CN117853295A - Safety environmental protection emergency system based on industry interconnection and digital panorama - Google Patents
Safety environmental protection emergency system based on industry interconnection and digital panorama Download PDFInfo
- Publication number
- CN117853295A CN117853295A CN202311813974.7A CN202311813974A CN117853295A CN 117853295 A CN117853295 A CN 117853295A CN 202311813974 A CN202311813974 A CN 202311813974A CN 117853295 A CN117853295 A CN 117853295A
- Authority
- CN
- China
- Prior art keywords
- data
- image
- panoramic
- waste gas
- exhaust gas
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000007613 environmental effect Effects 0.000 title claims description 11
- 239000007789 gas Substances 0.000 claims abstract description 76
- 238000012937 correction Methods 0.000 claims abstract description 57
- 239000002912 waste gas Substances 0.000 claims abstract description 48
- 238000012545 processing Methods 0.000 claims abstract description 17
- 230000000007 visual effect Effects 0.000 claims abstract description 14
- 238000005516 engineering process Methods 0.000 claims abstract description 6
- 230000002159 abnormal effect Effects 0.000 claims description 44
- 238000012544 monitoring process Methods 0.000 claims description 34
- 238000000034 method Methods 0.000 claims description 28
- 230000009466 transformation Effects 0.000 claims description 25
- 238000012800 visualization Methods 0.000 claims description 22
- 238000004458 analytical method Methods 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 15
- 230000008859 change Effects 0.000 claims description 8
- 238000007405 data analysis Methods 0.000 claims description 7
- 238000007781 pre-processing Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 5
- PXFBZOLANLWPMH-UHFFFAOYSA-N 16-Epiaffinine Natural products C1C(C2=CC=CC=C2N2)=C2C(=O)CC2C(=CC)CN(C)C1C2CO PXFBZOLANLWPMH-UHFFFAOYSA-N 0.000 claims description 4
- 238000004220 aggregation Methods 0.000 claims description 4
- 230000002776 aggregation Effects 0.000 claims description 4
- 238000004140 cleaning Methods 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 claims description 4
- 238000007619 statistical method Methods 0.000 claims description 4
- 230000002194 synthesizing effect Effects 0.000 claims description 4
- 238000012549 training Methods 0.000 claims description 4
- 230000009471 action Effects 0.000 claims 1
- 230000000977 initiatory effect Effects 0.000 claims 1
- 238000001514 detection method Methods 0.000 abstract 2
- 230000008569 process Effects 0.000 description 5
- 239000003344 environmental pollutant Substances 0.000 description 4
- 238000011835 investigation Methods 0.000 description 4
- 231100000719 pollutant Toxicity 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000009776 industrial production Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
Landscapes
- Testing Or Calibration Of Command Recording Devices (AREA)
Abstract
The invention discloses a safety environment-friendly emergency system based on industrial interconnection and digital panorama, relates to the technical field of safety environment-friendly emergency systems, and solves the technical problem that the detection result is inaccurate due to the fact that low-temperature air is liquefied when waste gas is detected in the prior art; according to the invention, the correction factors are obtained through the inverse proportion relation between the gas concentration and the temperature, the correction model is constructed based on the correction factors to correct the collected waste gas concentration, so that the accuracy of waste gas detection is improved, the panoramic image is constructed through the digital panoramic technology, meanwhile, the data monitored in real time are displayed on a visual interface through visual processing, so that staff can obtain more visual information and more judgment basis, and the accuracy of judging the cause of the problem in advance is improved.
Description
Technical Field
The invention belongs to the field of emergency systems, relates to industrial interconnection and digital panorama technology, and particularly relates to a safe and environment-friendly emergency system based on industrial interconnection and digital panorama.
Background
With the acceleration of the industrialization process, the environmental pollution problem is increasingly prominent, especially the industrial pollution has no negligible influence on the environment and the health and safety of human beings; various pollutants can be generated in the industrial production process, and how to effectively monitor the pollutants in real time is a great challenge in the environment protection and industrial production fields.
