Noise control method for gas power plant

Abstract

The invention relates to the technical field of power plant noise reduction, in particular to a gas power plant noise control method which comprises the following steps: determining a region division mode according to a noise distribution coefficient and a noise threshold; determining the type of the power plant to be analyzed according to the sound source difference degree and the effective division area proportion; determining a power plant selection mode according to the power plant similarity and a difficulty threshold, the power plant selection mode being an optimization mode determined according to the estimated noise difference degree and the proportion of one type of to-be-analyzed power plants, or selecting a monitoring power plant according to an associated power plant cluster; a noise control method is determined according to the noise elimination reference mean value of the monitored power plant, and the noise control method comprises the steps that the number of silencers is determined according to the control coefficient extreme value, or a noise elimination optimization mode is determined according to the regional noise elimination difference degree of the feature monitored power plant and the regional control extreme value; the noise control effect of the gas power plant to be built can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power plant noise reduction, and in particular to a noise control method for a gas power plant. Background Art

[0002] With the advancement of my country's urbanization process, the construction of gas-fired power plants is getting closer and closer to urban residential areas, making their noise control more and more important in the design and construction process of power plants. However, when building gas-fired power plants, they are often only prevented and controlled according to the actual layout of the power plants, and are unable to flexibly respond to various noise sources and noise propagation characteristics, resulting in a lack of sufficient adaptability of noise prevention methods, and it is often difficult to achieve the expected noise reduction effect. Therefore, how to choose a suitable noise reduction scheme to improve the noise prevention and control effect of the gas-fired power plant to be built is a technical problem that technical personnel in this field need to solve urgently.

[0003] Chinese patent publication number CN117933064A discloses a method, device and computer equipment for optimizing noise control of the floor of a control room, the method comprising: constructing an initial control room floor plan model of the target power plant according to the power plant layout characteristic information, fire protection specification information and production process information of the target power plant; inputting the initial control room floor plan model into the building simulation model corresponding to the target power plant, and obtaining the room indoor sound pressure level and room reverberation time of each target room in the control room floor plan model; when the room indoor sound pressure level and / or room reverberation time do not meet the preset value, adjusting the initial control room floor plan model until the room indoor sound pressure level and room reverberation time meet the preset value, and obtaining the target control room floor plan model; the target control room floor plan model is used to guide the construction of the control room floor of the target power plant. It can be seen that the above technical solution has the following problems: noise control is only based on the building layout of the power plant, and it is impossible to adaptively adjust the noise prevention method according to the actual noise characteristics, resulting in poor noise elimination effect. Summary of the invention

[0004] To this end, the present invention provides a gas power plant noise control method to overcome the problem that the prior art only controls noise based on the power plant building layout and cannot adaptively adjust the noise prevention method according to the actual noise characteristics, resulting in poor noise reduction effect.

[0005] To achieve the above object, the present invention provides a gas power plant noise control method, comprising:

[0006] Determine the area division method according to the noise distribution coefficient and the noise threshold, and the area division method is associated radiation area division or single radiation area division;

[0007] Select effective division areas according to the redundancy coefficient and regional noise value, determine the difference of sound sources according to the sound source influence coefficient corresponding to each effective division area, and determine the type of power plant to be analyzed according to the difference of sound sources and the proportion of effective division areas;

[0008] Determine the power plant selection method based on the power plant similarity and difficulty threshold. The power plant selection method is to determine the optimization method based on the estimated noise difference and the proportion of a type of power plant to be analyzed, or select the monitoring power plant based on the associated power plant cluster;

[0009] The optimization method is to select monitoring power plants based on the difference of gas equipment or based on comprehensive evaluation values;

[0010] Determine the noise control method based on the noise reduction reference mean value of the monitored power plant. The noise control method is to determine the number of silencers based on the extreme value of the control coefficient, or determine the noise reduction optimization method based on the regional noise reduction difference of the characteristic monitored power plant and the regional control extreme value;

[0011] The noise reduction optimization method is to determine the number of silencers in the target power plant according to the regional prevention coefficient of the characteristic area or to adjust the number of silencers in the target power plant according to the sub-silencing threshold;

[0012] The regional prevention coefficient is determined based on the obstacle influence coefficient and the associated sound attenuation ratio or based on the associated sound attenuation ratio.

[0013] Further, the area division method is determined according to the noise distribution coefficient and the noise threshold;

[0014] If the noise distribution coefficient is less than the preset noise distribution coefficient or the noise threshold is less than the preset noise threshold, the area division method is the associated radiation area division, and in the associated radiation area division, the smallest rectangle containing the radiation area corresponding to each noise source in the single associated noise source combination is recorded as a division area;

[0015] If the noise distribution coefficient is greater than or equal to the preset noise distribution coefficient and the noise threshold is greater than or equal to the preset noise threshold, the area division method is single radiation area division, in which the radiation area corresponding to a single noise source is recorded as a division area;

[0016] The associated noise source combination is determined according to the noise difference and the distance reference value;

[0017] The radiation area corresponding to a single noise source is a circle with the noise source as the center and the radiation length as the radius.

[0018] Furthermore, when selecting effective partitioning regions according to the redundancy coefficient and the regional noise value, the partitioning regions that meet the preset conditions are recorded as effective partitioning regions;

[0019] Determine the sound source difference according to the sound source influence coefficient corresponding to each effective divided area, wherein the sound source influence coefficient is determined according to the sound source radiation value;

[0020] If the sound source radiation value is greater than or equal to the preset sound source radiation value, the sound source influence coefficient is determined according to the coverage threshold and the regional influence coefficient;

[0021] If the sound source radiation value is less than the preset sound source radiation value, the sound source influence coefficient is determined according to the regional influence coefficient;

[0022] The preset condition is that the redundancy coefficient of the divided area is greater than the preset redundancy coefficient or the regional noise value is greater than the preset regional noise value.

[0023] Furthermore, the categories of power plants to be analyzed are determined based on the difference in sound sources and the proportion of effective division areas. The categories of power plants to be analyzed include:

[0024] A type of power plant to be analyzed whose sound source difference is greater than or equal to a preset sound source difference or whose effective divided area ratio is greater than or equal to a preset effective divided area ratio;

[0025] The second type of power plants to be analyzed have sound source differences less than the preset sound source differences and the effective division area ratio is less than the preset effective division area ratio.

