CN109816252B - Tailing pond comprehensive risk quantitative early warning method and device - Google Patents
Tailing pond comprehensive risk quantitative early warning method and device Download PDFInfo
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Abstract
The invention relates to the field of tailing pond safety system engineering, in particular to a tailing pond comprehensive risk quantitative early warning method and device. According to the method, the attributes of various types of risk variable data are scientifically distinguished, the data are divided into three categories of important steady state variables, basic guarantee variables and key dynamic variables according to the time, space, function and other information embodied by the data, risk distinguishing modes are respectively adopted for the variables of different categories, risk related information contained in the variable data is comprehensively utilized to the maximum extent, the risk early warning value of the tailing pond is quantitatively calculated, and the risk early warning signal of the corresponding level is sent according to different levels corresponding to the risk early warning value. The method adopts all-weather real-time monitoring on key dynamic variables, carries out real-time change curve analysis, and carries out continuous and timely monitoring on the catastrophe evolution process. The risk variable data are subjected to spatialization, time domain, organization, data classification, membership and hierarchical ordered operation, data management data are realized, and artificial intelligence is deepened.
Description
Technical Field
The invention relates to the field of tailing pond safety system engineering, in particular to a tailing pond comprehensive risk quantitative early warning method and device.
Background
As a necessary facility for maintaining normal production of metal mines in places where metal or nonmetal mine industrial waste residues are piled up, a tailing pond is a great risk source with high potential energy artificial debris flow, and once a dam break occurs, the great risk source can seriously threaten the life and property safety and the environment of downstream residents. Along with rapid industrial development in recent years, the number of domestic and foreign tailing ponds increases dramatically, and along with frequent dam break accidents, safety evaluation and risk early warning of the tailing ponds are problems to be solved urgently.
The safety evaluation and risk early warning of the tailing pond are based on the research of the safety condition of the tailing dam and the affiliated structures thereof, so that the safety level of the tailing pond is evaluated, the danger sources in the operation process are reduced and controlled, the safety risk is reduced, the accidents are prevented, and the stability of the periphery of the pond area is kept. The factors influencing the safe operation of the tailing pond are many, including a tailing pond stockpiling system, a tailing pond flood discharging system, a tailing pond backwater system, safety management of the tailing pond, damage caused by dam break of the tailing pond and the like, and each subsystem comprises a plurality of indexes to influence the overall safety performance of the tailing pond together, so that the system is a typical nonlinear and coupled complex system.
The inventor finds that the currently adopted tailing pond risk early warning scheme is mainly from a traditional risk assessment method, namely, a traditional method for judging according to comparison between actual detection data and a threshold value by adopting a single index or a few indexes is used for evaluating the single index, the multivariate information contained in each index data is not considered, particularly, time, space and functional information embodied by each index are necessary resources for researching tailing pond risk early warning of each index, and comprehensive quantitative evaluation of tailing pond risk is difficult to perform. Meanwhile, the risks of the tailing pond are dynamic, and the risks can be effectively controlled only by adopting a real-time, accurate and quantitative evaluation method, and early warning signals are sent out in time, so that risk prevention and control measures are convenient to take. In conclusion, the current tailing pond risk data information has the defects of low utilization degree, difficult quantitative evaluation of risks, weak early warning real-time performance and the like.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a tailing pond comprehensive risk quantitative early warning method which scientifically classifies the risk variables of a tailing pond according to time, space and functional attributes and provides the information utilization degree of monitoring data.
