CN112801527A - Safety monitoring information visualization platform - Google Patents
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Abstract
The invention provides a safety monitoring information visualization platform which is used for preliminarily processing appearance instrument and appearance instrument data and patrol inspection information which are monitored in real time, integrating various analysis methods to comprehensively analyze the monitoring data, carrying out digital processing and statistical analysis on the patrol inspection information, and acquiring and visually displaying an operation condition evaluation result of a project according to a comprehensive analysis result of the monitoring data and a digital statistical result of the patrol inspection. And alarming and marking the abnormal information, and alarming the abnormal analysis result and/or the operation condition to realize the health diagnosis of the engineering. And (3) overall management of the multi-project safety monitoring work at the same time, and risk grading early warning and information push are carried out on abnormal measuring points, fault equipment, geological disasters, abnormal analysis and inspection defects in the building operation process. Real-time query of monitoring information, intelligent patrol inspection, comprehensive analysis and visual display of monitoring data, and positioning of abnormal results and early warning information to corresponding scenes for timely response are achieved.
Description
Technical Field
The invention relates to the field of safety monitoring information, in particular to a safety monitoring information visualization platform.
Background
With the development of computer and information internet technology, the information transmission and processing technology is rapidly improved, and the engineering safety monitoring data processing work is fundamentally changed. In the face of the problems of huge monitoring data volume, various data types, large data identification, processing and analysis workload and the like of a safety monitoring project, related units develop and establish safety monitoring platforms in a dispute, and integrated management from an independent information management platform of each project to each type of monitoring project improves the working efficiency of practitioners, standardizes an operation program for processing data, and improves the accuracy of monitoring results.
With regard to the safety monitoring data platform widely applied at present, the functions of transmitting monitoring data and managing monitoring information are basically realized. Daily monitoring data storage to each item can be accomplished fast through current platform, carries out the discovery and the processing of abnormal data, carries out conventional statistical analysis to the monitoring data, realizes the diagnosis to monitoring devices operation conditions and the judgement of monitoring data reliability to implement the warning, accomplished functions such as APP development and monitoring information release simultaneously.
Specifically, the existing automatic safety monitoring platform can support automatic safety monitoring of multiple types of engineering projects, management of multiple types of monitoring projects and multiple types of project monitoring data is achieved by setting corresponding configuration information for each project or project into the platform, then performing data acquisition, storage, analysis, auditing, statistics, diagnosis and other operations on monitoring equipment according to the configuration information, setting judgment conditions to diagnose and analyze the running state and data effectiveness of the monitoring equipment, guaranteeing standardized storage of warehousing monitoring data, and achieving basic statistical analysis of the safety monitoring data.
But the prior art has the following disadvantages:
A. the lack of a data analysis method of a platform can not carry out comprehensive analysis on the monitoring data: the existing safety monitoring information management platform can count audit data according to configuration information to generate statistical data, the statistical data are stored in a database, the form of the statistical data is usually simple and is generally conventional statistical parameters such as mean value, maximum value, minimum value and speed, the existing platform does not have a system data analysis method, and real physical significance, slight change and potential risk of the monitoring data cannot be deeply mined.
B. Effective statistical processing cannot be performed on inspection records, images, video image information and the like: the existing safety monitoring information management platform can passively receive patrol inspection records and image information, or actively (regularly) collect image information of monitoring videos and store the image information in a database; the platform can not carry out system integration and classification statistical analysis on a plurality of messy information such as routing inspection records, images and videos, and can not clearly show defect distribution and development change conditions.
C. The visual display of safety monitoring data and analysis results thereof, inspection tour and statistical results thereof, risk early warning information and the like cannot be realized: the existing safety monitoring information management platform can carry out real-time acquisition, abnormal value judgment and alarm on monitoring data and conventional statistical parameter calculation, realizes standardized storage of the monitoring data and formatted storage of statistical results, but cannot visually display the real-time monitoring data, specialized analysis results, inspection results, risk early warning information and the like on an engineering model.
However, for the increasing demand of automatic safety monitoring, the realization of monitoring and managing different types of projects by switching different monitoring platforms is an important reason causing low working efficiency, so how to construct a set of data management analysis display platform suitable for multiple types of monitoring projects, the realization of safety monitoring comprehensive information management digitization, information acquisition and processing real-time, safety analysis and evaluation specialization, information disposal and release visualization, and the comprehensive improvement of the scientific management level of engineering safety operation becomes an urgent problem to be solved.
Disclosure of Invention
The invention provides a safety monitoring information visualization platform, which is used for solving the problem that the data management analysis and display of multiple types of monitoring projects cannot be realized on the same platform in the prior art.
In order to achieve the above object, a technical solution of the present invention provides a security monitoring information visualization platform, which is characterized in that the platform includes: and acquiring project information, and acquiring weather forecast data, current weather data and earthquake information in real time. The endoscopical instrument consisting of the seepage monitoring sensor group, the stress-strain monitoring sensor group, the pressure monitoring sensor group, the deformation monitoring sensor group and the strong earthquake monitoring sensor group acquires seepage information, stress-strain information, pressure/load information, deformation information and strong earthquake information in real time and integrates the seepage information, the stress-strain information, the pressure/load information, the deformation information and the strong earthquake information into endoscopical instrument data. The method comprises the steps that appearance deformation data are obtained in real time by a total station and meteorological acquisition equipment of an intelligent integrated station or a receiver and antenna equipment of a GNSS integrated station and are integrated into appearance data; and acquiring frame image information of video monitoring, acquiring pictures and record information of inspection tour and digitizing. And monitoring whether the data of the inside appearance instrument, the data of the outside appearance instrument, the frame image information, the picture and the record information are normal or not in real time, otherwise, alarming, and sending alarm information to a worker, so that the worker checks the instrument corresponding to the corresponding data to realize the marking of the fault equipment, the updating and correction of each data and the re-inspection to realize the updating of the frame image, the picture and the record information. Comprehensively evaluating and analyzing the data of the appearance instrument and the data of the appearance instrument to obtain evaluation of data analysis results; the comprehensive evaluation analysis at least comprises one of time process analysis, measured value statistical analysis, measured value distribution analysis, variation rate analysis, correlation analysis, periodicity analysis, historical synchronization analysis and typical event analysis. And carrying out digital processing and defect analysis on the frame image information, the picture and the recorded information to obtain a defect space-time distribution result and defect grade evaluation. And obtaining the operation condition evaluation result of the current project according to the data analysis result evaluation and the defect grade evaluation. Respectively carrying out visual display on the operation condition evaluation result and the monitoring result on a model interface, wherein the visual display comprises the following steps: the method comprises the steps of generating a visual view of safety monitoring information for processed endoscopical instrument data and appearance instrument data, generating a visual view of inspection after the video monitoring and inspection information is processed in a digital mode, generating a visual view of data analysis for a comprehensive analysis result of the endoscopical instrument data and the appearance instrument data, generating a visual view of risk early warning information for the monitoring result, generating a visual view of engineering health diagnosis according to an operation condition evaluation result, and enabling workers to work on the next step according to the visual views.
Preferably, as a preferred option of the above technical solution, the safety monitoring is performed on the data of the appearance instrument and the data of the appearance instrument, including the range of the instrument, the historical threshold and the 3 σ fluctuation range, and when any one of the data is abnormal, an alarm mechanism is started; specifically, if the data exceeds the instrument range, the staff is informed to check the corresponding instrument through information push. And if the current data of the interior appearance instrument and/or the data of the exterior appearance instrument exceed the range of the historical threshold value, sending alarm information, and reserving or discarding the data, wherein the historical threshold value is the maximum value in the historical monitoring data or the maximum change rate in the corresponding statistical period. And if the fluctuation range of the current appearance instrument data and/or the appearance instrument data is within +/-3 sigma, the normal working condition is established, and if not, an alarm mechanism is started.
Preferably, as an optimization of the above technical solution, when any one of the acquired weather forecast data, current weather data, and earthquake information has abnormal weather and/or natural disaster information, a special working condition alarm mechanism is started.
Preferably, the data analysis result evaluation obtained by performing the comprehensive evaluation analysis on the appearance instrument data and the appearance instrument data includes: calculating the data of the appearance instrument and the data of the appearance instrument to obtain the average value, the maximum value, the minimum value, the range value, the variance value and the standard deviation value of the data of each sensor, and combining the average value, the maximum value, the minimum value, the range value, the variance value and the standard deviation value with the corresponding statistical period to generate dataAnd forming the safety monitoring information visualization views with different evaluation indexes. Preferably, the comprehensive evaluation and analysis of the appearance instrument data includes: and analyzing the time process, acquiring the data of the appearance instrument and the data of the appearance instrument of the monitoring values of the items of the measuring points or the items, and acquiring the corresponding change process. And (4) carrying out statistical analysis on the measured values, and comparing various characteristic values of different mutually associated measuring points to obtain the difference level of the measured values of the measuring points and the relation between the difference level and the environmental factors. And (4) analyzing the distribution of the measured values, acquiring a change rule according to the distribution condition of the inner appearance data and the outer appearance data following the measuring points, and acquiring the difference level between the measuring points. And analyzing the variation, and obtaining the variation trend of each measuring point in different statistical periods. And (4) analyzing the change rate, wherein the relatively stable state of the measuring point can be judged by using a change rate analysis method. Performing correlation analysis, selecting at least two data with correlation for analysis, selecting a fitting function by a platform according to the data characteristics of the data to draw a correlation distribution diagram and calculating a judgment coefficient R2Thereby obtaining the degree of correlation of the data with correlation.
Preferably, in the above technical solution, the comprehensive evaluation and analysis of the appearance instrument data and the appearance instrument data further includes: the method comprises the steps of periodic analysis, wherein characteristic values of monitoring point objects and objective variables are analyzed in a periodic variation interval to obtain a periodic variation rule of dependent variables along with the objective variables; historical synchronization analysis, namely comparing and analyzing the monitoring value of the measuring point and a historical synchronization measured value of a set comparison period; and analyzing the influence degree of the specific factor on the building to obtain the influence degree of the specific factor on the building.
Preferably, as a preferred aspect of the foregoing technical solution, the performing digital processing and defect statistical analysis on the frame image information, the picture and the recording information to obtain a defect space-time distribution result and a defect level evaluation includes: the defect space-time distribution result comprises the time distribution result of defect discovery, development and repair of the specified part; specifying a defect spatio-temporal distribution result of the defect type; specifying the defect spatio-temporal distribution results of the defect levels, etc. And (3) as a result of the defect grade evaluation, the platform comprises 4 defect grades (i.e. I grade, II grade, III grade and IV grade) of engineering operation, and an alarm mechanism is started to carry out information push on the engineering defects reaching the III grade and above so as to realize defect grading and alarm management.
Preferably, the visually displaying the operation condition evaluation result and the monitoring result on the model interface includes: a safety monitoring information visualization view of an engineering model in combination with the processed appearance data and/or the appearance data; the visual inspection view of the engineering model, the video monitoring information and the digital inspection result is combined; a data analysis visualization view of the engineering model in combination with the results of the comprehensive analysis of the appearance instrument data and/or the appearance instrument data; a risk early warning information visualization view combining the engineering model and the alarm information details; and the engineering model and the operation condition evaluation result are combined to form an engineering health diagnosis visual view.
The technical scheme of the invention provides a safety monitoring information visualization platform, which integrates various professional analysis methods to perform comprehensive analysis on monitoring data by performing preliminary processing on appearance instrument and appearance instrument data monitored in real time and acquired meteorological information, performs digital processing and statistical analysis on inspection information, and acquires and visually displays an operation condition evaluation result of a project according to a comprehensive analysis result of the monitoring data and a digital statistical result of inspection. And alarming and marking abnormal information during primary processing, and alarming an abnormal analysis result and/or an operation condition so as to realize health diagnosis of the project.
The method has the advantages that a safety monitoring visual special scene is established, the simultaneous overall management of multi-project safety monitoring work is realized, and risk grading early warning and information pointing pushing are performed on abnormal measuring points, fault equipment, geological disasters, analysis abnormity, inspection defects and the like in the operation process of the building. The method and the system realize that a user completes real-time inquiry of monitoring information, digital processing of inspection tour and inspection, comprehensive analysis of monitoring data in a special topic scene, and positions an abnormal result and early warning information in the special topic scene, so that the user can find and position the place where the event is reminded in time, and the event can be responded and processed in time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief description will be given below of the drawings required for the embodiments or the technical solutions in the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a security monitoring information visualization platform according to an embodiment of the present invention.
Fig. 2 is a detailed flowchart of a security monitoring information visualization platform according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of time-course analysis of monitoring data of a rock-fill dam panel void gauge according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a statistical analysis result of measured values of a rock-fill dam panel void gauge based on different statistical periods according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of a statistical analysis result of measured values of various types of characteristic values of a rock-fill dam panel unidirectional joint meter according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a distribution analysis result of a measured value of a saturation line of a typical monitoring section of a rock-fill dam according to an embodiment of the present invention.
Fig. 7 is a diagram illustrating the comparative analysis result of the variation over the years of the measured value of the rear osmometer of the toe board of the dam according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of comparison analysis results of monitoring value variation of a typical monitoring section osmometer of a dam according to a specific embodiment in the technical scheme of the present invention.
Fig. 9 is a schematic diagram showing the analysis result of the variation rate of the measured values of the osmometer behind the toe board of the dam and the reservoir water level according to an embodiment of the present invention.
Fig. 10 is a schematic diagram of the analysis result of the correlation between the channel bottom osmometer of the water diversion channel and the channel water level according to an embodiment of the present invention.
Fig. 11 is a schematic view showing a result of periodically analyzing a measured value of back-pressure of a toe board of a dam according to an embodiment of the present invention.
Fig. 12 is a schematic diagram of a result of analyzing the historical date of the hydropower station flood season reservoir water level by using a specific embodiment in the technical scheme of the present invention.
Fig. 13 is a schematic diagram illustrating an analysis of the influence degree of the earthquake of a certain hydropower station on all monitoring projects of a project according to a specific embodiment of the present invention.
Fig. 14 is a visualization layout diagram of a dam osmotic pressure monitoring project when the safety monitoring information visualization is realized according to the technical scheme of the invention.
FIG. 15 is a cross-sectional control diagram of the osmotic pressure monitoring project obtained from FIG. 14.
Fig. 16 is a diagram of a dam horizontal displacement monitoring engineering layout of a hydraulic structure when data analysis result visualization is realized according to the technical scheme of the invention.
Fig. 17 is an overall interface for visualization of inspection tour in the technical solution of the present invention.
FIG. 18 shows the statistical analysis result of the digital inspection information of the diversion channel engineering of the present invention.
Fig. 19 is a comprehensive view of the inspection operation of the process shown in fig. 18.
Fig. 20 is a diagram of measuring point layout of a panel deflection deformation monitoring project when visualization of risk early warning information is realized according to the technical scheme of the invention.
Fig. 21 is a schematic diagram of a model for realizing a risk early warning information visualization project inspection in a certain project according to the technical scheme of the present invention.
