Flying dust source positioning and video tracking integrated device and method for thermal power plant

Abstract

The invention discloses a flying dust source positioning and video tracking integrated device and method for a thermal power plant, and relates to the field of environment monitoring, and the main scheme is as follows: collecting multiple data of flying dust in real time; calculating the flying dust content to further obtain the comprehensive flying dust content; calculating a wind direction angle and obtaining a wind speed based on the wind direction angle; calculating a comprehensive environment index according to the comprehensive flying dust content, the wind direction angle and the wind speed, and comparing the comprehensive environment index with a threshold to judge a flying dust risk level; calculating a monitoring view angle and a focal length, respectively calculating a dust source change rate and a frame number based on the video image information data, and further obtaining a dust source position parameter at the current moment; calculating a received information accuracy index, further calculating a synchronism index, and comparing the synchronism index with a preset threshold to judge whether the dust source position displayed by the monitoring center is synchronous with the actual dust source position or not; according to the method, the flying dust source of the thermal power plant can be accurately positioned, real-time monitoring is achieved through video tracking, dust falling measures can be taken in time, and environmental pollution is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to an integrated device and method for dust source positioning and video tracking in a thermal power plant. Background Art

[0002] Thermal power plants generate a lot of dust during operation, which not only affects the operation of equipment in the plant, but also pollutes the surrounding environment and harms human health. Accurately locating the dust source and effectively tracking it is crucial to take dust reduction measures in a timely manner. However, due to the large number of equipment in thermal power plants, locating and tracking dust sources has always been a technical problem in this field.

[0003] Some existing technologies attempt to solve the dust problem in thermal power plants. For example, some thermal power plants use a method of installing dust concentration sensors at fixed locations to monitor dust conditions.

[0004] Although existing technologies have helped to solve the dust problem in thermal power plants to a certain extent, there are still many defects. Relying solely on dust concentration sensors can only determine that dust exceeds the standard in a local area, but cannot accurately locate the dust source. In addition, there is a lack of means to effectively combine dust source positioning with video tracking. After determining the possible dust source area, it is impossible to quickly adjust the video monitoring equipment for accurate tracking, and it is impossible to update the location information of the dust source in real time. As a result, when dust reduction measures are implemented, the dust source may have moved or spread, reducing the dust reduction effect. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the shortcomings of the prior art, the present invention provides an integrated device and method for dust source positioning and video tracking in a thermal power plant. By collecting multiple dust data in real time, the comprehensive dust content, wind direction angle and wind speed are calculated respectively, and the comprehensive environmental index is further obtained, which is compared with the threshold to determine the dust risk level; the monitoring field of view angle and focal length are calculated; the dust source change rate and frame number are calculated respectively, and then the dust source position parameters at the current moment are obtained; the accuracy index of the received information is calculated, and then the synchronization index is calculated, and compared with the preset threshold to determine whether the dust source position displayed by the monitoring center is synchronized with the actual dust source position; the problems of inaccurate positioning, incomplete monitoring and untimely tracking are solved.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: an integrated method for dust source positioning and video tracking in a thermal power plant, comprising:

[0009] Real-time collection of dust concentration data, wind speed data, equipment operation status data and video image information data;

[0010] Calculate the dust content CB based on the dust concentration data and the equipment operation status data; calculate the comprehensive dust content CC based on the dust content CB; calculate the wind direction angle θ based on the equipment operation status data; calculate the wind speed VM based on the wind speed data and the equipment operation status data; calculate the comprehensive environmental index RHM based on the comprehensive dust content CC, wind direction angle θ and wind speed VM; compare the comprehensive environmental index RHM with the comprehensive environmental index threshold, and determine whether there is a dust risk in the area based on the results;

[0011] When there is a dust risk in the area, the monitoring field of view angle α is calculated based on the comprehensive environmental indicator RHM and the video image information data, and the focal length f is further obtained; based on the video image information data, the dust source change rate RF and the number of frames NC are calculated respectively; according to the dust source change rate RF, the number of frames NC, the monitoring field of view angle α and the focal length f, the dust source position parameter PT at the current moment is calculated;

[0012] The received information accuracy index WE is calculated based on the dust source position parameter PT at the current moment; the synchronization index PQ is calculated based on the video image information data, the dust source position parameter PT at the current moment and the received information accuracy index WE; a synchronization index threshold is preset, and the synchronization index PQ is compared with the synchronization index threshold, and it is determined according to the result whether the dust source position displayed by the monitoring center is synchronized with the actual dust source position; when the position is not synchronized, the video monitoring equipment automatically adjusts the angle.

[0013] In the preferred embodiment of the integrated method of dust source location and video tracking in the above thermal power plant: the method for calculating the comprehensive dust content CC is:

[0014] The dust concentration data include initial dust concentration CA;

[0015] Equipment operating status data includes the operating power PH of different dust-generating equipment i , running time TH i And the distance DH between the dust-generating equipment and the dust-generating area i ;

[0016] According to the initial dust concentration CA, operating power PH i , running time TH i The distance between the dust-generating equipment and the dust-generating area DH i , calculate the dust content CB, the calculation formula is:

[0017]

[0018] Among them, PH iis the operating power of the i-th dust-generating equipment, i is [1, n], n is the number of dust-generating equipment, and is a positive integer; TH i is the operating time of the i-th dust-generating equipment; DH i is the distance between the ith dust-generating equipment and the dust-generating area;

[0019] Based on the dust content CB, the comprehensive dust content CC is calculated using the following formula:

[0020]

[0021] Where V is the ventilation coefficient of the dust-generating area; H j is the obstruction coefficient of the j-th obstacle to ventilation, the value of j is [1, m], m is the number of obstacles, and the value is a positive integer.