[0026] Further, a power plant selection method is determined based on the power plant similarity and difficulty threshold;

[0027] If the power plant similarity is less than the preset power plant similarity or the difficulty threshold is greater than or equal to the preset difficulty threshold, the power plant selection method is to determine the optimization method based on the estimated noise difference and the proportion of a type of power plants to be analyzed;

[0028] If the power plant similarity is greater than or equal to the preset power plant similarity and the difficulty threshold is less than the preset difficulty threshold, the power plant selection method is to select the monitoring power plant according to the associated power plant cluster.

[0029] Further, an optimization method is determined according to the estimated noise difference and the proportion of a type of power plants to be analyzed;

[0030] If the estimated noise difference is greater than or equal to the preset estimated noise difference or the proportion of a type of power plants to be analyzed is greater than or equal to the preset proportion of a type of power plants to be analyzed, the optimization method is to select the monitoring power plant according to the difference of gas equipment. When selecting the monitoring power plant according to the difference of gas equipment, select a type of power plant to be analyzed with a gas equipment difference less than the preset gas equipment difference as the monitoring power plant for noise reduction monitoring;

[0031] If the estimated noise difference is less than the preset estimated noise difference and the proportion of a type of power plants to be analyzed is less than the preset proportion of a type of power plants to be analyzed, the optimization method is to select the monitoring power plant according to the comprehensive evaluation value. When selecting the monitoring power plant according to the comprehensive evaluation value, the sequence of the power plants to be analyzed is sorted in descending order according to the comprehensive evaluation value as the reference sequence, and the reference sequence is divided into n equal parts, and the power plants to be analyzed located at each equal point are used as monitoring power plants for noise reduction monitoring.

[0032] Further, the monitoring power plant is selected according to the associated power plant cluster, including:

[0033] Perform correlation analysis on each power plant to be analyzed. When performing correlation analysis on a single power plant to be analyzed, the power plant to be analyzed is recorded as a target power plant to be analyzed, and the power plants to be analyzed other than the target power plant that are not recorded in the associated power plant cluster are recorded as reference power plants to be analyzed;

[0034] Recording the reference power plants to be analyzed whose difference coefficients with the target power plant to be analyzed are less than the preset difference coefficient and the target power plant to be analyzed into a related power plant cluster;

[0035] And continue to perform association analysis on the power plants to be analyzed that are not recorded in the associated power plant cluster until all the power plants to be analyzed are recorded in the associated power plant cluster;

[0036] Noise elimination monitoring is performed on the monitoring power plants corresponding to each associated power plant cluster, wherein the number of monitoring power plants randomly selected in a single associated power plant cluster is a preset number.

[0037] Further, the noise prevention and control method is determined based on the noise reduction reference mean value of the monitored power plant;

[0038] If the noise reduction reference mean is greater than or equal to the preset noise reduction reference mean, the noise prevention method is to determine the number of silencers according to the extreme value of the prevention coefficient;

[0039] When determining the number of mufflers based on the extreme value of the prevention coefficient, the number of mufflers is determined based on the ratio of the estimated noise reference value to the extreme value of the prevention coefficient;

[0040] If the noise reduction reference mean is less than the preset noise reduction reference mean, the noise prevention method is to determine the noise reduction optimization method based on the regional noise reduction differences of the characteristic monitoring power plant and the regional prevention and control extreme values.

[0041] Furthermore, the optimization method of noise reduction is determined based on the regional noise reduction differences and regional control extreme values ​​of the characteristic monitoring power plant;

[0042] If the regional noise reduction difference is greater than or equal to the preset regional noise reduction difference and the regional control extreme value is greater than or equal to the preset regional control extreme value, the noise reduction optimization method is to determine the number of silencers according to the regional control coefficient of the characteristic area;

[0043] When determining the number of silencers based on the regional prevention coefficient of the characteristic area, the number of silencers is determined based on the ratio of the estimated noise reference value to the regional prevention coefficient of the characteristic area;

[0044] If the regional noise reduction difference is less than the preset regional noise reduction difference or the regional control extreme value is less than the preset regional control extreme value, the noise reduction optimization method is to increase the number of silencers according to the sub-silencing threshold;

[0045] The characteristic monitoring power plant is a monitoring power plant corresponding to the extreme value of the prevention and control coefficient, the characteristic area is an effective division area corresponding to the regional prevention and control extreme value in the characteristic monitoring power plant, and the increase value of the silencer quantity is negatively correlated with the sub-silence threshold.

[0046] Furthermore, the regional prevention coefficient is determined according to the redundancy coefficient;

[0047] If the redundancy coefficient is greater than or equal to the preset redundancy coefficient, the regional prevention coefficient is determined according to the obstacle influence coefficient and the associated noise reduction ratio;

[0048] If the redundancy coefficient is less than the preset redundancy coefficient, the regional prevention coefficient is determined according to the associated silencer ratio.

[0049] Compared with the prior art, the beneficial effect of the present invention lies in that, in the technical solution of the present invention, the noise situation of the power plant to be analyzed is effectively reflected through the noise distribution coefficient and the noise threshold, and then different regional division methods are adaptively selected according to the noise distribution coefficient and the noise threshold, so that the selection of regional division method is more in line with the actual application scenario, and then the effective division area is selected according to the redundancy coefficient and the regional noise value, avoiding the problem that the selected effective division area cannot meet the actual monitoring needs, and then the difference degree of noise in the power plant to be analyzed is effectively reflected through the sound source difference and the proportion of effective division areas, and then according to the sound source difference and the effective division area ratio, the selection of regional division method is more in line with the actual application scenario. The category of the power plant to be analyzed is determined based on the effective division area ratio, so that the determination of the category of the power plant to be analyzed is more in line with the actual application scenario, which is conducive to the subsequent determination of the optimization method according to the estimated noise difference and the ratio of a type of power plant to be analyzed. The estimated noise difference and the ratio of a type of power plant to be analyzed effectively reflect the noise difference between the target power plant and the power plant to be analyzed and the ratio of power plants to be analyzed with high noise complexity, which makes the selection of the optimization method more in line with the actual power plant situation, avoids the problems of poor pertinence and effectiveness of monitoring of the monitored power plant, makes the design of the silencing scheme closer to the actual needs of the target power plant, and thus improves the noise prevention and control effect.

