CN115174864B - Hydraulic engineering safety monitoring data automatic acquisition early warning device - Google Patents
Hydraulic engineering safety monitoring data automatic acquisition early warning device Download PDFInfo
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Abstract
The invention relates to the technical field of monitoring, acquisition and early warning, in particular to an automatic acquisition and early warning device for hydraulic engineering safety monitoring data, which comprises a server, a data monitoring and processing unit, a data storage unit, a data adjusting unit and a judgment and early warning unit; the invention is to monitor and process the project construction site of the hydraulic engineering through the data monitoring and processing unit, thus facilitate to know and monitor the project construction site situation of the hydraulic engineering, make the monitoring situation more comprehensive and accurate, transfer the abnormality that appears in the project site through the data regulating unit, increase the security of various areas, judge and analyze and early warn the deployment of the project site through judging the early warning unit, thus increase the security of the data monitoring and acquisition area, avoid the occurrence of abnormality in the monitoring and acquisition area, unable to maintain in time.
Description
Technical Field
The invention relates to the technical field of monitoring, acquisition and early warning, in particular to an automatic acquisition and early warning device for hydraulic engineering safety monitoring data.
Background
Along with the development of society, the development of the water conservancy project can lead the development of the country to generate a qualitative leap, and the country also builds a large number of water conservancy projects, which play an important role in flood control, waterlogging removal, irrigation, power generation and the like;
at present, in the project implementation process of the water engineering, the data of the water engineering site are monitored and collected through the cameras, so that a large amount of human resources are saved, but the existing monitoring and collection require technical personnel to monitor in real time in a control room, only when the cameras are thoroughly damaged, the monitoring and collection can not be found out, and the data analysis can not be carried out according to the cameras and the real-time data of the site, so that the integrity and the accuracy of the data collected by monitoring are ensured, and the real-time early warning can not be carried out according to the analysis and the processing of the data.
Disclosure of Invention
The invention aims to provide an automatic acquisition and early warning device for hydraulic engineering safety monitoring data, which monitors and processes project construction sites of hydraulic engineering through a data monitoring processing unit, so that the project construction site conditions of the hydraulic engineering are conveniently known and monitored, the monitoring conditions are more comprehensive and accurate, the abnormal conditions occurring in the project sites are mobilized through a data adjusting unit, the safety of various areas is improved, the judgment analysis and early warning are carried out on the allocation of the project sites through a judgment and early warning unit, the safety of a data monitoring acquisition area is improved, the abnormal conditions occurring in the monitoring acquisition area are avoided, the data cannot be maintained in time, the real-time acquisition and monitoring conditions are analyzed, the accuracy of the data analysis is improved, the accuracy of the data acquisition is improved, and the working efficiency is improved.
The aim of the invention can be achieved by the following technical scheme:
the hydraulic engineering safety monitoring data automatic acquisition early warning device comprises a server, a data monitoring processing unit, a data storage unit, a data adjusting unit and a judgment early warning unit;
the server generates monitoring and monitoring signaling and sends the monitoring and monitoring signaling to the data monitoring and processing unit, the data monitoring and processing unit monitors and processes project construction sites of hydraulic engineering to obtain monitoring safety signals or monitoring abnormal signals, the server generates adjusting signaling and sends the adjusting signaling to the data adjusting unit, the data adjusting unit is used for mobilizing the abnormality of the project sites to match mobilizers, the server generates acquisition early warning signaling and sends the acquisition early warning signaling to the judgment early warning unit, the judgment early warning unit is used for judging and analyzing the allocation of the project sites and early warning the allocation of the project sites to obtain alarm signals and sending out alarms, and corresponding abnormal position data is displayed.
Further, the data monitoring processing unit monitors and monitors the hydraulic engineering according to the monitoring processing signaling, and the specific operation process of the monitoring and monitoring operation is as follows:
the data monitoring processing unit adjusts the angle of the camera in real time to carry out omnibearing shooting, and the specific adjusting method comprises the following steps:
monitoring and collecting plane data of an area of a project construction site, calibrating the plane data into area plane data, establishing a virtual plane rectangular coordinate system, imaging the area plane data in the virtual plane rectangular coordinate system, calibrating corner points of the project construction site in the imaged area plane data into area corner coordinates, and carrying out area division processing according to the coordinates of the area plane data to obtain a plurality of sub-areas;
collecting the number of the internal monitoring cameras according to each sub-area, calibrating the number of the internal monitoring cameras as pickup data, collecting the area size of each sub-area in the interior according to each sub-area, calibrating the area size of each sub-area as sub-area data, collecting the monitored range of the internal cameras according to each sub-area, calibrating the monitored range as pickup area data, collecting the area covered by the monitored area of the internal cameras according to each sub-area, and calibrating the area as pickup area data;
extracting the shot data in the ith sub-area and marking as SLi, extracting the sub-area surface data in the ith sub-area and marking as ZMi, extracting the shot surface data in the ith sub-area and marking as sma, extracting the shot area data in the ith sub-area and marking as SQi, i=1, 2, 3..n, and n being the total number of sub-areas;
sub-area face data ZMi in the i-th sub-area and shot face data sma in the i-th sub-area are extracted, and the two are brought into a duty ratio calculation formula: the ratio of the shot surface=shot surface data/sub-area surface data, the shot surface ratio is calculated for a plurality of sub-areas according to the calculation method of the shot surface ratio, the plurality of shot surface ratio is calculated, the average value of the plurality of shot surface ratio is calculated, calculating a shot surface duty ratio average value, respectively carrying out difference calculation on a plurality of shot surface duty ratios and the shot surface duty ratio average value, calculating a plurality of shot surface duty ratio difference values, carrying out average value calculation on a plurality of shot surface duty ratio difference values, and calculating a shot surface duty ratio average difference value;
and extracting the shot region data SQI in the ith sub-region, carrying out monitoring judgment on the shot region data SQI, the shot region average value and the shot region average difference value to obtain a monitoring safety signal and a monitoring abnormal signal, transmitting the monitoring safety signal and the monitoring abnormal signal to a server, and transmitting the monitoring safety signal and the monitoring abnormal signal to a data regulating unit by the server.
