CN117649061B - Multi-node networking electricity analysis method and system for environmental protection monitoring - Google Patents
Multi-node networking electricity analysis method and system for environmental protection monitoring Download PDFInfo
- Publication number
- CN117649061B CN117649061B CN202410122624.4A CN202410122624A CN117649061B CN 117649061 B CN117649061 B CN 117649061B CN 202410122624 A CN202410122624 A CN 202410122624A CN 117649061 B CN117649061 B CN 117649061B
- Authority
- CN
- China
- Prior art keywords
- monitoring
- frame
- monitoring node
- environmental protection
- dynamic
- 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.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 371
- 230000007613 environmental effect Effects 0.000 title claims abstract description 154
- 230000006855 networking Effects 0.000 title claims abstract description 52
- 238000004458 analytical method Methods 0.000 title claims abstract description 35
- 230000005611 electricity Effects 0.000 title claims abstract description 26
- 230000008859 change Effects 0.000 claims description 138
- 238000010586 diagram Methods 0.000 claims description 47
- 238000000034 method Methods 0.000 claims description 36
- 230000002159 abnormal effect Effects 0.000 claims description 21
- 238000012806 monitoring device Methods 0.000 claims description 20
- 238000013507 mapping Methods 0.000 claims description 18
- 238000011156 evaluation Methods 0.000 claims description 16
- 238000012163 sequencing technique Methods 0.000 claims description 13
- 238000006243 chemical reaction Methods 0.000 claims description 10
- 230000000737 periodic effect Effects 0.000 claims description 8
- 230000002035 prolonged effect Effects 0.000 claims description 8
- 238000012216 screening Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 description 7
- 238000010276 construction Methods 0.000 description 3
- 238000012935 Averaging Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000010865 sewage Substances 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Tourism & Hospitality (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computing Systems (AREA)
- Multimedia (AREA)
- Water Supply & Treatment (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Primary Health Care (AREA)
- Software Systems (AREA)
- Public Health (AREA)
- Medical Informatics (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Databases & Information Systems (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses a multi-node networking electricity analysis method and a system for environmental protection monitoring, which relate to the technical field of environmental protection monitoring equipment monitoring.
Description
Technical Field
The invention relates to the technical field of monitoring of environment-friendly monitoring equipment, in particular to a multi-node networking electricity analysis method and system for environment-friendly monitoring.
Background
With the acceleration of industrialization and the expansion of the production scale of factories, industrial emissions are one of the main sources of environmental pollution. The use of environmental monitoring equipment in industrial and production environments is becoming increasingly important in order to effectively monitor and mitigate the adverse environmental impact of industrial emissions. Since the pollution emission of individual factories is not strictly controlled in order to reduce the operation cost, the cheating phenomenon of the environmental protection monitoring equipment application exists, and the cheating phenomenon of the environmental protection monitoring equipment application possibly existing in a plurality of factories facing the same block cannot be tracked in real time for the sewage monitoring organization, an analysis method and an analysis system capable of integrally monitoring the environmental protection monitoring equipment applied in the factories belonging to the same block are needed.
Disclosure of Invention
The invention aims to provide an analysis method and an analysis system capable of integrally monitoring environmental protection monitoring equipment applied to a factory with the same area.
The invention discloses a multi-node networking electricity analysis method for environmental protection monitoring, which comprises the following steps:
acquiring the position of environmental protection monitoring equipment of each environmental protection monitoring enterprise on an environmental protection monitoring enterprise list, respectively constructing a monitoring node dynamic diagram aiming at each environmental protection monitoring enterprise, and mapping environmental protection monitoring nodes in the monitoring node dynamic diagram aiming at the position of the environmental protection monitoring equipment in the environmental protection monitoring enterprise;
Sequencing environmental protection monitoring enterprises, and constructing a multi-enterprise networking environmental protection monitoring dynamic diagram by combining the monitoring node dynamic diagrams based on the sequencing result;
Acquiring the power utilization state of each environment-friendly monitoring node at different time nodes, and carrying out mapping configuration in the dynamic graph of the monitoring node which belongs to based on the power utilization state of each environment-friendly monitoring node at different time nodes;
performing cycle analysis on each monitoring node dynamic graph to obtain a first time period, and marking the monitoring node dynamic graph in the first time period;
Acquiring first change characteristics of the monitoring node dynamic graph in a plurality of times of first time periods, and carrying out average conversion on the first change characteristics for a plurality of times to obtain second change characteristics;
configuring the multi-enterprise networking environment-friendly monitoring dynamic graph based on the second change characteristic of each monitoring node dynamic graph to obtain a first multi-enterprise networking environment-friendly monitoring dynamic graph;
Acquiring the power utilization state of each environment-friendly monitoring node in real time, and mapping the power utilization state of the environment-friendly monitoring node acquired in real time in the dynamic diagram of the monitoring node to which the power utilization state belongs to obtain the dynamic diagram of the real-time monitoring node;
And comparing and analyzing all the real-time monitoring node dynamic graphs with the first multi-enterprise networking environment-friendly monitoring dynamic graph to determine the overall application condition of the multi-enterprise environment-friendly monitoring equipment.
In some embodiments of the present disclosure, a method of mapping environmental monitoring nodes within a monitoring node dynamic graph for a location of environmental monitoring equipment within an environmental monitoring enterprise includes:
Acquiring an enterprise plan of an environment-friendly monitoring enterprise, and acquiring the relative position of environment-friendly monitoring equipment in the enterprise plan;
and positioning the center position of the enterprise plan, configuring a plurality of node direction lines in the monitoring node dynamic diagram based on the direction of each environmental protection monitoring device relative to the center position in the enterprise plan, and marking the distance on the corresponding node direction line based on the distance of each environmental protection monitoring device relative to the center position in the enterprise plan.
In some embodiments of the present disclosure, a method for performing a cycle analysis on a dynamic graph of each monitoring node includes:
Analyzing the change characteristics of the dynamic graph of the monitoring node based on a first preset time period, and if the change characteristics of the first preset time scale appear repeatedly, determining the time period before the change characteristics appear repeatedly in the first preset time period as the first time period;
if the variation characteristic of the first preset time scale does not appear repeatedly in the first preset time period, the first preset time period is prolonged until the variation characteristic of the first preset time scale appears repeatedly, and the prolonged first preset time period is regarded as the first time period.