[0050] Furthermore, in the present invention, the similarity between the target power plant and the power plant to be analyzed and the complexity of the noise in the target power plant are reflected through the power plant similarity and the difficulty threshold, and then different power plant selection methods are adaptively selected according to the power plant similarity and the difficulty threshold, so that the selection of the power plant selection method is more in line with the actual application scenario, avoiding the problem of a large degree of difference between the selected monitoring power plant and the target power plant, making the target power plant silencing measures more accurate and effective, thereby improving the silencing effect of the target power plant.

[0051] Furthermore, in the present invention, the noise reduction situation of the monitored power plant is effectively reflected by the noise reduction reference mean, and then different noise control methods are adaptively selected according to the noise reduction reference mean of the monitored power plant, so that the selection of noise control method is more in line with the actual application scenario, avoiding the problem that the noise control method of the target power plant lacks sufficient adaptability and is difficult to achieve the expected noise reduction effect, thereby improving the pertinence and effectiveness of noise control.

[0052] Furthermore, the present invention effectively reflects the differences in the noise reduction effects of each sub-region in the characteristic monitoring power plant through the regional noise reduction differences and regional prevention and control extreme values ​​of the characteristic monitoring power plant, and then adaptively selects different noise reduction optimization methods according to the regional noise reduction differences and regional prevention and control extreme values ​​of the characteristic monitoring power plant, so that the selection of the noise reduction optimization method is more in line with the actual application scenario, avoiding the problem of poor noise reduction effect due to a small number of silencers, and thus improving the noise reduction effect of the target power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a gas power plant noise control method according to the present invention;

[0054] Figure 2 This is a flow chart of the present invention for determining the category of a power plant to be analyzed based on the difference in sound sources and the proportion of effective divided areas;

[0055] Figure 3 A flow chart of the present invention for determining a power plant selection method according to power plant similarity and difficulty threshold;

[0056] Figure 4 The present invention is a flow chart of a method for determining a noise prevention and control method according to a noise reduction reference mean value of a monitored power plant. DETAILED DESCRIPTION

[0057] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0058] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0059] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0060] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] See also Figures 1 to 4 As shown, the present invention provides a gas power plant noise control method, comprising:

[0062] Determine the area division method according to the noise distribution coefficient and the noise threshold, and the area division method is associated radiation area division or single radiation area division;

[0063] Select effective division areas according to the redundancy coefficient and regional noise value, determine the difference of sound sources according to the sound source influence coefficient corresponding to each effective division area, and determine the type of power plant to be analyzed according to the difference of sound sources and the proportion of effective division areas;

[0064] Determine the power plant selection method based on the power plant similarity and difficulty threshold. The power plant selection method is to determine the optimization method based on the estimated noise difference and the proportion of a type of power plant to be analyzed, or select the monitoring power plant based on the associated power plant cluster;

[0065] The optimization method is to select monitoring power plants based on the difference of gas equipment or based on comprehensive evaluation values;

[0066] Determine the noise control method based on the noise reduction reference mean value of the monitored power plant. The noise control method is to determine the number of silencers based on the extreme value of the control coefficient, or determine the noise reduction optimization method based on the regional noise reduction difference of the characteristic monitored power plant and the regional control extreme value;

[0067] The noise reduction optimization method is to determine the number of silencers in the target power plant according to the regional prevention coefficient of the characteristic area or to adjust the number of silencers in the target power plant according to the sub-silencing threshold;

[0068] The regional prevention coefficient is determined based on the obstacle influence coefficient and the associated sound attenuation ratio or based on the associated sound attenuation ratio.

[0069] The application scenario of the present invention is the noise control of a gas-fired power plant to be built, the target power plant is a gas-fired power plant to be built, and the power plant to be analyzed is an existing gas-fired power plant. In the present invention, several historical records are correspondingly provided, and any historical record records the noise distribution coefficient, noise threshold, noise difference, regional noise value, power plant similarity and difficulty threshold, etc. in the historical process of at least one target power plant silencing method, and each historical record corresponds to a qualified mark, which records whether the silencing effect of the target power plant silencing method meets user requirements, and the qualified mark can be recorded manually.

[0070] The present invention is provided with a continuously cyclic monitoring cycle, and the data status is determined once at the end of each monitoring cycle. The duration of the monitoring cycle can be set according to the needs of the user. The greater the user's demand for the accuracy of data status monitoring, the shorter the monitoring cycle duration. A value of the monitoring cycle is provided, and the monitoring cycle is 24 hours.

[0071] The present invention applies a deep learning network, which includes but is not limited to a feedforward neural network, a convolutional neural network, and a recurrent neural network. Users can choose according to actual needs, and then perform deep learning based on historical records to obtain the effects of different parameters on the effectiveness of regional noise prevention and control. This is content that is easy for technicians in this field to understand and will not be described in detail.

[0072] Specifically, the area division method is determined according to the noise distribution coefficient and the noise threshold;

[0073] If the noise distribution coefficient is less than the preset noise distribution coefficient or the noise threshold is less than the preset noise threshold, the area division method is the associated radiation area division, and in the associated radiation area division, the smallest rectangle containing the radiation area corresponding to each noise source in the single associated noise source combination is recorded as a division area;

[0074] If the noise distribution coefficient is greater than or equal to the preset noise distribution coefficient and the noise threshold is greater than or equal to the preset noise threshold, the area division method is single radiation area division, in which the radiation area corresponding to a single noise source is recorded as a division area;

[0075] The associated noise source combination is determined according to the noise difference and the distance reference value;

[0076] The radiation area corresponding to a single noise source is a circle with the noise source as the center and the radiation length as the radius.

[0077] Among them, the noise distribution coefficient is the average value of the reference minimum distance corresponding to each noise source. For a single noise source, the noise source is recorded as the target noise source, and other noise sources other than the target noise source are recorded as reference noise sources. The shortest distance from the target noise source to each reference noise source is detected, and the minimum value of each shortest distance is recorded as the reference minimum distance corresponding to the target noise source; the noise threshold is the average value of the maximum noise value corresponding to each noise source in the current monitoring period, and the maximum noise value is the maximum noise value of a single noise source in the current monitoring period. In the present invention, the noise source in the power plant to be analyzed is determined by a phase meter, and the noise value is measured by a noise measuring instrument. This is content that is easy to understand for those skilled in the art and will not be described in detail;

[0078] The radiation length is positively correlated with the sound power corresponding to the noise source. The sound power can be measured by the sound pressure method. This is easy for those skilled in the art to understand and will not be described in detail.