In the prior art for monitoring industrial pollutants, when the waste gas is collected, the influence of the temperature on the waste gas is not considered, and when the waste gas encounters cold air with low temperature, the gas can be liquefied, so that gas data collected by a sensor are different from actual data; in addition, according to the prior art, when an unexpected situation is found in the treatment process of the waste gas, for example, the safety index after the waste gas treatment does not reach the standard, for investigation reasons, staff analyzes possible abnormal reasons through collected data, because the analysis basis is few, and meanwhile, the accuracy of judging the abnormal reasons in advance is not high due to the fact that the change of the data cannot be intuitively observed, so that the problem reasons cannot be found in the first time, and the treatment progress is affected;
the invention provides a safety environment-friendly emergency system based on industrial interconnection and digital panorama, which aims to solve the problems.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art; therefore, the invention provides a safety environment-friendly emergency system based on industrial interconnection and digital panorama, which is used for solving the problem that the prior art monitors industrial pollution, and when waste gas is collected, the influence of temperature on the waste gas is not considered, so that the gas data collected by a sensor is different from actual data; and when an unexpected situation is found in the treatment process of the waste gas, for example, the safety index after the waste gas treatment does not reach the standard, and the technical problem that the accident can not be treated at the first time is solved.
To achieve the above object, a first aspect of the present invention provides a safety and environmental protection emergency system based on industrial interconnection and digital panorama, comprising: the data analysis module is connected with the data acquisition module and the emergency processing module;
and a data acquisition module: collecting image data of a plurality of collecting angles of a target area by using panoramic collecting equipment; the panoramic acquisition equipment comprises a panoramic camera or a VR (virtual reality) camera, and the target area is an exhaust gas treatment area; the method comprises the steps of,
acquiring monitoring data through data sensors distributed in a target area; the data sensor comprises an air quality sensor and a temperature sensor;
and a data analysis module: synthesizing image data of a plurality of acquisition angles based on a panoramic stitching tool and a stitching algorithm to obtain a panoramic image; the panoramic stitching tool comprises PTGui, hugin or Adobe Photoshop software, and the stitching algorithm comprises SIFT algorithm or SURF algorithm; the method comprises the steps of,
extracting air quality data in the monitoring data, and correcting the air quality data to obtain corrected data; identifying whether the correction data is abnormal or not through a depth analysis model; if yes, sending an early warning signal to an emergency processing module; the depth analysis model is constructed based on an artificial intelligent model;
and an emergency processing module: after receiving the early warning signal, positioning an abnormal position on the panoramic image based on the correction data, and marking the abnormal position as an accident position; starting an emergency plan to take emergency measures for the accident position; the method comprises the steps of,
using a visualization tool to visually display the accident position and the monitoring data; wherein the visualization tool comprises Tableau, power BI, D3.Js or matplotlib.
Preferably, the capturing image data of a plurality of capturing angles of the target area by using the panoramic capturing device includes:
and selecting a reference point from the target area, and shooting the target area by 360 degrees in full coverage by using panoramic acquisition equipment based on the reference point.
Preferably, the data sensor arranged in the target area collects monitoring data, including:
acquiring the actual concentration of the waste gas and the actual temperature of the waste gas corresponding to the acquisition time in real time through a temperature sensor and an air quality sensor which are arranged in the exhaust port; the method comprises the steps of,
acquiring the ambient temperature by a temperature sensor arranged outside the exhaust port; wherein the ambient temperature is not affected by the exhaust port.
Preferably, the panorama stitching tool and stitching algorithm are used for compositing image data of a plurality of acquisition angles to obtain a panoramic image, and the method comprises the following steps:
detecting and matching the image data through a panoramic stitching tool to obtain feature points; calculating the feature points based on a splicing algorithm to obtain descriptors; matching in the image data based on the descriptors to obtain feature point pairs; the method comprises the steps of,
obtaining an image transformation relation of the feature point pairs by using a geometric transformation model; wherein the geometric transformation model comprises affine transformation or projective transformation; and constructing and obtaining the panoramic image based on the image data and the image transformation relation.