Further, the specific processing procedure of performing the region division processing according to the coordinates of the region plane data is as follows:
calculating Y-axis numerical values corresponding to a plurality of points of the unified X-axis coordinate in a pairwise manner, calculating a plurality of Y-axis numerical value differences, selecting the largest Y-axis difference value in the Y-axis numerical value differences, calibrating the Y-axis difference value as length data, dividing the length data into a plurality of equal-length equal-parts on average, marking in a virtual plane rectangular coordinate system according to the equal-length value of each equal-length equal-part, and calibrating a plurality of marked coordinate points as Y-axis equal-part points;
calculating X-axis numerical values corresponding to a plurality of points of the unified Y-axis coordinate in a pairwise manner, calculating a plurality of X-axis numerical value differences, selecting the largest X-axis difference value in the X-axis numerical value differences, calibrating the largest X-axis difference value as width data, dividing the width data into a plurality of equal-width equal-value aliquots, marking in a virtual plane rectangular coordinate system according to the equal-width equal-value aliquots of each width, and calibrating the marked plurality of coordinate points as X-axis equal-value aliquots;
and (3) horizontally etching the X-axis bisector point to form a straight line perpendicular to the X-axis, horizontally etching the Y-axis bisector point to form a straight line perpendicular to the Y-axis, horizontally etching the X-axis bisector point to form a straight line perpendicular to the X-axis and horizontally etching the Y-axis bisector point to form an area plane data formed by intersecting the straight line perpendicular to the Y-axis, and calibrating the area plane data into a plurality of sub-areas.
Further, the specific process of monitoring and judging is as follows:
the shot region data Sqi and the shot surface duty ratio average value are monitored together to obtain a calculation formula:
JKi = [ SQI ] u1+ (MZi +MCi) u2]/SLi, calculating to obtain a monitoring coefficient JKi of the ith sub-area, and calibrating the monitoring coefficient JKi as a sub-area monitoring coefficient, wherein u1 is represented as a weight coefficient of the shot area data, MZi is represented as a shot face duty ratio average value of the ith sub-area, MCi is represented as a shot face duty ratio average difference value of the ith sub-area, u2 is represented as a weight coefficient of the shot face duty ratio average value, and u1 and u2 are both preset values, and u2 is larger than u1;
extracting a subregion monitoring coefficient JKi of the ith subregion, and comparing the subregion monitoring coefficient JKi of the ith subregion with a monitoring safety threshold M1, wherein the specific comparison process is as follows:
when the sub-area monitoring coefficient JKi of the ith sub-area is larger than or equal to the monitoring safety threshold M1, judging that the monitoring safety in the ith sub-area is high, and generating a monitoring safety signal;
when the sub-area monitoring coefficient JKi of the ith sub-area is smaller than the monitoring safety threshold value M1, the monitoring safety in the ith sub-area is judged to be low, and a monitoring abnormal signal is generated.
