Flue gas detection system based on Internet of Things analysis

Abstract

The invention relates to the technical field of flue gas detection, in particular to a flue gas detection system based on Internet of Things analysis, which comprises a data acquisition module, an extraction module, a temporary determination module, an abnormity determination module, a correction module, an adjustment module and an alarm module. According to the invention, through real-time acquisition and comprehensive analysis of smoke concentration, wind speed and image information of each shadow area in a factory, the problem that smoke gathering in the shadow areas is not easy to perceive is effectively solved, and the areas often become blind spots of smoke detection due to insufficient illumination or equipment shielding. The system not only extracts the shadow area, the light spot width and the position in the real-time image, but also can accurately identify the abnormal flue gas gathering area in combination with the flue gas concentration and wind speed data, and can dynamically adjust the detection standard to find the potential flue gas dangerous area in time, thereby improving the detection efficiency. The problem that the smoke detection precision of the shadow area is low due to limited monitoring range and single analysis data source is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of smoke detection, and in particular to a smoke detection system based on Internet of Things analysis. Background Art

[0002] In a flue gas treatment plant, the collection, filtration and discharge of flue gas are the core links. However, due to the complexity of flue gas flow, especially in the shadowed areas inside the plant, equipment gaps or around pipes, some flue gas may not be collected in time, resulting in high-concentration smoke accumulation in local areas. The accumulation of smoke in these hidden areas not only affects the overall emission control, but may also reduce the treatment efficiency and even pose a threat to the health of workers. Traditional smoke detection systems often rely on fixed-point monitoring or overall concentration analysis, which makes it difficult to accurately identify abnormal local accumulation of smoke. Especially in a factory environment with complex aerodynamics, factors such as wind speed, flow direction, and obstacles will affect the diffusion and deposition of smoke, causing the smoke concentration in some areas to increase abnormally but not be discovered in time. Therefore, accurate detection of smoke accumulation in shadowed areas and dynamic adjustment of the alarm mechanism are important directions for improving the safety and efficiency of flue gas treatment plants.

[0003] The patent document with publication number CN111896683A discloses a flue gas online detection system based on cloud services, which includes: an on-site quality control monitoring platform, a remote quality control monitoring platform and an environmental protection monitoring platform, and is characterized in that: the on-site quality control monitoring platform converts the monitoring data of the flue gas sampling and analysis in the on-site chimney into electrical signals and transmits them to the environmental protection monitoring platform through the Internet, and converts the quality inspection data of the flue gas sampling and analysis into radio wave signals and wirelessly transmits them to the remote quality control monitoring platform. The remote quality control monitoring platform issues quality control instructions to the on-site quality control monitoring platform to monitor the quality of the flue gas in the on-site chimney, and converts the monitoring data into electrical signals and transmits them to the environmental protection monitoring platform through the Internet.

[0004] It can be seen that the smoke detection system has the following problems: the system focuses on overall smoke quality monitoring, lacks a local adaptive adjustment mechanism for the smoke diffusion characteristics inside the factory, and it is difficult to dynamically optimize standard parameters to improve detection accuracy; the system only relies on smoke sampling and analysis, resulting in low recognition accuracy for local smoke accumulation, which is prone to missed detection or false alarms; the system relies on cloud services and remote monitoring, and data transmission and processing are easily affected by network delays, resulting in a slow response to sudden smoke accumulation and difficulty in timely warning and adjustment. Summary of the invention

[0005] To this end, the present invention provides a smoke detection system based on Internet of Things analysis, which is used to overcome the problem of low smoke detection accuracy in shadow areas due to limited monitoring range and single analysis data source in the prior art by combining smoke concentration, dynamic scenes and dynamic thresholds.

[0006] To achieve the above object, the present invention provides a smoke detection system based on Internet of Things analysis, comprising: A data acquisition module is used to obtain real-time smoke concentration collected by a number of smoke sensors at each shadow area in the factory, real-time wind speed collected by a number of anemometers, and real-time images collected by an image sensor; An extraction module, connected to the data acquisition module, for extracting the real-time shadow area, the real-time average width of the light spot and the real-time light spot position of each of the real-time images; A temporary determination module, which is connected to the data acquisition module and the extraction module respectively, and is used to determine a number of temporary areas according to the real-time smoke concentration, the real-time shadow area and a preset standard synchronization degree; an abnormality determination module, which is connected to the extraction module and the temporary determination module respectively, and is used to determine a number of abnormal areas according to the real-time light spot average width, the real-time light spot position and a preset standard distribution degree in the temporary area; A correction module, which is connected to the abnormality determination module and the data acquisition module respectively, and is used to correct the abnormal area according to the real-time smoke concentration and the real-time wind speed of any two adjacent abnormal areas to form a plurality of correction areas; an adjustment module, which is connected to the temporary determination module and the correction module respectively, and is used to adjust the preset standard synchronization degree according to the number of the correction areas and the real-time shadow area within a preset adjustment period to form an adjustment standard synchronization degree, or adjust the preset standard distribution degree to form an adjustment standard distribution degree; An alarm module is connected to the abnormality determination module and is used to issue a smoke accumulation alarm for the abnormal area determined based on the adjustment standard synchronization degree or the adjustment standard distribution degree.

[0007] Furthermore, the temporary determination module includes: A concentration fluctuation calculation unit, used to calculate the standard deviation of the real-time smoke concentration within a preset temporary determined time period to form a concentration fluctuation value; An area fluctuation calculation unit, used to calculate the standard deviation of the real-time shadow area within the preset temporary determination time length to form an area fluctuation value; A temporary determination unit is connected to the concentration fluctuation calculation unit and the area fluctuation calculation unit respectively, and is used to determine a plurality of temporary areas according to the concentration fluctuation value, the area fluctuation value and the preset standard synchronization degree.

[0008] Further, the temporary determination unit includes: A concentration curve drawing subunit is used to draw a change curve of the concentration fluctuation value within the preset temporary determined time period to form a concentration curve; An area curve drawing subunit is used to draw a change curve of the area fluctuation value within the preset temporary determined time period to form an area curve; a synchronization degree calculation unit, which is connected to the concentration curve drawing subunit and the area curve drawing subunit respectively, and is used to calculate the cosine similarity of the concentration curve and the area curve to form a change synchronization degree; The temporary determination subunit is connected to the synchronization degree calculation unit and is used to determine the shadow area as the temporary area when the change synchronization degree is less than the preset standard synchronization degree, so as to determine a plurality of temporary areas.

[0009] Furthermore, the abnormality determination module includes: A width fluctuation calculation unit, used to calculate the standard deviation of the average width of the real-time light spot within a preset abnormal determination time length to form a width fluctuation value; An abnormality determination unit is connected to the width fluctuation calculation unit and is used to determine a number of abnormal areas according to the real-time spot position, the preset distribution center and the preset standard distribution degree when the width fluctuation value is greater than the preset width fluctuation threshold.

[0010] Furthermore, the abnormality determination unit includes: A distribution degree calculation unit, used to calculate the standard deviation of the distances from all the real-time light spot positions to the preset distribution center to form a concentrated distribution degree; An abnormality determination unit is connected to the distribution degree calculation unit and is used to determine that the temporary area is the abnormal area when the concentrated distribution degree is less than the preset standard distribution degree, so as to determine a plurality of abnormal areas.

[0011] Furthermore, the correction module includes: A concentration change rate calculation unit, used for calculating the ratio of the difference between the real-time smoke concentrations of the two abnormal areas and the distance between the two abnormal areas to form a concentration change rate; A wind speed change rate calculation unit, used for calculating the ratio of the difference between the real-time wind speeds of the two abnormal areas and the distance between the two abnormal areas to form a wind speed change rate; A correction unit is connected to the concentration change rate calculation unit and the wind speed change rate calculation unit respectively, and is used to correct the abnormal area according to the concentration change rate and the wind speed change rate to form a plurality of correction areas.

[0012] Furthermore, the correction unit comprises: a normalization subunit, used for normalizing the concentration change rate to form a normalized concentration change rate, and for normalizing the wind speed change rate to form a normalized wind speed change rate; a correction index calculation subunit, connected to the normalization subunit, for performing weighted summation on the concentration normalization change rate, the preset concentration change rate weight, the wind speed normalization change rate, and the preset wind speed change rate weight to form a correction determination index; a deviation calculation subunit, connected to the correction index calculation subunit, for calculating the relative deviation between the correction determination index and the preset standard determination index to form a correction deviation; The correction subunit is connected to the deviation calculation subunit and is used to determine that the area extending outward from the corresponding abnormal area by a preset length is a correction area when the correction deviation is greater than a preset deviation threshold, so as to form a plurality of correction areas.

[0013] Furthermore, the adjustment module includes: an average area calculation unit, used to calculate the ratio of the sum of all the real-time shadow areas at each moment in the preset adjustment period to the number of the correction areas to form a plurality of average shadow areas; A shadow fluctuation calculation unit, connected to the average area calculation unit, for calculating the standard deviation of all the average shadow areas to form a shadow fluctuation value; An adjustment unit is connected to the shadow fluctuation calculation unit, and is used to adjust the preset standard synchronization degree according to the shadow fluctuation value to form the adjusted standard synchronization degree, or adjust the preset standard distribution degree to form the adjusted standard distribution degree.

[0014] Furthermore, the adjustment unit includes: an adjustment determination subunit, for determining that the preset standard distribution degree needs to be adjusted when the shadow fluctuation value is less than the minimum value of the preset shadow fluctuation range, and forming a distribution degree adjustment determination result; and for determining that the preset standard synchronization degree needs to be adjusted when the shadow fluctuation value is greater than the maximum value of the preset shadow fluctuation range, and forming a synchronization degree adjustment determination result; The standard adjustment subunit is connected to the adjustment judgment subunit and is used to adjust the preset standard distribution degree when forming the distribution degree adjustment judgment result to form the adjusted standard distribution degree, and to adjust the preset standard synchronization degree when forming the synchronization degree adjustment judgment result to form the adjusted standard synchronization degree.

[0015] Further, the standard adjustment subunit adjusts the preset standard distribution degree including: increasing the preset standard distribution degree according to the minimum value of the preset shadow fluctuation range and the relative deviation of the shadow fluctuation value and a preset adjustment coefficient to form the adjusted standard distribution degree; The standard adjustment subunit adjusts the preset standard synchronization degree including: increasing the preset standard synchronization degree according to the relative deviation between the shadow fluctuation value and the maximum value of the preset shadow fluctuation range and the preset adjustment coefficient to form the adjusted standard synchronization degree.

[0016] Compared with the prior art, the beneficial effect of the present invention is that, by real-time acquisition and comprehensive analysis of the smoke concentration, wind speed and image information of each shadow area in the factory, the problem of smoke accumulation in the shadow area is effectively solved. These areas often become blind spots of smoke detection due to insufficient light or equipment obstruction. The system not only extracts the shadow area, spot width and position in the real-time image, but also combines the smoke concentration and wind speed data to accurately identify abnormal areas of smoke accumulation. Through temporary determination, abnormal determination and correction modules, the system dynamically adjusts the detection standards, improves the sensitivity and accuracy of detection, and ensures that potential smoke danger areas can be discovered in time. Finally, the system optimizes the detection accuracy by adjusting the synchronization and distribution, and issues a smoke accumulation alarm to ensure that workers can get the warning in the first time, thereby effectively reducing the health risks and safety hazards caused by smoke accumulation in the factory, and effectively solving the problem of low smoke detection accuracy in the shadow area due to limited monitoring range and single source of analysis data.

[0017] Furthermore, by calculating the fluctuation values ​​of smoke concentration and shadow area, the changing trends of smoke and shadow areas can be effectively captured, and then areas with abnormal changes can be identified, which can accurately reflect the dynamic changes of smoke diffusion and occlusion in the factory environment, avoiding the errors caused by relying on static data or a single parameter. By real-time monitoring of concentration and shadow fluctuations, potential smoke accumulation problems can be discovered in time, avoiding the lag and false alarm risks in traditional detection methods, thereby improving the response speed and accuracy of the system, ensuring the safety of the factory environment while improving the stability and reliability of the system.