Preferably, the correcting the air quality data to obtain corrected data includes:
the actual concentration of the collected waste gas is marked as C, the actual temperature of the waste gas corresponding to the collection is marked as T, the ambient temperature is marked as T0, and a correction model is obtained: cx=c×f, where Cx is the corrected exhaust gas concentration and F is the correction factor; the method comprises the steps of,
based on the formula pv=nrt and the relation c=n/V of gas concentration to volume, the formula is deduced: c=p/RT, giving the gas concentration inversely proportional to the temperature, giving a correction factor f=axx (T0/T), i.e. a correction model cx=cxaxx (T0/T), where P represents the pressure, V represents the gas volume, n represents the number of moles, R is the ideal gas constant, and a is the proportionality coefficient.
In the prior art, when the concentration of the exhaust gas is collected, the influence of the temperature on the concentration of the gas is not considered, so that the concentration of the collected exhaust gas is different from the actual concentration of the exhaust gas, and the difference mainly comes from the fact that when the exhaust gas encounters cold air with low temperature, the gas can be liquefied, and the concentration of the collected exhaust gas is reduced;
according to the invention, the acquired exhaust gas concentration is corrected by constructing the correction model, so that the acquired corrected gas concentration is more similar to the actual gas concentration, and the accuracy of the acquired data is improved.
Preferably, the identifying whether the correction data is abnormal by the depth analysis model includes:
generating standard input data based on the actual concentration of the exhaust gas and the actual temperature of the exhaust gas corresponding to the exhaust gas history data; obtaining corresponding historical correction data by inputting standard input data into a depth analysis model, wherein the depth analysis model is obtained based on artificial intelligence model training; the method comprises the steps of,
based on the comparison of the history correction data and the safety emission index of the waste gas, if the history correction data exceeds the safety emission index, judging that the quality of the waste gas is abnormal, and sending an early warning signal to an early warning processing module; the exhaust gas history data is the history data of the collection target area.
Preferably, the locating the abnormal position on the panoramic image based on the correction data, marked as an accident position, includes:
positioning the accident position on the panoramic image based on the position information of the abnormal sensor corresponding to the correction data; based on the accident position, calling the image information of the corresponding abnormal sensor in the panoramic image; wherein the location information includes: longitude and latitude and pixel position relative to the panoramic image; the image information includes: the specific location of the anomaly sensor and the surrounding environment and building facilities.
In the prior art, when abnormal sensor data is found, the reasons for the abnormal occurrence are found through data analysis and field investigation, so that the maintenance time is prolonged, the factory cannot normally run as early as possible, and meanwhile, when the field investigation is carried out, the safety of staff can be influenced due to long-time stay;
according to the invention, the panoramic image is established, the position information of the abnormal sensor is utilized, the image information of the corresponding abnormal sensor in the panoramic image is called, the position of the abnormal sensor, the surrounding environment and the building facilities are provided for the staff, the staff can intuitively observe the abnormal area, and the accurate decision making and countermeasures taking at the first time are facilitated.
Preferably, the step of starting the emergency plan takes emergency measures for the accident position, including:
based on a wireless communication technology, the emergency treatment module is connected with the waste gas treatment equipment, and when an early warning signal is received, the emergency treatment module sends an instruction to the waste gas treatment equipment to take emergency measures for the accident position; wherein the emergency measures include: stopping the production process, reducing the generation of waste gas, closing the exhaust port, warning the staff, and monitoring the data of the waste gas in real time for the staff to refer.
Preferably, the visual display of the accident position and the monitoring data by using the visual tool includes:
the visual data is obtained by preprocessing the correction data, wherein the preprocessing comprises the following steps: data cleaning, aggregation, calculation of derivative indexes and statistical analysis treatment; generating image data associating the visualization data with the chart based on the visualization data; based on the image data, displaying real-time monitoring data and early warning information through a chart; the method comprises the steps of,
based on the real-time monitoring data, a data curve is generated through a visualization tool, and the data change trend is reflected.
In the prior art, the abnormal cause is analyzed by collecting data, which may cause that the accuracy of the abnormal cause which is judged by the staff in advance is not high, and the main cause of the problem is that single data cannot be provided for excessive information of the staff, and meanwhile, the analyzed data are all past data, so that the judgment basis obtained by the staff is limited, and the accuracy of judging the abnormal cause is not high.
The acquired data is visualized and displayed on the visualization interface, so that more reliable and easily-observed chart data can be provided for staff, and the trend of data change can be reflected through real-time monitoring, so that the staff can obtain more visual information, more judgment basis can be obtained, and the judgment accuracy is improved.