In some embodiments of the present disclosure, a method for determining the repeated occurrence of a change feature of a first predetermined time scale includes:
Determining a scanning time interval when the change feature is analyzed based on the length of the first preset time scale;
Based on a scanning time interval for analyzing the change characteristics, carrying out frame-by-frame interception on the change characteristics of the dynamic graph of the monitoring node to obtain a plurality of frames needing attention;
and sequencing the intercepted frames to be focused according to a time sequence, and if the number of frames of the frames to be focused, which appear continuously, reaches a preset repeated judgment frame number and accords with the repeated judgment standard of the frames, determining that the change characteristic appears repeatedly.
In some embodiments of the present disclosure, a method for determining that a frame repetition determination criterion is met includes:
Analyzing the content of a single image frame of the environmental protection monitoring node in the power-on state in each image frame needing to be focused, and analyzing the total content of the environmental protection monitoring nodes in the power-on state in the image frames needing to be focused of the continuous preset repeated judgment frame number;
Determining the repetition degree of the frame to be focused of the continuous preset repetition judgment frame number and the previous frames to be focused based on the single frame content and the total content of the frames to be focused of the continuous preset repetition judgment frame number, and judging that the frames to be focused in the current continuous preset repetition judgment frame number accord with the frame repetition judgment standard if the repetition degree is larger than a preset value;
wherein, the expression for calculating the repetition degree is:
；
wherein, For the degree of repetition the number of the steps,For the first degree of importance the coefficients are converted,For the second degree of importance the coefficients are converted,For continuously presetting a difference degree identification function of single content of a frame to be focused and a frame to be focused of an nth frame within the repeated judgment frame, if the difference amount of the single content of the corresponding frame to be focused is larger than a preset value, the difference degree identification function outputs 0, if the difference amount of the single content of the corresponding frame to be focused is smaller than or equal to the preset value, the difference degree identification function outputs 1,The constant is adjusted for the first degree of importance,In order to continuously preset the difference between the total content of the picture frame to be focused and the previous picture frame to be focused in the repeated judgment frame number,The constant is adjusted for the second degree of importance.
In some embodiments of the present disclosure, a method for averaging a plurality of first variation characteristics includes:
Based on a preset time interval, carrying out frame interception on first change characteristics of the dynamic graph of the monitoring node to obtain a plurality of first change graph frames, and sequencing the first change graph frames according to a time sequence;
Comparing the first change image frames with different first change characteristics according to the corresponding relation of the equal time nodes, and screening out first change image frame groups with differences;
analyzing the first change image frame group with the difference, determining a difference environmental protection monitoring node showing the difference, and determining the configuration of the power utilization state of the difference environmental protection monitoring node based on the time occupation proportion of the difference environmental protection monitoring node in different power utilization states;
updating the first change image frame with the difference based on the configuration of the power utilization state of the difference environmental protection monitoring node;
and generating a second change characteristic of the dynamic graph of the monitoring node by combining the updated first change graph frame and the first change graph frame without difference.
In some embodiments of the present disclosure, a method for comparing and analyzing all real-time monitoring node dynamic graphs with a first multi-enterprise networking environmental protection monitoring dynamic graph includes:
Establishing a cycle time reference axis;
Correlating the real-time monitoring node dynamic graphs of the same time section on a periodic time reference axis, carrying out frame-dividing interception on each real-time monitoring node dynamic graph based on a preset time interval to obtain a plurality of second change graph frames, and corresponding the second change graph frames to the periodic time reference axis;
Correlating a plurality of first monitoring node dynamic images in the first multi-enterprise networking environment-friendly monitoring dynamic image with a period time reference axis, carrying out frame-dividing interception on each first monitoring node dynamic image based on a preset time interval to obtain a plurality of third change image frames, and corresponding the third change image frames with the period time reference axis;
Respectively comparing first difference characteristics of a second change image frame and a third change image frame which correspond to each other between the dynamic images of the single monitoring node in a preset monitoring time period;
analyzing second difference characteristics of all the second change image frames and the third change image frames in a preset monitoring time period;
based on the first and second difference features, an overall anomaly evaluation of the multi-enterprise environmental monitoring device is determined.
In some embodiments of the present disclosure, a method of determining a first difference feature and a second difference feature comprises:
Judging the non-conforming number of the corresponding second change image frames and third change image frames between the dynamic images of the single monitoring node, and judging the abnormal node number of the environment monitoring nodes with different electricity utilization states in the non-conforming image frame pairs;
And determining a first difference characteristic based on the number of non-conforming frames and the number of abnormal nodes between the dynamic graphs of the single monitoring node, and determining a second difference characteristic based on the first difference characteristic between the dynamic graphs of different monitoring nodes.
In some embodiments of the present disclosure, the expression for calculating the overall anomaly evaluation of a multi-enterprise environmental monitoring device is:
；
wherein, Is the overall abnormal evaluation value of the environmental protection monitoring equipment of multiple enterprises,For the abnormal evaluation of the conversion coefficient,For the q-th monitoring node dynamic graph weight coefficient,For the number of abnormal nodes of the nth frame of the q-th monitoring node dynamic graph,The coefficient is adjusted for the number of nodes of the q-th monitoring node dynamic graph,The coefficient is adjusted for the number of frames of the q-th monitoring node dynamic graph,For the number of frame inconsistencies of the q-th monitoring node dynamic graph,And adjusting a constant for the difference characteristic of the q-th monitoring node dynamic diagram.
In some embodiments of the present disclosure, a multi-node networking electrical analysis system for environmental monitoring is also disclosed, comprising:
a first module for acquiring the positions of the environmental protection monitoring devices of each environmental protection monitoring enterprise on the environmental protection monitoring enterprise list, respectively constructing a monitoring node dynamic diagram for each environmental protection monitoring enterprise, mapping environmental protection monitoring nodes in the monitoring node dynamic diagram for the positions of the environmental protection monitoring devices in the environmental protection monitoring enterprise, and sequencing the environmental protection monitoring enterprises, combining and constructing the monitoring node dynamic graphs based on the sequencing result to generate a multi-enterprise networking environment-friendly monitoring dynamic graph, acquiring the power utilization state of each environment-friendly monitoring node at different time nodes, and carrying out mapping configuration in the monitoring node dynamic graph based on the power utilization state of each environment-friendly monitoring node at different time nodes;
The second module is used for carrying out cycle analysis on each monitoring node dynamic graph to obtain a first time period, marking the monitoring node dynamic graph in the first time period, obtaining first change characteristics of the monitoring node dynamic graph in a plurality of times of the first time period, carrying out average conversion on the first change characteristics in a plurality of times of the first change characteristics to obtain second change characteristics, and configuring the multi-enterprise networking environment-friendly monitoring dynamic graph according to the second change characteristics of each monitoring node dynamic graph to obtain a first multi-enterprise networking environment-friendly monitoring dynamic graph;
The third module is used for acquiring the power utilization state of each environment-friendly monitoring node in real time, mapping the power utilization state of the environment-friendly monitoring node acquired in real time in the dynamic diagram of the monitoring node to which the power utilization state belongs, and obtaining the dynamic diagram of the real-time monitoring node;
And the fourth module is used for comparing and analyzing all the real-time monitoring node dynamic graphs with the first multi-enterprise networking environment-friendly monitoring dynamic graph to determine the overall application condition of the multi-enterprise environment-friendly monitoring equipment.