Fig. 22 is a health diagnosis visualization overall interface for implementing engineering operation condition evaluation according to the technical solution of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The technical solution of the present invention will now be described in general with reference to fig. 1:
the platform consists of an information management platform, a data analysis platform and a visual display platform:
Specifically, the information management platform is the basis of the platform and is used for meeting the requirements of information acquisition and interactive support of users at each layer. The safety monitoring system is responsible for managing safety monitoring data, safety monitoring and alarm management and safety monitoring knowledge base management, and realizes the standardized processing of safety monitoring data, the safety monitoring risk management and control and the standardized filing of safety monitoring data. The management of the safety monitoring data comprises the following steps: the method realizes the collection, the pretreatment, the audit, the statistics and the storage of relevant data and records of safety monitoring, inspection tour and the like of each hydraulic structure. The safety monitoring and alarm management comprises the following steps: the aims of rapid alarm information prompt and accurate alarm information receiving and pushing are achieved by setting an information pushing mechanism for managing abnormal measuring points, fault equipment, process deviation, earthquake alarm, flood alarm, patrol result alarm or other abnormal state alarm information. The safety monitoring knowledge base management comprises the following steps: the collection, filing, classified retrieval and output of basic information data, document report data, operation and maintenance information and the like are realized.
Further, the platform presets various alarm states, alarm judgment conditions, alarm modes (such as short messages, WeChat and system platform alarm) and alarm receiving objects. The receiving and setting of the alarm pushing provides a plurality of options, supports selection according to departments or selection according to personnel, sets an information pushing mechanism of classification, classification and division, pushes the alarm information to receiving personnel preset by a platform, and achieves the aims of rapid alarm information prompting and accurate alarm information receiving and pushing. When the abnormal safety monitoring and alarm information occurs, the equipment is abnormal, the monitoring data is abnormal, the inspection work is abnormal, the inspection is abnormal, the important defects are found, the special working conditions and the important monitoring project operation is abnormal, and the like.
And 102, performing data comprehensive analysis and defect statistical analysis on corresponding data according to the primary processing result by the data analysis platform to obtain an operation condition evaluation result.
Specifically, the data analysis platform performs multidimensional analysis and specialized interpretation on the safety monitoring data and generates a corresponding result: carrying out digital processing and intelligent statistical analysis on inspection related data to generate corresponding data results, integrating the data results to generate data analysis result evaluation and defect grade result evaluation, and evaluating the running condition of the current project according to the data analysis result evaluation and the defect grade result evaluation.
103, performing visual display on the abnormal primary processing result, each monitoring information, the comprehensive analysis result, the inspection result, the engineering operation evaluation result and the risk early warning.
Specifically, the visual display platform is used for visual display of results. The method generates different patterns for displaying safety monitoring information, monitoring data and analysis results, inspection and statistical results, various alarming risk early warning information, and positions monitoring abnormity early warning information in a special scene, so that a user can timely find and position a place where an event is reminded to occur, and timely response and processing are performed on the event.
The special scene modeling can automatically select a 3D background design, a 2D and 3D combined design mode for free configuration according to different requirements of a user. The 3D background design needs to consider enough local geographic data resources on the spot, consider model resources and geographic resource data, provide technical guidance and theoretical direction as the actual manufacturing process in the later period, then collect texture information and model control proportion of main hydraulic buildings, and build three-dimensional visual models of all buildings by combining related design drawings. The 2D background design mainly utilizes a model and a programmed chartlet generated by programming to ensure the detail degree and the texture precision of the model and build a visual model.
Further, the safety monitoring information visualization platform provided by the present invention is described in detail with reference to fig. 2, as shown in fig. 2:
The visualization platform provided by the invention monitors a plurality of projects, namely project 1, project 2 and project … ….
Wherein the information and data obtained in steps 202 and 203 includes weather and seismic data relevant to the location of all the projects.
The platform acquires data information of the China meteorological office and the China earthquake office in real time through steps 202 and 203, and executes the step D of special working condition alarm when objective factors possibly influencing engineering safety appear in an engineering project area.
And step 204, the endoscopical instrument collects the data of the endoscopical instrument in real time.
The method comprises the following steps: the endoscopical instrument consisting of the seepage monitoring sensor group, the stress-strain monitoring sensor group, the pressure monitoring sensor group, the deformation monitoring sensor group and the strong earthquake monitoring sensor group acquires seepage information, stress-strain information, pressure/load information, deformation information and strong earthquake information in real time and integrates the seepage information, the stress-strain information, the pressure/load information, the deformation information and the strong earthquake information into endoscopical instrument data. The seepage monitoring sensor group comprises a seepage gauge, a water level gauge, a pressure measuring pipe and a flowmeter; the stress monitoring sensor group comprises a steel bar meter, a strain gauge, a steel plate meter, a stress-free meter and a thermometer; the pressure monitoring sensor group comprises a soil pressure gauge, an anchor cable dynamometer and an anchor rod stress meter; the deformation monitoring sensor group comprises a joint meter, a displacement meter and an inclinometer; the strong shock monitoring sensor group is an acceleration sensor.
And step 205, the appearance instrument collects appearance instrument data in real time.
The method comprises the following steps: and acquiring appearance deformation data in real time by a total station and meteorological acquisition equipment of the intelligent integrated station or a receiver and antenna equipment of the GNSS integrated station, and integrating the appearance deformation data into appearance data. Appearance data specifically includes, current real-time meteorological data, the instantaneous deformation condition of the body monitored at present.
And step 206, transmitting and summarizing appearance instrument and appearance instrument data.
The transmission of the monitoring data is realized by wired and wireless devices, for example, the technologies of Ftp, Web service, MySQL and the like are applied to realize the transmission and receiving services in the different networks, and the whole process of data acquisition, encryption, transmission, reception, decryption and warehousing is completed.
And step 207, receiving the acquired data by the platform according to a preset acquisition frequency.
For example, in a normal state, the platform acquires appearance instrument data and appearance instrument data according to the acquisition frequency of the first preset mode and performs subsequent processes, when an alarm caused by abnormal data occurs, the acquisition frequency is adjusted according to the alarm level, and the acquisition frequency is higher when the alarm level is higher.
And step 208, preprocessing the data of the appearance instrument and the appearance instrument.
Specifically, the pretreatment comprises the following steps: preprocessing an abnormal value, wherein the judgment criterion of the abnormal value comprises an instrument measuring range, a historical threshold, a design standard, a physical meaning and a 3 sigma fluctuation range.
The instrument range refers to the normal measurement range of the instrument, alarm information is sent out when the monitoring value exceeds the range (step A, equipment is abnormal and gives an alarm), the instrument is possibly damaged, and a worker or a platform is reminded to check the working state of the instrument.
And (C) a historical threshold value which refers to the maximum value (the maximum value reached in a normal state) in the historical monitoring data of the measuring points or the maximum change rate of the measuring points in a corresponding statistical period, the platform automatically calculates and updates the stored historical threshold value according to the historical monitoring process of the monitoring data, when the monitoring data exceeds the range of the historical measuring values, the platform gives an alarm (step B, the monitoring data alarms), and the abnormal data is determined to be reserved or discarded after being audited by technicians.
And (4) a design standard refers to design parameters of a monitored position of the building, and when the set related design parameters reach or are about to reach critical values, the platform gives an alarm (simultaneously executes the monitoring data alarm in the step B and the important monitoring project alarm in the step E) to remind a worker of checking the engineering state of a measuring point.
And the physical significance refers to the normal measurement value range of each type of monitoring item in the physical significance, an alarm mechanism is triggered for data exceeding a set condition, abnormal alarm of the equipment in the step A and alarm of the monitoring data in the step B are simultaneously executed, and the distortion of the monitoring data is prompted, wherein the condition is usually caused by the fault or failure of the monitoring equipment, so that a worker or a platform can check corresponding instruments in time.
The real and effective monitoring data can ensure the continuity and the integrity of the data series, the fluctuation of the data series does not exceed a certain range, and the invention adopts a +/-3 sigma fluctuation range. The +/-3 sigma fluctuation range is used for judging whether the data fluctuation monitored by the observer and the appearance instrument is normal or not, and starting an alarm mechanism for the data of the observer or the data of the appearance instrument which exceeds the range (step B), so that a worker is prompted to pay attention to the fact that the data is probably gross error or the operation condition of a monitored part corresponding to the data of the worker is prompted to change obviously.
Wherein σ is: and the standard deviation of the monitoring data series is that effective monitoring data series within nearly 1 year are selected to ensure smooth operation of the platform.
When the sensor monitoring data monitored by any one of the appearance instrument data and the appearance instrument data shows an abnormal state, starting the step B: and monitoring data abnormity alarming is carried out, so that abnormity alarming and interception are started for data exceeding the judgment standard, a worker carries out data auditing work according to the alarming information, acceptance or rejection of the abnormal data is confirmed, and the reserved monitoring data enters a platform database for calling and fetching various functional modules of the platform.
The running states of the equipment (including instrument equipment and network communication) comprise normal state, fault state, maintenance state and shutdown state, and judgment is carried out through equipment heartbeat, whether data are uploaded normally, conditions set manually and the like; when the equipment is in a fault, maintenance and shutdown state, the platform executes the step A: and (5) alarming the abnormality of the equipment.
And step 209, collecting frame image information of video monitoring.
And step 210, acquiring pictures and records of patrol inspection.
In steps 209 and 210, the manual recording data and the monitoring data of the patrol inspection of each hydraulic structure are mainly acquired and collected.
And step 211, carrying out standardized processing on the image information, the pictures and the recorded data.
Specifically, video monitoring and inspection tour inspection are uploaded to non-compliant image data, inspection tour records and photos of the platform to be intercepted, and workers are prompted to re-record related information.
The inspection work state of patrolling includes normally, late arrival, absence from duty etc. and the platform realizes the work state management through the positioning data of checking the card that acquires inspection personnel mobile terminal APP, if corresponding data is not gathered to the platform in step 210, then explains that the staff does not develop inspection work of patrolling on time, and the platform carries out step F operating condition and reports to the police, notifies relevant staff and managers.
And step 212, performing digital processing. The method mainly digitizes manual records and non-digitized images obtained from a patrol inspection APP so as to facilitate subsequent statistical analysis application.
Specifically, each patrol inspection record of daily patrol inspection includes contents such as patrol numbers, patrol dates, patrol structure parts, defect levels, patrol personnel, patrol characters, patrol pictures, defect processing states, defect processing results and the like. The system carries out data classification processing on a plurality of messy information and carries out system integration, thereby being convenient for automatically generating the inspection tour statistical analysis result in the set statistical period in the follow-up process.
The management of a safety monitoring knowledge base can be realized according to the acquired data, the safety monitoring knowledge base mainly relates to safety monitoring basic information data (such as design data, installation embedded records, instrument parameters and the like), document report data (such as briefing, reports, security certificates, acceptance check, registration, regular inspection and the like), operation and maintenance information and the like, and the safety monitoring knowledge base has the functions of global search, uploading/downloading, knowledge classification, list browsing, online check and the like, and enhances the practicability of a platform. Wherein the document management function includes: the personal document library can be automatically filed, and can also be used for additionally establishing a personal folder, so that all file information can be synchronized by multiple terminals; a team document library, a team common document library, such as a regulation and a regulation system, a business form template, post work attention and the like, and establishing team unified data; sharing the document; fourthly, exchanging experiences; the documents are associated, so that the related deep information of the documents can be conveniently known, and the summary sharing is convenient; document labels can flexibly set personal or team labels and set own exclusive classification; fast searching is carried out, and a desired file is found from multiple terminals; and (8) paying attention to the document.
And step 213, performing basic data statistics on the preprocessed data.
Specifically, the statistical characteristic values include an average value, a maximum value, a minimum value, a range, a variance, a standard deviation, and the like, and the statistical period includes day, week, month, season, year, and the like. The platform automatically selects a prefabricated and matched statistical period according to the data acquisition frequency, performs statistical calculation on the data and forms statistical data, and the statistical data is stored in a statistical database to realize the standardized and formatted storage of the monitoring data; meanwhile, the statistical data can be conveniently called during the subsequent data comprehensive analysis, and the response speed of the data analysis platform is improved.
And step 214, comprehensively analyzing the data.
The method comprises the following steps: including but not limited to temporal process analysis, statistical analysis of measured values, distribution analysis of measured values, variance analysis, rate of change analysis, correlation analysis, periodicity analysis, historical synchronization analysis, and typical event analysis. The method is suitable for data analysis of single-point, multi-point analysis of single-type monitoring data, comprehensive analysis of multi-type points and the like, a user can independently configure an analysis method, and a platform automatically calculates at regular time and generates an analysis result; meanwhile, manual personalized analysis is supported, a user can freely select an analysis method, and analysis results are checked at any time and stored for application.
Specifically, the method comprises the following steps:
time course analysis: the time is used as an abscissa, and the monitored data is used as an ordinate to draw a process line of the measured value changing along with the time. By inspecting the process line of the measured value, the rule of the measured value changing along with the time is known, and whether the change is periodic or not, whether the change trend is abnormal or not and the like are analyzed. The change process analysis of a plurality of measuring points or a plurality of project monitoring values can be compared to know the relation and difference among the measuring points or the project monitoring values.
A time course analysis is illustrated with one embodiment:
fig. 3 is a time course analysis curve of monitoring data 2012.1.1 to 2017.12.31 of a certain rockfill dam panel void gauge. As can be seen from the figure, the measured values of the void at the monitoring point position of the rock-fill dam panel 8 are all negative, which indicates that the panel has no void deformation; meanwhile, the monitoring data of TS-1-01, 02, 03, 04 and 07 is stable, and the fluctuation of the monitoring data of TS-1-08, 09 and 10 is large. Through time process analysis, the operation condition of panel void and the change situation of measurement can be mastered more clearly.
Statistical analysis of measured values: the platform calls characteristic values in the statistical database, can set a statistical period as an abscissa and any characteristic value as an ordinate, and draws a time distribution graph of the characteristic values of a single measuring point or a plurality of measuring points; the feature value type can also be set as the abscissa, and the distribution diagram of various feature values of a single measuring point or a plurality of measuring points in the set observation interval can be considered. Through characteristic value analysis, the change range of the measured value can be known; for the analysis of various characteristic values of different mutually related measuring points, the difference level of the measured values of the measuring points, the relation between the measured values and the main environmental factors and the like can be compared.
Statistical analysis of the measurements is illustrated using one embodiment:
fig. 4 shows the result of statistical analysis of measured values of a rockfill dam panel void gauge based on different statistical periods. As can be seen from the figure, the standard deviation of the air release gauge of each year at the monitoring point positions of 2012.1.1-2017.12.31 rock-fill dam panels 8 is 0.01-0.90 mm; in any year, the standard deviation of TS-1-08, 09 and 10 is higher than that of TS-1-01, 02, 03, 04 and 07, which shows that the data has large dispersion degree and severe fluctuation, and the phenomenon is particularly obvious in 2014. The results of this analysis statistically represent the data fluctuations seen in FIG. 1.
Fig. 5 shows the statistical analysis result of measured values of various types of characteristic values of a unidirectional joint meter for a rock-fill dam panel. As can be seen from the figure, the average value of the unidirectional joint meters at the monitoring point positions of the 2009.1.1-2010.12.31 rock-fill dam panels 9 is-0.47-3.24 mm, and the measured values of J-1-17, 18 and 19 are negative and are expressed as a pressed state; the measured values of the other measuring points are positive, and the state is shown as a tension state; the 9 unidirectional seam measuring scores are distributed at the same elevation of the panel, and under the action of water pressure, the stress of the opening degree of the panel seam is expressed as that two sides are pulled and the middle is pressed; the average value statistical result expresses the 2009-2010 average running condition of the joint meter with the same elevation of the panel under the stress characteristic. In the same way, the maximum value, the minimum value and the current value respectively represent the maximum level, the minimum level and the current level of the joint deformation in 2009-2010; the standard deviation represents the measured discrete level of seam deformation in 2009-2010.
And (3) analyzing distribution of measured values: analyzing monitoring data or characteristic values of the monitoring data of certain associated measuring points of a certain determined observation date or a certain observation time period, and drawing a spatial distribution map of the multiple measuring points by taking the measuring points as abscissa and the monitoring data or the characteristic values thereof as ordinate. By analyzing the distribution of measured values of multiple measuring points, the change of a certain monitoring index (such as dam seepage) along with the space (the distribution position of the multiple measuring points) is known, and the irregular distribution, the difference level among the measuring points and the like are known.
The analysis of the distribution of measured values is explained by means of a specific embodiment:
fig. 6 shows the distribution analysis result of the measured value of the saturation line of a typical monitoring section of a certain face rockfill dam. In the figure, the measuring points P-1-07, 25, 26, 28, 30, 31 and 32 are respectively osmometers embedded in a dam foundation of a main control section in the rock-fill dam body from upstream to downstream, and the measured values of all the osmometers are connected to show the distribution condition of the infiltration lines of the section. In addition, the analysis chart compares the distribution levels of the saturation lines in each year from 2010 to 2019 by setting different statistical periods, the saturation lines of the dam body of the observation section decline year by year, the performance of the saturation lines at the upstream (anti-seepage structure) of the dam body is obvious, and the gradual self-healing function of the leakage channel of the dam body is illustrated.
Analysis of variation: calculating the variation of the measuring points in a set statistical period, drawing a line graph or a distribution histogram and the like by taking the statistical period as a horizontal coordinate and the variation as a vertical coordinate, and intuitively mastering the time distribution of the main variation of the measuring points; for the analysis of the variation of the multiple measuring points, the variation of each measuring point can be compared, and the variation condition of each measuring point in different statistical periods can be known.
The variance analysis is now described with a specific embodiment:
FIG. 7 is the comparative analysis result of the measured value of the osmotic pressure monitoring point P-1-06 behind the toe board of a certain hydropower station. Selecting a statistical period from 2006-1-1 to 2020-12-31, calculating the variation of the measuring point in each year, and drawing a histogram. As can be seen from the figure, the measured value of the measuring point is reduced on the whole, the reduction range of the measured value is large in 2009-2015 years, and the reduction range of the measured value is gradually reduced in 2016-2020 years, which shows that the leakage level of the measuring point is gradually reduced along with the increase of the operation age of the project.
Fig. 8 is a comparison analysis result of monitoring value variation of an osmometer of a section 0+203 of a certain hydropower station dam. Selecting a statistical period of 2020.1.1-2020.12.31, and calculating the variation of each measuring point in 2020. As can be seen from the graph, all measured values of all measuring points show a decreasing trend in 2020, the measured point with the maximum variation is P-1-07, and the observed value is decreased by 4.68 kPa; the minimum variation occurrence measuring point is P-1-32, and the observed value is reduced by 0.03 kPa; except for the P-1-25 measuring point, the variation (reduction amplitude) of the osmotic pressure of the 0+203 section of the dam is gradually reduced from the upstream to the downstream of the dam body.
Analysis of rate of change: and counting the accumulated variation in a set counting period, and drawing a variation rate development process diagram by calculating the variation rate. Because most monitoring data of the monitoring instrument mostly show a periodic change rule, a relatively stable state of a measuring point can be judged by using a change rate analysis method.
The rate of change analysis is now described with a specific embodiment:
FIG. 9 shows the analysis result of the variation rate of the measured values of the osmometer and the reservoir water level behind the toe plate of a dam. It can be seen from the figure that the variation trend of the measuring point of the osmometer P-1-06 is consistent with that of the measuring point of the reservoir water level DC-1-01, but the variation rate is more stable than that of the reservoir water level, when the reservoir water level rises in the flood season of 7 months per year, the osmotic pressure is increased therewith, the reservoir water level drops in winter, the measured value of the osmometer also shows a negative variation rate, and the variation rate of the osmometer and the reservoir water level in the same period of each year is equivalent.
And (3) correlation analysis: analyzing two or more variable elements with certain relation or probability, automatically selecting a fitting function by a program according to the characteristics of the monitored data to draw a correlation distribution diagram and calculating a judgment coefficient R2Thereby measuring the degree of closeness of correlation of the two physical variable factors. Wherein R is2Is a measure of the goodness of fit of the estimated regression equation.
The correlation analysis is now described with a specific embodiment:
FIG. 10 shows the correlation between the channel bottom osmometer and the water level of a water diversion channel. As can be seen from the figure, the osmometer (P3-1) has strong linear correlation with the water level (DZ-2) of the canal, and the correlation coefficient R20.8183, the fitting function Y is 0.0994X +0.5819, which indicates that the measured value of the bottom leakage pressure varies with the water level of the channel, and the channel section is likely to have a leakage channel. The leakage condition of the part can be preliminarily judged by analyzing the correlation between the observed value of the canal bottom osmotic pressure and the water level of the canal at the corresponding part.
Periodic analysis: analyzing the statistical characteristic values of the monitoring point object and objective variables (such as reservoir level, temperature and the like) according to a certain set periodic variation interval (year, season, month and the like), arranging the periodic statistical results of a plurality of groups of data according to the sequence of objective variables from low to high, drawing a statistical value curve, obtaining the periodic variation rule of the dependent variables along with the objective variables, and inspecting whether the monitoring quantity is influenced by the objective factors or not.
The periodic analysis is now described with a specific embodiment:
FIG. 11 shows the results of a periodic analysis of the measured value of the back osmometer of a dam toe board. As can be seen from the graph, the whole observed value of the reservoir water level (DC-1-01) in 2010 to 2020 is 1390 to 1420m, the water level change range in each year is not obvious, but the measured value of the osmotic pressure (P-1-06) is reduced year by year, for example, the osmotic pressure in 2010 is 201.34kPa on average, the osmotic pressure in 2012 is 177.93kPa on average, the osmotic pressure in 2020 is 149.29kPa on average, and the reduction degree of the osmotic pressure is obvious. Periodic variation analysis visually shows the annual observation level of the measuring point of the rear toe board osmometer P-1-06 under the action of the water level factor, and is favorable for carrying out analysis and evaluation on the variation trend of a certain observation item under the action of a specific working condition.
Historical contemporaneous analysis: and comparing and analyzing the monitoring value of the measuring point and the historical synchronous measuring value of the set comparison period. For a long time, in the stable operation period of the engineering, the difference between the measured value of the instrument and the measured value of the same period of the past year is not large; in short term, the comparison of the measured values in the same period of the month, the season and the like can reflect the change of the measured values along with the time. The method takes the statistical time as an abscissa, draws a measuring point data histogram of a certain historical date, obtains the change rule of the historical contemporaneous measured value of the measuring point along with the time, and judges the deviation degree of the measured value compared with the historical contemporaneous measured value.
The historical contemporaneous analysis is illustrated with a specific embodiment:
fig. 12 shows the historical contemporaneous analysis result of the reservoir water level in the flood period of a certain hydropower station. The normal water storage level of the hydropower station is 1420m, the daily measured value of the dam body after water storage in the past 4 months and 30 months is counted, and the reservoir water level measured value in 2007-2020 is found to be in the range of 1390.49-1406.25 m. The highest reservoir water level in 2009 is 1406.25 m; the lowest reservoir water level in 2017 is 1390.49 m; the reservoir water level is 1393.73m in 2020. By adopting a historical contemporaneous change analysis method, the overall decline trend of the reservoir water level of the hydropower station before the year flood is very intuitively seen.
Typical event analysis analyzes the influence degree of a certain time or event on a building. The change of the external environment threatens the normal operation of the building, and when geological disasters such as earthquake, rainstorm (snow) and the like occur or a flood period passes, the building can be influenced to a certain extent. The system can position and give warning to the measuring points exceeding the set change standard by calculating the variation or the variation percentage of various types of monitoring data of all monitoring items before and after a certain event occurs and arranging the variation or the variation percentage according to the sequence from large to small. The method can comprehensively analyze the influence degree of the event on the building.
A typical event analysis is illustrated with a specific embodiment:
fig. 13 is a graph for analyzing the influence degree of an earthquake of a certain hydropower station on all monitoring projects of a project, wherein the graph shows the monitoring value change condition of the anchor dynamometer before and after the earthquake, and the measuring points are arranged according to the change rate from large to small. The influence of the earthquake on the anchor rod stress monitoring project of the power station is small, the change rate of most measuring points is within the range of 0.07-0.11%, and the change rate is small; only the RB-6-40-3 measuring point is affected to a large extent, the pre-earthquake value of the instrument is-2.97 MPa, the post-earthquake value is-3.43 MPa, and the measured change rate is 15.43%. Through the statistical analysis and sequencing of the measured values of the event, the influence degree of the event on the engineering can be macroscopically grasped, the position of a measuring point (RB-6-40-3) with a remarkable influence is positioned, and relevant workers are guided to the position of the measuring point to carry out engineering operation safety condition inspection.
In the data analysis methods provided above, different data analysis methods may perform the following partial or complete parameter configuration according to algorithm requirements: configurable "start-stop times"; configurable "watch points"; the "statistical period" (year, season, month, week, day) and the "statistical type" (mean, maximum, minimum, standard deviation) can be switched autonomously; calculating a selected statistical value type of a specified statistical period as a data source of an analysis chart; the statistical chart supports full screen viewing, printing or downloading (PNG, JPEG, PDF, SVG, etc. formats).
And step 215, obtaining data analysis result evaluation according to the comprehensive analysis result.
And comprehensively evaluating the analysis results of time process analysis, measured value statistical analysis, measured value distribution analysis, variation rate analysis, correlation analysis, periodicity analysis, historical synchronization analysis and typical event analysis according to preset grade evaluation indexes so as to evaluate the variation state of the project.
And step 216, performing defect statistical analysis on the inspection data to obtain a defect space-time distribution result.
Specifically, for the digitized processing result of the inspection tour in step 212, according to a preset statistical period, the platform will automatically perform statistical calculation as follows: statistics of inspection times of patrol in a specified time period; counting the number of defects in a specified time period; counting and sequencing the routing inspection defects according to different classifications (such as defect pile numbers, defect parts, defect types, defect grades and the like); and counting the defect processing condition and the current running state in a specified time period.
The platform can also realize the statistics of the patrol working conditions in the appointed time period, including the statistics of the work staff on duty and the patrol workload.
Through the content statistics, the platform can automatically carry out routing inspection information integration and statistical analysis, and a user can independently check and master the space-time distribution result of the defects. If the user specifies a part or a pile number, inquiring the whole process of defect discovery, development and repair at the part; or browsing the defect space distribution result of the specified defect type; or searching the defect space distribution of the set level.
The defect space-time distribution result comprises the defect discovery time distribution of the specified part, the defect development time distribution of the specified part and the defect repair time distribution of the specified part; and the method also comprises the defect space-time distribution of the specified defect type and the defect space-time distribution result of the specified defect grade.
The defect space-time distribution result is illustrated by taking a defect A in a building bearing column as an example: the method comprises the discovery time of the defect A at the bearing column, the development process from the discovery of the defect A at the bearing column to the time, the time and the times for repairing the defect A at the bearing column, the appearance time of the defect A at each position of the current building, and the distribution of the defect A with different or same defect grades in time and space.
And step 217, evaluating the defect level.
And determining the defect grade of the engineering operation according to the defect statistical analysis result in the step 216 (the platform divides the defects into four grades, namely I grade, II grade, III grade and IV grade), starting a major defect alarm program (step C) for the engineering defects reaching the III grade and above, and pushing the information of the inspected part, the defect type and the defect grade to related workers.
Further, the platform automatically generates a defect distribution report and a report (including a defect space-time distribution result) according to the statistical analysis result of the step 216, and pushes information to realize classification and alarm management of the defects.
Step 213 to step 217, integration and application of various specialized data analysis methods are realized, mainly safety monitoring data are integrated and counted, multi-dimensional comprehensive analysis is carried out on historical monitoring data, and historical development change rules of the hydraulic structure monitoring data are better revealed; carrying out digital processing on the inspection data, and carrying out statistical analysis on inspection defects to obtain inspection defect grade evaluation; the comprehensive analysis result of the comprehensive safety monitoring data and the statistical analysis result of the inspection information can provide scientific basis for evaluating the operation condition of the engineering, and the automatic safety monitoring work is more intelligently served.
And step 218, evaluating the current operation condition according to the analysis result and the defect grade.
And 219, visually displaying the monitoring information, the analysis result and the engineering health diagnosis conclusion.
Specifically, the modeling, the identification and the display of the special scenes of the hydraulic buildings are realized, and the contents (safety monitoring information, monitoring data and analysis results, inspection and statistical results, risk early warning information of various alarms and the like) of the information management platform and the data analysis platform of each hydropower station can be visually displayed in different categories.
Specifically, the method comprises the following steps:
the safety monitoring information is visualized, seamless connection and display of an engineering model and the safety monitoring information are realized, and a user browses or inquires the spatial positions of the measuring points, the parameters of monitoring instrument equipment, installation and burying information, measured values and process curves of the measuring points, a monitoring data distribution diagram, a monitoring point control distribution diagram and the like based on the engineering model in a thematic scene. And aiming at the multi-period monitoring result data, the dynamic digital simulation of the deformation process of the measuring points, the measuring lines and the sections is completed by combining a time axis.
For example, when entering a certain project, the platform presents an engineering model of the whole project, spatial position distribution, current measured value data and time process lines of all monitoring equipment on the model, and can view section control charts of different monitoring projects, browse parameters of each instrument and equipment, installation and burying information and the like. The platform can display monitoring information according to the type of the monitoring equipment, or display the monitoring information according to the structural part, or simply display the monitoring arrangement result of a certain monitoring section, and the like. In addition, the user can also perform historical query, and check the data results of any historical monitoring date by selecting the date to be queried.
Specifically, the method comprises the following steps:
fig. 14 is a visual layout diagram of an osmotic pressure monitoring project of a dam of a certain hydropower station, and firstly, the diagram shows an overall engineering model of the project, spatial layout positions of all osmometers on the model, current measured value data and the like, and the parameters, installation and burying information, historical process lines and the like of each instrument and equipment can be browsed by clicking measuring points; the dam 0+203 is selected to monitor the section, so that a section control chart of the osmotic pressure monitoring item shown in fig. 15 can be displayed, and the distribution of the wetting line of the section can be clearly understood from the section control chart. In addition, the user can also perform historical query, and check the data results of any historical monitoring date by selecting the date to be queried.
The data analysis result is visualized, seamless connection and display of the engineering model and the safety monitoring data analysis result are achieved, the analysis result is output in a visualized mode, and a user can check any data analysis result of each measuring point, measuring line, section and engineering project based on the engineering model in a thematic scene. The automatic analysis chart display and the corresponding prompt of the abnormal result in the special topic scene are realized, and the visual display of the intelligent analysis result of the monitoring engineering is really realized.
For example, when entering an engineering model of a special topic scene of a certain project, a user can select any monitoring point on the model, check the measured value statistical result and the data analysis result of the monitoring point in a right click mode, and select a certain measuring line or section to check the multi-point comprehensive analysis result of a certain type of monitoring project. Similarly, the platform displays the data analysis results up to the latest period by default, and the user can select parameters such as start-stop time, statistical period and the like to freely configure through historical query to obtain different analysis results.
Specifically, fig. 16 is a layout diagram of a dam horizontal displacement monitoring project of a hydraulic structure, a user can select a certain measuring point on a model, and after right click, the user can select different data analysis methods to analyze data of the measuring point and generate a data analysis chart; in a specific engineering monitoring section, a multi-point comprehensive analysis result of the whole monitoring project can be drawn, and the deformation distribution condition in the section can be clearly mastered through the equal-proportion connecting line of data of each point. The platform displays the data analysis results ending to the latest period by default, and a user can select parameters such as start-stop time, statistical period and the like to freely configure through historical query to obtain different analysis results.
The inspection result is visual, seamless butt joint and display of the engineering model, inspection information and inspection analysis result are realized, and a user can check the inspection point position, inspection detailed information and the like in a special scene. The platform acquires the card punching positioning data of the mobile terminal APP in real time, draws a patrol route map in a visual special topic scene, and displays patrol working conditions along the line. All inspection information is classified, counted and intelligently analyzed according to time, position, defect development process, processing state and the like, and the aims of digitized inspection result processing and defect rating of inspection are finally achieved.
For example, entering a special scene of inspection tour of a certain project, displaying the positions of inspection tour card punching positioning stake numbers of the hydropower stations by the platform, and checking different numbers to check inspection tour point stake numbers, inspection tour dates, inspection tour personnel, defect structure parts, defect types, character descriptions, pictures and video image data information of inspection tour; the patrol work route map of patrol workers can be checked, and the patrol work conditions (the on-duty conditions, the work completion conditions and the like of related workers) can be concerned in real time; and the digital processing and statistical analysis results of the inspection tour of the project can be checked in real time, and the time-space distribution result and the defect rating result of the inspection tour defects are visually displayed in a thematic scene.
Specifically, fig. 17 is an overall interface for visualization of the patrol inspection. Entering a special scene of inspection of a certain project, displaying the inspection punching card positioning post number position of the hydropower station by the platform, and checking different numbers to check the inspection point post number, the inspection date, the inspection personnel, the defect structure part, the defect type, the character description, the picture and video image data information and the like of the inspection; FIG. 18 is a statistical analysis result of inspection information of a certain diversion channel project in 12 months in 2020, the upper right corner of the statistical analysis result is in a pie chart form to count the number of times of finding various defects in the time period, and the time-space distribution result of the inspection defects is visually displayed in a special scene; FIG. 19 is a diagram of a work situation of a patrol inspection for a certain project, wherein a page visually shows a real-time patrol work route diagram of a patrol inspector, post numbers which have finished the patrol inspection are green, and uncompleted post numbers are gray, so that the patrol inspection work situation can be paid attention to in real time, the functions of checking the card and counting attendance of the patrol inspector are realized, and if the patrol inspector does not finish the patrol inspection task according to the specified time, the work situation can be triggered to give an alarm.
The risk early warning information is visual, and the platform can automatically carry out classification and classification statistics on various alarm information and carry out visual display. The method and the system realize real-time flicker of corresponding parts of various alarm information models in a thematic scene, display alarm statistical information of monitoring parts in a charting and visualization mode, have simple pages, are prominent in key points, are visual and easy to read, and facilitate managers to quickly acquire risk information and make decisions.
For example, entering an engineering model of a project topic scene, selecting a monitoring part, and displaying all monitoring points of the structural part by a platform. When the color of the monitoring point (equipment number) is green, the instrument equipment is normal, the red indicates that the instrument equipment has a fault, and the gray indicates that the monitoring instrument equipment is stopped; when the color of the monitoring data is green, the measured value is normal, and orange indicates that the measured value is abnormal. For a special scene of patrol inspection, the color of a patrol card punching position (a positioning pile number) is green to indicate no defect, red to indicate defect, yellow to indicate I-grade defect, light orange to indicate II-grade defect, dark orange to indicate III-grade defect, and red to indicate IV-grade defect. Through the visual page of the early warning information, the user can timely find and position the place where the abnormal event occurs so as to timely respond and process the event.
Specifically, fig. 20 is a layout diagram of measuring points of a flexural deformation monitoring project of a certain engineering panel, which shows all monitoring points and monitoring data of the structural part, wherein the colors of the monitoring points in the diagram represent the operating state of the monitoring equipment, green indicates that the instrument equipment is normal (such as measuring points TM-1-01, 02, 08 and the like), yellow indicates that the instrument equipment has a fault (such as measuring point TM-1-03), gray indicates that the monitoring instrument equipment is stopped (such as measuring points TM-1-09, TM-1-19, TM-1-21), blue indicates that the monitoring instrument is in a selected state, and the left side of a page correspondingly displays monitoring information (such as equipment information, data information, statistical information and the like) of the measuring point; the color of the monitoring data represents the measured value state of the monitoring data, green represents that the measured value is normal (such as measuring points TM-1-06, TM-1-23 and the like), and red represents that the measured value is abnormal (such as measuring points TM-1-03, TM-1-11 and TM-1-24); FIG. 21 is a model of a project inspection tour for a project, where the colors of the positions (numbers) of the tour pins are green to indicate no defect (e.g., numbers J1F-17 and J1F-19 of the pins), yellow to indicate class I defect (e.g., numbers J1H-05 and J1H-07 of the pins), light orange to indicate class II defect, dark orange to indicate class III defect, and red to indicate class IV defect. Through the visual page of the early warning information, the user can timely find and position the place where the abnormal event occurs so as to timely respond and process the event.
The engineering health diagnosis is visual, the platform can intensively display the data results of the key operation indexes of the engineering, automatically acquire various monitoring data comprehensive analysis results and inspection defect grade evaluation results, perform overall evaluation, obtain the evaluation results of the operation conditions of the whole engineering, and perform visual display.
FIG. 22 is an overall interface for project health assessment. The real-time data (such as water level indexes) of key operation indexes of various items of system integration are displayed in the figure, and the comprehensive analysis result of various monitoring data of the item and the inspection defect grade evaluation result are combined to obtain the conclusion that the health diagnosis result of the dam is normal and the stable analysis result of the side slope is normal.
Furthermore, the platform can set independent alarm conditions of key operation indexes (such as reservoir water level, gate difference water level, seepage flow, channel water level, flood receiving port water level, channel bank deformation and the like) according to the importance of monitoring items, and when the monitoring data of a certain index exceeds the set conditions, an important monitoring item alarm is started (step E). The alarm mechanism of the important monitoring project fully considers the actual operation condition of the project and the emergency response speed of personnel, a grading (early warning, alarming and emergency alarming) alarm program is set, the alarm information comprises a current measured value and a change rate, and the data acquisition frequency is correspondingly adjusted according to the alarm grade.
The safety monitoring information visualization platform provided by the invention can:
(1) the method has the advantages that the large amount of monitoring data and various data types of safety monitoring projects are effectively improved by utilizing the internet technology, and large-scale manual operation such as data identification, processing and analysis is realized;
(2) integrating a plurality of data analysis methods suitable for the safety monitoring field, and realizing intelligent application of the analysis methods on a software platform and visual display of analysis results;
(3) establishing a set of digital inspection system suitable for the safety monitoring field, realizing Bluetooth beacon card-punching inspection through the development of a refined inspection APP, and performing digital processing and visual display on inspection results;
(4) developing a safety monitoring specialized risk management and control tool and an information service model, and carrying out risk grading early warning and information pointing pushing aiming at abnormal measuring points, fault equipment, process deviation, earthquake warning, flood warning, inspection result warning and the like in the operation process of a building;
(5) the real-time dynamic safety evaluation analysis of the safety monitoring engineering operation is realized, the specific monitoring data can be deeply analyzed, the patrol inspection information can be systematically integrated, the engineering operation condition can be integrally and timely mastered, and the engineering safety problem can be prevented;
(6) the platform can be used for realizing the overall management of the multi-project safety monitoring work at the same time.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A security monitoring information visualization platform, the platform comprising:
acquiring project information, and acquiring weather forecast data, current weather data and earthquake information in real time;
an endoscopical instrument consisting of a seepage monitoring sensor group, a stress-strain monitoring sensor group, a pressure monitoring sensor group, a deformation monitoring sensor group and a strong earthquake monitoring sensor group acquires seepage information, stress-strain information, pressure/load information, deformation information and strong earthquake information in real time and integrates the seepage information, the stress-strain information, the pressure/load information, the deformation information and the strong earthquake information into endoscopical instrument data;
the method comprises the steps that appearance deformation data are obtained in real time by a total station and meteorological acquisition equipment of an intelligent integrated station or a receiver and antenna equipment of a GNSS integrated station and are integrated into appearance data;
acquiring frame image information of video monitoring, acquiring pictures and record information of inspection tour and digitizing;
monitoring whether the inside appearance data, the outside appearance data, the frame image information, the picture and the record information are normal or not in real time, otherwise, alarming, and sending alarm information to a worker to enable the worker to check the instrument corresponding to the corresponding data so as to realize the marking of fault equipment, the updating and correction of each data and the re-inspection to realize the updating of the frame image, the picture and the record information;
comprehensively evaluating and analyzing the appearance instrument data and the appearance instrument data to obtain data analysis result evaluation; wherein the comprehensive evaluation analysis at least comprises at least one of time process analysis, measured value statistical analysis, measured value distribution analysis, variation rate analysis, correlation analysis, periodicity analysis, historical synchronization analysis and typical event analysis;
carrying out digital processing and defect statistical analysis on the frame image information, the pictures and the recorded information to obtain a defect space-time distribution result and defect grade evaluation;
obtaining an operation condition evaluation result of the current project according to the data analysis result evaluation and the defect grade evaluation;
and respectively carrying out visual display on the operation condition evaluation result and the monitoring result on a model interface, wherein the visual display comprises the following steps: the method comprises the steps of generating a visual view of safety monitoring information for processed endoscopical instrument data and appearance instrument data, generating a visual view of inspection after the video monitoring and inspection information is processed in a digital mode, generating a visual view of data analysis for a comprehensive analysis result of the endoscopical instrument data and the appearance instrument data, generating a visual view of risk early warning information for the monitoring result, generating a visual view of engineering health diagnosis according to the operation condition evaluation result, and enabling workers to work on the next step according to the visual views.
2. The security monitoring information visualization platform of claim 1, comprising:
carrying out safety monitoring on the data of the appearance instrument and the data of the appearance instrument, wherein the safety monitoring comprises instrument measuring range, historical threshold and 3 sigma fluctuation range, and when any one of the instrument measuring range, the historical threshold and the 3 sigma fluctuation range is abnormal, an alarm mechanism is started;
specifically, if the data exceeds the instrument range, the staff is informed to check the corresponding instrument through information push;
if the current appearance instrument data and/or the appearance instrument data exceed the range of a historical threshold value, sending alarm information, and reserving or discarding the data, wherein the historical threshold value is the maximum value in the historical monitoring data or the maximum change rate in a corresponding statistical period;
and if the fluctuation range of the current appearance instrument data and/or the appearance instrument data is within +/-3 sigma, the normal working condition is established, and if not, an alarm mechanism is started.
3. The safety monitoring information visualization platform according to claim 2, wherein a special condition alarm mechanism is activated when abnormal weather and/or natural disaster information occurs in any one of the acquired weather forecast data, the current weather data and the earthquake information.
4. The safety monitoring information visualization platform according to claim 1, wherein the performing of the comprehensive evaluation analysis on the appearance instrument data and the appearance instrument data to obtain a data analysis result evaluation comprises:
and calculating the data of the appearance instrument and the data of the appearance instrument to obtain the average value, the maximum value, the minimum value, the range value, the variance value and the standard deviation value of the data of each sensor, and generating the visual views of the safety monitoring information of different evaluation indexes according to the average value, the maximum value, the minimum value, the range value, the variance value and the standard deviation value and the corresponding statistical period.
5. The safety monitoring information visualization platform of claim 1, wherein the performing of the comprehensive evaluation analysis on the appearance instrument data and the appearance instrument data comprises:
analyzing the time process, acquiring the data of the appearance instrument and the data of the appearance instrument of the monitoring values of a plurality of measuring points or a plurality of projects, and acquiring the corresponding change process;
the statistical analysis of measured values, compare various characteristic values of different measuring points correlated with each other, get the difference level of the measured value of each measuring point and its relation with environmental factor;
measuring value distribution analysis, namely acquiring a change rule and acquiring a difference level between each measuring point according to the distribution condition of the inner appearance data and the outer appearance data following the measuring points;
analyzing the variation, namely acquiring the variation trend of each measuring point in different statistical periods;
analyzing the change rate, namely judging the relatively stable state of the measuring point by using a change rate analysis method;
performing correlation analysis, selecting at least two data with correlation for analysis, selecting a fitting function by a platform according to the data characteristics of the data to draw a correlation distribution diagram and calculating a judgment coefficient R2Thereby obtaining the correlation degree of the data with correlation.
6. The safety monitoring information visualization platform of claim 1, wherein the comprehensive evaluation analysis of the appearance instrument data and the appearance instrument data further comprises:
the method comprises the steps of periodic analysis, wherein characteristic values of monitoring point objects and objective variables are analyzed in a periodic variation interval to obtain a periodic variation rule of dependent variables along with the objective variables;
historical synchronization analysis, namely comparing and analyzing the monitoring value of the measuring point and a historical synchronization measured value of a set comparison period;
and analyzing the influence degree of the specific factor on the building to obtain the influence degree of the specific factor on the building.
7. The safety monitoring information visualization platform according to claim 1, wherein the step of performing digital processing and defect statistical analysis on the frame image information, the picture and the record information to obtain a defect spatio-temporal distribution result and a defect grade evaluation comprises:
the defect space-time distribution result comprises the defect discovery time distribution of the specified part, the defect development time distribution of the specified part and the defect repair time distribution of the specified part; the method also comprises the steps of specifying defect space-time distribution of defect types and specifying defect space-time distribution results of the grades of the defects;
and the defect grade evaluation result platform comprises 4 defect grades of engineering operation, namely I grade, II grade, III grade and IV grade, and starts an alarm mechanism and pushes information for the engineering defects reaching the III grade and above so as to realize defect grading and alarm management.
8. The safety monitoring information visualization platform according to claim 1, wherein the visually displaying the operation condition evaluation result and the monitoring result on a model interface respectively comprises:
a safety monitoring information visualization view of an engineering model in combination with the processed appearance data and/or the appearance data;
the visual inspection view of the engineering model, the video monitoring information and the digital inspection result is combined;
a data analysis visualization view of the engineering model in combination with the results of the comprehensive analysis of the appearance instrument data and/or the appearance instrument data;
a risk early warning information visualization view combining the engineering model and the alarm information details;
and the engineering model and the operation condition evaluation result are combined to form an engineering health diagnosis visual view.
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