Furthermore, the data adjusting unit extracts and identifies abnormal values of the project site according to the adjusting signaling, and carries out mobilization processing operation according to the extraction and identification of the abnormal values, wherein the specific operation process of the mobilization processing operation is as follows:
extracting a monitoring safety signal and a monitoring abnormal signal, identifying the monitoring safety signal and the monitoring abnormal signal, and when the monitoring safety signal is identified, not performing mobilization processing, and when the monitoring abnormal signal is identified, performing mobilization processing, wherein the specific process of mobilization processing is as follows:
monitoring and collecting the current time point on-duty staff, marking the current time point on-duty staff as an alternative staff, calibrating the position of the alternative staff as alternative position data, performing distance calculation in a virtual plane rectangular coordinate system, and calculating a plurality of distance data;
monitoring experience information corresponding to the acquired candidate personnel, wherein the experience information comprises processing times, processing completion times, processing failure times and processing time, the processing times refer to the problem corresponding to how many times the candidate personnel process the abnormal signals together, the processing completion times refer to the successful times in the total times of processing of the candidate personnel, the processing failure times refer to the failed times in the total times of processing of the candidate personnel, and the processing time refers to the time point when the candidate personnel process the problem corresponding to the abnormal signals each time;
selecting the processing times, the processing completion times and the processing failure times, carrying out successful duty ratio calculation on the processing times and the processing completion times, carrying out failure duty ratio calculation on the processing times and the processing failure times, carrying out difference value calculation on the successful duty ratio and the failure duty ratio, and calculating a success-failure difference value, wherein the success-failure difference value can be positive or negative;
selecting processing time corresponding to the processing times of the candidate personnel, calculating the difference between the processing time of the last processing and the processing time of the first processing, and calculating an interval difference;
bringing the interval difference, success/failure difference, number of processes, and distance data into a mobilization selection calculation formula:
dxr= [ JLr ] e1+ (ccr×e2) (cbr×e3) JGr ]. Pz, calculating an mobilization adaptation value DXr of the r-th candidate, r indicating the r-th candidate, r=1, 2, 3..the value of m, m being a positive integer, m being the total number of candidates, JLr indicating the number of processing times corresponding to the r-th candidate, JGr indicating the interval difference corresponding to the r-th candidate, CBr indicating the success-failure difference corresponding to the r-th candidate; e1 is represented as an adaptation conversion coefficient of the distance data, e2 is represented as an adaptation conversion coefficient of the processing times, e3 is represented as an adaptation conversion coefficient of the success-failure difference value, pz is represented as a deviation adjustment factor for mobilizing adaptation, and e1, e2, e3 and pz are all preset values;
and sorting the mobilization adaptive values DXR corresponding to the m candidate persons from large to small, selecting the first candidate person of which the mobilization adaptive values DXR are sorted, calibrating the first candidate person as a mobilizer, and sending monitoring abnormal signals and abnormal position data corresponding to the subareas to a mobile phone terminal of the mobilizer.
Further, the judging and early-warning unit analyzes and judges the in-place condition of personnel on the project site according to the acquisition and early-warning signaling, and carries out early warning according to the analysis and judgment, and the specific processes of the analysis and judgment and the early warning are as follows:
the method comprises the steps of calibrating a time point of transmitting monitoring abnormal signals and abnormal position data to a mobile phone terminal of a mobilizer by a server as a deployment time point, obtaining moving speeds of the mobilizer when carrying out abnormal processing each time, carrying out average value calculation on a plurality of moving speeds, calculating a moving average value, carrying out difference value calculation on the plurality of moving speeds and the moving average value respectively, calculating a plurality of moving difference values, carrying out average value calculation on the plurality of moving difference values, and calculating a moving average value;
extracting distance data corresponding to mobilizers, and allocating budget to the distance data, a moving average value and a moving average value, wherein the method specifically comprises the following steps: calculating a deployment time value PS of a mobilizer by PS=HC+ [ JLr/(PV+PJ) ]. G, wherein HC is expressed as a preparation time during deployment, PV is expressed as a moving average value, PJ is expressed as a moving average value, g is expressed as a deviation adjustment factor of the deployment time, g is a preset value, and JLr is distance data corresponding to the mobilizer;
and carrying out summation calculation on the allocation time value PS and the allocation time point to calculate an allocation arrival time point, judging that the scheduling is successful when the allocation arrival time point has the position corresponding to the abnormal position data of the allocation personnel, judging that the allocation is failed when the allocation arrival time point has no position corresponding to the abnormal position data of the allocation personnel, generating an alarm signal, and sending out an alarm and displaying the corresponding abnormal position data.