The invention discloses a multi-node networking electricity analysis method for environmental protection monitoring, which relates to the technical field of environmental protection monitoring equipment monitoring.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
FIG. 1 is a method step diagram of a multi-node networking electricity analysis method for environmental monitoring disclosed in an embodiment of the present invention;
fig. 2 is a schematic diagram of a multi-enterprise networking environment-friendly monitoring dynamic diagram disclosed in an embodiment of the invention.
Detailed Description
The technical scheme of the invention is further described below through the attached drawings and the embodiments.
The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments, it being understood that the preferred embodiments described herein are for illustrating and explaining the present invention only and are not to be construed as limiting the scope of the present invention, and that some insubstantial modifications and adaptations can be made by those skilled in the art in light of the following disclosure. In the present invention, unless explicitly specified and defined otherwise, technical terms used in the present invention should be construed in a general sense as understood by those skilled in the art to which the present invention pertains.
The embodiment of the invention discloses a multi-node networking electricity analysis method for environmental protection monitoring, referring to fig. 1 and 2, comprising the following steps:
Step S100, the position of environmental protection monitoring equipment of each environmental protection monitoring enterprise on an environmental protection monitoring enterprise list is obtained, a monitoring node dynamic diagram is respectively built for each environmental protection monitoring enterprise, and environmental protection monitoring nodes are mapped in the monitoring node dynamic diagram according to the position of the environmental protection monitoring equipment in the environmental protection monitoring enterprise.
In the above steps, the construction of the monitoring node dynamic graph may be referred to a planning graph of a park, or may refer to satellite geographic information of a GIS system, where the constructed monitoring node dynamic graph is used for mapping an on condition of an environmental monitoring device in an environmental monitoring enterprise, for example, when the environmental monitoring device in the environmental monitoring enterprise is on in a specific time period, the state of the monitoring node dynamic graph is dynamically transformed into an on state, where the state change corresponding to each environmental monitoring node in the construction of the monitoring node dynamic graph may be associated with a transformation of a boolean element in LABVIEW software, where drawing software for a drawing frame applied to the dynamic transformation in the monitoring node dynamic graph is not limited, and may be conventional computer drawing software, photoshop drawing software, or the like.
In the step, the position information of monitoring equipment of each environmental protection monitoring enterprise is acquired through an enterprise list; this includes the geographical coordinates of the device for subsequent construction of the monitoring node dynamic map.
And step S200, sorting the environmental protection monitoring enterprises, and constructing and combining the monitoring node dynamic graphs based on the sorting result to generate a multi-enterprise networking environmental protection monitoring dynamic graph.
In the above steps, the method for ordering the environmental protection monitoring enterprises may be set by the monitoring staff of the environmental protection equipment in the park, and the ordering logic may be the spatial relative position of the environmental protection monitoring enterprises, the importance of the environmental protection monitoring enterprises or the credit evaluation of the environmental protection monitoring enterprises on the application behavior of the environmental protection monitoring equipment.
In the step, the environmental monitoring enterprises are ordered, and then the ordered enterprises are combined according to a certain standard to construct a multi-enterprise networking environmental monitoring dynamic diagram; the system is enabled to process monitoring information of a plurality of enterprises more orderly.
Step S300, the electricity utilization state of each environment-friendly monitoring node at different time nodes is obtained, and mapping configuration is carried out in the dynamic diagram of the monitoring node which belongs to based on the electricity utilization state of each environment-friendly monitoring node at different time nodes.
In this step, the power utilization state of each monitoring node at different time points is acquired, and the data can be real-time or periodically acquired; these power usage states will be used for subsequent configuration and analysis.
Step S400, carrying out cycle analysis on each monitoring node dynamic graph to obtain a first time period, and marking the monitoring node dynamic graph in the first time period;
in this step, a cyclic period analysis is performed on each monitoring node dynamic graph, a first time period is obtained, and a marking is performed on the monitoring node dynamic graph, which is used for expressing the periodic behavior of the monitoring node.
Step S500, obtaining first change characteristics of the monitoring node dynamic diagram in a plurality of first time periods, and carrying out average conversion on the first change characteristics for a plurality of times to obtain second change characteristics.
In this step, the first variation features are averaged to reduce the influence of the variability between the first variation features on the post-information comparison process.
Step S600, based on the second change characteristic of each monitoring node dynamic diagram, configuring the multi-enterprise networking environment-friendly monitoring dynamic diagram to obtain a first multi-enterprise networking environment-friendly monitoring dynamic diagram.
And step S700, acquiring the power utilization state of each environment-friendly monitoring node in real time, and mapping the power utilization state of the environment-friendly monitoring node acquired in real time in the dynamic diagram of the monitoring node to which the power utilization state belongs to obtain the dynamic diagram of the real-time monitoring node.
In this step, the power consumption state information of each monitoring node is acquired in real time to reflect the real-time data of the current state.
And step S800, comparing and analyzing all the real-time monitoring node dynamic graphs with the first multi-enterprise networking environment-friendly monitoring dynamic graph to determine the overall application condition of the multi-enterprise environment-friendly monitoring equipment.
In this step, the real-time monitoring node dynamic diagram is compared with the first multi-enterprise networking environmental protection monitoring dynamic diagram to determine the overall application condition of the multi-enterprise environmental protection monitoring equipment, and the cheating condition of the multi-enterprise environmental protection monitoring equipment application is intuitively expressed.
In some embodiments of the present disclosure, referring to fig. 2, a method for mapping environmental monitoring nodes within a monitoring node dynamic graph for a location of environmental monitoring equipment within an environmental monitoring enterprise includes:
step S101, an enterprise plan of an environment-friendly monitoring enterprise is obtained, and the relative position of environment-friendly monitoring equipment in the enterprise plan is obtained.
Step S102, the center position of the enterprise plan is positioned, a plurality of node direction lines are configured in the monitoring node dynamic diagram based on the direction of each environmental protection monitoring device relative to the center position in the enterprise plan, and the distance is marked on the corresponding node direction line based on the distance of each environmental protection monitoring device relative to the center position in the enterprise plan.