[0022] In the preferred embodiment of the integrated method for dust source location and video tracking in the thermal power plant, the method for calculating the wind direction angle θ is:

[0023] Equipment operating status data also includes the dust generation intensity IN of different dust generating equipment i ;

[0024] Based on dust generation intensity IN i , calculate the wind direction angle θ, the calculation formula is:

[0025]

[0026] Among them, IN i is the dust generation intensity of the i-th dust generating equipment; RN i is the relative position coefficient between the ith dust-generating equipment and the wind direction; SL j is the size of the jth obstacle; RK j is the blocking angle coefficient between the jth obstacle and the wind direction.

[0027] In the preferred embodiment of the integrated method for dust source location and video tracking in the above thermal power plant: the method for calculating the wind speed VM is:

[0028] Wind speed data include initial wind speed VK;

[0029] According to the initial wind speed VK, operating power PH i , the distance between dust-generating equipment and dust-generating area DH i And wind direction angle θ, calculate wind speed VM, based on the formula:

[0030]

[0031] Among them, LK j is the distance between the jth obstacle and the dust-generating area.

[0032] In the optimal solution of the integrated method for dust source location and video tracking in the above thermal power plant, the method for determining whether there is a dust risk in the area is as follows:

[0033] According to the comprehensive dust content CC, the wind direction angle θ, and the wind speed VM, calculate the comprehensive environmental index RHM. The calculation formula is:

[0034] RHM = ω1 × CC + ω2 × θ + ω3 × VM

[0035] Among them, ω1 is the weight coefficient of the comprehensive dust content CC, with a value range of 0.1 to 0.4; ω2 is the weight coefficient of the wind direction angle θ, with a value range of 0.2 to 0.5; ω3 is the weight coefficient of the wind speed VM, with a value range of 0.3 to 0.4; and ω1 + ω2 + ω3 = 1;

[0036] The comprehensive environmental index thresholds include the comprehensive environmental index threshold one RHM1 and the comprehensive environmental index threshold two RHM2, and RHM1 < RHM2;

[0037] When RHM ≤ RHM1, it is determined that there is no dust risk in the area;

[0038] When RHM1 < RHM ≤ RHM2, it is determined that there is a medium dust risk in the area;

[0039] When RHM > RHM2, it is determined that there is a high dust risk in the area.

[0040] In the optimal solution of the integrated method for dust source location and video tracking in the above thermal power plant, the method for calculating the focal length f is as follows:

[0041] The video image information data includes the initial field of view angle α0 and the initial focal length f0;

[0042] When there is a dust risk in the area, according to the comprehensive environmental index RHM and the initial field of view angle α0, calculate the monitoring field of view angle α. The calculation formula is:

[0043]

[0044] Among them, d is the adjustment coefficient of the comprehensive environmental index RHM;

[0045] According to the monitoring field of view angle α, the initial field of view angle α0, and the initial focal length f0, calculate the focal length f. The calculation formula is:

[0046]

[0047] In the optimal solution of the integrated method for dust source location and video tracking in the above thermal power plant, the method for calculating the dust source position parameter PT at the current moment is as follows:

[0048] The video image information data also includes the initial scale index SK, the current scale index SN and the frame rate F of the dust source in the video image;

[0049] According to the initial scale index SK of the dust source in the video image and the scale index SN at the current moment, the dust source change rate RF is calculated. The calculation formula is:

[0050]

[0051] Based on the frame rate F, the number of frames NC of the video image in time t is calculated, and the calculation formula is:

[0052] NC=F×t

[0053] According to the dust source change rate RF, frame number NC, monitoring field of view angle α and focal length f, the dust source position parameter PT at the current moment is calculated based on the formula:

[0054]

[0055] Among them, P0 is the dust source position parameter at the previous moment; DB is the pixel distance between the dust source position parameter at the previous moment and the dust source position parameter at the current moment.

[0056] In the preferred embodiment of the integrated method for dust source location and video tracking in the above thermal power plant: the method for calculating the received information accuracy index WE is:

[0057] According to the dust source position parameter P0 at the previous moment and the dust source position parameter PT at the current moment, the received information accuracy index WE is calculated, and the calculation formula is:

[0058]

[0059] Among them, Δt is the time interval; TF is the data transmission delay time; C is the clarity index of the dust source in the video image; S is the stability coefficient of data transmission.

[0060] In the preferred embodiment of the integrated method for dust source location and video tracking in the above thermal power plant: the method for determining whether the dust source location displayed by the monitoring center is synchronized with the actual dust source location is:

[0061] The video image information data also includes the dust source location update frequency FU;

[0062] According to the dust source position update frequency FU, frame rate F, current dust source position parameter PT, previous dust source position parameter P0 and received information accuracy index WE, the synchronization index PQ is calculated based on the formula:

[0063]

[0064] Preset synchronization index threshold PQ th ; When PQ≤PQ th When PQ>PQ th When the dust source position displayed by the monitoring center is judged to be synchronized with the actual dust source position.

[0065] The present invention also discloses an integrated device for dust source positioning and video tracking of a thermal power plant, which can be used to implement the integrated method for dust source positioning and video tracking of the thermal power plant.

[0066] (III) Beneficial effects

[0067] The present invention provides an integrated device and method for dust source positioning and video tracking in a thermal power plant, which has the following beneficial effects:

[0068] (1) The collection of dust concentration data can directly obtain the dust pollution situation on site and provide basic data for subsequent analysis and decision-making. Wind speed data can help understand the air flow state and play an important role in determining the diffusion direction and speed of dust. Equipment operation status data helps to determine the source of dust. Video image information data can intuitively display the on-site situation and play a key role in the subsequent dust source tracking and positioning process.

[0069] (2) By accurately calculating the dust content and comprehensive dust content, the amount of dust generated can be accurately grasped. The comprehensive environmental index obtained by combining the wind direction angle and wind speed data can comprehensively consider the impact of natural factors and dust-generating factors on dust diffusion. By comparing it with the threshold, it can be timely and accurately judged whether there is a dust risk in the area, providing a basis for taking dust reduction measures in advance and effectively preventing the spread of dust pollution.

