An active resistance noise reduction supervision method and system for expressways

Abstract

The present invention discloses an active resistance noise reduction supervision method and system for expressways, belonging to the technical field of dynamic supervision; the expressway is evenly divided into several route segments, and noise sensors are arranged; the operation state data of the noise reduction equipment within the route segment is obtained, and a periodic data acquisition sequence is constructed; a noise fluctuation coordinate system and a noise fluctuation curve of the route segment are constructed, and the slope of the noise fluctuation curve is calculated; a slope threshold is preset, if there is abnormal noise fluctuation in the route segment, the active resistance noise reduction index of the noise reduction equipment within the route segment is calculated, a preset index threshold interval is set, the active resistance noise reduction index of the noise reduction equipment within the route segment at the next data acquisition cycle node is predicted, and based on the index threshold interval, the noise reduction equipment with abnormal operation at the next data acquisition cycle node is analyzed and uniformly warned, which not only improves the operation efficiency of the noise reduction equipment on the expressway and reduces the risk of noise pollution, but also enhances the initiative of system regulation.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic supervision, and specifically provides an active resistance noise reduction supervision method and system for highways. Background Art

[0002] In recent years, with the development of intelligent perception and automation technologies, active noise reduction devices have gradually entered the field of traffic engineering applications. They have the ability to dynamically adjust power responses according to noise changes and have become an important supplement to traditional passive noise reduction means. However, most existing highway noise control systems mainly operate in a "fixed response" mode and lack a refined supervision mechanism for the actual operating conditions of equipment. As a result, when problems such as response lag, ineffective adjustment, or abnormal long-term operation occur in the noise reduction device, it is often difficult to detect and intervene in a timely manner, restricting the control efficiency and operation and maintenance economy of the active noise reduction system.

[0003] Current highway noise supervision methods mainly focus on the spatial distribution evaluation of noise intensity and the comparative analysis of long-term average values, lacking real-time quantitative indicators for "dynamic response capabilities". Some existing studies have attempted to conduct auxiliary analysis by combining equipment operation parameters such as current and voltage, but most still remain at the static diagnosis level and are difficult to accurately describe the dynamic adaptation capabilities of noise reduction equipment under actual noise fluctuations. In addition, existing systems mostly rely on manual regular inspections and experience judgments, unable to form a timely early warning mechanism at the initial stage of noise anomalies and also difficult to provide predictable data support for equipment regulation in the next cycle. Summary of the Invention

[0004] The purpose of the present invention is to provide an active resistance noise reduction supervision method and system for highways to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solutions:

[0006] An active resistance noise reduction supervision method for expressways, the method comprising the following steps: Step S1: Uniformly divide the expressway into a number of route segments, and deploy noise sensors within the route segments; obtain the operating state data of the noise reduction devices within the route segments, and construct a periodic data acquisition sequence; Step S2: According to the noise data, construct a noise fluctuation coordinate system and a noise fluctuation curve for the route segment at all data acquisition cycle nodes, and calculate the slope of the noise fluctuation curve between adjacent two coordinate points; Step S3: Preset a slope threshold. If there is abnormal noise fluctuation between adjacent two data acquisition cycle nodes of the route segment, calculate the active resistance noise reduction index of the noise reduction devices within the route segment, and preset an index threshold range; Step S4: Based on the active resistance noise reduction index, predict the active resistance noise reduction index of the noise reduction devices within the route segment at the next data acquisition cycle node, and based on the index threshold range, analyze and issue a unified warning for the noise reduction devices with abnormal operation at the next data acquisition cycle node.

[0007] As a preferred solution of the active resistance noise reduction supervision method for expressways described in the present invention, retrieve the route map of the expressway from the official website of the expressway. Based on the route map, uniformly divide the expressway into a number of route segments, and deploy noise sensors within the route segments, where one route segment corresponds to one noise sensor; obtain the operating state data of the noise reduction devices within the route segment, and the operating state data includes current data and voltage data;

[0008] Construct a periodic data acquisition sequence, denoted as , where represents the nth data acquisition cycle node, and N represents the total number of data acquisition cycle nodes; obtain the noise data of the ith route segment and the current data and voltage data of the ath noise reduction device within the ith route segment at the data acquisition cycle node , and denote them as , and .