Compared with the prior art, the invention has the beneficial effects that:
1. in the prior art, the monitoring of industrial pollutants does not consider the influence of temperature on the exhaust gas when the exhaust gas is collected, and when the exhaust gas encounters cold air with low temperature, the gas can be liquefied, so that gas data collected by a sensor is different from actual data; according to the invention, the correction factors are obtained through the inverse relation between the gas concentration and the temperature, the correction model is constructed based on the correction factors, and the acquired gas concentration is corrected, so that the acquired corrected gas concentration is more similar to the actual gas concentration, and the accuracy of the acquired data is improved.
2. In the prior art, the data acquired by the sensor in the treatment process of the waste gas are abnormal, so that for investigation reasons, staff can analyze possible abnormal reasons through the acquired data, and the accuracy of judging the abnormal reasons in advance is not high because the analysis basis is little and the change of the data cannot be intuitively observed; according to the invention, the acquired data is subjected to visual processing, the chart data is displayed on a visual interface, and meanwhile, the trend of data change is reflected through real-time monitoring, so that not only is more visual information obtained by staff, but also more judgment basis is obtained, and the judgment accuracy is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic view of an overall frame of an embodiment of the present invention;
fig. 2 is a schematic flow chart of an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, an embodiment of a first aspect of the present invention provides a safety and environmental protection emergency system based on industrial interconnection and digital panorama, comprising: the data analysis module is connected with the data acquisition module and the emergency processing module;
and a data acquisition module: collecting image data of a plurality of collecting angles of a target area by using panoramic collecting equipment; the panoramic acquisition equipment comprises a panoramic camera or a VR (virtual reality) camera, and the target area is an exhaust gas treatment area; the method comprises the steps of,
acquiring monitoring data through data sensors distributed in a target area; the data sensor comprises an air quality sensor and a temperature sensor;
selecting a reference point in a target area, and shooting the target area by 360 degrees in full coverage by using panoramic acquisition equipment based on the reference point; acquiring the actual concentration of the waste gas and the actual temperature of the waste gas corresponding to the acquisition time in real time through a temperature sensor and an air quality sensor which are arranged in the exhaust port; and acquiring the ambient temperature by a temperature sensor arranged outside the exhaust port; wherein the ambient temperature is not affected by the exhaust port.
For example: an exhaust treatment area is provided, which is required to monitor the concentration and temperature of the exhaust gas and to know the temperature of the environment; and using a panoramic camera as panoramic acquisition equipment, and acquiring data by using a temperature sensor and an air quality sensor.
Firstly, selecting a reference point in a target area, such as the center position of the area; then, based on the reference point, shooting the target area by using a panoramic camera in 360 degrees of full coverage; thus, the image data of each direction of the target area can be obtained;
meanwhile, a temperature sensor and an air quality sensor are arranged in the exhaust port; the sensors can acquire the actual concentration of the exhaust gas and the actual temperature of the exhaust gas at the corresponding acquisition time in real time; in addition, a temperature sensor is arranged outside the exhaust port, and the sensor collects the ambient temperature; since it is not affected by the exhaust port, accurate ambient temperature data can be provided.
And a data analysis module: synthesizing image data of a plurality of acquisition angles based on a panoramic stitching tool and a stitching algorithm to obtain a panoramic image; the panoramic stitching tool comprises PTGui, hugin or Adobe Photoshop software, and the stitching algorithm comprises SIFT algorithm or SURF algorithm; the method comprises the steps of,
extracting air quality data in the monitoring data, and correcting the air quality data to obtain corrected data; identifying whether the correction data is abnormal or not through a depth analysis model; if yes, sending an early warning signal to an emergency processing module; the depth analysis model is constructed based on an artificial intelligent model;
detecting and matching the image data through a panoramic stitching tool to obtain feature points; calculating the feature points based on a splicing algorithm to obtain descriptors; matching in the image data based on the descriptors to obtain feature point pairs; obtaining an image transformation relation of the feature point pairs by using a geometric transformation model; wherein the geometric transformation model comprises affine transformation or projective transformation; and constructing and obtaining the panoramic image based on the image data and the image transformation relation.