[0070] (3) When there is a risk of dust in an area, the monitoring field of view angle and focal length are calculated by integrating environmental indicators and video image information data, so that the video monitoring equipment can quickly focus on the possible dust source area, improving monitoring efficiency and accuracy. The dust source change rate and frame number are calculated based on the video image information data, and the dust source position parameters at the current moment are calculated in combination with the monitoring field of view angle and focal length, thus achieving accurate tracking and positioning of the dust source.

[0071] (4) By calculating the accuracy index of received information, the reliability of monitoring data can be evaluated. The calculation and comparison of synchronization index can ensure that the dust source location displayed by the monitoring center is consistent with the actual situation. When asynchrony occurs, the early warning device is triggered to ensure continuous and accurate monitoring of the dust source, and accurate dust source location information can be obtained in real time, so that timely measures can be taken to reduce dust hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 The figure is a schematic diagram of the steps of the integrated method for dust source positioning and video tracking of a thermal power plant of the present invention. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] See also Figure 1 The present invention provides an integrated method for dust source positioning and video tracking in a thermal power plant, comprising:

[0075] Step 1: Collect dust concentration data, wind speed data, equipment operation status data and video image information data in real time.

[0076] Step 101: Install dust concentration sensors in coal storage yards, coal handling trestles, coal crusher rooms and other areas of the thermal power plant that are prone to dust generation, and obtain dust concentration data in real time. Install mechanical anemometers in open, unobstructed areas of the thermal power plant to obtain wind speed data in real time. Connect to the industrial Ethernet control system of the thermal power plant equipment to directly obtain equipment operation status data from the control system of the equipment. Arrange multiple video surveillance cameras in the thermal power plant, and use the cameras to collect video images in real time to obtain video image information data.

[0077] Dust concentration data and wind speed data can help accurately locate dust sources and quickly determine the area where dust is generated. Equipment operation status data can timely understand whether the equipment is operating normally and prevent abnormal dust emissions caused by equipment failure. Video image information data can intuitively present the on-site conditions of thermal power plants, monitor and analyze the on-site conditions more comprehensively, facilitate the rapid adoption of effective dust reduction measures, and ensure the environmental safety of thermal power plants and the normal operation of equipment.

[0078] Step 2: Calculate the dust content CB based on the dust concentration data and the equipment operation status data; calculate the comprehensive dust content CC based on the dust content CB; calculate the wind direction angle θ based on the equipment operation status data; calculate the wind speed VM based on the wind speed data and the equipment operation status data; calculate the comprehensive environmental index RHM based on the comprehensive dust content CC, wind direction angle θ and wind speed VM; compare the comprehensive environmental index RHM with the comprehensive environmental index threshold, and determine whether there is a dust risk in the area based on the result.

[0079] Step 201: The dust concentration data includes the initial dust concentration CA. By using dust concentration sensors installed in dust-prone areas such as coal storage yards, coal conveyor bridges, and coal crusher rooms of thermal power plants, the sensors will automatically collect dust particle concentration data in the air, thereby obtaining the initial dust concentration CA.

[0080] Equipment operating status data includes the operating power PH of different dust-generating equipment i , running time TH i And the distance between the dust-generating equipment and the dust-generating area DH i ;in,

[0081] The control system of dust-generating equipment can monitor the operating status of the equipment in real time, such as crushers, concrete mixers, tower cranes and other dust-generating equipment, and directly obtain the operating power PH of different dust-generating equipment. i .

[0082] Through the control system of the dust-generating equipment, the start time and stop time of different dust-generating equipment can be directly obtained, and then the running time TH of the equipment can be calculated. i .

[0083] By selecting several monitoring points in the thermal power plant, installing dust concentration monitoring instruments, and regularly collecting and analyzing dust concentration data, if the dust concentration in a certain area is continuously higher than a certain threshold, the area is a dust-generating area. By using a laser rangefinder to measure the distance between the boundary point of the dust-generating area and the center point of the corresponding dust-generating equipment, the distance DH between the dust-generating equipment and the dust-generating area is obtained. i .

[0084] Step 202: According to the initial dust concentration CA and the operating power PH i , running time TH i The distance between the dust-generating equipment and the dust-generating area DH i , calculate the dust content CB, the calculation formula is:

[0085]

[0086] Among them, PH i is the operating power of the i-th dust-generating equipment, i represents the serial number of the dust-generating equipment, and its value is [1, n], and n is the number of dust-generating equipment, and its value is a positive integer; TH i is the operating time of the i-th dust-generating equipment; DH i is the distance between the ith dust-generating equipment and the dust-generating area.

[0087] It should be noted that the initial dust concentration CA is the basic value of dust concentration without considering the influence of dust-generating equipment; PH i ×TH iIndicates that the dust-generating equipment is running for TH i Due to its operating power PH i A measure of the amount of dust generated. The greater the operating power and the longer the operating time, the more dust is generated. It is a distance-related attenuation factor, which represents the distance DH between the dust-generating equipment and the dust-generating area. i Impact on dust emission. The greater the distance, the more dust will diffuse and settle during the propagation process, and the smaller the contribution to the dust content in the dust-generating area. This formula sums the dust contribution of all dust-generating equipment to accurately evaluate the dust situation in the dust-generating area when the equipment is running.