[0079] The values ​​of the preset noise distribution coefficient and the preset noise threshold can be determined by the user according to the actual application scenario. The larger the values ​​of the preset noise distribution coefficient and the preset noise threshold, the greater the user's demand for associated radiation area division. A value of the preset noise distribution coefficient and the preset noise threshold is provided, and the historical records of associated radiation area division are detected. The average value of the noise distribution coefficient corresponding to the historical records that can meet the user's needs is recorded as the preset noise distribution coefficient, and the average value of the noise threshold corresponding to the historical records that can meet the user's needs is recorded as the preset noise threshold.

[0080] The associated noise source combination is determined according to the noise difference and the distance reference value, wherein a combined analysis is performed on each noise source in a single power plant to be analyzed. When a combined analysis is performed on a single noise source, the noise source is recorded as a target noise source, and noise sources other than the target noise source that are not recorded in the associated noise source combination are recorded as reference noise sources. A set of reference noise sources whose noise difference with the target noise source is less than a preset noise difference and whose distance reference value is less than a preset distance reference value and the target noise source are recorded as an associated noise source set, and a combined analysis is continued for noise sources that are not recorded in the associated noise source combination until each noise source is recorded in the associated noise source combination;

[0081] The noise difference is the absolute value of the difference between the noise reference values ​​corresponding to the two noise sources, and the noise reference value = noise fluctuation value + noise mean; the noise fluctuation value is the standard deviation of the noise extreme values ​​corresponding to each monitoring point in the current monitoring period, and the noise mean is the average value of the noise extreme values ​​corresponding to each monitoring point in the current monitoring period. The noise extreme value is the maximum value of the noise values ​​corresponding to each noise source in a single monitoring point and a single power plant to be analyzed. Among them, the monitoring point is set by the user, and a monitoring point setting method is provided. The start time of the current monitoring period is recorded as a monitoring point, and in the order of time from early to late, every 30 minutes is recorded as a monitoring point, that is, the monitoring parameters are recorded every 30 minutes; the distance reference value is the shortest distance between the two noise sources;

[0082] The values ​​of the preset noise difference and the preset distance reference value can be determined by the user according to the actual application scenario. The greater the user's demand for the similarity of the noise sources in a single associated noise source combination, the smaller the values ​​of the preset noise difference and the preset distance reference value are. A value of the preset noise difference and the preset distance reference value is provided, and the historical records of the associated radiation area division are detected. The average value of the noise difference corresponding to the historical records that can meet the user's needs is recorded as the preset noise difference. The preset distance reference value is 10m.

[0083] Specifically, when selecting effective partitioning regions according to the redundancy coefficient and the regional noise value, the partitioning regions that meet the preset conditions are recorded as effective partitioning regions;

[0084] Determine the sound source difference according to the sound source influence coefficient corresponding to each effective divided area, wherein the sound source influence coefficient is determined according to the sound source radiation value;

[0085] If the sound source radiation value is greater than or equal to the preset sound source radiation value, the sound source influence coefficient is determined according to the coverage threshold and the regional influence coefficient;

[0086] If the sound source radiation value is less than the preset sound source radiation value, the sound source influence coefficient is determined according to the regional influence coefficient;

[0087] The preset condition is that the redundancy coefficient of the divided area is greater than the preset redundancy coefficient or the regional noise value is greater than the preset regional noise value.

[0088] The redundancy coefficient is confirmed in the following way: for a single partition area in a single power plant to be analyzed, the partition area is recorded as the target partition area, and other partition areas outside the target partition area are recorded as reference partition areas. The redundancy coefficient = the area of ​​the target partition area and the reference partition area overlapping / the area of ​​the target partition area; the regional noise value is the average of the monitoring mean values ​​corresponding to each noise source in the single partition area, and the monitoring mean value is the average of the noise values ​​corresponding to each monitoring point in the current monitoring cycle;

[0089] The values ​​of the preset redundancy coefficient and the preset regional noise value can be determined by the user according to the actual application scenario. The greater the user's demand for the selected effective division area to meet the noise elimination monitoring, the smaller the values ​​of the preset redundancy coefficient and the preset regional noise value are. Provide a value of the preset redundancy coefficient and the preset regional noise value, the preset redundancy coefficient is 40%, and the average value of the regional noise value corresponding to the historical records that can meet the user's needs is recorded as the preset regional noise value;

[0090] The maximum value of the sound source influence coefficient corresponding to each effective division area in a single power plant to be analyzed is recorded as a1, and the minimum value is recorded as a2. The sound source difference = (a1-a2) / a1. The sound source radiation value is confirmed in the following way: for a single effective division area, the effective division area is recorded as the target effective division area, and other effective division areas outside the target effective division area are recorded as reference effective division areas. The sound source radiation value is the sum of the number of noise sources in each reference effective division area that overlaps with the target effective division area. It can be understood that if the target effective division area does not overlap with each reference effective division area, the sound source radiation value is 0; the value of the preset sound source radiation value can be determined by the user according to the actual application scenario. The larger the value of the preset sound source radiation value, the greater the user's demand for determining the sound source influence coefficient according to the regional influence coefficient. A preset sound source radiation value is provided, and the historical records of determining the sound source influence coefficient according to the regional influence coefficient are detected. The average value of the sound source radiation value corresponding to the historical records that can meet the user's needs is recorded as the preset sound source radiation value;

[0091] When the sound source radiation value is greater than or equal to the preset sound source radiation value, the sound source influence coefficient = coverage threshold + regional influence coefficient; when the sound source radiation value is less than the preset sound source radiation value, the sound source influence coefficient and the regional influence coefficient are positively correlated; coverage threshold = the area of ​​the target effective division area overlapping with each reference effective division area / sound source radiation value, regional influence coefficient = the area of ​​the target effective division area / the number of noise sources in the target effective division area.

[0092] Specifically, the categories of power plants to be analyzed are determined based on the difference in sound sources and the proportion of effective division areas. The categories of power plants to be analyzed include:

[0093] A type of power plant to be analyzed whose sound source difference is greater than or equal to a preset sound source difference or whose effective divided area ratio is greater than or equal to a preset effective divided area ratio;

[0094] The second type of power plants to be analyzed have sound source differences less than the preset sound source differences and the effective division area ratio is less than the preset effective division area ratio.