For example: carrying out panoramic stitching on the image 1, the image 2 and the image 3; and using the PTGui as a panoramic stitching tool, and selecting a SIFT algorithm to detect and match the feature points.
Firstly, importing image data into PTGui software; PTGui automatically detects and matches the feature points to generate feature point pairs; then, calculating descriptors of the feature points by using a splicing algorithm; the descriptor represents the unique characteristic of the characteristic point and can be used for matching the characteristic point; next, matching is carried out in the image data through the descriptors, and feature point pairs are obtained; the pairs of feature points represent feature points at corresponding positions in different images.
In this example, assume that PTGui generates the following feature point pairs:
characteristic point pair of image 1: (p 1, p 2), (p 3, p 4)
Characteristic point pairs of image 2: (p 5, p 6), (p 7, p 8)
Characteristic point pairs of image 3: (p 9, p 10), (p 11, p 12)
Then, calculating an image transformation relationship between the feature point pairs using a geometric transformation model (e.g., affine transformation or projective transformation); these transformations describe how feature points on one image are moved to corresponding locations on another image; finally, constructing a panoramic image based on the image data and the image transformation relation; and overlapping and fusing each image according to the corresponding transformation relation, so that a final panoramic image can be obtained.
The actual concentration of the collected waste gas is marked as C, the actual temperature of the waste gas corresponding to the collection is marked as T, the ambient temperature is marked as T0, and a correction model is obtained: cx=c×f, where Cx is the corrected exhaust gas concentration and F is the correction factor; and, based on the formula pv=nrt and the relation c=n/V of gas concentration and volume, the formula is deduced: c=p/RT, giving the inverse ratio of gas concentration and temperature, thus obtaining a correction factor f=axx (T0/T), i.e. a correction model cx=cxaxx (T0/T), where P represents pressure, V represents gas volume, n represents moles, R is an ideal gas constant, a is a proportionality coefficient; generating standard input data based on the actual concentration of the exhaust gas and the actual temperature of the exhaust gas corresponding to the exhaust gas history data; obtaining corresponding historical correction data by inputting standard input data into a depth analysis model, wherein the depth analysis model is obtained based on artificial intelligence model training; and comparing the historical correction data with the safety emission index of the waste gas, judging that the quality of the waste gas is abnormal if the historical correction data exceeds the safety emission index, and sending an early warning signal to an early warning processing module; the exhaust gas history data is the history data of the collection target area.
For example: an exhaust gas collection system that can collect the exhaust gas concentration and the exhaust gas temperature in the target area; the following exhaust history data is assumed to be collected: the actual exhaust gas concentration c=100 ppm, the actual exhaust gas temperature t=300K, the ambient temperature t0=298K, and the proportionality coefficient a=2.
From the correction model cx=c×f, we can calculate the correction factor F:
F＝A×(T0/T)＝2×(298K/300K)＝1.9866
applying the correction factor to the exhaust gas concentration to obtain a corrected exhaust gas concentration:
Cx＝C×A×(T0/T)＝100×1.9866＝198.66
the actual concentration and the actual temperature of the exhaust gas are input into the depth analysis model as standard input data. The depth analysis model is based on an artificial intelligent model obtained through training, can analyze and process input data, and generates historical correction data; and comparing the historical correction data with the exhaust gas safety emission index. And if the corrected waste gas concentration exceeds the safety emission index, namely Cx > safety emission index, judging that the waste gas quality is abnormal, and sending an early warning signal to an early warning processing module.
And an emergency processing module: after receiving the early warning signal, positioning an abnormal position on the panoramic image based on the correction data, and marking the abnormal position as an accident position; starting an emergency plan to take emergency measures for the accident position; the method comprises the steps of,
using a visualization tool to visually display the accident position and the monitoring data; wherein the visualization tool comprises Tableau, power BI, D3.Js or matplotlib.