[0088] Step 203: Obtain the ventilation coefficient V of the dust-generating area and the obstruction coefficient H of the obstacle to ventilation j , the method is:

[0089] Obtain the ventilation coefficient V, because the layout of the ventilation duct, the size and position of the vents will affect the ventilation efficiency. Reasonable ventilation duct design can ensure that the air flows smoothly in the dust-producing area so that the dust can be discharged in time. The size and position of the vents determine the efficiency of air exchange. Larger and properly located vents help improve ventilation efficiency, while smaller vents reduce ventilation efficiency. Therefore, a ventilation coefficient V for the dust-producing area is introduced to reflect the impact of the ventilation duct on the dust-producing equipment. According to the maximum air flow rate Q of the ventilation duct max and the actual measured air flow Q act , the ventilation coefficient can be calculated

[0090]

[0091] Obtain the resistance coefficient H j Obstacles of different shapes, sizes and layouts will have different degrees of obstruction to air flow. When air flows through obstacles, eddy currents and pressure changes will occur, resulting in a decrease in air velocity and an increase in flow resistance. At this time, it is necessary to introduce an obstacle coefficient H. j To reflect the degree of obstruction of ventilation by obstacles. In a free flow field without obstacles, use a mechanical anemometer to measure the wind speed as H0, and measure the wind speed again as H1 at the same position after placing the obstacle. The formula for calculating the obstruction coefficient is:

[0092] Step 204: Based on the dust content CB, the ventilation coefficient V of the dust-generating area and the obstruction coefficient H of the obstacle to ventilation j , calculate the comprehensive dust content CC, the calculation formula is:

[0093]

[0094] Among them, H j is the obstruction coefficient of the jth obstacle to ventilation, j represents the sequence number of the obstacle, and its value is [1, m], and m is the number of obstacles, and its value is a positive integer.

[0095] It should be noted that It represents the sum of the obstruction coefficients of all obstacles to ventilation. The more obstacles there are, the greater the sum. V is the ventilation coefficient of the dust-generating area, which reflects the ventilation capacity of the area. The better the ventilation, the greater the value of V. This term represents the ratio of the ventilation coefficient to the sum of the obstacle resistance coefficients. When the ventilation is good and the obstacle resistance is small, this ratio is larger. This ratio is subtracted from 1. When ventilation is good and there are few obstacles, this value is close to 1, indicating that the dust content is less affected by ventilation and obstacles; when ventilation is poor and there are many obstacles, this value is small, indicating that the dust content will increase due to poor ventilation and many obstacles. Finally, the dust content CB is multiplied by this adjustment factor The comprehensive dust content CC is obtained.

[0096] Step 205: The equipment operation status data includes the dust generation intensity IN of different dust generating equipment i ; By using a light scattering dust meter, based on the principle of light scattering, when light is irradiated on dust particles, scattering occurs. The light scattering dust meter measures the dust concentration by detecting the intensity of scattered light, and obtains the dust intensity IN of different dust-generating equipment. i .

[0097] Step 206: Obtaining relative position coefficient RN i , blocking angle coefficient RK j and the scale of the obstacle SL j The method is:

[0098] Get the relative position coefficient RN i , because for dust-generating equipment, its position relative to the wind direction will affect the diffusion path of dust. For example, if the dust-generating equipment is facing the wind direction, the dust is more easily carried and diffused by the wind; if the dust-generating equipment is perpendicular to the wind direction, the diffusion of dust in the direction perpendicular to the wind direction is relatively weak. At this time, it is necessary to introduce a relative position coefficient RN between the dust-generating equipment and the wind direction. i To reflect the influence of wind direction on dust. Use a wind vane to measure wind direction and obtain the wind direction angle θ w , and measure the azimuth angle of the dust-generating equipment relative to the true north direction as θ p , then calculate the azimuth angle θ of the dust-generating equipment relative to the wind direction k =|θ w -θ p |; Based on the azimuth angle θ of the dust-generating equipment relative to the wind directionk , calculate the relative position coefficient RN i , the calculation formula is:

[0099]

[0100] Get the blocking angle coefficient RK j According to a rectangular obstacle, if its long side is parallel to the wind direction, then its blocking angle to the wind is relatively small; but if its long side is perpendicular to the wind direction, then the blocking effect to the wind will be very obvious. For irregularly shaped obstacles, the wind will produce complex flow changes when bypassing the obstacle, so it is necessary to introduce a blocking angle coefficient RK between the obstacle and the wind direction j To reflect the impact of obstacles on dust.

[0101] Calculate the size of the obstacle SL j By obtaining a clear image containing obstacles, the image is processed using image analysis software such as the OpenCV library to extract the outline of the obstacle; and the number of pixels occupied by different obstacles in the image is obtained. j Place an object with a length of LRE and a width of CRE in the image and obtain the number of pixels PRE occupied by the object in the image. j , length LRE, width CRE and number of pixels PRE, calculate the scale SL of the obstacle j , the calculation formula is:

[0102]

[0103] Among them, PK j is the number of pixels occupied by the jth obstacle in the image.

[0104] Step 207: According to the dust generation intensity IN i , the scale of obstacles SL j , the relative position coefficient RN between the dust-generating equipment and the wind direction i and the blocking angle coefficient RK between the obstacle and the wind direction j , calculate the wind direction angle θ, the calculation formula is:

[0105]

[0106] Among them, IN i is the dust generation intensity of the i-th dust generating equipment; RN i is the relative position coefficient between the ith dust-generating equipment and the wind direction; SL j is the size of the jth obstacle; RK j is the blocking angle coefficient between the jth obstacle and the wind direction.

[0107] It should be noted that It means that the combined effect of the dust generation intensity of all dust-generating equipment and their relative position to the wind direction is taken into account. i The larger the value, the greater the impact on the wind direction angle. At the same time, the relative position coefficient RN i It also plays an important role. Indicates that the scale of all obstacles and their combined impact with the wind direction blocking angle are taken into account. Obstacle scale SL j The larger it is, the greater the obstruction to wind direction; this formula calculates the ratio of the comprehensive impact of dust-generating equipment on wind direction to the comprehensive impact of obstacles on wind direction, and then uses the inverse tangent function to obtain the wind direction angle θ.

[0108] Step 208: The wind speed data includes the initial wind speed VK; the initial wind speed VK is directly obtained by installing mechanical anemometers at different locations such as the coal storage yard and coal transport trestle of the thermal power plant and using the mechanical anemometers for real-time monitoring.