The beneficial effects of the invention are as follows:
according to the invention, the project construction site of the hydraulic engineering is monitored and processed through the data monitoring and processing unit, so that the project construction site condition of the hydraulic engineering is conveniently known and monitored, the monitoring condition is more comprehensive and accurate, the abnormality occurring in the project site is mobilized and processed through the data adjusting unit, the safety of various areas is improved, the judgment and analysis and the early warning are carried out on the allocation of the project site through the judgment and early warning unit, the safety of the data monitoring and acquisition area is improved, the occurrence of abnormality in the production time of the monitoring and acquisition area is avoided, the maintenance cannot be carried out in time, the data analysis is carried out on the condition of real-time acquisition and monitoring, the accuracy of the data analysis is improved, the accuracy of the data acquisition is improved, and the working efficiency is improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a system block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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, the invention relates to an automatic acquisition and early warning device for hydraulic engineering safety monitoring data, which comprises a server, a data monitoring processing unit, a data storage unit, a data adjusting unit and a judgment early warning unit;
the server generates monitoring and monitoring signaling and sends the monitoring and monitoring signaling to the data monitoring and processing unit, and the data monitoring and processing unit monitors and processes the project construction site of the hydraulic engineering, so that the condition of the project construction site of the hydraulic engineering is convenient to know and monitor, the monitoring condition is more comprehensive and accurate, the server generates and sends the adjusting signaling to the data adjusting unit, the data adjusting unit mobilizes the abnormality of the project site, the safety of various areas is improved, the server generates and sends the acquisition and early warning signaling to the judgment and early warning unit, the judgment and early warning unit judges and analyzes the allocation of the project site, the safety of the data monitoring and acquisition area is improved, the abnormality of the production time of the monitoring and acquisition area is avoided, and the safety cannot be maintained in time;
the data monitoring processing unit comprises a camera and is used for acquiring video information of a project construction site in real time and transmitting the video information to the data storage unit for storage;
the data monitoring processing unit monitors and monitors the hydraulic engineering according to the monitoring processing signaling, and the specific operation process of the monitoring and monitoring operation is as follows:
the data monitoring processing unit adjusts the angle of the camera in real time to carry out omnibearing shooting, and the specific adjustment method comprises the following steps:
monitoring and collecting plane data of an area of a project construction site, calibrating the plane data into area plane data, establishing a virtual plane rectangular coordinate system, imaging the area plane data in the virtual plane rectangular coordinate system, and calibrating corner points of the project construction site in the imaged area plane data as area corner coordinates;
calculating Y-axis numerical values corresponding to a plurality of points of the unified X-axis coordinate in a pairwise manner, calculating a plurality of Y-axis numerical value differences, selecting the largest Y-axis difference value in the Y-axis numerical value differences, calibrating the Y-axis difference value as length data, dividing the length data into a plurality of equal-length equal-parts on average, marking in a virtual plane rectangular coordinate system according to the equal-length value of each equal-length equal-part, and calibrating a plurality of marked coordinate points as Y-axis equal-part points;
calculating X-axis numerical values corresponding to a plurality of points of the unified Y-axis coordinate in a pairwise manner, calculating a plurality of X-axis numerical value differences, selecting the largest X-axis difference value in the X-axis numerical value differences, calibrating the largest X-axis difference value as width data, dividing the width data into a plurality of equal-width equal-value aliquots, marking in a virtual plane rectangular coordinate system according to the equal-width equal-value aliquots of each width, and calibrating the marked plurality of coordinate points as X-axis equal-value aliquots;
the method comprises the steps of horizontally etching an X-axis bisection point to form a straight line perpendicular to the X-axis, horizontally etching a Y-axis bisection point to form a straight line perpendicular to the Y-axis, horizontally etching the X-axis bisection point to form a straight line perpendicular to the X-axis, and horizontally etching the Y-axis bisection point to form area plane data formed by intersecting the straight line perpendicular to the Y-axis to form a plurality of sub-areas;
collecting the number of the internal monitoring cameras according to each sub-area, calibrating the number of the internal monitoring cameras as pickup data, collecting the area size of each sub-area in the interior according to each sub-area, calibrating the area size of each sub-area as sub-area data, collecting the monitored range of the internal cameras according to each sub-area, calibrating the monitored range as pickup area data, collecting the area covered by the monitored area of the internal cameras according to each sub-area, and calibrating the area as pickup area data;
extracting the shot data in the ith sub-area and marking as SLi, extracting the sub-area surface data in the ith sub-area and marking as ZMi, extracting the shot surface data in the ith sub-area and marking as sma, extracting the shot area data in the ith sub-area and marking as SQi, i=1, 2, 3..n, and n being the total number of sub-areas;
sub-area face data ZMi in the i-th sub-area and shot face data sma in the i-th sub-area are extracted, and the two are brought into a duty ratio calculation formula: the ratio of the shot surface=shot surface data/sub-area surface data, the shot surface ratio is calculated for a plurality of sub-areas according to the calculation method of the shot surface ratio, the plurality of shot surface ratio is calculated, the average value of the plurality of shot surface ratio is calculated, calculating a shot surface duty ratio average value, respectively carrying out difference calculation on a plurality of shot surface duty ratios and the shot surface duty ratio average value, calculating a plurality of shot surface duty ratio difference values, carrying out average value calculation on a plurality of shot surface duty ratio difference values, and calculating a shot surface duty ratio average difference value;
extracting shot region data Sqi in the ith sub-region, and carrying out monitoring calculation together with a shot surface duty ratio average value and a shot surface duty ratio average difference value, wherein the specific monitoring calculation comprises the following steps of:
JKi = [ SQI ] u1+ (MZi +MCi) u2]/SLi, calculating to obtain a monitoring coefficient JKi of the ith sub-area, and calibrating the monitoring coefficient JKi as a sub-area monitoring coefficient, wherein u1 is represented as a weight coefficient of the shot area data, MZi is represented as a shot face duty ratio average value of the ith sub-area, MCi is represented as a shot face duty ratio average difference value of the ith sub-area, u2 is represented as a weight coefficient of the shot face duty ratio average value, and u1 and u2 are both preset values, and u2 is larger than u1;
extracting a subregion monitoring coefficient JKi of the ith subregion, and comparing the subregion monitoring coefficient JKi of the ith subregion with a monitoring safety threshold M1, wherein the specific comparison process is as follows:
when the sub-area monitoring coefficient JKi of the ith sub-area is larger than or equal to the monitoring safety threshold M1, judging that the monitoring safety in the ith sub-area is high, and generating a monitoring safety signal;
when the sub-area monitoring coefficient JKi of the ith sub-area is smaller than the monitoring safety threshold M1, judging that the monitoring safety in the ith sub-area is low, and generating a monitoring abnormal signal;
extracting a monitoring safety signal and a monitoring abnormal signal, transmitting the monitoring safety signal and the monitoring abnormal signal to a server, and transmitting the monitoring safety signal and the monitoring abnormal signal to a data adjusting unit by the server;
the data adjusting unit extracts and identifies abnormal values of the project site according to the adjusting signaling, and carries out mobilization processing operation according to the extraction and identification of the abnormal values, wherein the specific operation process of the mobilization processing operation is as follows:
extracting a monitoring safety signal and a monitoring abnormal signal, identifying the monitoring safety signal and the monitoring abnormal signal, and when the monitoring safety signal is identified, not performing mobilization processing, and when the monitoring abnormal signal is identified, performing mobilization processing, wherein the specific process of mobilization processing is as follows:
monitoring and collecting the current time point on-duty staff, marking the current time point on-duty staff as an alternative staff, marking the position of the alternative staff as alternative position data, marking the position of a subarea where monitoring abnormal signals appear as abnormal position data, establishing a virtual plane rectangular coordinate system, marking the abnormal position data and the alternative position data in the virtual plane rectangular coordinate system, so as to obtain coordinate points corresponding to the two positions, calculating the distance between the two coordinate points according to the Pythagorean theorem, marking the distance between the two coordinate points as distance data, calculating the distance between the on-duty staff and the subarea position according to a distance data calculation method, and calculating a plurality of distance data;
monitoring experience information corresponding to the acquired candidate personnel, wherein the experience information comprises processing times, processing completion times, processing failure times and processing time, the processing times refer to the problem corresponding to how many times the candidate personnel process the abnormal signals together, the processing completion times refer to the successful times in the total times of processing of the candidate personnel, the processing failure times refer to the failed times in the total times of processing of the candidate personnel, and the processing time refers to the time point when the candidate personnel process the problem corresponding to the abnormal signals each time;
selecting the processing times, the processing completion times and the processing failure times, and carrying out successful duty ratio on the processing times and the processing completion times, wherein the calculation formula is as follows: success ratio = number of processing completions/number of processing times, failure ratio is performed on the number of processing times and the number of processing failures, and the formula is calculated: failure ratio = processing failure times/processing times, calculating the difference value between the success ratio and the failure ratio, and calculating the success-failure difference value, wherein the success-failure difference value can be positive or negative;
selecting processing time corresponding to the processing times of the candidate personnel, calculating the difference between the processing time of the last processing and the processing time of the first processing, and calculating an interval difference;
bringing the interval difference, success/failure difference, number of processes, and distance data into a mobilization selection calculation formula:
dxr= [ JLr ] e1+ (ccr×e2) (cbr×e3) JGr ]. Pz, calculate an adjustment fit value DXr of the r-th candidate, r denotes the r-th candidate, r=1, 2, 3..the value of m, m is a positive integer, m is the total number of candidates, JLr is distance data corresponding to the r-th corresponding candidate, CCr is the number of treatments corresponding to the r-th corresponding candidate, JGr is represented as an interval difference value corresponding to the r-th corresponding candidate person, CBr is represented as a success-failure difference value corresponding to the r-th corresponding candidate person, e1 is represented as an adaptive conversion coefficient of distance data, e2 is represented as an adaptive conversion coefficient of the number of processing times, e3 is represented as an adaptive conversion coefficient of the success-failure difference value, pz is represented as a deviation adjustment factor for adjusting the adaptation, and e1, e2, e3 and pz are all preset values;
sorting the mobilization adaptive values DXR corresponding to m candidate persons from large to small, selecting a first candidate person of which the mobilization adaptive values DXR are sorted, calibrating the first candidate person as a mobilizer, and sending monitoring abnormal signals and abnormal position data corresponding to the subareas to a mobile phone terminal of the mobilizer;
the judgment and early warning unit analyzes and judges the personnel in-place condition of the project site according to the acquisition and early warning signaling, and carries out early warning according to the analysis and judgment, wherein the specific processes of the analysis and judgment and the early warning are as follows:
the method comprises the steps of calibrating a time point of transmitting monitoring abnormal signals and abnormal position data to a mobile phone terminal of a mobilizer by a server as a deployment time point, obtaining moving speeds of the mobilizer when carrying out abnormal processing each time, carrying out average value calculation on a plurality of moving speeds, calculating a moving average value, carrying out difference value calculation on the plurality of moving speeds and the moving average value respectively, calculating a plurality of moving difference values, carrying out average value calculation on the plurality of moving difference values, and calculating a moving average value;
extracting distance data corresponding to mobilizers, and allocating budget to the distance data, a moving average value and a moving average value, wherein the method specifically comprises the following steps: calculating a deployment time value PS by ps=hc+ [ JLr/(pv+pj) ] + ], wherein HC is represented as a preparation time during deployment, PV is represented as a moving average value, PJ is represented as a moving average value, g is represented as a deviation adjustment factor of deployment time, and g is a preset value, JLr in the formula refers to distance data corresponding to a deployment person, the deployment person is a member of m candidate persons, and specifically refers to distance data corresponding to a deployment person selected from the plurality of candidate persons;
and carrying out summation calculation on the allocation time value PS and the allocation time point to calculate an allocation arrival time point, judging that the scheduling is successful when the allocation arrival time point has the position corresponding to the abnormal position data of the allocation personnel, judging that the allocation is failed when the allocation arrival time point has no position corresponding to the abnormal position data of the allocation personnel, generating an alarm signal, and sending out an alarm and displaying the corresponding abnormal position data.