Positioning the accident position on the panoramic image based on the position information of the abnormal sensor corresponding to the correction data; based on the accident position, calling the image information of the corresponding abnormal sensor in the panoramic image; wherein the location information includes: longitude and latitude and pixel position relative to the panoramic image; the image information includes: the specific position of the abnormal sensor, the surrounding environment and the building facilities; based on a wireless communication technology, the emergency treatment module is connected with the waste gas treatment equipment, and when an early warning signal is received, the emergency treatment module sends an instruction to the waste gas treatment equipment to take emergency measures for the accident position; wherein the emergency measures include: stopping the production process, reducing the generation of waste gas, closing the exhaust port, warning the staff, and monitoring the data of the waste gas in real time for the staff to refer. The visual data is obtained by preprocessing the correction data, wherein the preprocessing comprises the following steps: data cleaning, aggregation, calculation of derivative indexes and statistical analysis treatment; generating image data associating the visualization data with the chart based on the visualization data; based on the image data, displaying real-time monitoring data and early warning information through a chart; and generating a data curve by the visualization tool based on the real-time monitoring data, and reflecting the data change trend.
For example: and obtaining correction data of the concentration of the exhaust gas through the correction model and the depth analysis model, and receiving an early warning signal of abnormal quality of the exhaust gas. The following is an example illustrating how the accident location is located on the panoramic image and visually presented based on the correction data:
first, the accident position is located on the panoramic image based on the position information of the anomaly sensor corresponding to the correction data. It is assumed that the pixel coordinates of the accident position in the panoramic image have been determined to be (x, y).
Then, image information corresponding to the accident position in the panoramic image is called; this includes the specific location where the anomaly sensor is located, the surrounding environment and the building facilities; may be presented by extracting areas in the image or marking the location of the accident.
The accident location and monitoring data are visually presented using a visualization tool (e.g., tableau, power BI, d3.Js, or matplotlib). For example, the location of the accident may be marked on the panoramic image and the correction data for the exhaust gas concentration, as well as other relevant monitoring data (e.g., temperature, pressure, etc.), may be displayed via a data chart.
The emergency treatment module is connected with the waste gas treatment equipment based on the wireless communication technology. When the early warning signal is received, the emergency processing module can send a command to the waste gas treatment equipment to take emergency measures for the accident position. Such emergency measures may include stopping the production process, reducing the generation of exhaust gas, closing the exhaust port, etc. Meanwhile, the staff is warned, and the data of the waste gas are monitored in real time for the staff to refer to.
By preprocessing the correction data, visual data can be obtained. This includes the steps of data cleaning, aggregation, calculation of derived indicators, statistical analysis, and the like.
Based on the visualization data, image data is generated that associates the visualization data with the chart. And proper visualization tools can be selected for operation according to actual demands so as to display real-time monitoring data and early warning information.
And finally, generating a data curve by a visualization tool based on the real-time monitoring data so as to reflect the data change trend. This can help the staff to know the exhaust gas monitoring data more intuitively and take corresponding measures in time.
The partial data in the formula is obtained by removing dimension and taking the numerical value for calculation, and the formula is obtained by simulating a large amount of acquired data through software and is closest to the real situation; the preset parameters and the preset threshold values in the formula are set by those skilled in the art according to actual conditions or are obtained through mass data simulation.
The working principle of the invention is as follows:
collecting image data of a plurality of collecting angles of a target area by using panoramic collecting equipment; collecting and obtaining monitoring data through data sensors distributed in a target area; synthesizing image data of a plurality of acquisition angles based on a panoramic stitching tool and a stitching algorithm to obtain a panoramic image; extracting air quality data in the monitoring data, and correcting the air quality data to obtain corrected data; identifying whether the correction data is abnormal or not through a depth analysis model; if yes, sending an early warning signal to an emergency processing module; the depth analysis model is constructed based on an artificial intelligent model; after receiving the early warning signal, positioning an abnormal position on the panoramic image based on the correction data, and marking the abnormal position as an accident position; starting an emergency plan to take emergency measures for the accident position; and visually displaying the accident position and the monitoring data by utilizing a visual tool.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (8)
1. An industrial interconnection and digital panorama-based safety and environmental protection emergency system, which is characterized by comprising: the data analysis module is connected with the data acquisition module and the emergency processing module;
and a data acquisition module: collecting image data of a plurality of collecting angles of a target area by using panoramic collecting equipment; the panoramic acquisition equipment comprises a panoramic camera or a VR (virtual reality) camera, and the target area is an exhaust gas treatment area; the method comprises the steps of,
acquiring monitoring data through data sensors distributed in a target area; the data sensor comprises an air quality sensor and a temperature sensor;
and a data analysis module: synthesizing image data of a plurality of acquisition angles based on a panoramic stitching tool to obtain a panoramic image; the panoramic stitching tool comprises PTGui, hugin or Adobe Photoshop software; the method comprises the steps of,
extracting air quality data in the monitoring data, and correcting the air quality data to obtain corrected data; identifying whether the correction data is abnormal or not through a depth analysis model; if yes, sending an early warning signal to an emergency processing module; the depth analysis model is constructed based on an artificial intelligent model;
and an emergency processing module: after receiving the early warning signal, positioning an abnormal position on the panoramic image based on the correction data, and marking the abnormal position as an accident position; starting an emergency plan to take emergency measures for the accident position; the method comprises the steps of,
using a visualization tool to visually display the accident position and the monitoring data; wherein the visualization tool comprises Tableau, power BI, D3.Js or matplotlib.
2. The industrial interconnect and digital panorama based safety and environmental protection emergency system according to claim 1, wherein said data sensors deployed in the target area collect monitoring data, comprising:
acquiring the actual concentration of the waste gas and the actual temperature of the waste gas corresponding to the acquisition time in real time through a temperature sensor and an air quality sensor which are arranged in the exhaust port; the method comprises the steps of,
acquiring the ambient temperature by a temperature sensor arranged outside the exhaust port; wherein the ambient temperature is not affected by the exhaust port.
3. The industrial interconnection and digital panorama-based safe and environment-friendly emergency system according to claim 1, wherein the panorama-based stitching tool synthesizes image data of a plurality of acquisition angles to obtain a panoramic image, and comprises:
detecting and matching the image data through a panoramic stitching tool to obtain feature points; calculating the feature points based on a splicing algorithm to obtain descriptors; matching in the image data based on the descriptors to obtain feature point pairs; the method comprises the steps of,
obtaining an image transformation relation of the feature point pairs by using a geometric transformation model; wherein the geometric transformation model comprises affine transformation or projective transformation; and constructing and obtaining the panoramic image based on the image data and the image transformation relation.
4. The industrial interconnection and digital panorama-based safety and environmental protection emergency system according to claim 1, wherein said correcting the air quality data to obtain corrected data comprises:
the actual concentration of the collected waste gas is marked as C, the actual temperature of the waste gas corresponding to the collection is marked as T, the ambient temperature is marked as T0, and a correction model is obtained: cx=c×f, where Cx is the corrected exhaust gas concentration and F is the correction factor; the method comprises the steps of,
based on the formula pv=nrt and the relation c=n/V of gas concentration to volume, the formula is deduced: c=p/RT, giving the gas concentration inversely proportional to the temperature, giving a correction factor f=axx (T0/T), i.e. a correction model cx=cxaxx (T0/T), where P represents the pressure, V represents the gas volume, n represents the number of moles, R is the ideal gas constant, and a is the proportionality coefficient.
5. The industrial interconnect and digital panorama based safety and environmental protection emergency system according to claim 1, wherein said identifying whether the corrected data is abnormal by the depth analysis model comprises:
generating standard input data based on the actual concentration of the exhaust gas and the actual temperature of the exhaust gas corresponding to the exhaust gas history data; generating standard output data based on whether the exhaust gas quality of the exhaust gas historical data is abnormal or not, and training a depth analysis model through the standard input data and the standard output data; wherein determining whether the exhaust gas quality of the exhaust gas history data is abnormal includes: correcting by a correction model based on the actual concentration of the exhaust gas and the actual temperature of the exhaust gas corresponding to the historical data to obtain historical correction data; the method comprises the steps of,
based on the comparison of the history correction data and the safety emission index of the waste gas, if the history correction data exceeds the safety emission index, judging that the quality of the waste gas is abnormal, and sending an early warning signal to an early warning processing module; the exhaust gas history data is the history data of the collection target area.
6. The industrial interconnect and digital panorama based safety and environmental protection emergency system according to claim 1, wherein said locating an abnormal location on the panorama image based on the correction data, labeled as an accident location, comprises:
positioning the accident position on the panoramic image based on the position information of the abnormal sensor corresponding to the correction data; based on the accident position, calling the image information of the corresponding abnormal sensor in the panoramic image; wherein the location information includes: longitude and latitude and pixel position relative to the panoramic image; the image information includes: the specific location of the anomaly sensor and the surrounding environment and building facilities.