[0009] As a preferred solution of the active resistance noise reduction supervision method for expressways described in the present invention, based on the noise data of the ith route segment at the data acquisition cycle node , construct a noise fluctuation coordinate system for the ith route segment at all data acquisition cycle nodes. The abscissa of the noise fluctuation coordinate system is N data acquisition cycle nodes arranged in sequence, and the ordinate of the noise fluctuation coordinate system is the noise data corresponding to the N data acquisition cycle nodes arranged in sequence;

[0010] All coordinate points in the noise fluctuation coordinate system are sequentially connected to construct a noise fluctuation curve, and the slope of the noise fluctuation curve between two adjacent coordinate points is calculated. The calculation formula is: ,in, Indicates the node of the i-th route segment at the data collection cycle To the data collection cycle node The slope of the noise fluctuation curve between Indicates the data collection cycle node The noise data within the next i-th route segment.

[0011] As a preferred solution of the active anti-noise monitoring method for highways described in the present invention, a slope threshold is preset, and if the i-th route segment is at the data collection cycle node To the data collection cycle node The slope of the noise fluctuation curve between If the slope is greater than or equal to the slope threshold, it is determined that the i-th route segment is at the data collection cycle node To the data collection cycle node If there is abnormal noise fluctuation between the two segments, the noise reduction equipment in the i-th route segment is calculated at the data collection cycle node To the data collection cycle node The active resistance noise reduction index between is calculated as follows:

[0012] ;

[0013] ;

[0014] in, Indicates the a-th noise reduction device in the i-th route segment at the data collection cycle node To the data collection cycle node The power variation between Indicates the data collection cycle node The current data of the ath silencer in the next ith route segment, Indicates the data collection cycle node The voltage data of the a-th silencer in the next ith route segment, Indicates the a-th noise reduction device in the i-th route segment at the data collection cycle node To the data collection cycle node Active resistance noise reduction index between;

[0015] It should be noted that the molecule It indicates the power change of the silencing equipment between two cycles, in watts, and the denominator is Indicates the change in noise intensity, usually measured in decibels. Therefore, the active resistance noise cancellation index has the unit of , which is an index of unit response efficiency. It represents how much power the device changes in response to a unit dB change in noise. That is to say, it reflects the strength of the device's response ability. Namely, the larger the value, the stronger the device's response to noise fluctuations; the smaller the value, the weaker the device's response, and there may be problems such as lag or low efficiency.

[0016] Preset the threshold range of the active resistance noise cancellation index. If the active resistance noise cancellation index of the a-th noise cancellation device in the i-th route segment between the data collection cycle node and the data collection cycle node does not fall within the preset threshold range of the active resistance noise cancellation index, it is determined that the a-th noise cancellation device in the i-th route segment has an abnormal operation between the data collection cycle node and the data collection cycle node .

[0017] It should be noted that by setting the slope threshold of the noise fluctuation curve, when abnormal noise fluctuations are detected, the active resistance noise cancellation index is further introduced to evaluate the device's response ability, realizing a leap from "event perception" to "device behavior quantification". This index combines the relationship between the power change of the noise cancellation device and the noise change, forming a unit response efficiency metric, which is a direct reflection of the "working intensity" and "environmental stimulus" of the noise cancellation device, and can accurately judge whether the noise cancellation device makes a timely and effective response to noise fluctuations, thereby identifying potential lag, overload, or ineffective operation situations.

[0018] As a preferred solution of the active resistance noise cancellation supervision method for highways described in the present invention, predict the active resistance noise cancellation index of the a-th noise cancellation device in the i-th route segment between the data collection cycle node and the data collection cycle node . The calculation formula is as follows:

[0019] ;

[0020] ;

[0021] Among them, represents the average value of the change in the active resistance noise cancellation index of the a-th noise cancellation device in the i-th route segment, represents the active resistance noise cancellation index of the a-th noise cancellation device in the i-th route segment between the data collection cycle node and the data collection cycle node , Indicates the active resistance noise reduction index of the a-th noise reduction device within the predicted i-th route segment between the data collection cycle node and the data collection cycle node ; Indicates the active resistance noise reduction index of the a-th noise reduction device within the i-th route segment between the data collection cycle node and the data collection cycle node ;