In this step, the method for locating the center position of the enterprise plan is that after the enterprise plan is determined, the edges of the enterprise plan are determined, and a point in the intersection area of all the edge vertical lines is regarded as the center position of the enterprise plan, and the method for locating the center position of the enterprise plan can also be that the positions of different environmental monitoring nodes are determined, and the center positions among the different environmental monitoring nodes are selected as the center position of the enterprise plan.
In some embodiments of the present disclosure, a method for performing a cycle analysis on a dynamic graph of each monitoring node includes:
step S401, analyzing the change characteristics of the dynamic diagram of the monitoring node based on a first preset time period, and if the change characteristics of the first preset time scale appear repeatedly, determining the time period before the change characteristics appear repeatedly in the first preset time period as the first time period;
Step S402, if the variation characteristic of the first preset time scale does not appear repeatedly in the first preset time period, the first preset time period is prolonged until the variation characteristic of the first preset time scale appears repeatedly, and the prolonged first preset time period is regarded as the first time period.
In the two steps, the change characteristics of the dynamic graph of the monitoring node are that the dynamic graph of different nodes changes in the dynamic change process of the dynamic graph frame of different nodes, for example, in the time node a, all the environment-friendly monitoring nodes in the dynamic graph frame are in an open state, in the time node b, all the specific environment-friendly monitoring nodes in the dynamic graph frame are in an open state, all the other specific environment-friendly monitoring nodes are in a closed state, in the time node c, all the environment-friendly monitoring nodes in the dynamic graph frame are in a closed state, and in the change process of the continuous time node, the change of the dynamic graph frame is the change characteristics of the dynamic graph of the monitoring node.
The first preset time period is a time scale for distinguishing a recognition standard of repeated occurrence of the change characteristics of the dynamic diagram of the monitoring node, the change characteristics lower than the first preset time scale are repeated, the change characteristics possibly coincide to a small extent in the change process of the dynamic diagram of the monitoring node, and the repeated occurrence of the change characteristics of the dynamic diagram of the monitoring node cannot be recognized.
In the above steps, a suitable time period, i.e. a first time period, is determined by periodically analyzing the change characteristics in the dynamic diagram of the monitoring node. The system can be used for identifying the periodic electricity utilization mode of the monitoring node, further performing deeper analysis, and finding a proper time scale by observing the change characteristics in the first preset time period so as to more accurately understand the electricity utilization behavior of the monitoring node.
In some embodiments of the present disclosure, a method for determining the repeated occurrence of a change feature of a first predetermined time scale includes:
in step S4010, a scan time interval for analyzing the change feature is determined based on the length of the first predetermined time scale.
In the above step, in order to reduce the system resources consumed in the repeated judging process of the dynamic graph change characteristics of the monitoring node, without scanning and analyzing each dynamic graph frame of the dynamic graph of the monitoring node, the dynamic graph frames may be scanned and analyzed in a regular sampling manner, if the first preset time scale is longer, which means that the scanning time interval can be relatively lengthened, the longer the first preset time scale is, the longer the scanning time interval for analyzing the change characteristics is.
Step S4011, based on the scanning time interval for analyzing the change characteristics, frame-dividing interception is carried out on the change characteristics of the dynamic graph of the monitoring node, and a plurality of frames needing attention are obtained.
Step S4012, the intercepted frames to be focused are ordered according to time sequence, if the frames of the frames to be focused continuously reach the preset repeated judgment frame number and accord with the repeated judgment standard of the frames, the changing characteristics are determined to repeatedly appear.
In some embodiments of the present disclosure, a method for determining that a frame repetition determination criterion is met includes:
step S40120 is to analyze the content of a single frame of the environmental protection monitoring nodes in the power-on state in each frame of interest, and analyze the total content of the environmental protection monitoring nodes in the power-on state in the frames of interest of continuously preset repeated judgment frames.
Step S40121, based on the single frame content and the total content of the frames to be focused of continuously preset repeated frames, determining the repetition degree of the frames to be focused of continuously preset repeated judgment frames and the previous frames to be focused, and judging that the frames to be focused in the current continuously preset repeated judgment frames meet the frame repeated judgment standard if the repetition degree is larger than a preset value.
In the above steps, the degree of repetition between frames of interest is determined by analyzing the content of a single frame and the total content. If the repetition degree meets the preset value, a plurality of frames to be focused in the continuous preset repetition judgment frame number are determined to meet the frame repetition judgment standard. This helps the system determine if the change feature is recurring within a time scale, thereby determining the first time period.
Wherein, the expression for calculating the repetition degree is:
。
wherein, For the degree of repetition the number of the steps,For the first degree of importance the coefficients are converted,For the second degree of importance the coefficients are converted,For continuously presetting a difference degree identification function of single content of a frame to be focused and a frame to be focused of an nth frame within the repeated judgment frame, if the difference amount of the single content of the corresponding frame to be focused is larger than a preset value, the difference degree identification function outputs 0, if the difference amount of the single content of the corresponding frame to be focused is smaller than or equal to the preset value, the difference degree identification function outputs 1,The constant is adjusted for the first degree of importance,In order to continuously preset the difference between the total content of the picture frame to be focused and the previous picture frame to be focused in the repeated judgment frame number,The constant is adjusted for the second degree of importance.
In some embodiments of the present disclosure, a method for averaging a plurality of first variation characteristics includes:
Step S501, based on a preset time interval, frame-cutting is carried out on first change features of the dynamic graph of the monitoring node to obtain a plurality of first change graph frames, and the first change graph frames are ordered according to a time sequence.
Step S502, comparing the first change frames with different first change characteristics according to the corresponding relation of the equivalent time nodes, and screening out the first change frame groups with differences.
Step S503, analyzing the first change image frame group with the difference, determining a difference environmental protection monitoring node showing the difference, and determining the configuration of the power utilization state of the difference environmental protection monitoring node based on the time occupation proportion of the difference environmental protection monitoring node in different power utilization states.
In this step, since the electricity consumption states of the environmental protection monitoring device are different at different time nodes, that is, the electricity consumption power is different at different time nodes, in order to more intuitively show the electricity consumption states of the different environmental protection monitoring nodes in the dynamic diagram of the monitoring nodes, the average value of the time occupation proportion of the different environmental protection monitoring nodes in the different electricity consumption states in the changing process can be calculated to configure the electricity consumption states of the different environmental protection monitoring nodes.
Step S504, updating the first change image frame with the difference based on the configuration of the electricity utilization state of the difference environmental protection monitoring node.
Step S505, a second change feature of the monitoring node dynamic graph is generated by combining the updated first change graph frame and the first change graph frame without difference.