7. The industrial interconnect and digital panorama based safety and environmental protection emergency system according to claim 1, wherein said initiating an emergency plan takes emergency action for the location of an accident, comprising:
based on a wireless communication technology, the emergency treatment module is connected with the waste gas treatment equipment, and when an early warning signal is received, the emergency treatment module sends an instruction to the waste gas treatment equipment to take emergency measures for the accident position; wherein the emergency measures include: stopping the production process, reducing the generation of waste gas, closing the exhaust port, warning the staff, and monitoring the data of the waste gas in real time for the staff to refer.
8. The industrial interconnection and digital panorama-based safety and environmental protection emergency system according to claim 1, wherein said utilizing visualization tools to visually display accident location and monitoring data comprises:
the visual data is obtained by preprocessing the correction data, wherein the preprocessing comprises the following steps: data cleaning, aggregation, calculation of derivative indexes and statistical analysis treatment; generating image data associating the visualization data with the chart based on the visualization data; based on the image data, displaying real-time monitoring data and early warning information through a chart; the method comprises the steps of,
based on the real-time monitoring data, a data curve is generated through a visualization tool, and the data change trend is reflected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311813974.7A CN117853295A (en) | 2023-12-25 | 2023-12-25 | Safety environmental protection emergency system based on industry interconnection and digital panorama |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311813974.7A CN117853295A (en) | 2023-12-25 | 2023-12-25 | Safety environmental protection emergency system based on industry interconnection and digital panorama |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117853295A true CN117853295A (en) | 2024-04-09 |
Family
ID=90531523
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311813974.7A Pending CN117853295A (en) | 2023-12-25 | 2023-12-25 | Safety environmental protection emergency system based on industry interconnection and digital panorama |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117853295A (en) |
-
2023
- 2023-12-25 CN CN202311813974.7A patent/CN117853295A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110850723B (en) | Fault diagnosis and positioning method based on transformer substation inspection robot system | |
| CN112291735B (en) | Visual chemical engineering intelligent monitoring system and method based on UWB | |
| CN112734694A (en) | Water quality monitoring method based on big data | |
| JP6610640B2 (en) | Position recognition method and system, and abnormality determination method and system | |
| CN115171361B (en) | Dangerous behavior intelligent detection and early warning method based on computer vision | |
| US20230162484A1 (en) | Apparatus and method for generating learning data for artificial intelligence model | |
| CN111753712A (en) | Method, system and equipment for monitoring safety of power production personnel | |
| CN114326741B (en) | Sea water desalination monitoring control system based on quadruped robot | |
| CN117761261A (en) | big data-based carbon emission monitoring system and method | |
| CN116678368B (en) | BIM technology-based intelligent acquisition method for assembled steel structure data | |
| CN110708519B (en) | Interactive monitoring method for industrial field environment | |
| CN116147697B (en) | Unattended monitoring method and system for aluminum hydroxide | |
| CN116311034A (en) | Robot inspection system based on contrast detection | |
| CN117853295A (en) | Safety environmental protection emergency system based on industry interconnection and digital panorama | |
| CN113516091B (en) | Method for identifying electric spark image of transformer substation | |
| CN115793673A (en) | Natural gas station robot inspection method and device based on VR technology | |
| CN115841730A (en) | Video monitoring system and abnormal event detection method | |
| CN116227849B (en) | Standardized management and early warning system for enterprise dangerous operation | |
| CN113591251B (en) | Equipment fault temperature analysis and diagnosis method | |
| JP3295482B2 (en) | Moving object detection method and apparatus | |
| CN113780224B (en) | Unmanned inspection method and system for transformer substation | |
| CN116449761B (en) | Intelligent pump station intelligent control system and method | |
| CN117057613B (en) | Chemical enterprise safety production management system and method | |
| CN117975372B (en) | Construction site safety detection system and method based on YOLOv and transducer encoder | |
| CN117830961B (en) | Environment-friendly equipment operation and maintenance behavior analysis method and system based on image analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |