CN112800602A - Integral visual analysis method for safety monitoring data - Google Patents
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Abstract
The technical scheme of the invention provides an integral visual analysis method of safety monitoring data, which is characterized in that different evaluation indexes are selected, calculation, comparison and analysis are carried out on measured value data of a plurality of monitoring points of each type of monitoring project in an engineering structure, the analysis result is vividly displayed in a measuring point distribution scene in the form of a heat point diagram, and the current states of a plurality of measuring points of a certain monitoring type and the change condition of each time period are visually displayed by hot point icons (represented by circles taking corresponding monitoring points as centers) with different color differences and intensities. Meanwhile, the method is applied to statistical analysis of data, and the analysis depth of the monitoring data is increased. The management of mass monitoring data is realized by adopting an information technology, and the monitoring data and the analysis result thereof are displayed in a visual mode, so that the safety monitoring work is more efficient and professional.
Description
Technical Field
The invention relates to the field of safety monitoring, in particular to an integral visual analysis method for safety monitoring data.
Background
In recent years, with rapid development of information technologies such as internet, cloud computing and internet of things, the whole world has entered a big data era, and mass data generated by various industries is never available. The existing value of mass data is transmitted through a reasonable expression mode after the mass data is processed and information is mined.
In the field of automatic safety monitoring, building structures are generally complex, and the number of sensor types and hot spots for structure monitoring is large; with the increase of the service life of the monitoring instrument, the amount of monitoring data is increasingly huge, various types of monitoring data have complex structures, and engineering technicians and operation managers often need a great amount of time and energy to process and analyze the monitoring data so as to understand the deep physical meaning of the monitoring data and further master the real operation state and potential risks of the building.
Currently, the disposal of the monitoring data is performed by establishing a system platform. The functions that can be realized by each program module of the existing platform include: collecting and storing monitoring data; calculating statistical parameters (such as average value, maximum value, minimum value, standard deviation and the like); performing analysis display of statistical results by using a data visualization chart (such as a line chart, a bar chart, a scatter chart, a bubble chart and the like); in order to make the monitoring data information intuitive and easy to understand, some platforms realize the association between the monitoring data and the monitoring points on the graph or the model by using a visual graph or establishing a visual model, and perform real-time dynamic display on the monitoring data.
The existing system platform calculates statistical parameters of monitoring data and expresses data characteristics of statistical analysis results in a visual chart form. The charts are generally relatively comprehensive statistical analysis results of single-point or multi-point long-series monitoring data, but users are often required to be familiar with engineering (for example, know the distribution positions of hot points in the charts) and have certain safety monitoring professional knowledge (for example, the analysis results of various charts can be read) to understand the monitoring information conveyed by the visual charts. Therefore, the form of the data visualization chart is more suitable for technical personnel to carry out professional analysis and scientific judgment, and certain data understanding difficulty still exists for common workers of common users.
Further, the existing evaluation methods mostly use "dispersion coefficient" (variation coefficient) in probability theory and statistics to represent a normalized measure of the dispersion degree of the data series distribution, which is defined as the ratio of standard deviation to average value.
Wherein σ is the standard deviation of the observed data series; μ is the average of the observation series. However, the discrete coefficient (coefficient of variation) is defined only when the average value is not zero, and is generally applicable to a case where the average value is larger than zero. In the field of safety monitoring data analysis, if the statistical mean value of the safety monitoring data has a zero value or a negative value, the discrete expression of the monitoring data cannot be realized by the variation coefficient.
Some system platforms dynamically display monitoring data in real time in a visual scene by using visual graphics or building visual models. The platforms of the programs achieve comparison of monitoring data and structural parts, and users of all types of floors can visually know monitoring states of buildings. However, this visualization mode only allows visual display of monitoring arrangement and real-time update of monitoring data, and cannot perform comparative evaluation of the current monitoring data state and the historical monitoring state. Such as the degree to which the current operating conditions have reached the average operating conditions of the last year (or the entire monitoring period); if the external load is increased under the current special working condition, the change of the monitoring data of the structure can reflect the influence degree of the event; however, in the existing visualization form, only real-time data display is performed, and the current monitoring condition cannot be compared with a normal monitoring condition (which means a monitoring condition that is not affected by a special working condition), and the influence degree of the event on the data can be visually displayed. Therefore, the current visualization form is insufficient in professional expression.
Therefore, it is an urgent need to provide a data analysis method that compensates for the unsuitability of the dispersion coefficient (coefficient of variation) for the evaluation of the discreteness of the monitored data, can perform systematic analysis and evaluation on the trend and discreteness of the monitored data, can reduce the difficulty in understanding the data, and can enable non-professionals to intuitively understand the operating state of the monitored data according to the displayed data result.