In some embodiments of the present disclosure, a method for comparing and analyzing all real-time monitoring node dynamic graphs with a first multi-enterprise networking environmental protection monitoring dynamic graph includes:
in step S801, a cycle time reference axis is established.
Step S802, associating the real-time monitoring node dynamic graphs of the same time zone on a periodic time reference axis, carrying out frame-dividing interception on each real-time monitoring node dynamic graph based on a preset time interval to obtain a plurality of second change graph frames, and corresponding the second change graph frames to the periodic time reference axis.
Step 803, associating the plurality of first monitoring node dynamic graphs in the first multi-enterprise networking environment-friendly monitoring dynamic graph with the cycle time reference axis, and based on a preset time interval, performing frame-division interception on each first monitoring node dynamic graph to obtain a plurality of third variation graph frames, and corresponding the third variation graph frames with the cycle time reference axis.
Step S804, respectively comparing the first difference features of the second change map frame and the third change map frame corresponding to each other in the preset monitoring time period.
Step S805, analyzing second difference features of all the second change map frames and the third change map frames in the preset monitoring period.
Step S806, determining overall abnormal evaluation of the environmental protection monitoring equipment of the multiple enterprises based on the first difference characteristic and the second difference characteristic.
In the above step, the data corresponding to the first difference features of the second change image frame and the third change image frame in the preset monitoring time period mainly include the number of non-conforming image frames and the number of abnormal nodes, and the second difference features are the accumulated performances of the first difference features of different monitoring node dynamic images in the same multi-enterprise networking environment-friendly monitoring dynamic image, where the relationship between the first difference features and the second difference features and the overall abnormal evaluation is that the larger the number of non-conforming image frames and the number of abnormal nodes in the first difference features, the larger the forward expansion influence of the first difference features and the second difference features on the corresponding values of the overall abnormal evaluation.
In some embodiments of the present disclosure, a method of determining a first difference feature and a second difference feature comprises:
Step S8040, judging the non-conforming number of the corresponding second change image frames and third change image frames between the dynamic images of the single monitoring node, and judging the abnormal node number of the environment monitoring nodes with different power utilization states in the non-conforming image frame pairs.
Step S8041, determining a first difference characteristic based on the number of non-conforming frames and the number of abnormal nodes between the dynamic graphs of the single monitoring node, and determining a second difference characteristic based on the first difference characteristic between the dynamic graphs of different monitoring nodes.
In some embodiments of the present disclosure, the expression for calculating the overall anomaly evaluation of a multi-enterprise environmental monitoring device is:
。
the expression of the overall anomaly evaluation may also be:
。
wherein, Is the overall abnormal evaluation value of the environmental protection monitoring equipment of multiple enterprises,For the abnormal evaluation of the conversion coefficient,For the q-th monitoring node dynamic graph weight coefficient,For the number of abnormal nodes of the nth frame of the q-th monitoring node dynamic graph,The coefficient is adjusted for the number of nodes of the q-th monitoring node dynamic graph,The coefficient is adjusted for the number of frames of the q-th monitoring node dynamic graph,For the number of frame inconsistencies of the q-th monitoring node dynamic graph,And adjusting a constant for the difference characteristic of the q-th monitoring node dynamic diagram.
In some embodiments of the present disclosure, a multi-node networking electrical analysis system for environmental monitoring is also disclosed, comprising: the first module, the second module, the third module and the fourth module.
The first module is configured to obtain a location of an environmental protection monitoring device of each environmental protection monitoring enterprise on an environmental protection monitoring enterprise list, respectively construct a monitoring node dynamic graph for each environmental protection monitoring enterprise, map environmental protection monitoring nodes in the monitoring node dynamic graph for the location of the environmental protection monitoring device in the environmental protection monitoring enterprise, sort the environmental protection monitoring enterprises, combine the monitoring node dynamic graphs based on the sorting result to construct and generate a multi-enterprise networking environmental protection monitoring dynamic graph, obtain a power consumption state of each environmental protection monitoring node at different time nodes, and map and configure the monitoring node dynamic graph based on the power consumption state of each environmental protection monitoring node at different time nodes.
The second module is configured to perform cycle analysis on each monitoring node dynamic graph to obtain a first time period, mark the monitoring node dynamic graph in the first time period, obtain first change features of the monitoring node dynamic graph in a plurality of times of the first time period, perform average conversion on the first change features in a plurality of times of the first change features to obtain second change features, and configure the multi-enterprise networking environmental protection monitoring dynamic graph according to the second change features of each monitoring node dynamic graph to obtain a first multi-enterprise networking environmental protection monitoring dynamic graph;
The third module is configured to obtain the power consumption state of each environmental protection monitoring node in real time, and map the power consumption state of the environmental protection monitoring node obtained in real time in the dynamic graph of the monitoring node to which the power consumption state belongs, so as to obtain the dynamic graph of the real-time monitoring node.
And the fourth module is used for comparing and analyzing all the real-time monitoring node dynamic graphs with the first multi-enterprise networking environment-friendly monitoring dynamic graph to determine the overall application condition of the multi-enterprise environment-friendly monitoring equipment.
From the above description of the embodiments, it will be clear to those skilled in the art that the present invention may be implemented in hardware, or may be implemented by means of software plus necessary general hardware platforms. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective implementation scenario of the present invention.
The invention discloses a multi-node networking electricity analysis method for environmental protection monitoring, which relates to the technical field of environmental protection monitoring equipment monitoring.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting it, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that: the technical scheme of the invention can be modified or replaced by the same, and the modified technical scheme cannot deviate from the spirit and scope of the technical scheme of the invention.