[0022] If the active resistance noise reduction index of the a-th noise reduction device within the predicted i-th route segment between the data collection cycle node and the data collection cycle node does not fall within the threshold interval of the active resistance noise reduction index , it is predicted that there will be an abnormal operation of the a-th noise reduction device within the i-th route segment between the data collection cycle node and the data collection cycle node ;

[0023] Let i = i + 1, traverse all the route segments within the expressway, obtain all the noise reduction devices predicted to have abnormal operations within the expressway, and send a warning and maintenance notice to the relevant staff.

[0024] An active resistance noise reduction supervision system for an expressway, the system includes: a data acquisition module, a coordinate system construction and slope calculation module, an index calculation module, and a prediction and warning output module;

[0025] The data acquisition module: evenly divides the expressway into several route segments, and arranges noise sensors within the route segments; obtains the operation status data of the noise reduction devices within the route segments, and constructs a periodic data collection sequence;

[0026] The coordinate system construction and slope calculation module: constructs a noise fluctuation coordinate system and a noise fluctuation curve of the route segment at all data collection cycle nodes according to the noise data, and calculates the slope of the noise fluctuation curve between two adjacent coordinate points;

[0027] The index calculation module: preset a slope threshold, if there is abnormal noise fluctuation between two adjacent data collection cycle nodes of the route segment, calculate the active resistance noise reduction index of the noise reduction devices within the route segment, and preset an index threshold interval;

[0028] The prediction and warning output module: based on the active resistance noise reduction index, predicts the active resistance noise reduction index of the noise reduction devices within the route segment at the next data collection cycle node, and based on the index threshold interval, analyzes and issues a unified warning for the noise reduction devices with abnormal operations at the next data collection cycle node.

[0029] Further, the data acquisition module includes a data acquisition unit;

[0030] The data acquisition unit: retrieves the route map of the highway from the official website of the highway, evenly divides the highway into several route segments based on the route map, and arranges noise sensors within the route segments, where one route segment corresponds to one noise sensor; acquires the operation status data of the noise elimination equipment within the route segment, and the operation status data includes current data and voltage data; constructs a periodic data acquisition sequence.

[0031] Further, the coordinate system construction and slope calculation module includes a coordinate system construction unit and a slope calculation unit;

[0032] The coordinate system construction unit: constructs a noise fluctuation coordinate system of the route segment at all data acquisition cycle nodes based on the noise data within the route segment at the data acquisition cycle nodes, where the abscissa of the noise fluctuation coordinate system is the sequentially arranged data acquisition cycle nodes, and the ordinate of the noise fluctuation coordinate system is the noise data corresponding to the sequentially arranged data acquisition cycle nodes;

[0033] The slope calculation unit: sequentially connects all the coordinate points in the noise fluctuation coordinate system to construct a noise fluctuation curve, and calculates the slope of the noise fluctuation curve between adjacent two coordinate points.

[0034] Further, the index calculation module includes an index calculation unit;

[0035] The index calculation unit: preset a slope threshold. If the slope of the noise fluctuation curve of the route segment between adjacent data acquisition cycle nodes is greater than or equal to the slope threshold, it is determined that there is an abnormal noise fluctuation of the route segment between adjacent data acquisition cycle nodes, and then calculate the active resistance noise elimination index of the noise elimination equipment within the route segment between adjacent data acquisition cycle nodes; preset an active resistance noise elimination index threshold interval. If the active resistance noise elimination index is not within the active resistance noise elimination index threshold interval, it is determined that there is an abnormal operation of the noise elimination equipment within the route segment between adjacent data acquisition cycle nodes.

[0036] Further, the prediction and early warning output module includes a prediction unit and an early warning output unit;

[0037] The prediction unit: predicts the active resistance noise elimination index of the noise elimination equipment within the route segment at the next data acquisition cycle node;

[0038] The warning output unit: If the predicted active resistance noise reduction index does not fall within the threshold range of the active resistance noise reduction index, the noise reduction equipment in the predicted route segment will have abnormal operation at the next data collection cycle node; traverse all route segments within the highway, obtain all noise reduction equipment predicted to have abnormal operation within the highway, and send a warning maintenance notice to relevant staff.