Disclosure of Invention
The invention provides an integral visual analysis method of safety monitoring data, which is used for solving the problems that the data displayed by a professional map in the prior art is difficult to understand and is not beneficial to non-professional understanding, and also saving the time for manually integrating measuring point information and comparing and analyzing results.
In order to achieve the above object, the present invention provides an overall visual analysis method for safety monitoring data, which includes: and collecting all historical data and real-time dynamic update data of the monitoring points, and selecting monitoring items and evaluation indexes. Calculating and obtaining corresponding data results according to the selected monitoring items and the selected evaluation indexes, wherein the evaluation indexes comprise a current value, a mean change rate, a mean ratio, a dispersion rate, a fluctuation rate and a range ratio; the monitoring items comprise at least one item of reservoir water level, seepage flow, reinforcing steel bar stress, concrete strain, soil pressure and the like.
And generating a hotspot graph according to at least one of the obtained data results of the current values of the monitoring items, the data result of the mean change rate, the data result of the mean ratio, the data result of the discrete rate, the data result of the fluctuation rate and the data result of the range ratio, and obtaining an analysis result according to the radius of a point on the hotspot graph. And the radius is in proportional relation with the current value, the mean change rate, the mean ratio, the dispersion rate, the fluctuation rate and the range ratio respectively.
Preferably, the obtaining of the mean change rate includes:
wherein x is the current value of the observed data,
is the average of the observed data under the conditions.
Preferably, the obtaining of the mean ratio includes: obtaining the average value of the observation data series in the i-th year
Obtaining the average value of each data in the observation data series
Preferably, the calculating of the dispersion ratio includes:
in the formula (I), the compound is shown in the specification,
to observe the standard deviation of the data series for year i,
for the whole observationMean values from series.
Preferably, the fluctuation ratio calculation includes:
in the formula (I), the compound is shown in the specification,
standard deviation, x, for year i of the observed data seriesmax、xminRespectively, the maximum and minimum values of the whole observation data series.
Preferably, the calculation of the range ratio includes:
in the formula (I), the compound is shown in the specification,
maximum and minimum values, x, of year i of the observation data seriesmax、xminRespectively, the maximum and minimum values of the whole observation data series.
Preferably, in the above-described aspect, generating a hotspot graph from at least one of the obtained current value data result, the obtained mean change rate data result, the obtained mean ratio data result, the obtained discrete rate data result, the obtained fluctuation rate data result, and the obtained range ratio data result, and obtaining an analysis result from a radius of a point on the hotspot graph includes: calculating and obtaining corresponding data results according to the selected monitoring items and the selected evaluation indexes, wherein the data results comprise: the current value of the reservoir water level, the mean change rate of the reservoir water level, the mean ratio of the reservoir water level, the dispersion rate of the reservoir water level, the fluctuation rate of the reservoir water level and the range ratio of the reservoir water level; the current value of the seepage flow, the mean change rate of the seepage flow, the mean ratio of the seepage flow, the dispersion rate of the seepage flow, the fluctuation rate of the seepage flow and the range ratio of the seepage flow; the stress of the steel bars is measured according to the current value, the mean change rate, the mean ratio, the dispersion rate, the fluctuation rate and the range ratio of the stress of the steel bars; the concrete strain is measured by the following steps of (1) measuring the current value of the concrete strain, the mean change rate of the concrete strain, the mean ratio of the concrete strain, the dispersion rate of the concrete strain, the fluctuation rate of the concrete strain and the range ratio of the concrete strain; the current value of the soil pressure, the mean change rate of the soil pressure, the mean ratio of the soil pressure, the dispersion rate of the soil pressure, the fluctuation rate of the soil pressure, the range ratio of the soil pressure and the like;
and generating a single index hotspot graph by any one of the data results for analysis, or combining more than two of the data results to generate a composite index hotspot graph for analysis.
Preferably, the obtaining of the analysis result according to the radius of the point on the hot spot map includes: the radius of each point on the heat point diagram represents at least one data result of a current value, a data result of a mean change rate, a data result of a mean ratio, a data result of a dispersion rate, a data result of a fluctuation rate and a data result of a range ratio, and different colors are set to represent the state, the change trend or the dispersion degree of the data results.
The technical scheme of the invention provides an integral visual analysis method of safety monitoring data, which is characterized in that different evaluation indexes are selected, calculation, comparison and analysis are carried out on measured value data of a plurality of monitoring points of each type of monitoring project in an engineering structure, the analysis result is vividly displayed in a measuring point distribution scene in the form of a heat point diagram, and the current states of a plurality of measuring points of a certain monitoring type and the change condition of each time period are visually displayed by hot point icons (represented by circles taking corresponding monitoring points as centers) with different color differences and intensities. Meanwhile, the method is applied to statistical analysis of data, and the analysis depth of the monitoring data is increased. The management of mass monitoring data is realized by adopting an information technology, and the monitoring data and the analysis result thereof are displayed in a visual mode, so that the safety monitoring work is more efficient and professional. Compared with the traditional data analysis chart, the method and the device have the advantages that the abstract data information is converted into the graphic language, the expression mode of the data information is enriched, and the readability of the data information is improved; therefore, the difficulty of understanding the monitoring data by the user is reduced, and the cognition of the user on the data analysis result is enhanced. And by utilizing the computer technology, the data analysis result can be rapidly acquired in real 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 an overall visualized analysis method of safety monitoring data according to an embodiment of the present invention.