[0109] Get the distance LK between the obstacle and the dust-generating area j By placing the laser rangefinder at the boundary point of the dust-generating area, aiming at another target point, and pressing the measurement button, the laser rangefinder will display the distance between the two, thereby obtaining the distance LK between different obstacles and the dust-generating area. j .

[0110] Step 209: According to the initial wind speed VK and the operating power PH i , the distance between dust-generating equipment and dust-generating area DH i And wind direction angle θ, calculate wind speed VM, based on the formula:

[0111]

[0112] Among them, LK j is the distance between the jth obstacle and the dust generating area.

[0113] It should be noted that It represents the ratio of the operating power of the i-th dust-generating equipment to its distance from the dust-generating area. The greater the operating power, the greater the impact on the wind speed; the greater the distance, the smaller the impact. Multiplying by cosθ is to consider the influence of the wind direction angle. When the wind direction is consistent with the direction of the line connecting the dust-generating equipment to the dust-generating area, cosθ=1, and the dust-generating equipment has the greatest impact on the wind speed; when the wind direction is vertical, cosθ=0, and the dust-generating equipment has the least impact on the wind speed; adding 1 is to ensure that the wind speed will not become negative due to the influence of the dust-generating equipment. It represents the ratio of the scale of the j-th obstacle to its distance from the dust-producing area. The larger the scale of the obstacle, the greater the impact on the wind speed; the farther the distance, the smaller the impact. Multiplying by sinθ takes into account the influence of the wind direction angle. When the wind direction is perpendicular to the line connecting the obstacle and the dust-producing area, sinθ = 1, and the obstacle has the greatest impact on the wind speed; when the wind direction is parallel, sinθ = 0, and the obstacle has the smallest impact on the wind speed. Subtracting this term by 1 is because the obstacle usually reduces the wind speed.

[0114] Step 210: According to the comprehensive dust content CC, the wind direction angle θ, and the wind speed VM, calculate the comprehensive environmental index RHM. The calculation formula is:

[0115] RHM = ω1×CC + ω2×θ + ω3×VM

[0116] Where, ω1 is the weight coefficient of the comprehensive dust content CC, with a value range of 0.1 - 0.4; ω2 is the weight coefficient of the wind direction angle θ, with a value range of 0.2 - 0.5; ω3 is the weight coefficient of the wind speed VM, with a value range of 0.3 - 0.4; and ω1 + ω2 + ω3 = 1.

[0117] It should be noted that this formula comprehensively considers the three important parameters: the comprehensive dust content CC, the wind direction angle θ, and the wind speed VM. Each parameter has a corresponding weight coefficient, indicating the degree of emphasis on different parameters when calculating the comprehensive environmental index RHM. By multiplying each parameter by its corresponding weight coefficient and then summing, a comprehensive environmental index RHM that can comprehensively describe dust is obtained.

[0118] Step 211: The comprehensive environmental index thresholds include the first comprehensive environmental index threshold RHM1 and the second comprehensive environmental index threshold RHM2, and RHM1 < RHM2; through long-term monitoring of the dust-producing area, a large amount of comprehensive environmental index data is accumulated. Statistical analysis is performed on these data to determine the value range of the RHM value under different dust risk states. The lower limit value of this value range is used as the first comprehensive environmental index threshold RHM1; the upper limit value of this value range is used as the second comprehensive environmental index threshold RHM2.

[0119] Step 212: When RHM ≤ RHM1, it is determined that there is no dust risk in this area;

[0120] When RHM1 < RHM ≤ RHM2, it is determined that there is a medium dust risk in this area;

[0121] When RHM > RHM2, it is determined that there is a high dust risk in this area.

[0122] The calculated comprehensive environmental indicators can provide a reliable basis for environmental management and help formulate reasonable dust prevention and reduction measures. Comparison with the threshold can timely identify dust risks, facilitate early warning and control measures, and ensure regional environmental quality. It also helps to optimize equipment operating parameters and improve production efficiency and environmental benefits.

[0123] Step 3: When there is a dust risk in the area, calculate the monitoring field of view angle α according to the comprehensive environmental indicator RHM and the video image information data, and further obtain the focal length f; calculate the dust source change rate RF and the number of frames NC based on the video image information data; calculate the dust source position parameter PT at the current moment according to the dust source change rate RF, the number of frames NC, the monitoring field of view angle α and the focal length f.

[0124] Step 301: The video image information data includes an initial field of view angle α0 and an initial focal length f0, and the acquisition method is: since the monitoring field of view angle and the initial focal length are fixed parameters, the monitoring field of view angle α and the initial focal length f0 of the video monitoring device are acquired according to the product manual of the video monitoring device.

[0125] The adjustment coefficient d of the comprehensive environmental index RHM is obtained, because different regions have different geographical environments, meteorological conditions and surrounding facilities. For example, in a thermal power plant, the coal loading and unloading area is close to the open area, the wind speed is high, the dust is easy to spread, and the air circulation is good. In this environment, the dust risk is relatively low. Therefore, for such areas, the adjustment coefficient d of the comprehensive environmental index RHM is 0.1-0.3, indicating that the environment has a small inhibitory effect on the spread of dust; while in closed areas such as the interior of the factory building, the air circulation is small, the dust is not easy to spread, and it is easy to accumulate. The dust risk in this environment is high. Therefore, for such areas, the adjustment coefficient d of the comprehensive environmental index RHM is 0.7-1, indicating that the environment has a large inhibitory effect on the spread of dust. By setting the adjustment coefficient d of the comprehensive environmental index RHM, the dust risk can be accurately assessed according to the actual environmental conditions of different regions.