[0039] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In an active resistance noise reduction supervision method and system for highways provided by the present invention, by dividing the highway into several route segments and arranging noise sensors, and simultaneously collecting the current and voltage of the noise reduction equipment, the real-time perception of the acoustic environment and equipment status is realized; further, by constructing a noise fluctuation coordinate system and analyzing its curve slope, sudden noise events are effectively identified; an active resistance noise reduction index is introduced, combining noise fluctuation with power change, accurately evaluating the response ability of the equipment, and identifying potential abnormal operations; finally, by predicting the change trend of this index and setting a threshold to achieve early warning, assisting equipment scheduling and maintenance, and ultimately achieving the beneficial effects of improving the operation efficiency of highway noise reduction equipment, reducing the risk of noise pollution, and enhancing the initiative of system regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention.

[0041] Figure 1 It is a schematic diagram of the steps of an active resistance noise reduction supervision method for highways of the present invention;

[0042] Figure 2 It is a schematic diagram of the structure of an active resistance noise reduction supervision system for highways of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] Please refer to Figure 1 , in the first embodiment: Provide an active resistance noise reduction supervision method for highways, and the method includes the following steps:

[0045] Step S1: Evenly divide the highway into several route segments, and deploy noise sensors within the route segments; obtain the operation status data of the noise elimination devices within the route segments, and construct a periodic data acquisition sequence.

[0046] Specifically, retrieve the route map of the highway from the official website of the highway. Based on the route map, evenly divide the highway into several route segments, and deploy noise sensors within the route segments, where one route segment corresponds to one noise sensor; obtain the operation status data of the noise elimination devices within the route segments, and the operation status data includes current data and voltage data.

[0047] Furthermore, construct a periodic data acquisition sequence, denoted as , where represents the nth data acquisition cycle node, and N represents the total number of data acquisition cycle nodes; obtain the noise data within the ith route segment and the current data and voltage data of the ath noise elimination device within the ith route segment at the data acquisition cycle node , and denote them as , and .

[0048] Step S2: According to the noise data, construct a noise fluctuation coordinate system and a noise fluctuation curve for the route segment at all data acquisition cycle nodes, and calculate the slope of the noise fluctuation curve between adjacent two coordinate points.

[0049] Specifically, based on the noise data within the ith route segment at the data acquisition cycle node , construct a noise fluctuation coordinate system for the ith route segment at all data acquisition cycle nodes. The abscissa of the noise fluctuation coordinate system is N data acquisition cycle nodes arranged in sequence, and the ordinate of the noise fluctuation coordinate system is the noise data corresponding to the N data acquisition cycle nodes arranged in sequence.

[0050] Furthermore, sequentially connect all the coordinate points in the noise fluctuation coordinate system to construct a noise fluctuation curve, and calculate the slope of the noise fluctuation curve between adjacent two coordinate points. The calculation formula is: , where represents the slope of the noise fluctuation curve of the ith route segment between the data acquisition cycle node and the data acquisition cycle node , represents the noise data within the ith route segment at the data acquisition cycle node .

[0051] Step S3: Preset a slope threshold. If there is abnormal noise fluctuation in the route segment between two adjacent data acquisition cycle nodes, calculate the active resistance noise reduction index of the noise reduction device in the route segment and preset the index threshold range.

[0052] Specifically, preset a slope threshold. If the slope of the noise fluctuation curve of the i-th route segment between the data acquisition cycle node and the data acquisition cycle node is greater than or equal to the slope threshold, it is determined that there is abnormal noise fluctuation in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node . Then calculate the active resistance noise reduction index of the noise reduction device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node . The calculation formula is as follows:

[0053] ;

[0054] ;

[0055] where, represents the power change amount of the a-th noise reduction device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node , represents the current data of the a-th noise reduction device in the i-th route segment at the data acquisition cycle node , represents the voltage data of the a-th noise reduction device in the i-th route segment at the data acquisition cycle node , represents the active resistance noise reduction index of the a-th noise reduction device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node ;