Fig. 2 is a time course line graph of the reservoir level from 2005.6 months to 2019.6 months.
Fig. 3 is a time course plot of seepage from 2005.6 months to 2019.6 months.
FIG. 4 is a graph showing the results of a mean ratio analysis of the data shown in FIGS. 2 and 3.
FIG. 5 is a graph of a dispersion ratio analysis of reservoir water level and seepage.
FIG. 6 is a graph showing the results of discrete analysis of R-1-08 (steel bar stress) monitoring data using a volatility indicator.
FIG. 7a is a graph of the results of comparative analysis of the dispersion of reservoir levels using volatility and dispersion indicators.
Fig. 7b is a graph showing the result of comparative analysis of the dispersion of the seepage amount using the fluctuation ratio and dispersion ratio index.
FIG. 8 is a graph showing the results of comparative analysis of the fluctuation of the R-1-08 (steel bar stress) monitoring data using the difference ratio and the fluctuation rate index.
Fig. 9 is a hot spot diagram of the current value evaluation index of the osmotic pressure observation item.
Fig. 10 is a hot spot diagram of the evaluation index of the mean change rate of the osmotic pressure observation item.
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 present application will now be described in detail with reference to specific embodiments:
first, a preliminary explanation is made, as shown in fig. 1, fig. 1 is a flowchart of an overall visualized analysis method of safety monitoring data according to an embodiment of the present invention:
step 101, collecting monitoring data.
The mainly acquired monitoring data comprises two parts of all historical data and real-time dynamic updating data, and the two parts of data jointly form a basic database for heat point diagram data analysis, so that the heat point diagram display service is provided for further statistical calculation, data analysis and heat point diagram display.
Specifically, the monitoring data includes: seepage monitoring data, deformation monitoring data, stress-strain monitoring data, pressure/load monitoring data and the like.
And 102, selecting a monitoring item.
And selecting a monitoring project to be analyzed and different evaluation indexes under the safety monitoring engineering, and entering a selected evaluation index display interface under the hotspot distribution of the monitoring project. Monitoring items are freely configured according to user requirements, such as seepage, deformation, stress strain, pressure/load monitoring items and the like.
Monitoring items include, but are not limited to, combinations of one or more of the following: reservoir water level, seepage flow, reinforcing steel bar stress, concrete strain, soil pressure and the like.
And 103, selecting an evaluation index.
The evaluation indexes include: current value, mean rate of change, mean ratio, dispersion ratio, fluctuation ratio, and range ratio. The user can independently add other evaluation indexes according to the requirement. The evaluation indexes can help explain the physical meaning of the change of the safety monitoring data, reveal the distribution change rule and the running state of the monitoring indexes in different dimensions of time and space, and are the core content of the analysis method of the safety monitoring data hotspot graph of the hydraulic structure. The current value refers to the latest observed data value of the monitoring point and is a reflection of the current operation state of the building. Through the index, the user can clearly master the real-time operation condition of the building.
And step 104, performing corresponding calculation according to the monitoring items selected in the step 102 and the evaluation indexes selected in the step 103, and obtaining a data result.
Wherein, the calculation comprises: calculating the mean change rate, calculating the mean ratio, calculating the dispersion ratio, calculating the fluctuation ratio and calculating the range ratio.
And 105, generating a heat point diagram according to the data result and displaying the heat point diagram.
And 106, acquiring an analysis result and an evaluation result according to the heat point diagram.
Specifically, the current value in step 103 is specifically: the latest observed data value of the monitoring point is the reflection of the current operation state of the building. Through the index, the user can clearly master the real-time operation condition of the building.
The calculation of each evaluation index mentioned in step 104 will now be described in detail:
1. for mean change rate:
the mean change rate is the ratio of the difference between the current observed value and the statistical mean of the observed data under certain operating conditions to the absolute value of the statistical mean, expressed in percentage. The index quantifies the degree of change in the current operating conditions of the building from the average operating conditions under certain conditions. By the index, the user can clearly know the degree that the current operation state of the building reaches the general operation state of the building under the set operation condition, and the level that the current operation state exceeds or is lower than the general operation state is quantitatively represented.
In the above formula, R is the mean change rate, x is the current value of the observed data,
is the average of the observed data under the conditions. When R is a positive value, it indicates that the current operating condition exceeds the level of the general operating condition, and when R is a negative value, it indicates that the current operating condition is lower than the level of the general operating condition.
It should be noted that: the 'certain conditions' in the application refer to time conditions, working condition conditions and the like closely related to safety monitoring, can be set by a user independently, and are calculated independently without mutual interference.
The time condition refers to a certain monitoring time period in history which has statistical significance on monitoring data analysis. The method mainly carries out comparative analysis on the current running condition of a certain type of monitoring project and the average running condition of a certain historical monitoring period. The system can be configured autonomously according to the statistical cycles of months, seasons, years and the like according to the requirements of users (for example, time periods of '1 month', '3 seasons', '1 year', '3 years', '5 years' and the like are set), when a certain time period (for example, '3 seasons') is selected by the user as a time condition for calculating a mean value or other numerical values, the system respectively calculates the historical monitoring data mean value of each measuring point of a specified monitoring item in the statistical time period as a comparison value, and then calculates the change rate of the current value and the comparison value of the corresponding measuring point as the data basis of a sorting table and a hot point diagram.
The operating condition refers to an action condition (independent variable) having a continuous influence on the currently analyzed monitoring item. The method mainly carries out comparative analysis on the current running condition of a certain monitoring project and the historical average running condition under the action of a certain working condition. The system can automatically configure working condition according to user requirements, when a user selects a certain working condition as the working condition of the calculated mean value, the system respectively calculates the historical monitoring data mean value of each measuring point of the specified monitoring item under the selected working condition as a comparison value, and then calculates the change rate of the current value and the comparison value of the corresponding hotspot as the data basis of the sorting table and the hotspot graph.
The average change rate evaluation index is used for comparing and evaluating the current monitoring data state and the historical monitoring state, so that some key problems in the safety monitoring field can be well solved, such as the degree of comparing the current running state to the average running state in the last year (or the whole monitoring period); if meet special operating mode at present, external load increases, and the monitoring data change of structure can reflect the influence degree of this incident, has solved and has only carried out real-time data show after current visualization, can't compare current monitoring situation and normal monitoring situation (the monitoring situation that does not receive the special operating mode influence) to the problem that the influence degree of this incident is audio-visual shows.
2. For the mean ratio Mi：
The mean ratio is the ratio of the annual mean value to the perennial mean value of the long series of monitoring data and is a measure of the annual variation trend of the monitoring data.
Obtaining the average value of the observation data series in the i-th year
Obtaining the average value of each data in the observation data series
i is the year number of the observation series.
Specifically, for the mean ratio: FIG. 2 is a time course line of reservoir water level from 2005.6 months to 2019.6 months, and it can be seen from the curve that the annual variation rule of reservoir water level is that the annual low value is reached at the end of 1 quarter, the annual high value is reached at the end of 3 quarters, each year is periodically changed, and the data trend is relatively stable; fig. 3 is a time course line of the seepage flow from 2005.6 months to 2019.6 months, and the seepage flow observation data also show periodic changes as a whole, but the whole trend shows a decrease. However, this is only the data variation trend seen from the time process line, and there is no quantitative index expression.
FIG. 4 is a mean ratio analysis of the two sets of observations (FIG. 2 and FIG. 3). The graph in fig. 4 shows that the annual average ratio of the reservoir water level is around 1.0, and the annual average ratio measurement value presents a stable straight line, which shows that the annual measurement values of the reservoir water level are equivalent (close to the general level of the whole series), and no obvious variation trend exists; the mean ratio of the seepage flow is reduced from 1.7 in 2007 to 0.6 in 2019, the measured value of the mean ratio year by year is presented as a descending curve, which shows that the seepage flow is gradually reduced year by year, and the change trend is descending. Therefore, it can be known that the mean ratio index measures the change trend of the monitored data every year, and is a beneficial index for evaluating the data trend.
3. For the dispersion ratio Yi：
The dispersion ratio is the ratio of the annual standard deviation to the annual mean of a long series of monitored data, expressed as a percentage, and is a measure of the normalized level of dispersion of the annual monitored data.
Wherein i is the year number of the observation data series;
standard deviation for year i of the observation data series;
is the average of the whole observation series.
The invention is used for evaluating the normalization level of the discrete degree of the observed data of each year by counting the annual standard deviation of the long series of observed data and respectively calculating the ratio of the annual standard deviation to the average value of the years.
FIG. 5 is a graph of a dispersion ratio analysis of reservoir water level and seepage. The change trend of the data of the reservoir level in each year is stable, and the discreteness of each year is relatively small (the statistical mean value of the dispersion rate of the reservoir level in 2007-2019 years is 0.54%, and the dispersion rate of each year is in the range of 0.29% -0.91%); the dispersion of the annual data of the seepage flow is larger than the reservoir water level (the statistical mean value of the annual seepage flow dispersion rate is 10.59% in 2007-2019, and the annual dispersion rate is in the range of 0.89% -16.01%), meanwhile, it is noted that in 2011, a seepage flow process line is presented as a section of a relatively stable straight line (actually, the observed database is inaccurate), however, from the aspect of data statistics, the observed value of the seepage flow in the period is not obviously fluctuated, the dispersion rate in 2011 is 0.89%, and is the minimum value of a statistical series, and the statistical index also reflects the abnormal condition in the period. Therefore, it can be seen that the dispersion ratio index measures the normalized level of the data dispersion degree of the monitoring data in each year, and is a beneficial index for evaluating the data dispersion.
According to the collected historical data and the combination of the calculation method, the overall visual analysis method for the safety monitoring data provided by the technical scheme of the invention can achieve the purposes of obtaining the quantitative result of the reservoir level and seepage flow variation trend by using the mean ratio index and obtaining the quantitative result of the reservoir level and seepage flow distribution dispersion by using the dispersion ratio index.
4. For the fluctuation ratio Si：
The fluctuation rate is the ratio of standard deviation per year to pole deviation per year of long-series monitored data, expressed as a percentage, and is a measure of the degree of dispersion of the monitored data relative to the fluctuation per year.
Wherein i is the year number of the observation data series;
standard deviation for year i of the observation data series; x is the number ofmax、xminRespectively, the maximum and minimum values of the whole observation data series.
The invention is used for evaluating the discrete degree of relative fluctuation of observation data of each year by counting the annual standard deviation of long series of observation data and respectively calculating the ratio of the annual standard deviation to the annual range deviation.
The fluctuation ratio and the range ratio will be described by taking the analysis of the stress of the reinforcing bars as an example, as shown in fig. 6 and 8.
FIG. 6 is a graph showing the results of discrete analysis of R-1-08 (steel bar stress) monitoring data using a fluctuation rate index. The statistical mean of the series is 0 as shown in fig. 6, the discrete coefficient is meaningless; the dispersion of R-0-08 is analyzed by adopting the fluctuation rate, the data fluctuation range in 2010 and 2016 is small, the dispersion degree is low, and the calculated fluctuation rates are 17.7% and 11.5% respectively; the data fluctuation range in 2012 and 2014 is large, the dispersion degree is high, and the calculated fluctuation rates are 25.6% and 24.9% respectively; the discrete rate index can quantify the discrete degree of the relative fluctuation of the data, and under the condition that the mean value of the analysis data series is zero or negative, the extreme difference is used for replacing the mean value, the degree of normalization of the discreteness of the data series is measured, and the feasibility is realized.
Further, according to the current data and the historical data of the collected reservoir water level and the collected seepage quantity, the following comparative analysis results are obtained by adopting the calculation mode of the fluctuation rate and the dispersion rate:
fig. 7a is a graph of the result of comparative analysis of the dispersion of reservoir water level by using the fluctuation rate and the dispersion rate index, fig. 7b is a graph of the result of comparative analysis of the dispersion of seepage flow by using the fluctuation rate and the dispersion rate index, and it is seen from the analysis curve that the trends of the analysis results of the two indexes are consistent, and the trend is more intuitive compared with the time line used in the prior art and is easy to understand by non-professionals.
5. For the pole difference ratio:
the range ratio is the ratio of annual range to perennial range of long-series monitored data, and is a measure of the relative fluctuation degree of the annual monitored data.
In the formula (I), the compound is shown in the specification,
maximum and minimum values, x, of year i of the observation data seriesmax、xminRespectively, the maximum and minimum values of the whole observation data series.
FIG. 8 is a diagram of the results of comparative analysis of the fluctuation of the R-1-08 (steel bar stress) monitoring data using the range ratio and the fluctuation rate index, wherein the range ratio actually expresses the quantitative index of the relative fluctuation degree of the monitoring data in each year. As seen from the analysis curves, the trend of the fluctuation results of the range ratio and the fluctuation rate in FIG. 8 is consistent throughout the years of analyzing the R-1-08 monitoring data.
Furthermore, the definition of the two indexes is easy to define, the range ratio is defined as the ratio of the range of the monitoring data in each year to the range of the monitoring data in many years, and the annual range is the absolute fluctuation quantity of the monitoring data in each year; the fluctuation rate is the ratio of the annual standard deviation and the annual range deviation, the standard deviation is the average value of the distances of the annual monitoring data of the monitoring data, and therefore the range ratio index reflects more intensely than the fluctuation rate index.
Then, different patterns of hotspot patterns are generated according to the obtained calculation results, wherein the hotspot pattern patterns include but are not limited to patterns shown as a current value hotspot pattern of the osmotic pressure in fig. 9 and a mean change rate hotspot pattern of the osmotic pressure in fig. 10.
In fig. 9 and 10, the light color represents a positive state or the change rate is in an increasing state, and the dark color represents a negative state or the change rate is in a decreasing state. And the current value heat point diagram generated according to the current value is an analysis display of the current running condition of each measuring point of a certain type of monitoring project. Specifically, on each measuring point of the measuring point distribution diagram, the relative size of the current monitoring value is represented by the radius of the circle, the data information of the current measuring value is visually expressed on the distribution positions of all hot points of the current monitoring item, and a user clearly grasps the overall measuring value distribution of the monitoring item and quickly positions the positions of the salient points or the abnormal points. Because the monitoring data has symbols which represent the direction of the monitoring data, circles with different colors can be used for representing the monitoring direction of the current measured value, blue represents that the current value is positive, and the measuring point is pulled or displaced in the positive direction; orange indicates that the current value is negative and the station is stressed or shifted in the negative direction. And when the mouse is placed in the range of the hotspot icon, the current value data of the measuring point is displayed. Meanwhile, the system sorts all the measuring points to be analyzed from large to small, and the interface displays a positive observation value sorting table and a negative observation value sorting table in real time respectively, wherein the positive observation value sorting table and the negative observation value sorting table comprise sorting, measuring point numbers and current values. Particularly, the display scale of the hot spot icon of each measuring point can be automatically zoomed according to the requirement of a user so as to achieve the best visualization effect.
For the hotspot graph generated according to the mean value change rate, the relative size of the change rate of the current monitored value compared with the mean value of the monitored data under a certain condition is also represented on each measuring point of the measuring point distribution graph by using the radius size of a circle, and the data information of the change rate of the current measured value compared with the mean value of the monitored data under a certain condition is visually expressed at the distribution positions of all measuring points of the current monitored item.
The hot spot graph generated by the mean change rate is a comparative analysis display of the current operation state of each monitoring point of a certain monitoring project and the mean operation state under a certain condition. In the hot spot diagram, circles with different colors are used for representing the comparison condition between the current measured value and the average value of the monitoring data under a certain condition, and yellow represents that the current observed value is increased compared with the average value of the observation data under a set comparison condition; green indicates that the current observed value is reduced compared with the average value of the observed data under the set contrast condition. And placing the mouse in the range of the hot spot icon, and displaying the current value, the contrast value and the change rate of the measuring point. The system sorts all the hot spots analyzed currently according to the change rate from large to small, and the interface displays a change rate sorting table in real time, wherein the change rate sorting table comprises sorting, measuring point numbers and change rates. Likewise, the hotspot icons of the measuring points can be freely scaled in equal proportion.
And for the hot spot graph generated according to the mean ratio, comparing, analyzing and displaying the annual average running condition and the annual average running condition of the monitoring points of a certain type of monitoring projects. On each measuring point of the measuring point distribution diagram, the relative size of the mean value ratio is represented by the radius of a circle, and data information of the ratio of the mean value of the selected year monitoring data to the average value of the years is visually represented at the distribution positions of all measuring points of the current monitoring project. Circles with different colors are used for representing the deviation degree of the mean value of the monitoring data of all measuring points of the current monitoring project in a selected year from the mean value in a plurality of years, yellow represents that the mean value ratio is greater than 1, and the annual observation value is higher than the general level; green means that the mean ratio is less than 1, and the annual observations are lower than the general level. And (5) placing the mouse in the range of the hot spot icon, and displaying the mean ratio data of the measuring point. The system sorts all the measuring points which are analyzed currently according to the average ratio from large to small, and the interface displays an average ratio sorting table in real time, wherein the average ratio sorting table comprises sorting, measuring point numbers and the average ratio. The hot spot icon display scale can be freely scaled.
For the heat point diagram generated according to the dispersion rate, circles with the same color (represented by blue) and different radiuses are used for representing the relative size of the dispersion rate of each measuring point on each measuring point of the measuring point distribution diagram, and data information of the ratio of the standard deviation of the monitoring data of the selected year to the multi-year average value of the data series is visually expressed at the distribution positions of all measuring points of the current monitoring project. And when the mouse is placed in the range of the hot spot icon, the dispersion rate data of the measuring point is displayed. The system sorts all the measuring points which are analyzed currently according to the dispersion rate from large to small, and a dispersion rate sorting table is displayed on an interface in real time and comprises sorting, measuring point number and dispersion rate. The hot spot icon display scale can be freely scaled.
And for the hotspot graph generated according to the fluctuation rate, analyzing and displaying the discrete degree of relative fluctuation of the annual observation values of the monitoring points of a certain type of monitoring items. On each measuring point of the measuring point distribution diagram, circles with the same color (represented by blue) and different radiuses represent the relative size of the fluctuation rate of each measuring point, and data information of the ratio of the standard deviation of the selected year monitoring data to the multi-year fluctuation range of the data series is visually expressed at the distribution positions of all measuring points of the current monitoring project. And (5) when the mouse is placed in the range of the hot spot icon, displaying the fluctuation rate data of the measuring point. The system sorts all the measuring points which are analyzed currently according to the fluctuation rate from large to small, and the interface displays a fluctuation rate sorting table in real time, wherein the fluctuation rate sorting table comprises sorting, measuring point number and fluctuation rate. The hot spot icon display scale can be freely scaled.