[0126] Step 302: When there is a dust risk in the area, the monitoring field of view angle α is calculated according to the comprehensive environmental index RHM, the adjustment coefficient d of the comprehensive environmental index RHM and the initial field of view angle α0. The calculation formula is:

[0127]

[0128] It should be noted that exp(-d+RHM) is an exponential function, where exp(x)=e x , e is a natural constant, with a value of 2.71828. When the comprehensive environmental index RHM increases, The value of approaches 1, the monitoring field of view angle α approaches the initial field of view angle α0, and a wider monitoring field of view angle is maintained to better observe and monitor the dust situation; when the comprehensive environmental index RHM decreases, As the value of approaches 0, the monitoring field of view angle α approaches 0. By reducing the monitoring field of view angle, a specific area can be observed in more detail.

[0129] Step 303: Calculate the focal length f according to the monitoring field of view angle α, the initial field of view angle α0 and the initial focal length f0. The calculation formula is:

[0130]

[0131] It should be noted that It is the tangent value of half of the initial field of view angle α0, which represents the viewing angle characteristics of the lens in the initial state. is the tangent value of half of the monitoring field of view angle α, which represents the viewing angle characteristics of the lens under the current monitoring state. When the monitoring field of view angle α changes, the new focal length f is calculated by the ratio of the initial focal length f0 and the viewing angle tangent value.

[0132] Step 304: The video image information data also includes the initial scale index SK, the current scale index SN and the frame rate F of the dust source in the video image, and the acquisition method is:

[0133] The initial scale index SK of the dust source is calculated by obtaining the pixel value PO occupied by the dust source in the initial video image and the area AP of each pixel; according to the pixel value PO occupied by the dust source in the initial video image and the area AP of each pixel, the initial scale index SK of the dust source is calculated, and the calculation formula is:

[0134] SK=PO×AP

[0135] Calculate the scale index SN at the current moment, track the dust source, determine the location of the dust source at the current moment Ti, and calculate the pixel value PO occupied by the dust source in the video image at the current moment Ti. Ti And the area AP of each pixel, calculate the scale index SN at the current moment, the calculation formula is:

[0136] SN=PO Ti ×AP

[0137] The frame rate F can be directly obtained by checking the manual of the video surveillance equipment.

[0138] Step 305: Calculate the dust source change rate RF according to the initial scale index SK and the current scale index SN of the dust source in the video image. The calculation formula is:

[0139]

[0140] Step 306: Based on the frame rate F, the number of frames NC of the video image in the time t is calculated, and the calculation formula is:

[0141] NC=F×t

[0142] Step 307: The method for calculating the pixel distance DB between the dust source position parameter at the previous moment and the dust source position parameter at the current moment is:

[0143] Get the coordinates of the dust source in the image at the last moment (x0, y0) and the coordinates of the dust source in the image at the current moment (x1, y1). According to the coordinates of the dust source in the image at the last moment (x0, y0) and the coordinates of the dust source in the image at the current moment (x1, y1), calculate the pixel distance DB between the position parameters of the dust source at the last moment and the position parameters of the dust source at the current moment. The calculation formula is:

[0144]

[0145] Step 308: Calculate the current dust source position parameter PT according to the pixel distance DB between the dust source position parameter at the previous moment and the dust source position parameter at the current moment, the dust source change rate RF, the number of frames NC, the monitoring field of view angle α and the focal length f, based on the formula:

[0146]

[0147] Among them, P0 is the dust source position parameter at the previous moment; specifically, when processing the dust source position parameter PT at the current moment, the dust source position parameter at the previous moment is the dust source position parameter P0 at the previous moment, and the calculation principle of the dust source position parameter P0 at the previous moment is the same as the dust source position parameter PT at the current moment.

[0148] It should be noted that (1+RF) NC This item takes into account the change of the dust source within the NC frame. The greater the dust source change rate RF, the greater the change in the position of the dust source after the NC frame. This item is related to the principle of optical imaging. The monitoring field of view angle α and focal length f determine the imaging position and size of the dust source in the video image. When the monitoring field of view angle α changes, The value of will also change, thus affecting the position of the dust source in the image. The larger the focal length f, the greater the imaging magnification, and the position of the dust source in the image will also change accordingly. This item takes into account the pixel distance DB between the dust source position parameter at the previous moment and the dust source position parameter at the current moment. When the pixel distance DB is larger, the dust source moves a greater distance in the image, and the greater the impact on the dust source position parameter PT at the current moment.

[0149] Calculating the monitoring field of view angle and focal length can optimize the range and clarity of video monitoring and better capture the dynamics of dust sources. Calculating the change rate and frame rate of dust sources can quantify the changes in dust sources and help accurately grasp the development trend of dust. Obtaining the location parameters of dust sources at the current moment can provide accurate location information for timely dust reduction measures, thereby more effectively controlling dust risks and ensuring environmental quality and production safety.

[0150] Step 4: Calculate the received information accuracy index WE based on the dust source position parameter PT at the current moment; calculate the synchronization index PQ based on the video image information data, the dust source position parameter PT at the current moment and the received information accuracy index WE; preset the synchronization index threshold, compare the synchronization index PQ with the synchronization index threshold, and determine whether the dust source position displayed by the monitoring center is synchronized with the actual dust source position based on the result; when the position is not synchronized, the video monitoring equipment automatically adjusts the angle.

[0151] Step 401: The method for calculating the time interval Δt is:

[0152] Get the video frame timestamp T1 corresponding to the dust source position parameter PT at the current moment and the video frame timestamp T0 corresponding to the dust source position parameter P0 at the previous moment;

[0153] According to the video frame timestamp T1 corresponding to the dust source position parameter PT at the current moment and the video frame timestamp T0 corresponding to the dust source position parameter P0 at the previous moment, the time interval Δt is calculated using the following formula:

[0154] Δt=T1-T0

[0155] Step 402: Obtain the data transmission delay time TF. When transmitting data, the transmitting device adds the current system time as the transmission timestamp to the data structure. At the receiving end, when receiving data, the current system time is used as the receiving timestamp, and then the transmitting timestamp is subtracted from the receiving timestamp to obtain the data transmission delay time TF.