In order to achieve the above purpose, the invention provides the following technical scheme:
a quantitative early warning method for comprehensive risks of a tailing pond is shown in figure 1 and comprises the following steps:
step A, dividing a risk variable of a tailing pond into a steady-state variable, a guarantee variable and a dynamic variable; the steady state variable satisfies that the variation of variable data in a preset time range and/or space range is smaller than a first preset threshold, and a single variable is related to a risk result; the guarantee variables meet the condition that the variable quantity of the variable data in a preset time range and/or space range is smaller than a second preset threshold, and the set of a plurality of variables is related to a risk result; the dynamic variable satisfies the condition that the variable data shows dynamic and random characteristics along with the change of time, and the single variable is related to a risk structure;
step B, obtaining a steady state variable k1,k2,…,ki,…,knPerforming 0-1 binary judgment on the steady state variable, wherein 0 corresponds to high risk of the variable and 1 corresponds to low risk, and calculating the early warning parameter of the steady state variable
Obtaining a guarantee variable and calibrating a risk value to obtain a risk value p1,p2,…,pi,…,pnCalculating early warning parameters of security variables, wherein small values correspond to high risks, large values correspond to low risks
Wherein A isiIs a risk index piA corresponding risk weight;
monitoring dynamic variables d in real time1,d2,…,di,…,dnAnd carrying out 0-1 interval judgment on the dynamic variable, wherein 0 corresponds to high risk of the variable and 1 corresponds to low risk, and calculating the early warning parameter of the dynamic variable
Step C, calculating a risk quantitative early warning value E which is K × P × D according to the steady state variable early warning parameter K, the guarantee variable early warning parameter P and the dynamic variable early warning parameter D;
and D, sending an early warning signal according to the risk quantitative early warning value E.
The preset time and/or the preset space can be adjusted according to the requirements of the early warning object and the early warning situation of the tailing pond. The steady state variable has high correlation with risks, data are kept relatively stable in a relative space-time range, the fluctuation period is relatively long, and enough time margin and space margin can be reserved for risk management work. And once the steady state variable fails, judging that the result of 0-1 judgment is 0, and judging that the hazard source is in a high risk state. In a specific implementation mode, variables such as reservoir capacity, dam height, downstream environment, flood control and drainage system, seepage drainage facility, dam body current situation and the like are set as steady-state variables, and the standard of 0-1 judgment is the design requirement of a tailings reservoir.
The safeguard variable has a significant correlation with risk, and usually shows that the set of such variable data has a more prominent relationship with risk.
The dynamic variable data presents a dynamic and random state and has a direct relation or linear relation with risks, and once the dynamic variable fails, a danger source is in a high-risk state. Particularly, after the tailing pond as the monitoring and early warning object enters early warning space-time, the key effect of the variable is obviously increased, and the data change condition of the dynamic variable must be controlled in real time.
Preferably, in the step B, when the dynamic variable is determined in the interval 0-1, at least 1 buffering determination threshold is included, and the buffering determination threshold is between (0, 1). Because the dynamic variable has the highest time sensitivity to the high-risk trigger, the monitoring value of the dynamic variable has a fluctuation interval with a larger range between the low risk and the high risk, the buffer judgment threshold value is further set for the fluctuation interval, and more precise dynamic variable detection value interval distribution division is carried out, so that a pre-prompt signal is favorably sent to specific personnel before a high-risk early warning signal is sent, and sufficient time margin is reserved for subsequent high-risk early warning signal prevention and control.
The method comprises the steps of setting the length of a flood control dry beach line as a first threshold, setting the length of the flood control dry beach line as a second threshold, setting the dynamic variable of the dry beach length as 1 when the length of the dry beach monitored in real time is greater than the first threshold, setting the dynamic variable of the dry beach length as 0.7 when the length of the dry beach monitored in real time is smaller than the first threshold and is greater than the second threshold, wherein the contribution of the risk degree of the dynamic variable is reflected in a risk quantitative early warning value E of K × P × D, and setting the dynamic variable of the dry beach length as 0 when the length of the dry beach monitored in real time is smaller than the second threshold, so that a risk early warning signal is directly triggered.
Preferably, after the step D, the method further comprises a step E, and after the early warning state is entered, the dynamic variable D is continuously monitored in real time1,d2,…,di,…,dnAt least one of the dynamic variables, plotting a time-dependent profile of at least one of the dynamic variables.
Optionally, the dynamic variable is one or more of tailings reservoir water level, dam crest-to-water level superelevation, dry beach length, saturation line, and structure displacement.
Preferably, after entering the early warning state, the dynamic variable continuously monitored in real time is the water level related quantity, and a change curve of the water level related quantity along with time is drawn. The change curve of the water level related quantity along with the time is pushed to a data terminal in real time in an APP (application) or WEB application mode, the amplitude and the fluctuation frequency of the water level related quantity at the current moment are presented in a visual mode, and the maximum peak value and the fluctuation condition of the water level related quantity can be conveniently and timely obtained.