And for the hot spot diagram generated according to the range ratio data, comparing, analyzing and displaying the annual observation value fluctuation degree and the perennial observation value fluctuation degree of the monitoring points of a certain type of monitoring items. On each measuring point of the measuring point distribution diagram, circles with the same color (represented by blue) and different radiuses are used for representing the size of the range difference ratio, and data information of the ratio of the fluctuation range of the selected year monitoring data to the fluctuation range of the measured value of years is visually represented at the distribution positions of all measuring points of the current monitoring item. And (4) placing the mouse in the range of the hot spot icon, namely displaying the extreme difference of the selected year of the measuring point of the analysis project, the extreme difference of multiple years and the extreme difference ratio data of the two groups of data. The system sorts all the measuring points which are analyzed currently according to the range ratio from large to small, and an interface displays a range ratio sorting table of the selected year in real time, wherein the range ratio sorting table comprises sorting, measuring point number and range ratio. The hot spot icon display scale can be freely scaled.
According to the steps 101 to 104, the invention can perform overall project comparison and analysis on the acquired safety monitoring data from different angles, including but not limited to: the current value of the reservoir water level, the mean change rate of the reservoir water level, the mean ratio of the reservoir water level, the dispersion rate of the reservoir water level, the fluctuation rate of the reservoir water level and the range ratio of the reservoir water level; the current value of the seepage flow, the mean change rate of the seepage flow, the mean ratio of the seepage flow, the dispersion rate of the seepage flow, the fluctuation rate of the seepage flow and the range ratio of the seepage flow; the stress of the steel bars is measured according to the current value, the mean change rate, the mean ratio, the dispersion rate, the fluctuation rate and the range ratio of the stress of the steel bars; the concrete strain is measured by the following steps of (1) measuring the current value of the concrete strain, the mean change rate of the concrete strain, the mean ratio of the concrete strain, the dispersion rate of the concrete strain, the fluctuation rate of the concrete strain and the range ratio of the concrete strain; and generating a visual heat point diagram comprising at least one data result of the current value of the soil pressure, the mean change rate of the soil pressure, the mean ratio of the soil pressure, the dispersion rate of the soil pressure, the fluctuation rate of the soil pressure, the range ratio of the soil pressure and the like.
A user (non-professional) can obtain a visual project state (analysis result) according to the visual heat point diagram of all the evaluation indexes of the selected monitoring project, so that a systematic and integral evaluation conclusion of the running condition of the monitoring project is obtained. Specifically, the patterns shown in the current value hotspot graph of the osmotic pressure of fig. 9 and the mean change rate hotspot graph of the osmotic pressure of fig. 10 are taken as examples for explanation.
In fig. 9, the light color is positive to represent the state that the current value is pulled or displaced in the positive direction, the dark color is negative to represent the state that the current value is pressed or displaced in the negative direction, the larger the radius of the further light color circle is, the higher the degree of pulling or displacement in the positive direction is, the smaller the radius is, the lower the degree of pulling or displacement in the positive direction is, the larger the radius of the dark color circle is, the higher the degree of pressing or displacement in the negative direction is, and the smaller the radius is, the lower the pressing or displacement in the negative direction is, so that the worker can clearly grasp the current operating condition of each monitoring point of the whole monitoring project, and obtain the analysis conclusion that the position with the.
In fig. 10, a light color indicates a rising state of the mean change rate, and a dark color indicates a falling state of the mean change rate. Specifically, the larger the radius of the light color circle is, the higher the growth rate is, the smaller the radius is, the more gentle the growth rate is, the larger the radius of the dark color circle is, the larger the negative growth rate is, and the smaller the radius is, the more gentle the negative growth rate is, so that a worker can clearly master the change degree of the average running condition of each monitoring point of the whole monitoring project under a certain condition, and obtain an analysis conclusion that the position with the larger positive/negative growth rate needs to be monitored emphatically.
Similarly, for the current value of the reservoir water level, the mean change rate of the reservoir water level, the mean ratio of the reservoir water level, the dispersion rate of the reservoir water level, the fluctuation rate of the reservoir water level and the range ratio of the reservoir water level; the current value of the seepage flow, the mean change rate of the seepage flow, the mean ratio of the seepage flow, the dispersion rate of the seepage flow, the fluctuation rate of the seepage flow and the range ratio of the seepage flow; the stress of the steel bars is measured according to the current value, the mean change rate, the mean ratio, the dispersion rate, the fluctuation rate and the range ratio of the stress of the steel bars; the concrete strain is measured by the following steps of (1) measuring the current value of the concrete strain, the mean change rate of the concrete strain, the mean ratio of the concrete strain, the dispersion rate of the concrete strain, the fluctuation rate of the concrete strain and the range ratio of the concrete strain; the heat point diagram with the same or similar patterns can be generated by the relevant engineering data such as the current value of the soil pressure, the mean change rate of the soil pressure, the mean ratio of the soil pressure, the dispersion rate of the soil pressure, the fluctuation rate of the soil pressure, the range ratio of the soil pressure and the like, so that non-professional workers can also visually obtain the analysis result and carry out the next work.
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 (6)
1. A method for integrated visual analysis of safety monitoring data, the method comprising:
collecting all historical data and real-time dynamic update data of monitoring points, and selecting monitoring items and evaluation indexes;
calculating and obtaining a corresponding data result according to the selected monitoring item and the selected evaluation index, wherein the evaluation index comprises a current value, a mean change rate, a mean ratio, a dispersion rate, a fluctuation rate and a range ratio; the monitoring items comprise at least one of reservoir water level, seepage, reinforcing steel bar stress, concrete strain and soil pressure;
wherein, a mean ratio M is obtainediThe method comprises the following steps:
obtaining the average value of the observation data series in the i-th year
Obtaining the average value of each data in the observation data series
Wherein, the standard deviation of each year of observation data corresponding to the corresponding monitoring project is obtained
After the maximum value and the minimum value in the observation data corresponding to the corresponding monitoring items are obtained, the fluctuation rate is obtained by adopting a range method:
generating a hotspot graph according to at least one of the obtained current-value data result, the obtained mean change rate data result, the obtained mean ratio data result, the obtained discrete-rate data result, the obtained fluctuation rate data result and the obtained range ratio data result of each monitoring item, and obtaining an analysis result according to the radius of a point on the hotspot graph;
and the radius is in proportional relation with the current value, the mean change rate, the mean ratio, the dispersion rate, the fluctuation rate and the range ratio respectively.
2. The method for the overall visual analysis of safety monitoring data according to claim 1, wherein the obtaining the mean rate of change R comprises:
wherein R is the mean change rate, x is the current value of the observed data,
is the average of the observed data under the conditions.
3. The safety monitoring data of claim 1The method for integral visual analysis according to (1), wherein the dispersion ratio is calculated as YiThe method comprises the following steps:
in the formula (I), the compound is shown in the specification,
to observe the standard deviation of the data series for year i,
is the average of the whole observation series.
4. The method for the holistic visual analysis of safety monitoring data according to claim 1, characterized in that the range ratio JiThe method comprises the following steps:
in the formula (I), the compound is shown in the specification,
respectively the maximum value and the minimum value of the i-th year of the observation data series,
xmax、xminrespectively, the maximum and minimum values of the whole observation data series.
5. The method for overall visual analysis of safety monitoring data according to claim 1, wherein the step of generating a hotspot graph from at least one of the obtained current value data result, the obtained mean change rate data result, the obtained mean ratio data result, the obtained discrete rate data result, the obtained fluctuation rate data result, and the obtained extreme difference ratio data result, and obtaining an analysis result according to a radius of a point on the hotspot graph comprises:
calculating and obtaining corresponding data results according to the selected monitoring items and the selected evaluation indexes, wherein the data results comprise:
the current value of the reservoir water level, the mean change rate of the reservoir water level, the mean ratio of the reservoir water level, the dispersion rate of the reservoir water level, the fluctuation rate of the reservoir water level and the range ratio of the reservoir water level; the current value of the seepage flow, the mean change rate of the seepage flow, the mean ratio of the seepage flow, the dispersion rate of the seepage flow, the fluctuation rate of the seepage flow and the range ratio of the seepage flow; the stress of the steel bars is measured according to the current value, the mean change rate, the mean ratio, the dispersion rate, the fluctuation rate and the range ratio of the stress of the steel bars; the concrete strain is measured by the following steps of (1) measuring the current value of the concrete strain, the mean change rate of the concrete strain, the mean ratio of the concrete strain, the dispersion rate of the concrete strain, the fluctuation rate of the concrete strain and the range ratio of the concrete strain; the current value of the soil pressure, the mean change rate of the soil pressure, the mean ratio of the soil pressure, the dispersion rate of the soil pressure, the fluctuation rate of the soil pressure, the range ratio of the soil pressure and the like;
and generating a single index hotspot graph by any one of the data results for analysis, or combining more than two of the data results to generate a composite index hotspot graph for analysis.
6. The method for the overall visual analysis of the safety monitoring data according to claims 1 to 5, wherein the obtaining of the analysis result according to the radius of the point on the hotspot graph comprises:
the radius of each point on the heat point diagram represents at least one data result of a current value, a data result of a mean change rate, a data result of a mean ratio, a data result of a dispersion rate, a data result of a fluctuation rate and a data result of a range ratio, and different colors are set to represent the state, the change trend or the dispersion degree of the data results.
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