The foregoing is merely illustrative and explanatory of the invention, as various modifications and additions may be made to the particular embodiments described, or in a similar manner, by those skilled in the art, without departing from the scope of the invention, or exceeding the scope of the invention as defined in the claims.
Claims (5)
1. The hydraulic engineering safety monitoring data automatic acquisition early warning device is characterized by comprising a server, a data monitoring processing unit, a data storage unit, a data adjusting unit and a judging early warning unit;
the server generates monitoring and monitoring signaling and sends the monitoring and monitoring signaling to the data monitoring and processing unit, the data monitoring and processing unit monitors and processes project construction sites of hydraulic engineering to obtain monitoring safety signals or monitoring abnormal signals, the server generates and sends adjusting signaling to the data adjusting unit, the data adjusting unit mobilizes the abnormality of the project sites to match with mobilizers, the server generates and gathers early warning signaling and sends the early warning signaling to the judging and early warning unit, the judging and early warning unit judges and analyzes the allocation of the project sites to obtain alarm signals and gives out alarms, and corresponding abnormal position data is displayed;
the data monitoring processing unit monitors and monitors the hydraulic engineering according to the monitoring processing signaling, and the specific operation process of the monitoring and monitoring operation is as follows:
the data monitoring processing unit adjusts the angle of the camera in real time to carry out omnibearing shooting, and the specific adjusting method comprises the following steps:
monitoring and collecting plane data of an area of a project construction site, calibrating the plane data into area plane data, establishing a virtual plane rectangular coordinate system, imaging the area plane data in the virtual plane rectangular coordinate system, calibrating corner points of the project construction site in the imaged area plane data into area corner coordinates, and carrying out area division processing according to the coordinates of the area plane data to obtain a plurality of sub-areas;
collecting the number of the internal monitoring cameras according to each sub-area, calibrating the number of the internal monitoring cameras as pickup data, collecting the area size of each sub-area in the interior according to each sub-area, calibrating the area size of each sub-area as sub-area data, collecting the monitored range of the internal cameras according to each sub-area, calibrating the monitored range as pickup area data, collecting the area covered by the monitored area of the internal cameras according to each sub-area, and calibrating the area as pickup area data;
extracting the shot data in the ith sub-area and marking as SLi, extracting the sub-area surface data in the ith sub-area and marking as ZMi, extracting the shot surface data in the ith sub-area and marking as sma, extracting the shot area data in the ith sub-area and marking as SQi, i=1, 2, 3..n, and n being the total number of sub-areas;
sub-area face data ZMi in the i-th sub-area and shot face data sma in the i-th sub-area are extracted, and the two are brought into a duty ratio calculation formula: the ratio of the shot surface=shot surface data/sub-area surface data, the shot surface ratio is calculated for a plurality of sub-areas according to the calculation method of the shot surface ratio, the plurality of shot surface ratio is calculated, the average value of the plurality of shot surface ratio is calculated, calculating a shot surface duty ratio average value, respectively carrying out difference calculation on a plurality of shot surface duty ratios and the shot surface duty ratio average value, calculating a plurality of shot surface duty ratio difference values, carrying out average value calculation on a plurality of shot surface duty ratio difference values, and calculating a shot surface duty ratio average difference value;
and extracting the shot region data SQI in the ith sub-region, carrying out monitoring judgment on the shot region data SQI, the shot region average value and the shot region average difference value to obtain a monitoring safety signal and a monitoring abnormal signal, transmitting the monitoring safety signal and the monitoring abnormal signal to a server, and transmitting the monitoring safety signal and the monitoring abnormal signal to a data regulating unit by the server.
2. The automatic acquisition and early warning device for hydraulic engineering safety monitoring data according to claim 1, wherein the specific processing procedure for carrying out regional division processing according to the coordinates of regional plane data is as follows:
calculating Y-axis numerical values corresponding to a plurality of points of the unified X-axis coordinate in a pairwise manner, calculating a plurality of Y-axis numerical value differences, selecting the largest Y-axis difference value in the Y-axis numerical value differences, calibrating the Y-axis difference value as length data, dividing the length data into a plurality of equal-length equal-parts on average, marking in a virtual plane rectangular coordinate system according to the equal-length value of each equal-length equal-part, and calibrating a plurality of marked coordinate points as Y-axis equal-part points;
calculating X-axis numerical values corresponding to a plurality of points of the unified Y-axis coordinate in a pairwise manner, calculating a plurality of X-axis numerical value differences, selecting the largest X-axis difference value in the X-axis numerical value differences, calibrating the largest X-axis difference value as width data, dividing the width data into a plurality of equal-width equal-value aliquots, marking in a virtual plane rectangular coordinate system according to the equal-width equal-value aliquots of each width, and calibrating the marked plurality of coordinate points as X-axis equal-value aliquots;
and (3) horizontally etching the X-axis bisector point to form a straight line perpendicular to the X-axis, horizontally etching the Y-axis bisector point to form a straight line perpendicular to the Y-axis, horizontally etching the X-axis bisector point to form a straight line perpendicular to the X-axis and horizontally etching the Y-axis bisector point to form an area plane data formed by intersecting the straight line perpendicular to the Y-axis, and calibrating the area plane data into a plurality of sub-areas.
3. The automatic acquisition and early warning device for hydraulic engineering safety monitoring data according to claim 1, wherein the specific process of monitoring and judging is as follows:
the shot region data Sqi and the shot surface duty ratio average value are monitored together to obtain a calculation formula:
JKi = [ SQI ] u1+ (MZi +MCi) u2]/SLi, calculating to obtain a monitoring coefficient JKi of the ith sub-area, and calibrating the monitoring coefficient JKi as a sub-area monitoring coefficient, wherein u1 is represented as a weight coefficient of the shot area data, MZi is represented as a shot face duty ratio average value of the ith sub-area, MCi is represented as a shot face duty ratio average difference value of the ith sub-area, u2 is represented as a weight coefficient of the shot face duty ratio average value, and u1 and u2 are both preset values, and u2 is larger than u1;
extracting a subregion monitoring coefficient JKi of the ith subregion, and comparing the subregion monitoring coefficient JKi of the ith subregion with a monitoring safety threshold M1, wherein the specific comparison process is as follows:
when the sub-area monitoring coefficient JKi of the ith sub-area is larger than or equal to the monitoring safety threshold M1, judging that the monitoring safety in the ith sub-area is high, and generating a monitoring safety signal;
when the sub-area monitoring coefficient JKi of the ith sub-area is smaller than the monitoring safety threshold value M1, the monitoring safety in the ith sub-area is judged to be low, and a monitoring abnormal signal is generated.
4. The automatic acquisition and early warning device for hydraulic engineering safety monitoring data according to claim 1, wherein the data adjusting unit extracts and identifies abnormal values of a project site according to adjusting signaling, and carries out mobilization processing operation according to the extraction and identification of the abnormal values, and the specific operation process of mobilization processing operation is as follows:
extracting a monitoring safety signal and a monitoring abnormal signal, identifying the monitoring safety signal and the monitoring abnormal signal, and when the monitoring safety signal is identified, not performing mobilization processing, and when the monitoring abnormal signal is identified, performing mobilization processing, wherein the specific process of mobilization processing is as follows:
monitoring and collecting the current time point on-duty staff, marking the current time point on-duty staff as an alternative staff, calibrating the position of the alternative staff as alternative position data, performing distance calculation in a virtual plane rectangular coordinate system, and calculating a plurality of distance data;
monitoring experience information corresponding to the acquired candidate personnel, wherein the experience information comprises processing times, processing completion times, processing failure times and processing time, the processing times refer to the problem corresponding to how many times the candidate personnel process the abnormal signals together, the processing completion times refer to the successful times in the total times of processing of the candidate personnel, the processing failure times refer to the failed times in the total times of processing of the candidate personnel, and the processing time refers to the time point when the candidate personnel process the problem corresponding to the abnormal signals each time;
selecting the processing times, the processing completion times and the processing failure times, carrying out successful duty ratio calculation on the processing times and the processing completion times, carrying out failure duty ratio calculation on the processing times and the processing failure times, carrying out difference value calculation on the successful duty ratio and the failure duty ratio, and calculating a success-failure difference value, wherein the success-failure difference value can be positive or negative;
selecting processing time corresponding to the processing times of the candidate personnel, calculating the difference between the processing time of the last processing and the processing time of the first processing, and calculating an interval difference;
bringing the interval difference, success/failure difference, number of processes, and distance data into a mobilization selection calculation formula:
dxr= [ JLr ] e1+ (ccr×e2) (cbr×e3) JGr ]. Pz, calculate an adjustment fit value DXr of the r-th candidate, r denotes the r-th candidate, r=1, 2, 3..the value of m, m is a positive integer, m is the total number of candidates, JLr is distance data corresponding to the r-th corresponding candidate, CCr is the number of treatments corresponding to the r-th corresponding candidate, JGr is represented as an interval difference value corresponding to the r-th corresponding candidate person, CBr is represented as a success-failure difference value corresponding to the r-th corresponding candidate person, e1 is represented as an adaptive conversion coefficient of distance data, e2 is represented as an adaptive conversion coefficient of the number of processing times, e3 is represented as an adaptive conversion coefficient of the success-failure difference value, pz is represented as a deviation adjustment factor for adjusting the adaptation, and e1, e2, e3 and pz are all preset values;
and sorting the mobilization adaptive values DXR corresponding to the m candidate persons from large to small, selecting the first candidate person of which the mobilization adaptive values DXR are sorted, calibrating the first candidate person as a mobilizer, and sending monitoring abnormal signals and abnormal position data corresponding to the subareas to a mobile phone terminal of the mobilizer.