[0095] Among them, the proportion of effective divided areas = the number of effective divided areas in a single power plant to be analyzed / the total number of divided areas in a single power plant to be analyzed; the values ​​of the preset sound source difference and the preset effective divided area ratio can be determined by the user according to the actual application scenario. The smaller the values ​​of the preset sound source difference and the preset effective divided area ratio, the greater the demand for determining the power plant to be analyzed as a Class II power plant to be analyzed. A preset sound source difference and a preset effective divided area ratio are provided, and the preset effective divided area ratio is 60%. The historical records of determining the power plant to be analyzed as a Class II power plant to be analyzed are detected, and the average value of the sound source difference corresponding to the historical records that can meet the user's needs is recorded as the preset sound source difference.

[0096] Specifically, the power plant selection method is determined based on the power plant similarity and difficulty threshold;

[0097] If the power plant similarity is less than the preset power plant similarity or the difficulty threshold is greater than or equal to the preset difficulty threshold, the power plant selection method is to determine the optimization method based on the estimated noise difference and the proportion of a type of power plants to be analyzed;

[0098] If the power plant similarity is greater than or equal to the preset power plant similarity and the difficulty threshold is less than the preset difficulty threshold, the power plant selection method is to select the monitoring power plant according to the associated power plant cluster.

[0099] Among them, the power plant similarity is the average value of the power generation difference between the target power plant and each power plant to be analyzed, the power generation difference is the absolute value of the difference between the power generation coefficient corresponding to the target power plant and the power generation coefficient corresponding to a single power plant to be analyzed, the power generation coefficient = (power generation / average power generation) + (total amount of gas equipment / average total amount of gas equipment), the power generation of the target power plant and the power plant to be analyzed are confirmed in different ways, the power generation of the target power plant = predicted minimum annual power generation / 365, the predicted minimum annual power generation is determined by load forecasting, which is easy for technicians in this field to understand, and will not be described in detail, the power generation of the power plant to be analyzed is the average value of the actual power generation corresponding to each historical monitoring period of a single power plant to be analyzed, the historical monitoring period is the 30 monitoring periods before the current monitoring period, and the total amount of gas equipment is a single The sum of the number of power generation areas corresponding to each gas equipment category in the power plants, the gas equipment categories include gas turbines, generators, waste heat boilers and steam turbines, the average power generation is the average power generation corresponding to each power plant to be analyzed, and the average total amount of gas equipment is the average total amount of gas equipment corresponding to each power plant to be analyzed; the difficulty threshold is the sum of the difficulty coefficients corresponding to each power generation area category, and the method for confirming the difficulty coefficient is to record the power generation area category as the target category for a single power generation area category, record other power generation area categories outside the target category as reference categories, and record the area of ​​the reference area corresponding to the target category and the reference area corresponding to the reference category as the difficulty coefficient corresponding to the target category. The reference area is the minimum rectangular area that can contain each power generation area corresponding to a single gas equipment category;

[0100] The values ​​of the preset power plant similarity and the preset difficulty threshold can be determined by the user according to the actual application scenario. The smaller the value of the preset power plant similarity and the larger the value of the preset difficulty threshold, the greater the user's need to select a monitored power plant based on an associated power plant cluster. A value of the preset power plant similarity and the preset difficulty threshold is provided, and the historical records of selecting a monitored power plant based on an associated power plant cluster are detected. The average value of the power plant similarities corresponding to the historical records that can meet the user's needs is recorded as the preset power plant similarity, and the average value of the difficulty threshold corresponding to the historical records that can meet the user's needs is recorded as the preset difficulty threshold.

[0101] Specifically, the optimization method is determined based on the estimated noise difference and the proportion of a type of power plants to be analyzed;

[0102] If the estimated noise difference is greater than or equal to the preset estimated noise difference or the proportion of a type of power plants to be analyzed is greater than or equal to the preset proportion of a type of power plants to be analyzed, the optimization method is to select the monitoring power plant according to the difference of gas equipment. When selecting the monitoring power plant according to the difference of gas equipment, select a type of power plant to be analyzed with a gas equipment difference less than the preset gas equipment difference as the monitoring power plant for noise reduction monitoring;

[0103] If the estimated noise difference is less than the preset estimated noise difference and the proportion of a type of power plants to be analyzed is less than the preset proportion of a type of power plants to be analyzed, the optimization method is to select the monitoring power plant according to the comprehensive evaluation value. When selecting the monitoring power plant according to the comprehensive evaluation value, the sequence of the power plants to be analyzed is sorted in descending order according to the comprehensive evaluation value as the reference sequence, and the reference sequence is divided into n equal parts, and the power plants to be analyzed located at each equal point are used as monitoring power plants for noise reduction monitoring.

[0104] Wherein, the estimated noise difference = the average value of the absolute value of the difference between the noise coefficient corresponding to each power plant to be analyzed and the noise coefficient of the target power plant / the estimated noise reference value of the target power plant;

[0105] The estimated noise reference value of the target power plant = ratio mean value × power generation coefficient, the ratio mean value is the average value of the ratio reference values ​​corresponding to each power plant to be analyzed, and the method for confirming the ratio reference value is that for a single power plant to be analyzed, the power plant to be analyzed is recorded as the target power plant to be analyzed, and the ratio reference value corresponding to the target power plant to be analyzed = the noise coefficient of the target power plant to be analyzed / the power generation coefficient of the target power plant to be analyzed, and the noise coefficient of the power plant to be analyzed is the average value of the regional noise values ​​corresponding to each divided area of ​​the single power plant to be analyzed;

[0106] The proportion of power plants to be analyzed in the first category = the number of power plants to be analyzed in the first category / the total number of power plants to be analyzed;

[0107] The values ​​of the preset estimated noise difference, the preset proportion of a class of power plants to be analyzed, and the preset gas equipment difference can be determined by the user according to the actual application scenario. The smaller the values ​​of the preset estimated noise difference and the preset proportion of a class of power plants to be analyzed, the greater the user's demand for selecting the power plant to be analyzed based on the comprehensive evaluation value. A preset estimated noise difference and a preset proportion of a class of power plants to be analyzed are provided. The preset estimated noise difference is 40%, and the preset proportion of a class of power plants to be analyzed is 70%. The historical records of selecting a class of power plants to be analyzed based on the gas equipment difference are detected, and the average value of the gas equipment difference corresponding to the historical records that can meet the user's needs is recorded as the preset gas equipment difference;