[0056] It should be noted that the numerator represents the power change amount of the noise reduction device between two cycles, and the unit is watt. The denominator represents the change amount of the noise intensity, and the unit is usually decibel. Therefore, the unit of the active resistance noise reduction index is , is an indicator of the unit response efficiency, which represents how much power the device changes in response to a unit dB change in noise. That is to say, it reflects the strength of the device's response ability. Namely, the larger the value, the stronger the device's response to noise fluctuations; the smaller the value, the weaker the device's response, and there may be problems such as hysteresis or low efficiency. By presetting the threshold range of the active resistance noise reduction indicator, it is possible to quickly determine whether the device is operating normally. When the indicator value is lower than the lower limit of the threshold, it indicates that the device responds sluggishly and cannot adjust the power in a timely manner according to the noise change, resulting in poor noise reduction effect; if it is higher than the upper limit of the threshold, it may mean that the device over-responds, causing energy waste. This helps to maintain and optimize the device targeted, and improve the overall operating efficiency of the noise reduction device.

[0057] Furthermore, preset the threshold range of the active resistance noise reduction indicator. If the active resistance noise reduction indicator of the a-th noise reduction device in the i-th route segment at the data acquisition cycle node to the data acquisition cycle node is not within the threshold range of the active resistance noise reduction indicator, it is determined that the a-th noise reduction device in the i-th route segment has an abnormal operation at the data acquisition cycle node to the data acquisition cycle node to the data acquisition cycle node between.

[0058] Step S4: Based on the active resistance noise reduction indicator, predict the active resistance noise reduction indicator of the noise reduction device in the route segment at the next data acquisition cycle node, and based on the indicator threshold range, analyze and give a unified warning to the noise reduction device with abnormal operation at the next data acquisition cycle node.

[0059] Specifically, predict the active resistance noise reduction indicator of the a-th noise reduction device in the i-th route segment at the data acquisition cycle node to the data acquisition cycle node between. The calculation formula is as follows:

[0060] ;

[0061] ;

[0062] Among them, represents the average value of the change in the active resistance noise reduction indicator of the a-th noise reduction device in the i-th route segment, represents the active resistance noise reduction indicator of the a-th noise reduction device in the i-th route segment at the data acquisition cycle node to the data acquisition cycle node between, represents the predicted active resistance noise reduction indicator of the a-th noise reduction device in the i-th route segment at the data acquisition cycle node to the data acquisition cycle node The active noise cancellation index between represents the active noise cancellation index of the a-th noise cancellation device in the i-th route segment between the data acquisition cycle nodes and the data acquisition cycle node The active noise cancellation index between;

[0063] In the present invention, by accumulating and averaging the differences in the active noise cancellation indexes of multiple adjacent cycles, the influence of short-term fluctuations can be effectively eliminated, and the long-term change trend of the indexes can be shown. During the long-term operation of the highway, the performance of the noise cancellation device may gradually decline due to factors such as component aging and environmental erosion. By observing the average value of the index change amount, the slow change of the device performance can be discovered in advance, providing data support for preventive maintenance. When predicting the active noise cancellation index of the noise cancellation device in the next cycle, this average value is used as an important reference, enabling the prediction model to fully consider the historical change situation of the device performance. Compared with predicting only relying on the data of the current cycle, combining the average value of the change amount can more accurately reflect the future state of the device, reduce the prediction error, improve the reliability of early warning, and gain more time for taking maintenance measures in a timely manner.

[0064] Further, if the predicted active noise cancellation index of the a-th noise cancellation device in the i-th route segment between the data acquisition cycle nodes and the data acquisition cycle node The active noise cancellation index between does not exist within the threshold interval of the active noise cancellation index, it is predicted that there will be an abnormal operation of the a-th noise cancellation device in the i-th route segment between the data acquisition cycle nodes and the data acquisition cycle node There will be an abnormal operation between;

[0065] Further, let i = i + 1, traverse all the route segments in the highway, obtain all the noise cancellation devices predicted to have abnormal operations in the highway, and send a warning maintenance notice to the relevant staff.