Claims (7)
1. The multi-node networking electricity analysis method for environmental protection monitoring is characterized by comprising the following steps of:
acquiring the position of environmental protection monitoring equipment of each environmental protection monitoring enterprise on an environmental protection monitoring enterprise list, respectively constructing a monitoring node dynamic diagram aiming at each environmental protection monitoring enterprise, and mapping environmental protection monitoring nodes in the monitoring node dynamic diagram aiming at the position of the environmental protection monitoring equipment in the environmental protection monitoring enterprise;
Sequencing environmental protection monitoring enterprises, and constructing a multi-enterprise networking environmental protection monitoring dynamic diagram by combining the monitoring node dynamic diagrams based on the sequencing result;
Acquiring the power utilization state of each environment-friendly monitoring node at different time nodes, and carrying out mapping configuration in the dynamic graph of the monitoring node which belongs to based on the power utilization state of each environment-friendly monitoring node at different time nodes;
performing cycle analysis on each monitoring node dynamic graph to obtain a first time period, and marking the monitoring node dynamic graph in the first time period;
Acquiring first change characteristics of the monitoring node dynamic graph in a plurality of times of first time periods, and carrying out average conversion on the first change characteristics for a plurality of times to obtain second change characteristics;
configuring the multi-enterprise networking environment-friendly monitoring dynamic graph based on the second change characteristic of each monitoring node dynamic graph to obtain a first multi-enterprise networking environment-friendly monitoring dynamic graph;
Acquiring the power utilization state of each environment-friendly monitoring node in real time, and mapping the power utilization state of the environment-friendly monitoring node acquired in real time in the dynamic diagram of the monitoring node to which the power utilization state belongs to obtain the dynamic diagram of the real-time monitoring node;
Comparing and analyzing all the real-time monitoring node dynamic graphs with the first multi-enterprise networking environment-friendly monitoring dynamic graph to determine the overall application condition of the multi-enterprise environment-friendly monitoring equipment;
The method for carrying out cycle analysis on each monitoring node dynamic graph comprises the following steps:
Analyzing the change characteristics of the dynamic graph of the monitoring node based on a first preset time period, and if the change characteristics of the first preset time scale appear repeatedly, determining the time period before the change characteristics appear repeatedly in the first preset time period as the first time period;
If the variation characteristic of the first preset time scale does not appear repeatedly in the first preset time period, the first preset time period is prolonged until the variation characteristic of the first preset time scale appears repeatedly, and the prolonged first preset time period is regarded as the first time period;
The method for judging the repeated occurrence of the change characteristic of the first preset time scale comprises the following steps:
Determining a scanning time interval when the change feature is analyzed based on the length of the first preset time scale;
Based on a scanning time interval for analyzing the change characteristics, carrying out frame-by-frame interception on the change characteristics of the dynamic graph of the monitoring node to obtain a plurality of frames needing attention;
Sequencing the intercepted frames to be focused according to a time sequence, and if the number of frames of the frames to be focused, which appear continuously, reaches a preset repeated judgment frame number and accords with the repeated judgment standard of the frames, determining that the change characteristic appears repeatedly;
The method for judging the coincidence of the frame repetition judgment standard comprises the following steps:
Analyzing the content of a single image frame of the environmental protection monitoring node in the power-on state in each image frame needing to be focused, and analyzing the total content of the environmental protection monitoring nodes in the power-on state in the image frames needing to be focused of the continuous preset repeated judgment frame number;
Determining the repetition degree of the frame to be focused of the continuous preset repetition judgment frame number and the previous frames to be focused based on the single frame content and the total content of the frames to be focused of the continuous preset repetition judgment frame number, and judging that the frames to be focused in the current continuous preset repetition judgment frame number accord with the frame repetition judgment standard if the repetition degree is larger than a preset value;
wherein, the expression for calculating the repetition degree is:
；
wherein, For the degree of repetition the number of the steps,For the first degree of importance the coefficients are converted,For the second degree of importance the coefficients are converted,For continuously presetting a difference degree identification function of single content of a frame to be focused and a frame to be focused of an nth frame within the repeated judgment frame, if the difference amount of the single content of the corresponding frame to be focused is larger than a preset value, the difference degree identification function outputs 0, if the difference amount of the single content of the corresponding frame to be focused is smaller than or equal to the preset value, the difference degree identification function outputs 1,The constant is adjusted for the first degree of importance,In order to continuously preset the difference between the total content of the picture frame to be focused and the previous picture frame to be focused in the repeated judgment frame number,The constant is adjusted for the second degree of importance.
2. The multi-node networking electricity analysis method for environmental protection monitoring according to claim 1, wherein the method for mapping environmental protection monitoring nodes in the monitoring node dynamic graph for the positions of environmental protection monitoring devices in an environmental protection monitoring enterprise comprises:
Acquiring an enterprise plan of an environment-friendly monitoring enterprise, and acquiring the relative position of environment-friendly monitoring equipment in the enterprise plan;
and positioning the center position of the enterprise plan, configuring a plurality of node direction lines in the monitoring node dynamic diagram based on the direction of each environmental protection monitoring device relative to the center position in the enterprise plan, and marking the distance on the corresponding node direction line based on the distance of each environmental protection monitoring device relative to the center position in the enterprise plan.
3. The multi-node networking electricity analysis method for environmental monitoring of claim 1, wherein the method for performing average conversion on the first change characteristics of the plurality of times comprises:
Based on a preset time interval, carrying out frame interception on first change characteristics of the dynamic graph of the monitoring node to obtain a plurality of first change graph frames, and sequencing the first change graph frames according to a time sequence;
Comparing the first change image frames with different first change characteristics according to the corresponding relation of the equal time nodes, and screening out first change image frame groups with differences;
analyzing the first change image frame group with the difference, determining a difference environmental protection monitoring node showing the difference, and determining the configuration of the power utilization state of the difference environmental protection monitoring node based on the time occupation proportion of the difference environmental protection monitoring node in different power utilization states;
updating the first change image frame with the difference based on the configuration of the power utilization state of the difference environmental protection monitoring node;
and generating a second change characteristic of the dynamic graph of the monitoring node by combining the updated first change graph frame and the first change graph frame without difference.
4. The multi-node networking electricity analysis method for environmental protection monitoring according to claim 1, wherein the method for comparing and analyzing all real-time monitoring node dynamic graphs with the first multi-enterprise networking environmental protection monitoring dynamic graph comprises the following steps:
Establishing a cycle time reference axis;
Correlating the real-time monitoring node dynamic graphs of the same time section on a periodic time reference axis, carrying out frame-dividing interception on each real-time monitoring node dynamic graph based on a preset time interval to obtain a plurality of second change graph frames, and corresponding the second change graph frames to the periodic time reference axis;
Correlating a plurality of first monitoring node dynamic images in the first multi-enterprise networking environment-friendly monitoring dynamic image with a period time reference axis, carrying out frame-dividing interception on each first monitoring node dynamic image based on a preset time interval to obtain a plurality of third change image frames, and corresponding the third change image frames with the period time reference axis;
Respectively comparing first difference characteristics of a second change image frame and a third change image frame which correspond to each other between the dynamic images of the single monitoring node in a preset monitoring time period;
analyzing second difference characteristics of all the second change image frames and the third change image frames in a preset monitoring time period;
based on the first and second difference features, an overall anomaly evaluation of the multi-enterprise environmental monitoring device is determined.