[0108] Gas equipment difference = |Gas equipment reference value corresponding to a single power plant to be analyzed - gas equipment reference value corresponding to the target power plant | / Gas equipment reference value corresponding to the target power plant. The power plant to be analyzed is recorded as the target power plant to be analyzed. The confirmation method of the gas equipment reference values ​​corresponding to the power plant to be analyzed and the target power plant is the same. For a single power plant, the power plant is recorded as the target power plant. The gas equipment reference value corresponding to the target power plant = the total number of gas equipment in the target power plant / the average value of the total number of gas equipment + the difficulty threshold corresponding to the target power plant / the average value of the difficulty threshold. The average value of the difficulty threshold is the average value of the difficulty thresholds corresponding to each power plant to be analyzed; Comprehensive evaluation value = proportion of effective divided areas + sound source difference; The value of n can be determined by the user according to actual needs. The greater the accuracy of the user's noise reduction monitoring, the larger the value of n. Provide a value of n, n is 10.

[0109] Specifically, the monitoring power plants are selected according to the associated power plant clusters, including:

[0110] Perform correlation analysis on each power plant to be analyzed. When performing correlation analysis on a single power plant to be analyzed, the power plant to be analyzed is recorded as a target power plant to be analyzed, and the power plants to be analyzed other than the target power plant that are not recorded in the associated power plant cluster are recorded as reference power plants to be analyzed;

[0111] Recording the reference power plants to be analyzed whose difference coefficients with the target power plant to be analyzed are less than the preset difference coefficient and the target power plant to be analyzed into a related power plant cluster;

[0112] And continue to perform association analysis on the power plants to be analyzed that are not recorded in the associated power plant cluster until all the power plants to be analyzed are recorded in the associated power plant cluster;

[0113] Noise elimination monitoring is performed on the monitoring power plants corresponding to each associated power plant cluster, wherein the number of monitoring power plants randomly selected in a single associated power plant cluster is a preset number.

[0114] It should be noted that when the reference power plant to be analyzed whose difference coefficient with the target power plant to be analyzed is less than the preset difference coefficient and the target power plant to be analyzed are recorded in an associated power plant cluster, the associated power plant cluster is recorded as the target associated power plant cluster, and when the associated analysis is continued for the power plants to be analyzed that are not recorded in the associated power plant cluster, the associated power plant cluster recorded is not the target associated power plant cluster, but a new associated power plant cluster. Therefore, several associated power plant clusters can be obtained by performing the associated analysis on each power plant to be analyzed;

[0115] The difference coefficient is the absolute value of the difference between the noise assessment values ​​corresponding to the two power plants to be analyzed. The noise assessment value = noise distribution coefficient + noise threshold. The value of the preset difference coefficient can be determined by the user according to the actual application scenario. The smaller the value of the preset difference coefficient, the smaller the degree of difference between the power plants to be analyzed in the associated power plant cluster. A value of the preset difference coefficient is provided, and the historical records of the power plants to be monitored are detected according to the associated power plant cluster. The average value of the difference coefficients corresponding to the historical records that can meet the user's needs is recorded as the preset difference coefficient; the value of the preset number can be determined by the user according to actual needs. A value of the preset number is provided, and the preset number is 30% of the number of power plants to be analyzed in a single associated power plant cluster.

[0116] Specifically, the noise control method is determined based on the noise reduction reference mean of the monitored power plant;

[0117] If the noise reduction reference mean is greater than or equal to the preset noise reduction reference mean, the noise prevention method is to determine the number of silencers according to the extreme value of the prevention coefficient;

[0118] When determining the number of mufflers based on the extreme value of the prevention coefficient, the number of mufflers is determined based on the ratio of the estimated noise reference value to the extreme value of the prevention coefficient;

[0119] If the noise reduction reference mean is less than the preset noise reduction reference mean, the noise prevention method is to determine the noise reduction optimization method based on the regional noise reduction differences of the characteristic monitoring power plant and the regional prevention and control extreme values.

[0120] Among them, the noise reduction reference mean is the average value of the noise reduction reference values ​​corresponding to each power plant to be analyzed. The noise reduction reference value is confirmed in that, for a single power plant to be analyzed, the power plant to be analyzed is recorded as the target power plant to be analyzed, and the noise reduction reference value corresponding to the target power plant to be analyzed = the noise threshold corresponding to the target power plant to be analyzed - the average value of the maximum noise values ​​corresponding to each noise source when the silencer of the target power plant to be analyzed is turned on;

[0121] The value of the preset noise reduction reference mean value can be determined by the user according to the actual application scenario. The smaller the value of the preset noise reduction reference mean value, the greater the user's demand for determining the number of silencers in the target power plant according to the extreme value of the prevention and control coefficient. A preset noise reduction reference mean value is provided, and the historical records of determining the number of silencers in the target power plant according to the extreme value of the prevention and control coefficient are detected. The average value of the noise reduction reference mean values ​​corresponding to the historical records that can meet the user's needs is recorded as the preset noise reduction reference mean value;

[0122] The extreme value of the prevention coefficient is the maximum value of the prevention coefficients corresponding to each power plant to be analyzed; the prevention coefficient is the average value of the regional prevention coefficients corresponding to each effective division area in a single power plant to be analyzed;

[0123] The number of silencers is the total number of silencers in the target power plant. When the number of silencers is determined based on the extreme value of the prevention and control coefficient, the number of silencers = estimated noise reference value of the target power plant / extreme value of the prevention and control coefficient.

[0124] Specifically, the optimization method of noise reduction is determined based on the regional noise reduction differences and regional control extreme values ​​of the characteristic monitoring power plant;

[0125] If the regional noise reduction difference is greater than or equal to the preset regional noise reduction difference and the regional control extreme value is greater than or equal to the preset regional control extreme value, the noise reduction optimization method is to determine the number of silencers according to the regional control coefficient of the characteristic area;

[0126] When determining the number of silencers based on the regional prevention coefficient of the characteristic area, the number of silencers is determined based on the ratio of the estimated noise reference value to the regional prevention coefficient of the characteristic area;

[0127] If the regional noise reduction difference is less than the preset regional noise reduction difference or the regional control extreme value is less than the preset regional control extreme value, the noise reduction optimization method is to increase the number of silencers according to the sub-silencing threshold;

[0128] The characteristic monitoring power plant is a monitoring power plant corresponding to the extreme value of the prevention and control coefficient, the characteristic area is an effective division area corresponding to the regional prevention and control extreme value in the characteristic monitoring power plant, and the increase value of the silencer quantity is negatively correlated with the sub-silence threshold.

[0129] Among them, regional noise reduction difference = (regional control extreme value - minimum value of regional control coefficients corresponding to each effective division area in the characteristic monitoring power plant) / regional control extreme value; regional control extreme value is the maximum value of regional control coefficients corresponding to each effective division area in the characteristic monitoring power plant; sub-noise reduction threshold = regional control extreme value / number of silencers in the characteristic area;

[0130] When the number of silencers is determined according to the regional prevention coefficient of the characteristic area, the number of silencers = the estimated noise reference value of the target power plant / the regional prevention coefficient of the characteristic area;

[0131] The values ​​of the preset regional silencer difference and the preset regional prevention and control extreme value can be determined by the user according to the actual application scenario. The smaller the values ​​of the preset regional silencer difference and the preset regional prevention and control extreme value are, the greater the user's demand for determining the number of silencers based on the regional prevention and control coefficient of the characteristic area. Provided are values ​​of the preset regional silencer difference and the preset regional prevention and control extreme value, and the preset regional silencer difference is 50%. The historical records of determining the number of silencers based on the regional prevention and control coefficient of the characteristic area are detected, and the average value of the regional prevention and control extreme values ​​corresponding to the historical records that can meet the user's needs is recorded as the preset regional prevention and control extreme value.

[0132] Specifically, the regional prevention coefficient is determined based on the redundancy coefficient;

[0133] If the redundancy coefficient is greater than or equal to the preset redundancy coefficient, the regional prevention coefficient is determined according to the obstacle influence coefficient and the associated noise reduction ratio;

[0134] If the redundancy coefficient is less than the preset redundancy coefficient, the regional prevention coefficient is determined according to the associated silencer ratio.

[0135] Among them, when the redundancy coefficient is greater than or equal to the preset redundancy coefficient, the regional prevention coefficient = associated noise reduction ratio × first coefficient + obstacle influence coefficient × second coefficient;

[0136] When the redundancy coefficient is less than the preset redundancy coefficient, the regional prevention coefficient and the associated noise reduction ratio are positively correlated;

[0137] The obstacle influence coefficient is confirmed in the following manner: the maximum value of the influence reference values ​​corresponding to each reference effective division area is recorded as the obstacle influence coefficient; for a single effective division area, the effective division area is recorded as the target effective division area; the effective division area overlapping with the target effective division area is recorded as the reference effective division area; for a single reference effective division area, the reference effective division area is recorded as the area to be analyzed; the influence reference value corresponding to the area to be analyzed = the average value of the maximum noise values ​​corresponding to each noise source in the area to be analyzed / the obstacle reference value; the obstacle reference value is the number of obstacles in the path with the shortest distance from the center point of the area to be analyzed to the center of the target effective division area; the obstacles include but are not limited to walls, doors, windows and gas equipment; the center point is the center of the circumscribed circle of the single effective division area;

[0138] Associated noise reduction ratio = (average value of the maximum noise values ​​corresponding to each noise source in the target effective divided area during the current monitoring period - average value of the maximum noise values ​​corresponding to each noise source in the target effective divided area when the muffler is turned on) / area of ​​the target effective divided area;

[0139] The values ​​of the first coefficient and the second coefficient can be obtained by the user through deep learning convolutional neural network learning based on historical records. It can be understood that the present invention reflects the effectiveness of regional noise control through the obstacle influence coefficient and the associated sound reduction ratio. The user can use deep learning to obtain the influence of the obstacle influence coefficient and the associated sound reduction ratio on the effectiveness of regional noise control according to the historical records, and then select the values ​​of the first coefficient and the second coefficient accordingly. The larger the values ​​of the first coefficient and the second coefficient, the greater the influence on the effectiveness of regional noise control. Among them, the first coefficient + the second coefficient = 1, and one value of the first coefficient and the second coefficient is provided, and the first coefficient is 0.6 and the second coefficient is 0.4.

[0140] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0141] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for controlling noise in a gas power plant, characterized in that: include: Determine the area division method according to the noise distribution coefficient and the noise threshold, and the area division method is associated radiation area division or single radiation area division; Select effective division areas according to the redundancy coefficient and regional noise value, determine the difference of sound sources according to the sound source influence coefficient corresponding to each effective division area, and determine the type of power plant to be analyzed according to the difference of sound sources and the proportion of effective division areas; Determine the power plant selection method based on the power plant similarity and difficulty threshold. The power plant selection method is to determine the optimization method based on the estimated noise difference and the proportion of a type of power plant to be analyzed, or select the monitoring power plant based on the associated power plant cluster; The optimization method is to select monitoring power plants based on the differences in gas equipment or based on comprehensive evaluation values; Determine the noise control method based on the noise reduction reference mean value of the monitored power plant. The noise control method is to determine the number of silencers based on the extreme value of the control coefficient, or determine the noise reduction optimization method based on the regional noise reduction difference of the characteristic monitored power plant and the regional control extreme value; The noise reduction optimization method is to determine the number of silencers in the target power plant according to the regional prevention coefficient of the characteristic area or to adjust the number of silencers in the target power plant according to the sub-silencing threshold; The regional prevention coefficient is determined based on the obstacle influence coefficient and the associated sound attenuation ratio or based on the associated sound attenuation ratio.

2. The gas power plant noise control method according to claim 1, characterized in that: Determine the area division method according to the noise distribution coefficient and the noise threshold; If the noise distribution coefficient is less than the preset noise distribution coefficient or the noise threshold is less than the preset noise threshold, the area division method is the associated radiation area division, and in the associated radiation area division, the smallest rectangle containing the radiation area corresponding to each noise source in the single associated noise source combination is recorded as a division area; If the noise distribution coefficient is greater than or equal to the preset noise distribution coefficient and the noise threshold is greater than or equal to the preset noise threshold, the area division method is single radiation area division, in which the radiation area corresponding to a single noise source is recorded as a division area; The associated noise source combination is determined according to the noise difference and the distance reference value; The radiation area corresponding to a single noise source is a circle with the noise source as the center and the radiation length as the radius.