[0018] Furthermore, by drawing concentration and area fluctuation curves and calculating their cosine similarity, the dynamic relationship between changes in smoke concentration and shadow area can be accurately captured. The synchronization calculation method helps to filter out short-term fluctuations caused by environmental changes or measurement errors, avoid unnecessary misjudgments, and ensure that only when the changing trends of smoke concentration and shadow area are significantly out of sync will they be judged as abnormal areas, thereby improving the judgment accuracy of the system, making smoke detection more sensitive and reliable, and able to maintain a high degree of accuracy under changing environmental conditions.

[0019] Furthermore, by calculating the fluctuation of the spot width and comparing it with the preset threshold, abnormal areas caused by smoke or other interfering objects can be effectively identified. The influence of unnecessary small fluctuations in the environment on the system judgment is avoided, and the stability and accuracy of detection are improved. A reasonably set width fluctuation threshold can accurately locate the smoke gathering area, reduce the possibility of false alarms, and thus improve the reliability and response speed of the system in a dynamic environment.

[0020] Furthermore, by analyzing the standard deviation of the light spot position, it is possible to accurately determine whether the light spot is abnormally diffused or concentrated. By calculating the concentration distribution, the system can effectively identify abnormal smoke areas, avoid misjudgment and missed judgment, improve the sensitivity and accuracy of smoke detection, ensure the safe monitoring of the factory environment, and accurately monitor and respond to smoke changes by combining the light spot position and distribution characteristics.

[0021] Furthermore, by calculating the concentration and wind speed change rate, the correction module can more accurately adjust the range of the abnormal area, making the smoke detection system more sensitive and accurate under different environmental conditions. Changes in wind speed and concentration directly affect the diffusion pattern of smoke. Correction based on these dynamic factors can avoid inaccurate division of abnormal areas due to local interference or errors, improve the adaptability of the system, ensure the accuracy and real-time performance of smoke monitoring, and dynamically adjust parameters to enable the system to respond to different situations, thereby achieving better monitoring effects.

[0022] Furthermore, by normalizing the concentration change rate and wind speed change rate, parameters of different dimensions can be processed under the same standard, thus avoiding the impact of differences in numerical ranges on the judgment results. The weighted summation step introduces preset weights, so that the contribution of different factors to the correction area can be adjusted according to actual needs, improving the flexibility and accuracy of the system. The accuracy of the correction is ensured by calculating the relative deviation, and correction is only made when the deviation is large, avoiding unnecessary adjustments, which can more accurately reflect the actual smoke diffusion situation, making the determination of the correction area more accurate, and effectively improving the stability and reliability of the monitoring system.

[0023] Furthermore, by calculating the fluctuation of the shadow area to adjust the synchronization or distribution, the changes in the shadow area under different environmental conditions can be effectively responded to, so that the system can maintain high stability and accuracy in a dynamic environment. By adjusting the standard synchronization or standard distribution, more accurate anomaly detection and area correction can be achieved, the performance of smoke detection can be optimized, the response speed and accuracy of the system can be improved, and efficient operation can be maintained in a changing factory environment.

[0024] Furthermore, by adjusting the standard synchronization and distribution according to the shadow fluctuation value calculated in real time, the system can dynamically respond to environmental changes, especially fluctuations in the shadow area. Specifically, when the shadow fluctuation value is less than the minimum value, it means that the change in the shadow area is very small, indicating that the system is not sensitive enough to environmental changes, resulting in a decrease in the ability to capture the light spot distribution. In this case, adjusting the distribution helps to improve the system's sensitivity to small changes and ensure that the light spot distribution can more accurately reflect the actual situation, thereby enhancing detection accuracy. When the shadow fluctuation value is greater than the maximum value, it means that the shadow area fluctuates too much because the external environment changes dramatically, causing the system's judgment of the light spot to become unstable. At this time, the synchronization needs to be adjusted to ensure that the system can effectively handle this instability and avoid overly sensitive response misjudgments. The focus will be placed on the control system's ability to adapt to large-scale changes, thereby maintaining overall detection accuracy and stability.

[0025] Furthermore, by dynamically adjusting the standard distribution and synchronization according to the deviation of the shadow fluctuation value from the preset range, it can ensure that the system responds sensitively and reasonably to different environmental conditions (such as light fluctuations and smoke changes), enhance the adaptability of the system, and enable it to maintain efficient operation in various actual environments, thereby improving the accuracy and reliability of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a schematic diagram of a smoke detection system based on Internet of Things analysis in this embodiment; Figure 2 A decision logic diagram for temporarily determining a subunit to determine a temporary area in this embodiment; Figure 3 This is a determination logic diagram of the abnormality determination unit of this embodiment for determining an abnormal area; Figure 4 This is a decision logic diagram for the correction subunit in this embodiment to determine the correction area. DETAILED DESCRIPTION

[0027] 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.

[0028] 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.

[0029] See also Figure 1 As shown, it is a schematic diagram of the smoke detection system based on Internet of Things analysis in this embodiment; This embodiment provides a smoke detection system based on Internet of Things analysis, including: A data acquisition module is used to obtain real-time smoke concentration collected by a number of smoke sensors at each shadow area in the factory, real-time wind speed collected by a number of anemometers, and real-time images collected by an image sensor; An extraction module, connected to the data acquisition module, for extracting the real-time shadow area, the real-time average width of the light spot and the real-time light spot position of each of the real-time images; A temporary determination module, which is connected to the data acquisition module and the extraction module respectively, and is used to determine a number of temporary areas according to the real-time smoke concentration, the real-time shadow area and a preset standard synchronization degree; an abnormality determination module, which is connected to the extraction module and the temporary determination module respectively, and is used to determine a number of abnormal areas according to the real-time light spot average width, the real-time light spot position and a preset standard distribution degree in the temporary area; A correction module, which is connected to the abnormality determination module and the data acquisition module respectively, and is used to correct the abnormal area according to the real-time smoke concentration and the real-time wind speed of any two adjacent abnormal areas to form a plurality of correction areas; an adjustment module, which is connected to the temporary determination module and the correction module respectively, and is used to adjust the preset standard synchronization degree according to the number of the correction areas and the real-time shadow area within a preset adjustment period to form an adjustment standard synchronization degree, or adjust the preset standard distribution degree to form an adjustment standard distribution degree; An alarm module is connected to the abnormality determination module and is used to issue a smoke accumulation alarm for the abnormal area determined based on the adjustment standard synchronization degree or the adjustment standard distribution degree.

[0030] Shadow areas refer to darker areas in an image where the brightness of some areas is lower than the set brightness threshold due to the influence of light sources or other obstructions. Usually, these areas appear as areas below a certain standard brightness value in the brightness distribution of the image. For example, if the brightness of a part of an image is less than the preset brightness threshold (less than 50% of the maximum brightness value), the part can be determined as a shadow area. The identification of shadow areas is of great significance for scenes such as smoke and pollutant distribution in analysis and monitoring, and can help accurately locate problem areas.

[0031] The preset standard synchronization degree is a standard value used to measure the degree of synchronization between the change in smoke concentration and the change in the light spot in the shadow area. It depends on the response sensitivity of the system and the speed of environmental changes. It is usually set between 0.7 and 1.0. In this embodiment, it is set to 0.85, which can ensure that in most cases when the synchronization degree is high, the system can more accurately judge the real-time status of smoke changes.

[0032] The preset standard distribution degree is a standard value used to measure the light spot position and smoke concentration distribution. It depends on the spatial layout inside the factory and the characteristics of smoke diffusion. It is usually set between 0.5 and 1.0. In this embodiment, it is set to 0.75, which helps the system to effectively identify abnormal smoke accumulation areas when the smoke distribution at different locations is relatively uniform.

[0033] The preset adjustment period is the time interval for adjusting the synchronization and distribution, which usually depends on the system's adaptability to changes and the speed of smoke diffusion. It is usually set between 10 minutes and 30 minutes. In this embodiment, it is set to 20 minutes, which can avoid too frequent adjustments while maintaining high sensitivity and reduce unnecessary system fluctuations.

[0034] The alarm module is connected to the abnormal determination module, and mainly identifies abnormal areas by analyzing the adjusted standard synchronization or standard distribution. Once the system detects that the smoke concentration or wind speed in these areas reaches the preset danger threshold, the alarm module will trigger an alarm and issue a smoke accumulation warning in time. This function effectively ensures the safety of the factory working environment and can quickly remind workers to take necessary safety measures in the early stage of smoke accumulation, thereby preventing threats to workers' health and the production environment due to smoke leakage or accumulation.

[0035] Multi-sensors collect smoke concentration, wind speed and image data of each shadow area in the factory in real time through wireless network, and upload the collected data to the data acquisition module through the Internet of Things device. The use of the Internet of Things ensures efficient data transmission, real-time and remote monitoring, and supports the system to accurately monitor and dynamically analyze the factory environment. The extraction module is connected to the data acquisition module through the image processing algorithm, receives image data from the image sensor in real time, uses image recognition technology to analyze the shadow area in the image, calculates the area of ​​each shadow area, and extracts the average width and position of the light spot. By performing edge detection, morphological processing and geometric analysis on the image, the extraction module can accurately identify and calculate the real-time shadow area, light spot width and position, thereby providing the necessary image feature data for subsequent analysis and judgment. The abnormal determination module analyzes the change of the light spot in the temporary area and determines the abnormal area. The correction module corrects the abnormal area according to the concentration and wind speed data of the adjacent abnormal area. The adjustment module adjusts the synchronization or distribution according to the number of correction areas and the shadow area to optimize the monitoring sensitivity. Finally, the alarm module issues a smoke accumulation alarm according to the adjusted synchronization or distribution.

[0036] By acquiring and comprehensively analyzing the smoke concentration, wind speed and image information of each shadow area in the factory in real time, the problem of smoke accumulation in the shadow area is effectively solved. These areas often become blind spots for smoke detection due to insufficient light or equipment obstruction. The system not only extracts the shadow area, spot width and position in the real-time image, but also combines the smoke concentration and wind speed data to accurately identify abnormal areas of smoke accumulation. Through temporary determination, abnormal determination and correction modules, the system dynamically adjusts the detection standards, improves the sensitivity and accuracy of detection, and ensures that potential smoke danger areas can be discovered in time. Finally, the system optimizes the detection accuracy by adjusting the synchronization and distribution, and issues a smoke accumulation alarm to ensure that workers can get the warning at the first time, thereby effectively reducing the health risks and safety hazards caused by smoke accumulation in the factory, and effectively solving the problem of low smoke detection accuracy in shadow areas due to limited monitoring range and single source of analysis data.

[0037] Specifically, the temporary determination module includes: A concentration fluctuation calculation unit, used to calculate the standard deviation of the real-time smoke concentration within a preset temporary determined time period to form a concentration fluctuation value; An area fluctuation calculation unit, used to calculate the standard deviation of the real-time shadow area within the preset temporary determination time length to form an area fluctuation value; A temporary determination unit is connected to the concentration fluctuation calculation unit and the area fluctuation calculation unit respectively, and is used to determine a plurality of temporary areas according to the concentration fluctuation value, the area fluctuation value and the preset standard synchronization degree.

[0038] The preset temporary determination time is the time window for calculating the fluctuation of smoke concentration and shadow area, which depends on the smoke diffusion speed and sensor response time of the factory environment. It is usually set between 5 seconds and 10 minutes. In this embodiment, it is set to 10 seconds, which can ensure that the system can capture the initial fluctuation of smoke concentration and shadow change in a short time, while avoiding the data noise problem caused by too short a time window. By setting the time reasonably, the accuracy and real-time nature of the data can be ensured, the system's response speed to abnormal situations can be improved, and the stability and efficiency of the detection effect can be guaranteed.

[0039] By calculating the fluctuation values ​​of smoke concentration and shadow area respectively, the change range of smoke concentration and shadow area is reflected. The concentration fluctuation calculation unit calculates the standard deviation of smoke concentration within a preset time period to obtain the concentration fluctuation value; while the area fluctuation calculation unit calculates the standard deviation of the shadow area to obtain the area fluctuation value. The temporary determination unit combines these two fluctuation values ​​and further determines those areas with significant changes and possible abnormalities based on the preset standard synchronization, and determines them as temporary areas, thereby providing a basis for subsequent abnormality detection and correction.

[0040] By calculating the fluctuation values ​​of smoke concentration and shadow area, the changing trends of smoke and shadow areas can be effectively captured, and then areas with abnormal changes can be identified. This can accurately reflect the dynamic changes of smoke diffusion and occlusion in the factory environment, avoiding the errors caused by relying on static data or a single parameter. By real-time monitoring of concentration and shadow fluctuations, potential smoke accumulation problems can be discovered in a timely manner, avoiding the lag and false alarm risks in traditional detection methods, thereby improving the response speed and accuracy of the system, ensuring the safety of the factory environment while improving the stability and reliability of the system.

[0041] Please continue reading Figure 2 As shown, it is a determination logic diagram of the temporary determination subunit determining the temporary area in this embodiment; The temporary determination unit includes: A concentration curve drawing subunit is used to draw a change curve of the concentration fluctuation value within the preset temporary determined time period to form a concentration curve; An area curve drawing subunit is used to draw a change curve of the area fluctuation value within the preset temporary determined time period to form an area curve; a synchronization degree calculation unit, which is connected to the concentration curve drawing subunit and the area curve drawing subunit respectively, and is used to calculate the cosine similarity of the concentration curve and the area curve to form a change synchronization degree; The temporary determination subunit is connected to the synchronization degree calculation unit and is used to determine the shadow area as the temporary area when the change synchronization degree is less than the preset standard synchronization degree, so as to determine a plurality of temporary areas.

[0042] The concentration curve drawing subunit and the area curve drawing subunit draw the change curves of the concentration fluctuation value and the shadow area fluctuation value, and then use the synchronization calculation unit to calculate the cosine similarity of the two curves to obtain the change synchronization degree. When the change synchronization degree is less than the preset standard synchronization degree, the temporary determination subunit determines that the shadow area is a temporary area, thereby determining a number of temporary areas.

[0043] By drawing concentration and area fluctuation curves and calculating their cosine similarity, the dynamic relationship between smoke concentration changes and shadow area changes can be accurately captured. The synchronization calculation method helps to filter out short-term fluctuations caused by environmental changes or measurement errors, avoid unnecessary misjudgments, and ensure that only when the changing trends of smoke concentration and shadow area are significantly out of sync will they be judged as abnormal areas. This improves the system's judgment accuracy, makes smoke detection more sensitive and reliable, and can maintain a high level of accuracy under changing environmental conditions.

[0044] Specifically, the abnormality determination module includes: A width fluctuation calculation unit, used to calculate the standard deviation of the average width of the real-time light spot within a preset abnormal determination time length to form a width fluctuation value; An abnormality determination unit is connected to the width fluctuation calculation unit and is used to determine a number of abnormal areas according to the real-time spot position, the preset distribution center and the preset standard distribution degree when the width fluctuation value is greater than the preset width fluctuation threshold.

[0045] The preset abnormal determination time refers to the time period used to calculate the standard deviation of the average width of the real-time spot, which is set according to the response requirements and stability requirements of the system. It is usually set to between 5 seconds and 10 seconds, and is set to 8 seconds in this embodiment, which helps to balance the response speed and data stability and avoid misjudgment due to instantaneous fluctuations.

[0046] The preset width fluctuation threshold refers to a standard value used to determine whether the spot width fluctuation is abnormal. It is set according to the specific characteristics of the factory environment and the sensitivity of the equipment. It is usually set between 1% and 5%. In this embodiment, it is set to 2%, which can effectively identify smoke fluctuations or other interferences while avoiding misjudgment.

[0047] The preset distribution center refers to a reference point used to determine abnormal areas when analyzing the position of the light spot. It is set based on factors such as the equipment layout in the factory and the location of the smoke source. It is usually set to the central location of the factory or the area of ​​the main smoke source. In this embodiment, it is set to the center of the factory to ensure that the detection system uses the most critical location as a reference to optimize the determination of abnormal areas.

[0048] The abnormality determination module calculates the standard deviation of the average width of the real-time spot and compares it with the preset width fluctuation threshold. If the width fluctuation value exceeds the threshold, the module determines the location and range of the abnormal area based on the real-time spot position, the preset distribution center and the standard distribution degree.

[0049] By calculating the fluctuation of the spot width and comparing it with the preset threshold, abnormal areas caused by smoke or other interfering objects can be effectively identified. The influence of unnecessary small fluctuations in the environment on the system judgment is avoided, and the stability and accuracy of detection are improved. Reasonably set width fluctuation thresholds can accurately locate the smoke gathering area, reduce the possibility of false alarms, and thus improve the reliability and response speed of the system in a dynamic environment.

[0050] Please continue reading Figure 3 As shown, it is a determination logic diagram of the abnormal area determined by the abnormality determination unit of this embodiment; The abnormality determination unit comprises: A distribution degree calculation unit, used to calculate the standard deviation of the distances from all the real-time light spot positions to the preset distribution center to form a concentrated distribution degree; An abnormality determination unit is connected to the distribution degree calculation unit and is used to determine that the temporary area is the abnormal area when the concentrated distribution degree is less than the preset standard distribution degree, so as to determine a plurality of abnormal areas.

[0051] The abnormality determination unit calculates the standard deviation of the distance between the real-time spot position and the preset distribution center to obtain the concentration distribution degree. If the concentration distribution degree is less than the preset standard distribution degree, the temporary area is determined to be an abnormal area, and then several abnormal areas are determined. This process compares the stability of the spot distribution with the preset standard to make an abnormal judgment, so that abnormal changes in the smoke concentration area can be identified in time.

[0052] By analyzing the standard deviation of the light spot position, it is possible to accurately determine whether the light spot is abnormally diffused or concentrated. By calculating the concentration distribution, the system can effectively identify abnormal smoke areas, avoid misjudgment and missed judgment, improve the sensitivity and accuracy of smoke detection, ensure safe monitoring of the factory environment, and accurately monitor and respond to smoke changes by combining the light spot position and distribution characteristics.

[0053] Specifically, the correction module includes: A concentration change rate calculation unit, used for calculating the ratio of the difference between the real-time smoke concentrations of the two abnormal areas and the distance between the two abnormal areas to form a concentration change rate; A wind speed change rate calculation unit, used for calculating the ratio of the difference between the real-time wind speeds of the two abnormal areas and the distance between the two abnormal areas to form a wind speed change rate; A correction unit is connected to the concentration change rate calculation unit and the wind speed change rate calculation unit respectively, and is used to correct the abnormal area according to the concentration change rate and the wind speed change rate to form a plurality of correction areas.

[0054] By calculating the ratio of the difference in real-time smoke concentration between two abnormal areas to the distance, the concentration change rate is obtained; at the same time, by calculating the ratio of the difference in wind speed to the distance, the wind speed change rate is obtained. The correction unit adjusts the judgment of the abnormal area according to the concentration change rate and the wind speed change rate to form several correction areas. This process takes into account the impact of smoke concentration and wind speed changes on abnormal areas, thereby further optimizing the regional division.

[0055] By calculating the concentration and wind speed change rate, the correction module can more accurately adjust the range of the abnormal area, making the smoke detection system more sensitive and accurate under different environmental conditions. Changes in wind speed and concentration directly affect the diffusion pattern of smoke. Correction based on these dynamic factors can avoid inaccurate division of abnormal areas caused by local interference or errors, improve the adaptability of the system, ensure the accuracy and real-time performance of smoke monitoring, and dynamically adjust parameters to enable the system to respond to different situations, thereby achieving better monitoring effects.

[0056] Please continue reading Figure 4 As shown, it is a determination logic diagram of the correction subunit determining the correction area in this embodiment; The correction unit comprises: a normalization subunit, used for normalizing the concentration change rate to form a normalized concentration change rate, and for normalizing the wind speed change rate to form a normalized wind speed change rate; a correction index calculation subunit, connected to the normalization subunit, for performing weighted summation on the concentration normalization change rate, the preset concentration change rate weight, the wind speed normalization change rate, and the preset wind speed change rate weight to form a correction determination index; a deviation calculation subunit, connected to the correction index calculation subunit, for calculating the relative deviation between the correction determination index and the preset standard determination index to form a correction deviation; The correction subunit is connected to the deviation calculation subunit and is used to determine that the area extending outward from the corresponding abnormal area by a preset length is a correction area when the correction deviation is greater than a preset deviation threshold, so as to form a plurality of correction areas.

[0057] The preset concentration change rate weight depends on the influence of smoke concentration on regional correction, and is usually set between 0.1 and 0.9. In this embodiment, it is set to 0.6, which can properly balance the influence of smoke concentration and wind speed on the correction area, ensuring that the influence of concentration change on regional correction is more significant.

[0058] The preset wind speed change rate weight depends on the effect of wind speed on smoke diffusion, and is usually set between 0.1 and 0.9. In this embodiment, it is set to 0.4, which helps to balance the contribution of wind speed and concentration changes to the correction area and avoid excessive influence of wind speed on the results.

[0059] The preset standard judgment index is a standard value usually set based on system historical data for determining the correction area, usually set between 0.2 and 0.8. In this embodiment, it is set to 0.5, which can ensure that the system has a certain degree of fault tolerance in determining the correction area while ensuring the accuracy of the correction.

[0060] The preset deviation threshold depends on the system's requirements for error tolerance and is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.3, which helps to control the strictness of the correction area judgment and avoid excessive correction of the misjudged area.

[0061] The preset length depends on the area size and smoke diffusion characteristics, and is usually set between 2 meters and 10 meters. In this embodiment, it is set to 5 meters, which can reasonably predict the smoke diffusion range and ensure that the size of the correction area is moderate.

[0062] First, the concentration change rate and the wind speed change rate are normalized to obtain the normalized concentration change rate and the normalized wind speed change rate. Then, the correction index calculation subunit performs weighted summation on the normalized change rate and the corresponding preset weight to obtain the correction judgment index. Next, the deviation calculation subunit calculates the relative deviation between the correction judgment index and the preset standard judgment index to form a correction deviation. Finally, when the correction deviation is greater than the preset deviation threshold, the correction subunit determines that the area extending outward from the abnormal area by a preset length is the correction area, and the formation of the correction area is completed. In addition, if a single abnormal area is determined to be corrected and not corrected at the same time, the correction operation is performed. For example, abnormal area A and abnormal area B are determined to need to be corrected, and abnormal area B and abnormal area C are determined not to be corrected, that is, abnormal area B is in a state of being determined to be corrected and not corrected at the same time. At this time, abnormal area B is still corrected. The priority execution of the correction operation is to ensure the safety and stability of the system. The correction operation can effectively eliminate potential risks and hidden dangers and avoid security vulnerabilities caused by uncertain or contradictory judgments. In addition, in order to maintain the consistency of the system and the reliability of operation, even if there is a judgment conflict, the correction operation can prevent the system from being in an inconsistent state, ensuring that the smoke area can be effectively controlled and adjusted in actual applications, minimizing environmental risks.

[0063] By normalizing the concentration change rate and wind speed change rate, parameters of different dimensions can be processed under the same standard, thus avoiding the impact of differences in numerical ranges on the judgment results. The weighted summation step introduces preset weights, so that the contribution of different factors to the correction area can be adjusted according to actual needs, improving the flexibility and accuracy of the system. The accuracy of the correction is ensured by calculating the relative deviation. Correction is only made when the deviation is large, avoiding unnecessary adjustments, reflecting the actual smoke diffusion situation more accurately, making the determination of the correction area more accurate, and effectively improving the stability and reliability of the monitoring system.

[0064] Specifically, the adjustment module includes: an average area calculation unit, used to calculate the ratio of the sum of all the real-time shadow areas at each moment in the preset adjustment period to the number of the correction areas to form a plurality of average shadow areas; A shadow fluctuation calculation unit, connected to the average area calculation unit, for calculating the standard deviation of all the average shadow areas to form a shadow fluctuation value; An adjustment unit is connected to the shadow fluctuation calculation unit, and is used to adjust the preset standard synchronization degree according to the shadow fluctuation value to form the adjusted standard synchronization degree, or adjust the preset standard distribution degree to form the adjusted standard distribution degree.

[0065] First, the average area calculation unit calculates the average value of the real-time shadow area at each moment in the preset adjustment period, that is, the average shadow area. Then, the shadow fluctuation calculation unit calculates the standard deviation based on these average shadow areas to obtain the shadow fluctuation value. Finally, the adjustment unit adjusts the preset standard synchronization degree or the preset standard distribution degree according to the shadow fluctuation value, thereby forming an adjusted synchronization degree or distribution degree to adapt to the impact of environmental changes on the shadow area.

[0066] By calculating the fluctuation of the shadow area to adjust the synchronization or distribution, the changes in the shadow area under different environmental conditions can be effectively responded to, so that the system can maintain high stability and accuracy in a dynamic environment. By adjusting the standard synchronization or standard distribution, more accurate anomaly detection and area correction can be achieved, the performance of smoke detection can be optimized, the response speed and accuracy of the system can be improved, and efficient operation can be maintained in a changing factory environment.

[0067] Specifically, the adjustment unit includes: an adjustment determination subunit, for determining that the preset standard distribution degree needs to be adjusted when the shadow fluctuation value is less than the minimum value of the preset shadow fluctuation range, and forming a distribution degree adjustment determination result; and for determining that the preset standard synchronization degree needs to be adjusted when the shadow fluctuation value is greater than the maximum value of the preset shadow fluctuation range, and forming a synchronization degree adjustment determination result; The standard adjustment subunit is connected to the adjustment judgment subunit and is used to adjust the preset standard distribution degree when forming the distribution degree adjustment judgment result to form the adjusted standard distribution degree, and to adjust the preset standard synchronization degree when forming the synchronization degree adjustment judgment result to form the adjusted standard synchronization degree.

[0068] The preset shadow fluctuation range refers to the upper and lower limits used to measure the fluctuation of the shadow area, which determines the tolerance of the system to shadow fluctuations within a certain period of time. It depends on the illumination changes, smoke concentration fluctuations and sensor accuracy in the actual environment. It is usually set between 0.1 and 5. The specific value is adjusted according to the illumination changes in the monitoring area and the actual operation requirements. In this embodiment, it is set to between 0.5 and 3, which can ensure that adjustments are made within the normal fluctuation range, avoid overreaction, and improve the adaptability and accuracy of the system in actual working conditions.

[0069] First, the shadow fluctuation value is compared with the minimum and maximum values ​​of the preset shadow fluctuation range to determine whether the preset standard distribution degree or standard synchronization degree needs to be adjusted. If the shadow fluctuation value is less than the minimum value, the distribution degree needs to be adjusted; if the shadow fluctuation value is greater than the maximum value, the synchronization degree needs to be adjusted. Then, the standard adjustment subunit adjusts the standard distribution degree or standard synchronization degree according to the adjustment judgment result, thereby forming an adjusted synchronization degree or distribution degree.

[0070] By adjusting the standard synchronization and distribution according to the shadow fluctuation value calculated in real time, the system can dynamically respond to environmental changes, especially fluctuations in the shadow area. Specifically, when the shadow fluctuation value is less than the minimum value, it means that the change in the shadow area is very small, indicating that the system is not sensitive enough to environmental changes, resulting in a decrease in the ability to capture the light spot distribution. In this case, adjusting the distribution helps to improve the system's sensitivity to small changes and ensure that the light spot distribution can more accurately reflect the actual situation, thereby enhancing detection accuracy. When the shadow fluctuation value is greater than the maximum value, it means that the shadow area fluctuates too much because the external environment changes dramatically, causing the system's judgment of the light spot to become unstable. At this time, the synchronization needs to be adjusted to ensure that the system can effectively handle this instability and avoid overly sensitive response misjudgments. The focus will be placed on the control system's ability to adapt to large-scale changes, thereby maintaining overall detection accuracy and stability.

[0071] Specifically, the standard adjustment subunit adjusts the preset standard distribution degree including: increasing the preset standard distribution degree according to the minimum value of the preset shadow fluctuation range and the relative deviation of the shadow fluctuation value and the preset adjustment coefficient to form the adjusted standard distribution degree; The standard adjustment subunit adjusts the preset standard synchronization degree including: increasing the preset standard synchronization degree according to the relative deviation between the shadow fluctuation value and the maximum value of the preset shadow fluctuation range and the preset adjustment coefficient to form the adjusted standard synchronization degree.

[0072] The preset adjustment coefficient is a multiplier factor used to adjust the standard distribution degree and synchronization degree changes. It depends on the sensitivity and accuracy requirements of the system. It is usually set between 0.1 and 1.0 to balance the adjustment sensitivity and stability. In this embodiment, it is set to 0.5, which can effectively adjust the system response speed and accuracy, avoid excessive fluctuations, and maintain a high responsiveness, ensuring the stability and reliability of the system in a dynamic environment.

[0073] By calculating the deviation between the shadow fluctuation value and the preset shadow fluctuation range, combined with the preset adjustment coefficient, the preset standard distribution degree and the preset standard synchronization degree are adjusted respectively. When the shadow fluctuation value deviates from the minimum value, the standard distribution degree is increased; and when the shadow fluctuation value deviates from the maximum value, the standard synchronization degree is increased. Through this adjustment, the system can adapt to changes in the actual environment and improve the accuracy of the detection results.

[0074] By dynamically adjusting the standard distribution and synchronization according to the deviation of the shadow fluctuation value from the preset range, the system can respond sensitively and reasonably to different environmental conditions (such as light fluctuations and smoke changes), enhancing the adaptability of the system and enabling it to operate efficiently in various actual environments, thereby improving the accuracy and reliability of detection.

[0075] 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.

Claims

1. A smoke detection system based on Internet of Things analysis, characterized in that: include: A data acquisition module is used to obtain real-time smoke concentration collected by a number of smoke sensors at each shadow area in the factory, real-time wind speed collected by a number of anemometers, and real-time images collected by an image sensor; An extraction module, connected to the data acquisition module, for extracting the real-time shadow area, the real-time average width of the light spot and the real-time light spot position of each of the real-time images; A temporary determination module, which is connected to the data acquisition module and the extraction module respectively, and is used to determine a number of temporary areas according to the real-time smoke concentration, the real-time shadow area and a preset standard synchronization degree; an abnormality determination module, which is connected to the extraction module and the temporary determination module respectively, and is used to determine a number of abnormal areas according to the real-time light spot average width, the real-time light spot position and a preset standard distribution degree in the temporary area; A correction module, which is connected to the abnormality determination module and the data acquisition module respectively, and is used to correct the abnormal area according to the real-time smoke concentration and the real-time wind speed of any two adjacent abnormal areas to form a plurality of correction areas; an adjustment module, which is connected to the temporary determination module and the correction module respectively, and is used to adjust the preset standard synchronization degree according to the number of the correction areas and the real-time shadow area within a preset adjustment period to form an adjustment standard synchronization degree, or adjust the preset standard distribution degree to form an adjustment standard distribution degree; An alarm module is connected to the abnormality determination module and is used to issue a smoke accumulation alarm for the abnormal area determined based on the adjustment standard synchronization degree or the adjustment standard distribution degree.

2. The smoke detection system based on Internet of Things analysis according to claim 1 is characterized in that: The temporary determination module comprises: A concentration fluctuation calculation unit, used to calculate the standard deviation of the real-time smoke concentration within a preset temporary determined time period to form a concentration fluctuation value; An area fluctuation calculation unit, used to calculate the standard deviation of the real-time shadow area within the preset temporary determination time length to form an area fluctuation value; A temporary determination unit is connected to the concentration fluctuation calculation unit and the area fluctuation calculation unit respectively, and is used to determine a plurality of temporary areas according to the concentration fluctuation value, the area fluctuation value and the preset standard synchronization degree.

3. The smoke detection system based on Internet of Things analysis according to claim 2 is characterized in that: The temporary determination unit includes: A concentration curve drawing subunit is used to draw a change curve of the concentration fluctuation value within the preset temporary determined time period to form a concentration curve; An area curve drawing subunit is used to draw a change curve of the area fluctuation value within the preset temporary determined time period to form an area curve; a synchronization degree calculation unit, which is connected to the concentration curve drawing subunit and the area curve drawing subunit respectively, and is used to calculate the cosine similarity of the concentration curve and the area curve to form a change synchronization degree; The temporary determination subunit is connected to the synchronization degree calculation unit and is used to determine the shadow area as the temporary area when the change synchronization degree is less than the preset standard synchronization degree, so as to determine a plurality of temporary areas.

4. The smoke detection system based on Internet of Things analysis according to claim 3 is characterized in that: The abnormality determination module comprises: A width fluctuation calculation unit, used to calculate the standard deviation of the average width of the real-time light spot within a preset abnormal determination time length to form a width fluctuation value; An abnormality determination unit is connected to the width fluctuation calculation unit and is used to determine a number of abnormal areas according to the real-time spot position, the preset distribution center and the preset standard distribution degree when the width fluctuation value is greater than the preset width fluctuation threshold.

5. The smoke detection system based on Internet of Things analysis according to claim 4 is characterized in that: The abnormality determination unit comprises: A distribution degree calculation unit, used to calculate the standard deviation of the distances from all the real-time light spot positions to the preset distribution center to form a concentrated distribution degree; An abnormality determination unit is connected to the distribution degree calculation unit and is used to determine that the temporary area is the abnormal area when the concentrated distribution degree is less than the preset standard distribution degree, so as to determine a plurality of abnormal areas.

6. The smoke detection system based on Internet of Things analysis according to claim 5 is characterized in that: The correction module comprises: A concentration change rate calculation unit, used for calculating the ratio of the difference between the real-time smoke concentrations of the two abnormal areas and the distance between the two abnormal areas to form a concentration change rate; A wind speed change rate calculation unit, used for calculating the ratio of the difference between the real-time wind speeds of the two abnormal areas and the distance between the two abnormal areas to form a wind speed change rate; A correction unit is connected to the concentration change rate calculation unit and the wind speed change rate calculation unit respectively, and is used to correct the abnormal area according to the concentration change rate and the wind speed change rate to form a plurality of correction areas.

7. The smoke detection system based on Internet of Things analysis according to claim 6 is characterized in that: The correction unit comprises: a normalization subunit, used for normalizing the concentration change rate to form a normalized concentration change rate, and for normalizing the wind speed change rate to form a normalized wind speed change rate; a correction index calculation subunit, connected to the normalization subunit, for performing weighted summation on the concentration normalization change rate, the preset concentration change rate weight, the wind speed normalization change rate, and the preset wind speed change rate weight to form a correction determination index; a deviation calculation subunit, connected to the correction index calculation subunit, for calculating the relative deviation between the correction determination index and the preset standard determination index to form a correction deviation; The correction subunit is connected to the deviation calculation subunit and is used to determine that the area extending outward from the corresponding abnormal area by a preset length is a correction area when the correction deviation is greater than a preset deviation threshold, so as to form a plurality of correction areas.

8. The smoke detection system based on Internet of Things analysis according to claim 7 is characterized in that: The adjustment module comprises: an average area calculation unit, used to calculate the ratio of the sum of all the real-time shadow areas at each moment in the preset adjustment period to the number of the correction areas to form a plurality of average shadow areas; A shadow fluctuation calculation unit, connected to the average area calculation unit, for calculating the standard deviation of all the average shadow areas to form a shadow fluctuation value; An adjustment unit is connected to the shadow fluctuation calculation unit, and is used to adjust the preset standard synchronization degree according to the shadow fluctuation value to form the adjusted standard synchronization degree, or adjust the preset standard distribution degree to form the adjusted standard distribution degree.

9. The smoke detection system based on Internet of Things analysis according to claim 8 is characterized in that: The adjustment unit comprises: an adjustment determination subunit, for determining that the preset standard distribution degree needs to be adjusted when the shadow fluctuation value is less than the minimum value of the preset shadow fluctuation range, and forming a distribution degree adjustment determination result; and for determining that the preset standard synchronization degree needs to be adjusted when the shadow fluctuation value is greater than the maximum value of the preset shadow fluctuation range, and forming a synchronization degree adjustment determination result; The standard adjustment subunit is connected to the adjustment judgment subunit and is used to adjust the preset standard distribution degree when forming the distribution degree adjustment judgment result to form the adjusted standard distribution degree, and to adjust the preset standard synchronization degree when forming the synchronization degree adjustment judgment result to form the adjusted standard synchronization degree.

10. The smoke detection system based on Internet of Things analysis according to claim 9 is characterized in that: The standard adjustment subunit adjusts the preset standard distribution degree including: increasing the preset standard distribution degree according to the minimum value of the preset shadow fluctuation range and the relative deviation of the shadow fluctuation value and the preset adjustment coefficient to form the adjusted standard distribution degree; The standard adjustment subunit adjusts the preset standard synchronization degree including: increasing the preset standard synchronization degree according to the relative deviation between the shadow fluctuation value and the maximum value of the preset shadow fluctuation range and the preset adjustment coefficient to form the adjusted standard synchronization degree.

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