5. The multi-node networking power consumption analysis method for environmental monitoring of claim 4, wherein the method of determining the first difference feature and the second difference feature comprises:
Judging the non-conforming number of the corresponding second change image frames and third change image frames between the dynamic images of the single monitoring node, and judging the abnormal node number of the environment monitoring nodes with different electricity utilization states in the non-conforming image frame pairs;
And determining a first difference characteristic based on the number of non-conforming frames and the number of abnormal nodes between the dynamic graphs of the single monitoring node, and determining a second difference characteristic based on the first difference characteristic between the dynamic graphs of different monitoring nodes.
6. The multi-node networking electricity analysis method for environmental monitoring according to claim 5, wherein the expression for calculating the overall abnormal evaluation of the environmental monitoring equipment of multiple enterprises is:
；
wherein, Is the overall abnormal evaluation value of the environmental protection monitoring equipment of multiple enterprises,For the abnormal evaluation of the conversion coefficient,For the q-th monitoring node dynamic graph weight coefficient,For the number of abnormal nodes of the nth frame of the q-th monitoring node dynamic graph,The coefficient is adjusted for the number of nodes of the q-th monitoring node dynamic graph,The coefficient is adjusted for the number of frames of the q-th monitoring node dynamic graph,For the number of frame inconsistencies of the q-th monitoring node dynamic graph,And adjusting a constant for the difference characteristic of the q-th monitoring node dynamic diagram.
7. A multi-node networking power consumption analysis system for environmental monitoring, comprising:
a first module for acquiring the positions of the environmental protection monitoring devices of each environmental protection monitoring enterprise on the environmental protection monitoring enterprise list, respectively constructing a monitoring node dynamic diagram for each environmental protection monitoring enterprise, mapping environmental protection monitoring nodes in the monitoring node dynamic diagram for the positions of the environmental protection monitoring devices in the environmental protection monitoring enterprise, and sequencing the environmental protection monitoring enterprises, combining and constructing the monitoring node dynamic graphs based on the sequencing result to generate a multi-enterprise networking environment-friendly monitoring dynamic graph, acquiring the power utilization state of each environment-friendly monitoring node at different time nodes, and carrying out mapping configuration in the monitoring node dynamic graph based on the power utilization state of each environment-friendly monitoring node at different time nodes;
The second module is used for carrying out cycle analysis on each monitoring node dynamic graph to obtain a first time period, marking the monitoring node dynamic graph in the first time period, obtaining first change characteristics of the monitoring node dynamic graph in a plurality of times of the first time period, carrying out average conversion on the first change characteristics in a plurality of times of the first change characteristics to obtain second change characteristics, and configuring the multi-enterprise networking environment-friendly monitoring dynamic graph according to the second change characteristics of each monitoring node dynamic graph to obtain a first multi-enterprise networking environment-friendly monitoring dynamic graph;
The third module is used for acquiring the power utilization state of each environment-friendly monitoring node in real time, mapping the power utilization state of the environment-friendly monitoring node acquired in real time in the dynamic diagram of the monitoring node to which the power utilization state belongs, and obtaining the dynamic diagram of the real-time monitoring node;
The fourth module is used for comparing and analyzing all the real-time monitoring node dynamic graphs with the first multi-enterprise networking environment-friendly monitoring dynamic graph to determine the overall application condition of the multi-enterprise environment-friendly monitoring equipment;
The method for carrying out cycle analysis on each monitoring node dynamic graph comprises the following steps:
Analyzing the change characteristics of the dynamic graph of the monitoring node based on a first preset time period, and if the change characteristics of the first preset time scale appear repeatedly, determining the time period before the change characteristics appear repeatedly in the first preset time period as the first time period;
If the variation characteristic of the first preset time scale does not appear repeatedly in the first preset time period, the first preset time period is prolonged until the variation characteristic of the first preset time scale appears repeatedly, and the prolonged first preset time period is regarded as the first time period;
The method for judging the repeated occurrence of the change characteristic of the first preset time scale comprises the following steps:
Determining a scanning time interval when the change feature is analyzed based on the length of the first preset time scale;
Based on a scanning time interval for analyzing the change characteristics, carrying out frame-by-frame interception on the change characteristics of the dynamic graph of the monitoring node to obtain a plurality of frames needing attention;
Sequencing the intercepted frames to be focused according to a time sequence, and if the number of frames of the frames to be focused, which appear continuously, reaches a preset repeated judgment frame number and accords with the repeated judgment standard of the frames, determining that the change characteristic appears repeatedly;
The method for judging the coincidence of the frame repetition judgment standard comprises the following steps:
Analyzing the content of a single image frame of the environmental protection monitoring node in the power-on state in each image frame needing to be focused, and analyzing the total content of the environmental protection monitoring nodes in the power-on state in the image frames needing to be focused of the continuous preset repeated judgment frame number;
Determining the repetition degree of the frame to be focused of the continuous preset repetition judgment frame number and the previous frames to be focused based on the single frame content and the total content of the frames to be focused of the continuous preset repetition judgment frame number, and judging that the frames to be focused in the current continuous preset repetition judgment frame number accord with the frame repetition judgment standard if the repetition degree is larger than a preset value;
wherein, the expression for calculating the repetition degree is:
；