3. The gas power plant noise control method according to claim 2, characterized in that: When selecting effective partitioning regions according to the redundancy coefficient and the regional noise value, the partitioning regions that meet the preset conditions are recorded as effective partitioning regions; Determine the sound source difference according to the sound source influence coefficient corresponding to each effective divided area, wherein the sound source influence coefficient is determined according to the sound source radiation value; If the sound source radiation value is greater than or equal to the preset sound source radiation value, the sound source influence coefficient is determined according to the coverage threshold and the regional influence coefficient; If the sound source radiation value is less than the preset sound source radiation value, the sound source influence coefficient is determined according to the regional influence coefficient; The preset condition is that the redundancy coefficient of the divided area is greater than the preset redundancy coefficient or the regional noise value is greater than the preset regional noise value.

4. The gas power plant noise control method according to claim 3, characterized in that: The power plant categories to be analyzed are determined based on the difference in sound sources and the proportion of effective division areas. The power plant categories to be analyzed include: A type of power plant to be analyzed whose sound source difference is greater than or equal to a preset sound source difference or whose effective division area ratio is greater than or equal to a preset effective division area ratio; The second type of power plants to be analyzed have sound source differences less than the preset sound source differences and the effective division area ratio is less than the preset effective division area ratio.

5. The gas power plant noise control method according to claim 4, characterized in that: Determine the power plant selection method based on power plant similarity and difficulty threshold; If the power plant similarity is less than the preset power plant similarity or the difficulty threshold is greater than or equal to the preset difficulty threshold, the power plant selection method is to determine the optimization method based on the estimated noise difference and the proportion of a type of power plants to be analyzed; If the power plant similarity is greater than or equal to the preset power plant similarity and the difficulty threshold is less than the preset difficulty threshold, the power plant selection method is to select the monitoring power plant according to the associated power plant cluster.

6. The gas power plant noise control method according to claim 5, characterized in that: Determine the optimization method based on the estimated noise difference and the proportion of the power plants to be analyzed in the first category; If the estimated noise difference is greater than or equal to the preset estimated noise difference or the proportion of a type of power plants to be analyzed is greater than or equal to the preset proportion of a type of power plants to be analyzed, the optimization method is to select the monitoring power plant according to the difference of gas equipment. When selecting the monitoring power plant according to the difference of gas equipment, select a type of power plant to be analyzed with a gas equipment difference less than the preset gas equipment difference as the monitoring power plant for noise reduction monitoring; If the estimated noise difference is less than the preset estimated noise difference and the proportion of a type of power plants to be analyzed is less than the preset proportion of a type of power plants to be analyzed, the optimization method is to select the monitoring power plant according to the comprehensive evaluation value. When selecting the monitoring power plant according to the comprehensive evaluation value, the sequence of the power plants to be analyzed is sorted in descending order according to the comprehensive evaluation value as the reference sequence, and the reference sequence is divided into n equal parts, and the power plants to be analyzed located at each equal point are used as monitoring power plants for noise reduction monitoring.

7. The method for controlling noise in a gas power plant according to claim 5, characterized in that: Select monitoring plants based on associated plant clusters, including: Perform correlation analysis on each power plant to be analyzed. When performing correlation analysis on a single power plant to be analyzed, the power plant to be analyzed is recorded as a target power plant to be analyzed, and the power plants to be analyzed other than the target power plant that are not recorded in the associated power plant cluster are recorded as reference power plants to be analyzed; Recording the reference power plants to be analyzed whose difference coefficients with the target power plant to be analyzed are less than the preset difference coefficient and the target power plant to be analyzed into a related power plant cluster; And continue to perform association analysis on the power plants to be analyzed that are not recorded in the associated power plant cluster until all the power plants to be analyzed are recorded in the associated power plant cluster; Noise elimination monitoring is performed on the monitoring power plants corresponding to each associated power plant cluster, wherein the number of monitoring power plants randomly selected in a single associated power plant cluster is a preset number.

8. The method for controlling noise in a gas power plant according to claim 7, characterized in that: Determine the noise prevention and control method based on the noise reduction reference mean of the monitored power plant; If the noise reduction reference mean is greater than or equal to the preset noise reduction reference mean, the noise prevention method is to determine the number of silencers according to the extreme value of the prevention coefficient; When determining the number of mufflers based on the extreme value of the prevention coefficient, the number of mufflers is determined based on the ratio of the estimated noise reference value to the extreme value of the prevention coefficient; If the noise reduction reference mean is less than the preset noise reduction reference mean, the noise prevention method is to determine the noise reduction optimization method based on the regional noise reduction differences of the characteristic monitoring power plant and the regional prevention and control extreme values.

9. The gas power plant noise control method according to claim 8, characterized in that: Determine the optimization method of noise reduction based on the regional noise reduction differences and regional control extreme values ​​of the characteristic monitoring power plant; If the regional noise reduction difference is greater than or equal to the preset regional noise reduction difference and the regional control extreme value is greater than or equal to the preset regional control extreme value, the noise reduction optimization method is to determine the number of silencers according to the regional control coefficient of the characteristic area; When determining the number of silencers based on the regional prevention coefficient of the characteristic area, the number of silencers is determined based on the ratio of the estimated noise reference value to the regional prevention coefficient of the characteristic area; If the regional noise reduction difference is less than the preset regional noise reduction difference or the regional control extreme value is less than the preset regional control extreme value, the noise reduction optimization method is to increase the number of silencers according to the sub-silencing threshold; The characteristic monitoring power plant is a monitoring power plant corresponding to the extreme value of the prevention and control coefficient, the characteristic area is an effective division area corresponding to the regional prevention and control extreme value in the characteristic monitoring power plant, and the increase value of the silencer quantity is negatively correlated with the sub-silence threshold.

10. The gas power plant noise control method according to claim 9, characterized in that: The regional prevention coefficient is determined according to the redundancy coefficient; If the redundancy coefficient is greater than or equal to the preset redundancy coefficient, the regional prevention coefficient is determined according to the obstacle influence coefficient and the associated noise reduction ratio; If the redundancy coefficient is less than the preset redundancy coefficient, the regional prevention coefficient is determined according to the associated silencer ratio.

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