Optionally, the water level related quantity is water level, dam crest to water level super elevation, or dry beach length. Because the dry beach slope surface angle can be measured, the same tailing pond can consider that the slope is unchanged, and the trigonometric function relation between the dry beach length and the superelevation can be simplified into a linear relation. Based on the water level, the super height or the dry beach length, the water quantity in the tailing pond can be rapidly calculated.
Preferably, step E further comprises calculating the time domain differential and/or integral of the water level related quantity in real time. By calculating the time-domain differential and integral of the water level related quantity in real time, the variation trend and the stage variation result of the water level related quantity can be displayed more deeply, including but not limited to the instantaneous value, the extreme value, the incremental change rate, the incremental change acceleration and the incremental total quantity in a time period of the water level related quantity.
Preferably, the difference between the instantaneous water collection and the drainage is calculated in real time according to the time domain differential of the water level related quantity, and the balance state of the instantaneous water collection and the drainage is accurately obtained. For example, if the instantaneous increment of the water level is positive, the instantaneous catchment amount is reflected to be larger than the instantaneous drainage amount, and the risk presents an increasing situation; and if the instantaneous increment of the water level is negative, the instantaneous catchment amount is smaller than the instantaneous drainage amount, and the risk is reduced. Those skilled in the art will readily appreciate that the calculation of the super high or dry beach length is contrary to the calculation of the water level. And calculating the difference value of instantaneous water collection and drainage, namely the increment of the instantaneous water quantity of the tailing pond in real time according to the increment calculation result of the water level related quantity and by combining the plane distribution condition of the tailing pond.
Further, calculating the maximum allowable rainfall capacity of the tailing pond in real time according to the difference value of the instantaneous water collecting and discharging and the instantaneous water level quantity. And calculating the maximum allowable rainfall capacity of the tailing pond in real time according to the increment of the instantaneous water quantity of the tailing pond and the instantaneous water quantity and by combining the maximum pond capacity of the design scheme. According to the maximum allowable rainfall and the real-time weather forecast information of the local region of the tailing pond, sufficient time margin can be strived for continuous early warning of subsequent risks and timely risk prevention and control measures.
Preferably, the catchment accumulation amount or the drainage accumulation amount in the appointed time period is calculated in real time according to the time domain integral of the water level related quantity, so that a basis is provided for accurately determining the safety situation of the dry beach and the sub-dam. The integral of the water level related quantity in the controlled time period is combined with the plane distribution condition of the tailing pond, and the water quantity increment cumulant of the tailing pond in the controlled time period can be calculated in real time. If the water quantity increment cumulant is positive, the water quantity in the controlled time period is reflected to present a net increase situation, and the safety risk of the dry beach and the sub-dam in the later period is increased; and if the cumulative quantity of the water quantity increment is negative, the water quantity in the controlled time period is reflected to present a net discharge situation, and the safety risk of the dry beach and the sub-dam in the later period is reduced.
Preferably, in step a, the set of steady state variables is a subset of the set of safeguard variables; or the set formed by the steady-state variables and the set formed by the guarantee variables have intersection. Although the steady state variables are determined in a mandatory 0-1 mode, a single variable of the type is directly related to a risk determination conclusion. However, for such variables in a low risk state, the variables are simultaneously divided into the set of the safeguard variables to participate in the calculation of the safeguard variable early warning parameter P, so that the utilization rate of risk variable data can be further improved, and the accuracy of risk early warning can be effectively improved.
Preferably, in step B, the dynamic variable d is monitored in real time1,d2,…,di,…,dnAnd if the instantaneous change rate and/or the instantaneous change acceleration of at least one item of dynamic variable exceeds a specified threshold, directly sending an early warning signal. Because the dynamic variable is closely related to the time attribute of risk occurrence, when the dynamic variable does not start from the low risk threshold value judged by 0-1, the instantaneous change rate and the instantaneous change acceleration of the dynamic variable often reflect the change trend in advance. By monitoring and calculating the related quantity of the change trend, the sending time of the risk early warning signal can be advanced to the maximum extent.
Preferably, the risk early warning signals of corresponding levels are sent according to different levels corresponding to the risk early warning values E.
In another aspect of the invention, a comprehensive risk quantitative early warning device for a tailing pond is provided, which comprises at least one processor and a memory, wherein the memory is in communication connection with the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described method of integrated tailings pond risk quantitative pre-warning.
Compared with the prior art, the invention has the beneficial effects that:
the method for quantitatively early warning the comprehensive risks of the tailing pond provided by the invention divides the attributes of various types of risk variable data into three categories, namely important steady-state variables, basic security variables and key dynamic variables according to the information of time, space, function and the like embodied by the data through scientific resolution, adopts a risk discrimination mode for the variables of different categories respectively, comprehensively utilizes the risk related information contained in the variable data to the maximum extent, quantitatively calculates the risk early warning values of the tailing pond, and sends risk early warning signals of corresponding levels according to different levels corresponding to the risk early warning values.
The invention fully considers the importance of the key dynamic variable after the early warning signal is sent out, monitors the key dynamic variable in real time in all weather, analyzes the real-time change curve of the key dynamic variable, and continuously and timely monitors the catastrophe evolution process.
The invention carries out spatialization, time-domain organization and organization on a plurality of risk variables of the tailing pond, which are called as 'three-way' for short. The data after the transformation can enter classification, membership and hierarchical ordered operation, so that data management is realized, and artificial intelligence is deepened.
Description of the drawings:
FIG. 1 is a flow chart of a comprehensive risk quantitative early warning method for a tailing pond in the embodiment 1 of the invention;
fig. 2 is a graph of data obtained by monitoring the length of a dry beach in embodiment 1 of the present invention.
Detailed Description
The present invention will be described in further detail with reference to test examples and specific embodiments. It should be understood that the scope of the above-described subject matter is not limited to the following examples, and any techniques implemented based on the disclosure of the present invention are within the scope of the present invention.
Example 1
The embodiment provides a method for quantitatively early warning comprehensive risks of a tailing pond, as shown in fig. 1, the method includes:
step A, dividing a risk variable of a tailing pond into a steady-state variable, a guarantee variable and a dynamic variable; the steady state variable satisfies that the variation of variable data in a preset time range and/or space range is smaller than a first preset threshold, and a single variable is related to a risk result; the guarantee variables meet the condition that the variable quantity of the variable data in a preset time range and/or space range is smaller than a second preset threshold, and the set of a plurality of variables is related to a risk result; the dynamic variable satisfies the condition that the variable data shows dynamic and random characteristics along with the change of time, and the single variable is related to a risk structure;
step B, obtaining a steady state variable k1,k2,…,ki,…,knPerforming 0-1 judgment on the steady state variable, wherein 0 corresponds to high risk of the variable and 1 corresponds to low risk, and calculating the early warning parameter of the steady state variable
Obtaining a guarantee variable and calibrating a risk value to obtain a risk value p1,p2,…,pi,…,pnCalculating early warning parameters of security variables, wherein small values correspond to high risks, large values correspond to low risks
Wherein A isiIs a risk index piA corresponding risk weight;
monitoring dynamic variables d in real time1,d2,…,di,…,dnAnd performing 0-1 judgment on the dynamic variable, wherein 0 corresponds to high risk of the variable and 1 corresponds to low risk, and calculating early warning parameters of the dynamic variable
And carrying out real-time waveform analysis on the dynamic variable;
step C, calculating a risk quantitative early warning value E which is K × P × D according to the steady state variable early warning parameter K, the guarantee variable early warning parameter P and the dynamic variable early warning parameter D;
and D, sending an early warning signal according to the risk quantitative early warning value E.
Selecting 6 indexes such as reservoir capacity, dam height, downstream environment, flood control and drainage system, seepage drainage facility, dam body current situation and the like as steady-state indexes, and carrying out 0-1 judgment according to a design scheme, wherein the judgment process and the judgment result are as follows:
TABLE 1 Steady State variable 0-1 determination
Steady state variable early warning parameter
The safeguard variable has a significant correlation with risk, and usually shows that the set of such variable data has a more prominent relationship with risk. Obtaining a guarantee variable and calibrating a risk value in a range of 1-9 to obtain a risk value p1,p2,…,pi,…,pnThe physical meaning of the risk value is a relative risk index of the current state of the guarantee variable relative to the design scheme, for example, if the dam height required by the design scheme is lower than 200 meters, the dam height is less than 30 meters and takes a value of 9; 30-60 meters, and the value is 6.3; 60-100 meters, and the value is 3.6; 100-200 m, and taking the value of 1.
As shown in Table 2, the safeguard variable early warning parameters are calculated
Wherein A isiIs a risk index piCorresponding risk weight. Risk weight AiThe method is obtained according to the correlation statistical analysis of guarantee variables and risk results in the conventional tailing pond risk early warning engineering practice.
TABLE 2 probability determination of safeguard variables
The method comprises the steps of setting the length of a flood control dry beach line as a first threshold value, setting the length of a warning dry beach line as a second threshold value, setting the dynamic variable of the dry beach length as 0.7 when the real-time monitored dry beach length is smaller than the first threshold value and larger than the second threshold value, wherein the risk contribution of the dynamic variable is embodied in a risk quantitative early warning value E of K × P × D, and setting the dynamic variable of the dry beach length as 0 when the real-time monitored dry beach length is smaller than the second threshold value, and directly triggering a risk early warning signal.
The flood regulation dry beach line is the dry beach length which meets the flood prevention and drainage requirements through flood regulation calculation according to the high-resolution satellite picture and the tailing pond health file; the warning dry beach line is the dry beach length which can cause dam overflowing accidents when the reservoir water level continuously rises under the condition of rainstorm and the dry beach length is gradually reduced, so that the emergency preparation time of a tailing reservoir and downstream people is met; the dangerous dry beach line is the minimum dry beach length of the tailings pond with the corresponding grade required by the specification. The relationship of the three is as follows: the dangerous dry beach < alert dry beach < flood regulation dry beach, the tailing pond is divided into four risk areas of 'red orange yellow blue' by three dry beach lines, the highest risk state is 'red', namely the length of the dry beach is less than that of the dangerous dry beach, and a management department needs to start an emergency plan to evacuate downstream personnel and important facility equipment and close related influence areas; the risk state is orange, namely the length of the dry beach is between the dangerous dry beach and the warning dry beach, and the management department needs to pay high attention and prepare to start emergency at any time; the risk state is 'yellow', namely the length of the dry beach is between the warning dry beach and the flood regulation dry beach, and an enterprise attendant needs to pay attention to the water level change at any time; the blue area is a safe area and corresponds to the flood regulation dry beach or above. As shown in fig. 2, a result diagram of real-time monitoring of changes in the length of dry beach of a tailings pond is realized by using a beidou location service system and a three-line four-zone method.
And D, after the step D, further comprising a step E, after entering an early warning state, continuously monitoring the length of the dry beach in real time, and drawing a change curve of the length of the dry beach along with time. The change curve of the length of the dry beach along with the time is pushed to a data terminal in real time in an APP (application) or WEB application mode, the amplitude and fluctuation frequency of the length of the dry beach at the current moment are presented in a visual mode, and the maximum peak value and fluctuation condition of the length of the dry beach can be conveniently and timely acquired.
Because the dry beach slope surface angle can be measured, the same tailing pond can consider that the slope is unchanged, and the trigonometric function relation between the dry beach length and the superelevation can be simplified into a linear relation. And based on the length of the dry beach, rapidly calculating the water amount in the tailing pond.
Step E further comprises calculating the time domain differential and/or integral of the beach length in real time. By calculating the time-domain differential and integral of the length of the dry beach in real time, the change trend and the stage change result of the length of the dry beach can be displayed more deeply, including but not limited to the instantaneous value, the extreme value, the incremental change rate, the incremental change acceleration and the incremental total amount in a time period of the length of the dry beach.
And calculating the difference value of instantaneous water collection and drainage in real time according to the time domain differential of the length of the dry beach, and accurately obtaining the balance state of instantaneous water collection and drainage. If the instantaneous increment of the length of the dry beach is positive, the instant catchment quantity is smaller than the instant drainage quantity, and the risk is reduced; and if the instantaneous increment of the length of the dry beach is negative, the instantaneous catchment quantity is larger than the instantaneous drainage quantity, and the risk is increased. And calculating the difference value of instantaneous water collection and drainage in real time according to the increment calculation result of the length of the dry beach and by combining the plane distribution condition of the tailing pond, namely the increment of the instantaneous water quantity of the tailing pond.
Further, calculating the maximum allowable rainfall capacity of the tailing pond in real time according to the difference value of the instantaneous water collecting and discharging and the instantaneous water level quantity. And calculating the maximum allowable rainfall capacity of the tailing pond in real time according to the increment of the instantaneous water quantity of the tailing pond and the instantaneous water quantity and by combining the maximum pond capacity of the design scheme. According to the maximum allowable rainfall and the real-time weather forecast information of the local region of the tailing pond, sufficient time margin can be strived for continuous early warning of subsequent risks and timely risk prevention and control measures.
And calculating the catchment cumulant or drainage cumulant in a specified time period in real time according to the time domain integral of the length of the dry beach, so as to provide a basis for accurately scheduling the safety situation of the dry beach and the sub-dam. The integral of the length of the dry beach in the controlled time period is combined with the plane distribution condition of the tailing pond, so that the water quantity increment cumulant of the tailing pond in the controlled time period can be calculated in real time. If the water quantity increment cumulant is positive, the water quantity in the controlled time period is reflected to present a net increase situation, and the safety risk of the dry beach and the sub-dam in the later period is increased; and if the cumulative quantity of the water quantity increment is negative, the water quantity in the controlled time period is reflected to present a net discharge situation, and the safety risk of the dry beach and the sub-dam in the later period is reduced.
In step A, the set of steady state variables is a subset of the set of safeguard variables; or intersection exists between the set formed by the steady state variables and the set formed by the guarantee variables, such as the storage capacity and the dam height. Although the steady state variables are determined in a mandatory 0-1 mode, a single variable of the type is directly related to a risk determination conclusion. However, for such variables in a low risk state, the variables are simultaneously divided into the set of the guarantee variables to participate in the calculation of the reserve variable early warning parameter P, so that the utilization rate of risk variable data can be further improved, and the accuracy of risk early warning can be effectively improved.
In step B, the dynamic variable d is monitored in real time1,d2,…,di,…,dnAnd if the instantaneous change rate and/or the instantaneous change acceleration of at least one item of dynamic variable exceeds a specified threshold, directly sending an early warning signal. Because the dynamic variable is closely related to the time attribute of risk occurrence, when the dynamic variable does not trigger the low risk threshold value of 0-1 discrimination, the instantaneous change rate and the instantaneous change acceleration of the dynamic variable often reflect the change trend in advance. By monitoring and calculating the related quantity of the change trend, the sending time of the risk early warning signal can be advanced to the maximum extent.
And sending risk early warning signals of corresponding levels according to different levels corresponding to the risk early warning numerical value E, wherein the comprehensive quantitative risk (E) evaluation mainly comprises the three evaluation parts, the comprehensive quantitative evaluation result E is K × P × D, the risk evaluation level is divided into 4 levels, E which is more than or equal to 0 and less than 3 is a major risk, E which is more than or equal to 3 and less than 5 is a major risk, E which is more than or equal to 5 and less than or equal to 5 is a general risk, E which is more than or equal to 6 and less than or equal to 9 is a low risk, and when E is less than 5, the risk early warning signals are analyzed and sent in real time.
And analyzing the reason causing the low risk early warning value under the condition that the E <5, respectively taking different types of early warning measures, sending a forced rectification suggestion when the risk early warning value E caused by the steady-state variable reason is low, and timely entering an early warning state and formulating an emergency plan when the risk early warning value caused by the dynamic variable reason is low.
Those skilled in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
When the integrated unit of the present invention is implemented in the form of a software functional unit and sold or used as a separate product, it may also be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The foregoing is merely a detailed description of specific embodiments of the invention and is not intended to limit the invention. Various alterations, modifications and improvements will occur to those skilled in the art without departing from the spirit and scope of the invention.
Claims (9)
1. A tailing pond comprehensive risk quantitative early warning method is characterized by comprising the following steps:
step A, dividing a risk variable of a tailing pond into a steady-state variable, a guarantee variable and a dynamic variable; the steady state variable satisfies that the variation of variable data in a preset time range and/or space range is smaller than a first preset threshold, and a single variable is related to a risk result; the guarantee variables meet the condition that the variable quantity of the variable data in a preset time range and/or space range is smaller than a second preset threshold, and the set of a plurality of variables is related to a risk result; the dynamic variable satisfies the condition that the variable data shows dynamic and random characteristics along with the change of time, and the single variable is related to a risk structure;
step B, obtaining a steady state variable k1,k2,…,ki,…,knPerforming 0-1 binary judgment on the steady state variable, wherein 0 corresponds to high risk of the variable and 1 corresponds to low risk, and calculating the early warning parameter of the steady state variable
Obtaining a guarantee variable and calibrating a risk value to obtain a risk value p1,p2,…,pi,…,pnCalculating early warning parameters of security variables, wherein small values correspond to high risks, large values correspond to low risks
Wherein A isiIs a risk index piA corresponding risk weight;
monitoring dynamic variables d in real time1,d2,…,di,…,dnAnd carrying out 0-1 interval judgment on the dynamic variable, wherein 0 corresponds to high risk of the variable and 1 corresponds to low risk, and calculating the early warning parameter of the dynamic variable
Step C, calculating a risk quantitative early warning value E which is K × P × D according to the steady state variable early warning parameter K, the guarantee variable early warning parameter P and the dynamic variable early warning parameter D;
step D, sending an early warning signal according to the risk quantitative early warning value E;
after the step D, the method also comprises a step E, after the early warning state is entered, the dynamic variable D is continuously monitored in real time1,d2,…,di,…,dnAt least one of drawing a time-dependent variation curve of at least one of the dynamic variables;
the step D also comprises the following steps:
step F: judging whether the risk quantitative early warning value E is I or II, if so, judging in the step G, and otherwise, carrying out standardized promotion and checking according to a plan;
step G: judging whether the dynamic variable is I or II, if so, entering an early warning state, otherwise, performing mandatory rectification and checking according to a plan;
and the step A, the step B, the step C and the step D are sequentially executed.
2. The warning method according to claim 1, wherein: in step B, when the dynamic variable is determined in the interval 0-1, at least 1 buffer determination threshold is included, and the buffer determination threshold is between (0, 1).
3. The warning method according to claim 1, wherein: and E, after entering an early warning state, continuously monitoring the dynamic variable in real time to be the water level related quantity, and drawing a change curve of the water level related quantity along with time.
4. The warning method according to claim 3, wherein: and E, calculating the time domain differential of the water level related quantity in real time, and calculating the difference and/or the integral of the instantaneous water collection and the drainage in real time according to the time domain differential of the water level related quantity.
5. The warning method according to claim 3, wherein: calculating the difference value of instantaneous water collection and drainage in real time according to the time domain differential of the water level related quantity; and/or calculating the catchment accumulation amount or the drainage accumulation amount in a specified time period in real time according to the time domain integral of the water level related quantity.
6. The warning method according to claim 4 or 5, characterized in that: the water level related quantity is the water level, the height from the top of the dam to the water level or the length of a dry beach.
7. The warning method according to claim 1, wherein: monitoring the dynamic variable d in step B in real time1,d2,…,di,…,dnAnd if the change rate and/or the change acceleration of at least one item of dynamic variable exceeds a specified threshold, directly sending an early warning signal.
8. The warning method according to claim 1, wherein: in step A, the set of steady state variables is a subset of the set of safeguard variables; or the set formed by the steady-state variables and the set formed by the guarantee variables have intersection.
9. The comprehensive risk quantitative early warning device for the tailing pond is characterized by comprising at least one processor and a storage connected with the at least one processor in a communication mode; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 8.
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| CN112783100A (en) * | 2019-11-06 | 2021-05-11 | 中国石油化工股份有限公司 | Memory, chemical enterprise safety production risk early warning method, equipment and device |
| CN112883458B (en) * | 2021-01-13 | 2021-12-14 | 中国安全生产科学研究院 | Rapid permeability reducing system and method for inner top pipe of metal mine tailing pond |
| CN113310515B (en) * | 2021-05-25 | 2022-10-21 | 上海同禾工程科技股份有限公司 | Tailing pond flood drainage facility monitoring system and monitoring method based on machine vision |
| CN114429308B (en) * | 2022-02-08 | 2024-06-07 | 河南鑫安利安全科技股份有限公司 | Enterprise safety risk assessment method and system based on big data |
| CN115099677B (en) * | 2022-07-14 | 2023-04-07 | 中国安全生产科学研究院 | Tailing pond safety production risk grading early warning method |
| CN116104052B (en) * | 2023-01-19 | 2023-09-05 | 中煤科工开采研究院有限公司 | Paste alkaline residue safe mining and digging method and dam dismantling method |
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