wherein, For the degree of repetition the number of the steps,For the first degree of importance the coefficients are converted,For the second degree of importance the coefficients are converted,For continuously presetting a difference degree identification function of single content of a frame to be focused and a frame to be focused of an nth frame within the repeated judgment frame, if the difference amount of the single content of the corresponding frame to be focused is larger than a preset value, the difference degree identification function outputs 0, if the difference amount of the single content of the corresponding frame to be focused is smaller than or equal to the preset value, the difference degree identification function outputs 1,The constant is adjusted for the first degree of importance,In order to continuously preset the difference between the total content of the picture frame to be focused and the previous picture frame to be focused in the repeated judgment frame number,The constant is adjusted for the second degree of importance.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410122624.4A CN117649061B (en) | 2024-01-30 | 2024-01-30 | Multi-node networking electricity analysis method and system for environmental protection monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410122624.4A CN117649061B (en) | 2024-01-30 | 2024-01-30 | Multi-node networking electricity analysis method and system for environmental protection monitoring |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117649061A CN117649061A (en) | 2024-03-05 |
| CN117649061B true CN117649061B (en) | 2024-04-26 |
Family
ID=90046422
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410122624.4A Active CN117649061B (en) | 2024-01-30 | 2024-01-30 | Multi-node networking electricity analysis method and system for environmental protection monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117649061B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011211556A (en) * | 2010-03-30 | 2011-10-20 | Nippon Telegr & Teleph Corp <Ntt> | Device and method for generating image, and program |
| JP2012065095A (en) * | 2010-09-15 | 2012-03-29 | Nippon Soken Inc | Communication system, transceiver, and node |
| WO2017025004A1 (en) * | 2015-08-07 | 2017-02-16 | 中兴通讯股份有限公司 | Method and device for competing for access |
| CN110490173A (en) * | 2019-08-28 | 2019-11-22 | 深圳市数字星河科技有限公司 | A kind of intelligent behaviour scoring system based on 3D body-sensing model |
| CN111639134A (en) * | 2020-05-30 | 2020-09-08 | 陈议尊 | Industrial link supervision method and system based on block chain |
| CN112990712A (en) * | 2021-03-19 | 2021-06-18 | 成都青云之上信息科技有限公司 | Enterprise production and operation analysis method and system based on power consumption monitoring |
| CN113095953A (en) * | 2021-03-29 | 2021-07-09 | 福建亿力优能电力科技有限公司 | Enterprise environment-friendly monitoring method based on electricity consumption data |
| CN113298422A (en) * | 2021-06-16 | 2021-08-24 | 福建亿力优能电力科技有限公司 | Pollution source enterprise illegal production monitoring method based on electricity consumption data |
| CN114003010A (en) * | 2021-10-30 | 2022-02-01 | 宝璟科技(深圳)有限公司 | Environmental protection equipment monitoring system |
| CN116895098A (en) * | 2023-07-20 | 2023-10-17 | 桂林电子科技大学 | Video human body action recognition system and method based on deep learning and privacy protection |
| CN116938513A (en) * | 2023-05-24 | 2023-10-24 | 华能中电威海风力发电有限公司 | Key management method and system applied to security management platform |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9300834B2 (en) * | 2009-05-20 | 2016-03-29 | Dacuda Ag | Image processing for handheld scanner |
| DE102022201347A1 (en) * | 2022-02-09 | 2023-08-10 | Siemens Healthcare Gmbh | Method and system for the automated determination of examination results in an image sequence |
-
2024
- 2024-01-30 CN CN202410122624.4A patent/CN117649061B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011211556A (en) * | 2010-03-30 | 2011-10-20 | Nippon Telegr & Teleph Corp <Ntt> | Device and method for generating image, and program |
| JP2012065095A (en) * | 2010-09-15 | 2012-03-29 | Nippon Soken Inc | Communication system, transceiver, and node |
| WO2017025004A1 (en) * | 2015-08-07 | 2017-02-16 | 中兴通讯股份有限公司 | Method and device for competing for access |
| CN110490173A (en) * | 2019-08-28 | 2019-11-22 | 深圳市数字星河科技有限公司 | A kind of intelligent behaviour scoring system based on 3D body-sensing model |
| CN111639134A (en) * | 2020-05-30 | 2020-09-08 | 陈议尊 | Industrial link supervision method and system based on block chain |
| CN112990712A (en) * | 2021-03-19 | 2021-06-18 | 成都青云之上信息科技有限公司 | Enterprise production and operation analysis method and system based on power consumption monitoring |
| CN113095953A (en) * | 2021-03-29 | 2021-07-09 | 福建亿力优能电力科技有限公司 | Enterprise environment-friendly monitoring method based on electricity consumption data |
| CN113298422A (en) * | 2021-06-16 | 2021-08-24 | 福建亿力优能电力科技有限公司 | Pollution source enterprise illegal production monitoring method based on electricity consumption data |
| CN114003010A (en) * | 2021-10-30 | 2022-02-01 | 宝璟科技(深圳)有限公司 | Environmental protection equipment monitoring system |
| CN116938513A (en) * | 2023-05-24 | 2023-10-24 | 华能中电威海风力发电有限公司 | Key management method and system applied to security management platform |
| CN116895098A (en) * | 2023-07-20 | 2023-10-17 | 桂林电子科技大学 | Video human body action recognition system and method based on deep learning and privacy protection |
Non-Patent Citations (2)
| Title |
|---|
| "P-ARQ: Controllable PLL ARQ method for wireless low power communication";Hyosun Hwang等;《2013 IEEE 10th Consumer Communications and Networking Conference (CCNC)》;20130328;第1-4页 * |
| "电视视频图像帧的检测与识别研究";盖怀存;《电视指南》;20171231;第256页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117649061A (en) | 2024-03-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107103754B (en) | Road traffic condition prediction method and system | |
| Wang et al. | On credibility estimation tradeoffs in assured social sensing | |
| Dong et al. | An Intrusion Detection Model for Wireless Sensor Network Based on Information Gain Ratio and Bagging Algorithm. | |
| CN113157800B (en) | Identification method for discovering dynamic target in air in real time | |
| CN115358332A (en) | Atmospheric pollution tracing method for multi-source data | |
| Wang et al. | Model to locate sensors for estimation of static origin–destination volumes given prior flow information | |
| CN112016834B (en) | Abnormal driving behavior detection method, device, equipment and storage medium | |
| Pinto et al. | Applicability and calibration of an irregular cellular automata model for land use change | |
| CN107786388A (en) | A kind of abnormality detection system based on large scale network flow data | |
| CN108337685A (en) | Wireless sensor network data fusion method based on sub-clustering DGM | |
| CN116881718A (en) | Artificial intelligence training method and system based on big data cleaning | |
| CN113438123B (en) | Network flow monitoring method and device, computer equipment and storage medium | |
| CN113225391B (en) | Atmospheric environment monitoring quality monitoring method based on sliding window anomaly detection and computing equipment | |
| CN117649061B (en) | Multi-node networking electricity analysis method and system for environmental protection monitoring | |
| Chandio et al. | Towards adaptable and tunable cloud-based map-matching strategy for GPS trajectories | |
| CN113065604B (en) | Air target grouping method based on DTW-DBSCAN algorithm | |
| CN114818945A (en) | Small sample image classification method and device integrating category adaptive metric learning | |
| Zhang et al. | A methodology for optimum sensor localization/selection in fault diagnosis | |
| Guohua et al. | Enhancing situation awareness of chemical release through source inversion | |
| CN113190403A (en) | Monitoring system, computer equipment, terminal and medium for operation state of big data platform | |
| Marinakis et al. | A practical algorithm for network topology inference | |
| Zhou et al. | Finding decomposable models for efficient distributed inference over sensor networks | |
| Zhao et al. | Prediction method of dust pollutant diffusion range in building demolition based on Euclidean distance transformation | |
| CN116468205B (en) | Method and system for monitoring environment-friendly detection quality of motor vehicle | |
| Zhou et al. | Towards learning in grey spatiotemporal systems: A prophet to non-consecutive spatiotemporal dynamics |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |