy panel for sound absorption, with a thickness of not less than 1.2 mm, a perforation rate ≥ 23%, a hole diameter of Φ3 mm. The surface (double-sided) of the profiled perforated aluminum alloy panel for sound absorption is sprayed with plastic, and the thickness of single-sided spraying is not less than 80 μm;

[0093] 5) Steel structure, using H-shaped steel as the support structure. The bidder should design the diagonal bracing support structure according to the wind load requirements and insert the barrier into the main column structure. The support structure adopts the hot-dip galvanizing process, and the average coating amount is not less than 610 g / m2.

[0094] Example 2: As Figure 5As shown in the figure, it is the simulated diagram of the noise of the cooling tower after using sound insulation and isolation. It can be seen from the figure that the noise decreases from the inside to the outside in turn. The noise of the outermost layer is only about 50 decibels. The noise of the cooling tower is greatly reduced and hardly has an impact on the environment.

[0095] A sound insulation and isolation method for a cooling tower group based on big data self - adaptation, comprising the following steps:

[0096] 1), Data pre - processing

[0097] Data collection: Receive real - time noise data (such as decibel value, frequency distribution) from the noise monitoring subsystem;

[0098] Receive wind direction, wind speed, temperature, and humidity data from the environmental parameter monitoring subsystem;

[0099] Data cleaning: Remove outliers or incorrect data (such as extreme values generated by sensor failures); Interpolate or estimate missing data;

[0100] Data integration:

[0101] Align the noise data and environmental parameter data according to the time stamp to form a unified data set;

[0102] 2), Noise propagation model, basic model establishment:

[0103] Adopt an acoustic propagation model (such as the geometric acoustics method, wave equation method, etc.) as the basic model of noise propagation, and consider the influence of fixed factors such as terrain and building distribution on the sound field;

[0104] Environmental parameter integration, take wind direction and wind speed as dynamic input parameters to adjust the noise propagation direction and attenuation coefficient;

[0105] Consider the influence of temperature and humidity on the sound speed and sound wave attenuation, and correct the model parameters;

[0106] 3), Prediction and optimization, noise prediction:

[0107] Based on the current environmental parameters and noise source data, use the noise propagation model to predict the noise distribution in the future for a period of time; Consider the superposition effect of noise and complex phenomena such as reflection and diffraction;

[0108] Optimization strategy generation:

[0109] According to the prediction results, evaluate the noise reduction effects under different sound insulation barriers and sound insulation mufflers configurations; Consider the normal air intake requirements of the cooling tower to ensure that the optimization strategy will not significantly affect the cooling efficiency; Use an optimization algorithm (such as genetic algorithm, particle swarm optimization, etc.) to search for the best configuration plan;

[0110] 4) Instruction Generation and Feedback: Instruction Generation: Convert the optimized sound insulation barrier and sound insulation and muffler configuration plan into specific adjustment instructions; the instructions include detailed information such as position, height, angle, material type, etc.

[0111] Instruction Execution and Feedback: Send the adjustment instructions to the sound insulation and isolation subsystem for execution; monitor the noise changes after adjustment, and collect feedback data for model verification and optimization;

[0112] 5) Model Verification and Update, Model Verification: Compare the noise data before and after adjustment, and evaluate the accuracy of model prediction; analyze the error sources and adjust the model parameters or algorithms.

[0113] Model Update: Regularly collect new environmental parameters and noise data, update the model database, and continuously optimize the noise propagation model and optimization algorithm according to the feedback data.

[0114] In summary, for the large data adaptive sound insulation and isolation system and method for cooling tower groups, the system includes a noise monitoring subsystem, an environmental parameter monitoring subsystem, a sound insulation and isolation subsystem, and a data center. The method includes data preprocessing, establishment of a noise propagation model and a basic model, prediction and optimization, noise prediction, instruction generation and feedback, model verification and update, and model verification steps. According to big data (noise data, environmental parameters), the configuration of the sound insulation and isolation subsystem for cooling tower groups can be adjusted. Based on the characteristics of the cooling tower water spraying noise source and the mechanism of the sound insulation barrier, considering the air intake requirements of the cooling tower, a sound insulation and muffler is installed in the lower part of the barrier. Placed between two groups of cooling tower groups, it forms a sound insulation and isolation for the two groups of cooling tower groups. The volume of the air intake muffler of the cooling tower can be adjusted according to needs; the total height of the cooling tower can also be adjusted according to needs. In this way, the inlet noise between the two rows of cooling towers will be blocked between the two isolations; at the same time, the air intake of the cooling tower inlet is not blocked.

[0115] For the large data adaptive sound insulation and isolation system and method for cooling tower groups, 1) Set up sound insulation and isolation, cancel the air intake muffler, and reduce the construction cost; 2) Set up sound insulation and isolation, which is convenient for maintenance; 3) Set up sound insulation and isolation, which does not increase the resistance of the cooling tower itself and does not affect the performance of the cooling tower; 4) Set up sound insulation and isolation, which has very good tolerance and is not affected by the local climate.

[0116] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an" does not exclude the presence of additional identical elements in the process, method, article or device comprising said element.

[0117] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A cooling tower group sound insulation system based on big data adaptation, characterized in that: Including noise monitoring subsystem, environmental parameter monitoring subsystem, sound insulation and barrier subsystem and data center; The noise monitoring subsystem includes noise sensors distributed around the cooling tower group and at key locations, which collect noise data in real time and upload it to the data center; The environmental parameter monitoring subsystem includes a wind direction sensor, a wind speed sensor, an air temperature sensor and an air humidity sensor, which monitor wind direction, wind speed, temperature and humidity parameters to provide basic data for noise control strategies; The sound insulation subsystem is located between the two rows of cooling towers. A sound insulation barrier is arranged between the two rows of cooling towers. The sound insulation barrier includes a sound insulation barrier and a sound insulation muffler. The height of the sound insulation barrier and the volume of the sound insulation muffler need to be set according to actual conditions. The structure of the sound insulation barrier adopts a combination of galvanized back plate, sound-absorbing cotton, hydrophobic glass cloth, and aluminum alloy perforated protective panel. The structure of the soundproof muffler adopts a combination of a muffler shell and a muffler sheet, wherein the muffler sheet includes glass wool, a sound-absorbing material protective panel, glass cloth, a frame, and a muffler sheet guide tip; The data center collects and analyzes noise monitoring and environmental parameter data, predicts noise propagation trends through algorithm models, and generates sound insulation and barrier adjustment data.

2. The cooling tower group sound insulation system based on big data self-adaptation according to claim 1 is characterized by: In the sound insulation subsystem, the sound insulation barrier, 1) The back panel of the screen is made of galvanized sheet and double-sided sprayed. The back panel of the screen is made of galvanized sheet with a thickness of not less than 1.2mm, and the coating weight is not less than 275g / m2. At the same time, the surface is double-sided sprayed, and the single-sided spraying thickness is not less than 80μm; 2) The screen backboard frame is made of galvanized sheet with a thickness of not less than 2.0mm, and the coating weight is not less than 275g / m2. At the same time, the surface is double-sided sprayed, and the single-sided spraying thickness is not less than 80μm. The frame spacing is ≤500mm×500mm; 3) Sound-absorbing cotton, using ultra-fine glass wool, the bulk density of which is not less than 48kg / m 3 , moisture content is not more than 1%, mass moisture absorption rate is not more than 5%, hydrophobicity is not less than 98%, and the flow resistance is appropriate, the pores are uniform, and it has high sound absorption performance and chemical stability. The allowable bulk density error of the sound-absorbing cotton does not exceed ±5%, the impurity content is not more than 3%, the sound absorption coefficient NRC ≥ 0.95, the fiber diameter is less than 6μm, it does not contain slag balls, it is moisture-proof and non-absorbent, the combustion performance of glass wool is Class A non-combustible, and the glass wool should be wrapped with plain alkali-free hydrophobic glass cloth; 4) The profiled faceplate is made of aluminum alloy perforated plate, with a thickness of not less than 1.2mm, a perforation rate of ≥23%, a hole diameter of Φ3mm, and the surface of the profiled faceplate is double-sided sprayed, and the single-sided spraying thickness is not less than 80μm; 5) Steel structure: H-shaped steel is used as the supporting structure. The bidder shall design the diagonal bracing structure according to the wind load requirements and insert the barrier into the main column structure. The supporting structure shall adopt hot-dip galvanizing process, and the average coating weight shall not be less than 610g / m2.

3. The cooling tower group sound insulation barrier system based on big data self-adaptation according to claim 1 is characterized by: In the sound insulation and barrier subsystem, the sound insulation muffler, 1) The muffler shell is made of galvanized sheet with a thickness of not less than 1.5mm, a coating weight of not less than 275g / m2, double-sided spraying, and a single-sided spraying thickness of not less than 80μm; 2) Noise-absorbing sheet unit Glass wool, use ultra-fine glass wool; the bulk density of ultra-fine glass wool is not less than 48kg / m 3 , moisture content is not more than 1%, mass moisture absorption rate is not more than 5%, hydrophobicity is not less than 98%, and the flow resistance is appropriate, the pores are uniform, and it has high sound absorption performance and chemical stability. The allowable bulk density error of the sound-absorbing cotton does not exceed ±5%, the impurity content is not more than 3%, the sound absorption coefficient NRC ≥ 0.95, the fiber diameter is less than 6μm, it does not contain slag balls, it is moisture-proof and non-absorbent, the combustion performance of glass wool is Class A non-combustible, and the glass wool should be wrapped with plain alkali-free hydrophobic glass cloth; The sound-absorbing material protective panel is made of high-corrosion-resistant 3003H24 aluminum alloy plate with a thickness of not less than 1.5mm, a perforation rate of ≥23%, and a pore size of φ3mm. The aluminum alloy plate is sprayed on both sides, and the single-side spraying thickness is not less than 80μm; The glass cloth wrapped around the sound-absorbing material is a plain woven alkali-free hydrophobic glass cloth; Frame: The silencer frame is made of galvanized sheet with a thickness of not less than 2.0 mm, and the coating weight is not less than 275 g / m2. Double-sided spraying, single-sided spraying thickness is not less than 80μm, Silencer guide tip: Made of highly corrosion-resistant 3003H24 aluminum alloy plate.

4. A cooling tower group sound insulation method based on big data adaptation, characterized by: The following steps are involved: 1) Data preprocessing Data collection: Receive real-time noise data from the noise monitoring subsystem; Receive wind direction, wind speed, temperature, and humidity data from the environmental parameter monitoring subsystem; Data cleaning: remove outliers or erroneous data; interpolate or estimate missing data; Data Integration: Align the noise data and environmental parameter data by timestamp to form a unified data set; 2) Noise propagation model, basic model establishment: The acoustic propagation model is used as the basic model of noise propagation, taking into account the influence of fixed factors such as terrain and building distribution on the sound field; Environmental parameter integration, using wind direction and wind speed as dynamic input parameters to adjust noise propagation direction and attenuation coefficient; Consider the influence of temperature and humidity on the speed of sound and sound wave attenuation, and modify the model parameters; 3) Prediction and optimization, noise prediction: Based on current environmental parameters and noise source data, the noise propagation model is used to predict the noise distribution in the future; the superposition effect of noise and complex phenomena such as reflection and diffraction are considered; Optimizing strategy generation: Based on the prediction results, the noise reduction effect of different noise barriers and noise muffler configurations is evaluated; the normal air intake demand of the cooling tower is considered to ensure that the optimization strategy does not significantly affect the cooling efficiency; the optimization algorithm is used to search for the best configuration solution; 4) Instruction generation and feedback: Instruction generation: Convert the optimized sound insulation barrier and sound insulation muffler configuration plan into specific adjustment instructions; the instructions include detailed information such as position, height, angle, material type, etc. Instruction execution and feedback: Send adjustment instructions to the sound insulation and barrier subsystem for execution; monitor noise changes after adjustment and collect feedback data for model verification and optimization; 5) Model verification and updating. Model verification: compare the noise data before and after adjustment to evaluate the accuracy of model prediction; analyze the source of error and adjust model parameters or algorithms; Model update: Regularly collect new environmental parameters and noise data, update the model database, and continuously optimize the noise propagation model and optimization algorithm based on feedback data.

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