5. The automatic acquisition and early warning device for hydraulic engineering safety monitoring data according to claim 1, wherein the judgment and early warning unit analyzes and judges the in-place situation of personnel on a project site according to the acquisition and early warning signaling, and performs early warning according to the analysis and judgment, and the specific processes of the analysis and judgment and early warning are as follows:
the method comprises the steps of calibrating a time point of transmitting monitoring abnormal signals and abnormal position data to a mobile phone terminal of a mobilizer by a server as a deployment time point, obtaining moving speeds of the mobilizer when carrying out abnormal processing each time, carrying out average value calculation on a plurality of moving speeds, calculating a moving average value, carrying out difference value calculation on the plurality of moving speeds and the moving average value respectively, calculating a plurality of moving difference values, carrying out average value calculation on the plurality of moving difference values, and calculating a moving average value;
extracting distance data corresponding to mobilizers, and allocating budget to the distance data, a moving average value and a moving average value, wherein the method specifically comprises the following steps: calculating a deployment time value PS of a mobilizer by PS=HC+ [ JLr/(PV+PJ) ]. G, wherein HC is expressed as a preparation time during deployment, PV is expressed as a moving average value, PJ is expressed as a moving average value, g is expressed as a deviation adjustment factor of the deployment time, g is a preset value, and JLr is distance data corresponding to the mobilizer;
and carrying out summation calculation on the allocation time value PS and the allocation time point to calculate an allocation arrival time point, judging that the scheduling is successful when the allocation arrival time point has the position corresponding to the abnormal position data of the allocation personnel, judging that the allocation is failed when the allocation arrival time point has no position corresponding to the abnormal position data of the allocation personnel, generating an alarm signal, and sending out an alarm and displaying the corresponding abnormal position data.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2012250287A1 (en) * | 2011-11-15 | 2013-05-30 | Bartco Traffic Equipment Pty Ltd | Method and Apparatus for Indicating Conditions |
| CN111912488A (en) * | 2020-08-04 | 2020-11-10 | 郑刚 | Water network monitoring device and monitoring method based on unmanned aerial vehicle image sensor |
| CN112969051A (en) * | 2021-01-30 | 2021-06-15 | 南京新高智联信息技术有限公司 | Hydraulic engineering management system based on big data |
| CN113533777A (en) * | 2021-07-29 | 2021-10-22 | 中铁水利水电规划设计集团有限公司 | Hydraulic engineering safety monitoring removes thing networking perception equipment |
| CN114268736A (en) * | 2021-11-23 | 2022-04-01 | 南京国图信息产业有限公司 | Tower footing dome camera shooting method with high space coverage |
-
2022
- 2022-07-11 CN CN202210810194.6A patent/CN115174864B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2012250287A1 (en) * | 2011-11-15 | 2013-05-30 | Bartco Traffic Equipment Pty Ltd | Method and Apparatus for Indicating Conditions |
| CN111912488A (en) * | 2020-08-04 | 2020-11-10 | 郑刚 | Water network monitoring device and monitoring method based on unmanned aerial vehicle image sensor |
| CN112969051A (en) * | 2021-01-30 | 2021-06-15 | 南京新高智联信息技术有限公司 | Hydraulic engineering management system based on big data |
| CN113533777A (en) * | 2021-07-29 | 2021-10-22 | 中铁水利水电规划设计集团有限公司 | Hydraulic engineering safety monitoring removes thing networking perception equipment |
| CN114268736A (en) * | 2021-11-23 | 2022-04-01 | 南京国图信息产业有限公司 | Tower footing dome camera shooting method with high space coverage |
Non-Patent Citations (1)
| Title |
|---|
| 信息化技术在小型水利工程运行管理中的应用;罗逸铭等;江西水利科技;第48卷(第1期);20-23 * |
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