[0066] Please refer to Figure 2 , in the second embodiment: A system for active noise cancellation supervision for highways is provided, and the system includes: a data acquisition module, a coordinate system construction and slope calculation module, an index calculation module, and a prediction and early warning output module;

[0067] The data acquisition module: evenly divides the highway into several route segments, and arranges noise sensors in the route segments; obtains the operation state data of the noise cancellation devices in the route segments, and constructs a periodic data acquisition sequence;

[0068] The coordinate system construction and slope calculation module: Based on the noise data, construct a noise fluctuation coordinate system and a noise fluctuation curve of the route segment at all data acquisition cycle nodes, and calculate the slope of the noise fluctuation curve between two adjacent coordinate points;

[0069] The index calculation module: Preset a slope threshold. If there is abnormal noise fluctuation in the route segment between two adjacent data acquisition cycle nodes, calculate the active resistance noise reduction index of the noise reduction equipment in the route segment, and preset an index threshold range;

[0070] The prediction and early warning output module: Based on the active resistance noise reduction index, predict the active resistance noise reduction index of the noise reduction equipment in the route segment at the next data acquisition cycle node, and based on the index threshold range, analyze and give a unified early warning to the noise reduction equipment with abnormal operation at the next data acquisition cycle node.

[0071] Further, the data acquisition module includes a data acquisition unit;

[0072] The data acquisition unit: Retrieve the route map of the highway from the official website of the highway. Based on the route map, evenly divide the highway into several route segments, and deploy noise sensors in the route segments, where one route segment corresponds to one noise sensor; obtain the operation status data of the noise reduction equipment in the route segment, and the operation status data includes current data and voltage data; construct a periodic data acquisition sequence.

[0073] Further, the coordinate system construction and slope calculation module includes a coordinate system construction unit and a slope calculation unit;

[0074] The coordinate system construction unit: Based on the noise data in the route segment at the data acquisition cycle node, construct a noise fluctuation coordinate system of the route segment at all data acquisition cycle nodes. The abscissa of the noise fluctuation coordinate system is the sequentially arranged data acquisition cycle nodes, and the ordinate of the noise fluctuation coordinate system is the noise data corresponding to the sequentially arranged data acquisition cycle nodes;

[0075] The slope calculation unit: Sequentially connect all the coordinate points in the noise fluctuation coordinate system to construct a noise fluctuation curve, and calculate the slope of the noise fluctuation curve between two adjacent coordinate points.

[0076] Further, the index calculation module includes an index calculation unit;

[0077] The index calculation unit: preset a slope threshold. If the slope of the noise fluctuation curve of a route segment between adjacent data collection cycle nodes is greater than or equal to the slope threshold, it is determined that there is abnormal noise fluctuation in the route segment between adjacent data collection cycle nodes, and then calculate the active resistance noise reduction index of the noise reduction device in the route segment between adjacent data collection cycle nodes; preset an active resistance noise reduction index threshold range. If the active resistance noise reduction index is not within the active resistance noise reduction index threshold range, it is determined that there is an abnormal operation of the noise reduction device in the route segment between adjacent data collection cycle nodes.

[0078] Further, the prediction and early warning output module includes a prediction unit and an early warning output unit;

[0079] The prediction unit: predicts the active resistance noise reduction index of the noise reduction device in the route segment at the next data collection cycle node;

[0080] The early warning output unit: if the predicted active resistance noise reduction index is not within the active resistance noise reduction index threshold range, it is predicted that there will be an abnormal operation of the noise reduction device in the route segment at the next data collection cycle node; traverse all the route segments in the expressway, obtain all the noise reduction devices predicted to have abnormal operations in the expressway, and send an early warning maintenance notice to the relevant staff.

[0081] It should be noted that in this article, 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 "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including 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.