[0156] Step 403: The method for obtaining the clarity index C of the dust source in the video image is:

[0157] Use the Canny edge detection algorithm to process the dust source area in the video image to obtain the edge strength E(x, y) of the image;

[0158] Based on the edge strength E(x, y), the clarity index C of the dust source in the video image is calculated using the following formula:

[0159]

[0160] Where N is the total number of image pixels.

[0161] Step 404: Calculate the received information accuracy index WE according to the data transmission delay time TF, the clarity index C of the dust source in the video image, the dust source position parameter P0 at the previous moment, and the dust source position parameter PT at the current moment. The calculation formula is:

[0162]

[0163] It should be noted that PT×Δt represents the location information of the dust source in the current time interval. The term TF×(1-C)×(1-S)×(PT-P0) represents the combined effect of the data transmission delay time TF, the clarity index C of the dust source in the video image, the stability coefficient S of the data transmission, and the change position of the dust source (PT-P0) on the accuracy of the received information. When the data transmission delay time TF is long, the clarity index C of the dust source in the video image is low, the stability coefficient S of the data transmission is low, and the change position of the dust source (PT-P0) is large, the value of this term will increase, resulting in an increase in the denominator and a decrease in the received information accuracy index WE.

[0164] The performance and reliability of network devices such as routers, switches, and wireless access points directly affect the stability of data transmission. High-performance and reliable network devices can ensure stable data transmission, while low-performance or faulty devices can cause data transmission interruptions or errors. At this time, it is necessary to introduce a data transmission stability coefficient S to reflect the stability of data transmission. For example, when the network device has excellent performance, the data transmission delay is extremely low, there is no jitter, no packet loss, and the bandwidth is sufficient and stable, the data transmission stability coefficient S = 1, indicating that the data transmission is extremely stable. As the performance of the network device decreases, the data transmission characteristics deteriorate, and the S value gradually decreases, ranging from 0 to 1. When a serious fault occurs in the network device, such as a device freeze or port failure, the data transmission stability coefficient S = 0, indicating that the data transmission is extremely unstable.

[0165] Step 405: The video image information data also includes the dust source position update frequency FU; the dust source position update frequency FU is calculated by the frame rate F of the video and the number of frames NV between each dust source position update, and the calculation formula is:

[0166]

[0167] Step 406: Calculate the synchronization index PQ according to the dust source position update frequency FU, the frame rate F, the current dust source position parameter PT, the previous dust source position parameter P0 and the received information accuracy index WE, and the formula based on which is:

[0168]

[0169] It should be noted that This part reflects the relative relationship between the dust source position update frequency and the video frame rate. When the dust source position update frequency FU is higher and the video frame rate F is lower, the value of this part is larger, indicating that the dust source position is updated more frequently relative to the video frame rate. This item takes into account the difference between the current dust source position parameters and the previous dust source position parameters. |PT-P0| is the position difference, It is the time interval corresponding to each frame. The larger the position difference, the larger the value of this item, indicating that the dust source position changes more. (1-WE) 2 This item is related to the received information accuracy index WE. When the received information accuracy index WE is lower, (1-WE) 2 The larger the value, the worse the accuracy of the received information.

[0170] Step 407: Preset the synchronization index threshold PQ th ; Set up a dust source at the experimental site, install video surveillance equipment, and record the actual location of the dust source and the location displayed by the monitoring center at different times; calculate the synchronization index PQ corresponding to each moment, draw a distribution histogram of the PQ value, and observe the distribution of the PQ value in different intervals. If it is found that when the PQ value is less than a certain value, the monitoring position is not synchronized with the actual position, then the specific value is used as the synchronization index threshold PQ th .

[0171] Step 408: When PQ≤PQ th When PQ>PQ th When the dust source position displayed by the monitoring center is judged to be synchronized with the actual dust source position.

[0172] The accuracy index of received information obtained from the location parameters can evaluate the reliability of data and ensure the quality of monitoring data. The synchronization index is calculated and compared with the preset threshold to accurately determine whether the dust source location displayed by the monitoring center is synchronized with the actual location, avoiding monitoring errors caused by asynchronous location.

[0173] On the other hand, the present invention also discloses an integrated device for dust source positioning and video tracking of a thermal power plant, which can be used to implement the integrated method for dust source positioning and video tracking of the above-mentioned thermal power plant.

[0174] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0175] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0176] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An integrated method for dust source location and video tracking in a thermal power plant, characterized in that: Including: Real-time collecting dust concentration data, wind speed data, equipment operation status data and video image information data; According to the dust concentration data and equipment operation status data, calculating the dust content CB; Based on the dust content CB, calculating the comprehensive dust content CC; Calculating the wind direction angle θ based on the equipment operation status data; According to the wind speed data and equipment operation status data, calculating the wind speed VM; According to the comprehensive dust content CC, wind direction angle θ and wind speed VM, calculating the comprehensive environmental index RHM; Comparing the comprehensive environmental index RHM with the comprehensive environmental index threshold, and judging whether there is a dust risk in this area according to the result; When there is a dust risk in this area, according to the comprehensive environmental index RHM and video image information data, calculating the monitoring field of view angle α, and further obtaining the focal length f; Based on the video image information data, respectively calculating the dust source change rate RF and the number of frames NC; According to the dust source change rate RF, the number of frames NC, the monitoring field of view angle α and the focal length f, calculating the dust source position parameter PT at the current moment; Calculating the received information accuracy index WE based on the dust source position parameter PT at the current moment; According to the video image information data, the dust source position parameter PT at the current moment and the received information accuracy index WE, calculating the synchronization index PQ; Presetting the synchronization index threshold, comparing the synchronization index PQ with the synchronization index threshold, and judging whether the dust source position displayed by the monitoring center is synchronized with the actual dust source position according to the result; When the positions are not synchronized, triggering the warning device.

2. The integrated method for dust source location and video tracking of a thermal power plant according to claim 1 is characterized in that: The method for calculating the comprehensive dust content CC is: The dust concentration data includes the initial dust concentration CA; Equipment operating status data includes the operating power PH of different dust-generating equipment i , running time TH i And the distance between the dust-generating equipment and the dust-generating area DH i ; According to the initial dust concentration CA, operating power PH i , running time TH i The distance between the dust-generating equipment and the dust-generating area DH i , calculate the dust content CB, the calculation formula is: Among them, PH i is the operating power of the i-th dust-generating equipment, i is [1, n], n is the number of dust-generating equipment, and is a positive integer; TH i is the operating time of the i-th dust-generating equipment; DH i is the distance between the ith dust-generating equipment and the dust-generating area; Based on the dust content CB, calculating the comprehensive dust content CC, and the calculation formula is: Where V is the ventilation coefficient of the dust-generating area; H j is the obstruction coefficient of the j-th obstacle to ventilation, the value of j is [1, m], m is the number of obstacles, and the value is a positive integer.

3. The integrated method for dust source location and video tracking of a thermal power plant according to claim 2 is characterized in that: The method for calculating the wind direction angle θ is: Equipment operating status data also includes the dust generation intensity IN of different dust generating equipment i ; Based on dust generation intensity IN i , calculate the wind direction angle θ, the calculation formula is: Among them, IN i is the dust generation intensity of the i-th dust generating equipment; RN i is the relative position coefficient between the ith dust-generating equipment and the wind direction; SL j is the size of the jth obstacle; RK j is the blocking angle coefficient between the jth obstacle and the wind direction.

4. The integrated method for dust source location and video tracking of a thermal power plant according to claim 3 is characterized in that: The method for calculating the wind speed VM is: The wind speed data includes the initial wind speed VK; According to the initial wind speed VK, operating power PH i , the distance between dust-generating equipment and dust-generating area DH i And wind direction angle θ, calculate wind speed VM, based on the formula: Among them, LK j is the distance between the jth obstacle and the dust generating area.

5. The integrated method for dust source location and video tracking of a thermal power plant according to claim 4 is characterized in that: The method for judging whether there is a dust risk in this area is: According to the comprehensive dust content CC, wind direction angle θ and wind speed VM, calculating the comprehensive environmental index RHM, and the calculation formula is: RHM = ω1×CC + ω2×θ + ω3×VM Wherein, ω1 is the weight coefficient of the comprehensive dust content CC, and the value range is 0.1 to 0.4; ω2 is the weight coefficient of the wind direction angle θ, and the value range is 0.2 to 0.5; ω3 is the weight coefficient of the wind speed VM, and the value range is 0.3 to 0.4; and ω1 + ω2 + ω3 = 1; The comprehensive environmental index threshold includes the comprehensive environmental index threshold one RHM1 and the comprehensive environmental index threshold two RHM2, and RHM1 < RHM2; When RHM ≤ RHM1, it is judged that there is no dust risk in this area; When RHM1 < RHM ≤ RHM2, it is judged that there is a medium dust risk in this area; When RHM > RHM2, it is judged that there is a high dust risk in this area.

6. The integrated method for dust source location and video tracking of a thermal power plant according to claim 5, characterized in that: The method for calculating the focal length f is: The video image information data includes the initial field of view angle α0 and the initial focal length f0; When there is a dust risk in this area, according to the comprehensive environmental index RHM and the initial field of view angle α0, calculating the monitoring field of view angle α, and the calculation formula is: Wherein, d is the adjustment coefficient of the comprehensive environmental index RHM; According to the monitoring field of view angle α, the initial field of view angle α0 and the initial focal length f0, the focal length f is calculated using the following formula:

7. The integrated method for dust source location and video tracking of a thermal power plant according to claim 6, characterized in that: The method for calculating the dust source position parameter PT at the current moment is: The video image information data also includes the initial scale index SK, the current scale index SN and the frame rate F of the dust source in the video image; According to the initial scale index SK of the dust source in the video image and the scale index SN at the current moment, the dust source change rate RF is calculated. The calculation formula is: Based on the frame rate F, the number of frames NC of the video image in time t is calculated, and the calculation formula is: NC=F×t According to the dust source change rate RF, frame number NC, monitoring field of view angle α and focal length f, the dust source position parameter PT at the current moment is calculated based on the formula: Among them, P0 is the dust source position parameter at the previous moment; DB is the pixel distance between the dust source position parameter at the previous moment and the dust source position parameter at the current moment.

8. The integrated method for dust source location and video tracking of a thermal power plant according to claim 7, characterized in that: The method for calculating the received information accuracy index WE is: According to the dust source position parameter P0 at the previous moment and the dust source position parameter PT at the current moment, the received information accuracy index WE is calculated, and the calculation formula is: Among them, Δt is the time interval; TF is the data transmission delay time; C is the clarity index of the dust source in the video image; S is the stability coefficient of data transmission.

9. The integrated method for dust source location and video tracking of a thermal power plant according to claim 8, characterized in that: The method to determine whether the dust source location displayed by the monitoring center is synchronized with the actual dust source location is: The video image information data also includes the dust source location update frequency FU; According to the dust source position update frequency FU, frame rate F, current dust source position parameter PT, previous dust source position parameter P0 and received information accuracy index WE, the synchronization index PQ is calculated based on the formula: Preset synchronization index threshold PQ th ; When PQ≤PQ th When PQ>PQ th When the dust source position displayed by the monitoring center is judged to be synchronized with the actual dust source position.

10. The integrated device for dust source positioning and video tracking in thermal power plants is characterized by: The method can be used to implement the integrated method of dust source positioning and video tracking in a thermal power plant according to any one of claims 1 to 9.

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