[0082] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An active resistance noise reduction supervision method for highways, characterized in that, The method includes the following steps: Step S1: Evenly divide the highway into several route segments, and deploy noise sensors within the route segments; obtain the operating state data of the noise elimination devices within the route segments, and construct a periodic data acquisition sequence; The operating state data includes current data and voltage data; Construct a periodic data acquisition sequence, denoted as , where represents the nth data acquisition cycle node, and N represents the total number of data acquisition cycle nodes; obtain the noise data in the ith route segment and the current data and voltage data of the ath noise elimination device in the ith route segment at the data acquisition cycle node , and denote them as , and ; Step S2: According to the noise data, construct a noise fluctuation coordinate system and a noise fluctuation curve for the route segment at all data acquisition cycle nodes, and calculate the slope of the noise fluctuation curve between two adjacent coordinate points; Step S3: Preset a slope threshold. If there is abnormal noise fluctuation between two adjacent data acquisition cycle nodes of the route segment, calculate the active resistance noise elimination index of the noise elimination devices within the route segment, and preset an index threshold interval; Calculate the active resistance noise reduction index of the noise elimination device within the i-th route segment between the data acquisition cycle node and the data acquisition cycle node . The calculation formula is as follows: ； ； Among them, represents the power change amount of the a-th noise elimination device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node ; represents the current data of the a-th noise elimination device in the i-th route segment at the data acquisition cycle node ; represents the voltage data of the a-th noise elimination device in the i-th route segment at the data acquisition cycle node ; represents the active resistance noise elimination index of the a-th noise elimination device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node ; Step S4: Based on the active resistance noise elimination index, predict the active resistance noise elimination index of the noise elimination devices within the route segment at the next data acquisition cycle node, and based on the index threshold interval, analyze and issue a unified warning for the noise elimination devices with abnormal operation at the next data acquisition cycle node; ； It represents the mean value of the change in the active resistance noise reduction index of the a-th noise reduction device within the i-th route segment; Indicates the active resistance noise reduction index of the a-th noise elimination device in the i-th predicted route segment between the data acquisition cycle node and the data acquisition cycle node Indicates the active resistance noise reduction index of the a-th noise elimination device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node ​​ 2. The active resistance noise reduction supervision method for expressways according to claim 1, wherein The specific implementation process of Step S1 includes: Retrieve the route map of the highway from the official website of the highway. Based on the route map, evenly divide the highway into several route segments, and deploy noise sensors within the route segments. One route segment corresponds to one noise sensor; obtain the operating state data of the noise elimination devices within the route segment.

3. The active resistance silencing supervision method for expressways according to claim 2, characterized in that, The specific implementation process of Step S2 includes: Based on the data acquisition cycle nodes the noise data within the i-th route segment , construct a noise fluctuation coordinate system for the i-th route segment under all data acquisition cycle nodes. The abscissa of the noise fluctuation coordinate system is N sequentially arranged data acquisition cycle nodes, and the ordinate of the noise fluctuation coordinate system is the noise data corresponding to the N sequentially arranged data acquisition cycle nodes; Sequentially connect all the coordinate points in the noise fluctuation coordinate system to construct a noise fluctuation curve, and calculate the slope of the noise fluctuation curve between two adjacent coordinate points. The calculation formula is: , where represents the slope of the noise fluctuation curve of the i-th route segment between the data acquisition cycle node and the data acquisition cycle node , represents the noise data within the i-th route segment at the data acquisition cycle node .

4. The active resistance noise reduction supervision method for expressways according to claim 3, characterized in that, The specific implementation process of Step S3 includes: A preset slope threshold. If the slope of the noise fluctuation curve of the i-th route segment between the data acquisition cycle node and the data acquisition cycle node is greater than or equal to the slope threshold, it is determined that there is an abnormal noise fluctuation in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node to the data acquisition cycle node ; Preset active resistance noise reduction index threshold interval, if the a-th noise reduction device in the i-th route segment is at the data collection cycle node To the data collection cycle node Active resistance noise reduction index between If the active resistance noise reduction index threshold value does not exist, it is determined that the a-th noise reduction device in the i-th route segment is at the data collection cycle node To the data collection cycle node There are operational anomalies.

5. The active resistance silencing supervision method for expressways according to claim 4, characterized in that, The specific implementation process of Step S4 includes: Predict the active noise reduction index of the a-th noise elimination device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node . The calculation formula is as follows: ； Among them, represents the active noise reduction index of the a-th noise elimination device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node ; If the active noise cancellation index of the a-th noise cancellation device in the i-th predicted route segment between the data acquisition cycle node and the data acquisition cycle node does not fall within the threshold range of the active noise cancellation index, it is predicted that there will be an abnormal operation of the a-th noise cancellation device in the i-th route segment between the data acquisition cycle node and the data acquisition cycle node and the data acquisition cycle node ; Let i = i + 1, traverse all the route segments within the highway, obtain all the noise elimination devices predicted to have abnormal operation within the highway, and send a warning and maintenance notice to the relevant staff.

6. An active resistance noise reduction supervision system for expressways, which executes an active resistance noise reduction supervision method for expressways as described in any one of claims 1-5, characterized in that, The system includes: a data acquisition module, a coordinate system construction and slope calculation module, an index calculation module, and a prediction and warning output module; The data acquisition module: Evenly divide the highway into several route segments, and deploy noise sensors within the route segments; obtain the operating state data of the noise elimination devices within the route segments, and construct a periodic data acquisition sequence; The coordinate system construction and slope calculation module: According to the noise data, construct a noise fluctuation coordinate system and a noise fluctuation curve for the route segment at all data acquisition cycle nodes, and calculate the slope of the noise fluctuation curve between two adjacent coordinate points; The index calculation module: Preset a slope threshold. If there is abnormal noise fluctuation between two adjacent data acquisition cycle nodes of the route segment, calculate the active resistance noise elimination index of the noise elimination devices within the route segment, and preset an index threshold interval; The prediction and warning output module: Based on the active resistance noise elimination index, predict the active resistance noise elimination index of the noise elimination devices within the route segment at the next data acquisition cycle node, and based on the index threshold interval, analyze and issue a unified warning for the noise elimination devices with abnormal operation at the next data acquisition cycle node.

7. The active resistance noise elimination supervision system for expressways according to claim 6, characterized in that: The data acquisition module includes a data acquisition unit; The data acquisition unit: retrieves the road map of the highway from the official website of the highway, evenly divides the highway into several road segments based on the road map, and arranges noise sensors within the road segments, where one road segment corresponds to one noise sensor; obtains the operation status data of the noise elimination equipment within the road segment, and the operation status data includes current data and voltage data; constructs a periodic data acquisition sequence.

8. An active resistance noise cancellation supervision system for expressways according to claim 7, characterized in that: The coordinate system construction and slope calculation module includes a coordinate system construction unit and a slope calculation unit; The coordinate system construction unit: constructs a noise fluctuation coordinate system of the road segment at all data acquisition cycle nodes based on the noise data within the road segment at the data acquisition cycle nodes, where the abscissa of the noise fluctuation coordinate system is the sequentially arranged data acquisition cycle nodes, and the ordinate of the noise fluctuation coordinate system is the noise data corresponding to the sequentially arranged data acquisition cycle nodes; The slope calculation unit: sequentially connects all the coordinate points in the noise fluctuation coordinate system to construct a noise fluctuation curve, and calculates the slope of the noise fluctuation curve between adjacent two coordinate points.

9. The active resistance noise reduction supervision system for expressways according to claim 8, characterized in that: The index calculation module includes an index calculation unit; The index calculation unit: preset a slope threshold, if the slope of the noise fluctuation curve of the road segment between adjacent data acquisition cycle nodes is greater than or equal to the slope threshold, it is determined that there is an abnormal noise fluctuation in the road segment between adjacent data acquisition cycle nodes, and then calculate the active resistance noise elimination index of the noise elimination equipment within the road segment between adjacent data acquisition cycle nodes; Preset an active resistance noise elimination index threshold range, if the active resistance noise elimination index is not within the active resistance noise elimination index threshold range, it is determined that there is an abnormal operation of the noise elimination equipment within the road segment between adjacent data acquisition cycle nodes.

10. The active resistance noise elimination supervision system for expressways according to claim 9, wherein: The prediction and early warning output module includes a prediction unit and an early warning output unit; The prediction unit: predicts the active resistance noise elimination index of the noise elimination equipment within the road segment at the next data acquisition cycle node; The early warning output unit: if the predicted active resistance noise elimination index is not within the active resistance noise elimination index threshold range, it is predicted that there will be an abnormal operation of the noise elimination equipment within the road segment at the next data acquisition cycle node; traverses all the road segments within the highway, obtains all the noise elimination equipment predicted to have abnormal operation within the highway, and sends a warning maintenance notice to the relevant staff.

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