A mine water treatment automation and remote monitoring system and method

Abstract

The present invention relates to the field of water treatment monitoring technology, specifically to a mine water treatment automation and remote monitoring system and method, the method comprising: data collection for the execution process of the processing flow, obtaining sample data, data processing for the sample data, determining the time unit sequence of the processing flow and the parameter analysis value of the time unit, determining the parameter state of the parameter analysis value by analyzing the monitoring data, performing cellular simulation processing on the time unit based on the parameter analysis value and the parameter state, constructing the information cell of each time unit, and determining the automated monitoring method of water treatment by calculating and analyzing the propagation value of the information cell. The present invention realizes monitoring at the level of each processing flow executed by the water treatment automation system, solving the problem that it is difficult to perform rational monitoring at the processing flow level.

Description

Technical Field

[0001] The present invention relates to the technical field of water treatment monitoring, and in particular to a mine water treatment automation and remote monitoring system and method. Background Art

[0002] Mine water mainly comes from seepage of underground aquifers, rainfall infiltration and mining activities that damage the groundwater system. Its composition is complex, containing suspended matter, heavy metals, acidic substances and harmful ions. Direct discharge will pollute the soil and surface water, destroy the ecological balance, and may cause mine water inrush accidents, threatening safe production. In order to ensure the safety of mines and optimize costs, remote monitoring of the automated treatment of mine water is required.

[0003] The Chinese invention patent with announcement number CN117590793B discloses an integrated water treatment monitoring system and method for a water plant based on the Internet of Things, including numerical monitoring of various water quality detection indicators fed back by the integrated sewage treatment system during each execution of the full process of sewage treatment; extracting the action time interval and efficiency value of the indicator items of any sewage treatment equipment acting on the target at any instruction switching node; judging and identifying the instruction switching nodes that satisfy the associated control relationship in different sewage treatment equipment; and capturing the correlation indexes between sewage treatment equipment that satisfy the associated control relationship.

[0004] However, the existing technology monitors and analyzes the command switching of the equipment, and the generation of the command depends on the feedback control system of the water treatment system, which leads to high complexity and redundancy of the system. At the same time, the water treatment system is composed of a large number of treatment equipment, and the correlation analysis between water treatment equipment and equipment also leads to a huge amount of calculation, especially for the monitoring level of whether the water treatment automation system has any abnormalities in the execution of each treatment process, which makes it difficult to carry out reasonable monitoring. Summary of the invention

[0005] The purpose of the present invention is to solve the problems existing in the background technology and to provide a mine water treatment automation and remote monitoring system and method.

[0006] The technical solution of the present invention is a mine water treatment automation and remote monitoring method, comprising the following steps:

[0007] Obtain the treatment process of mine water, collect data on the execution process of the treatment process based on the water treatment system, and obtain sample data;

[0008] The sample data is used as the target data, data processing is performed on the target data, the time unit sequence of each processing flow is determined, the target sub-data corresponding to the time unit in the time unit sequence is obtained, data analysis is performed on the target sub-data, and the parameter analysis value of the time unit is determined;

[0009] Monitor the mine water in real time to obtain monitoring data, use the monitoring data as target data, perform data processing on the target data, determine the parameter state of the parameter analysis value, perform cellular simulation processing on the time unit based on the parameter analysis value and the corresponding parameter state, and construct the information cell of each time unit;

[0010] Conduct infectivity analysis on information cells, determine the propagation value of each information cell and perform data analysis on the propagation value of the information cell, determine the automated monitoring method for water treatment, and supervise the water treatment system based on the automated monitoring method for water treatment.

[0011] Preferably, the sample data consists of collection times, processing flow, processing timestamp and several contaminated water parameters.

[0012] Preferably, the method for processing the target data includes:

[0013] Divide the processing timestamp of each processing flow into time periods to obtain a time unit sequence for each processing flow;

[0014] Methods for data analysis of target sub-data include:

[0015] For the same number of collections, the time unit sequence is traversed, and the time units are marked as target units in turn. It is periodically determined whether the polluted water parameter types contained in the target units all have corresponding parameter analysis values. If the target unit has a parameter analysis value, the mark of the target unit is canceled and the next time unit is marked.

[0016] If the target unit contains different types of polluted water parameters and corresponding parameter analysis values, perform the following operations:

[0017] Determine whether the target unit has a previous time unit, and if the target unit has a previous time unit, determine whether the previous time unit and the target time unit belong to the same processing flow;

[0018] If the previous time unit and the target unit belong to the same treatment process, the polluted water parameters of the previous time unit are obtained and marked as reference parameters; if the previous time unit and the target unit do not belong to the same treatment process, it is determined that there is no previous time unit;

[0019] If the target unit does not have a previous time unit, the polluted water parameters at the beginning of the treatment process are obtained and marked as reference parameters.

[0020] Preferably, the polluted water parameters at the end of the treatment process are obtained and marked as treatment result parameters;

[0021] Obtain the change value of the polluted water parameter in the target unit, and calculate the parameter analysis value of the polluted water parameter of the target unit through the parameter analysis formula , the parameter analysis formula is as follows:

[0022] ;

[0023] In the formula, k is the time unit number, and k is a positive integer; is the change value of water pollution parameter; is the reference parameter; is the processing result parameter; i is the water pollution parameter number, i is a positive integer; c is a constant.

[0024] Preferably, for the same time unit in different acquisition times, the parameter analysis values ​​of the same parameter type are Perform data comparison to determine the parameter range of the parameter type;

[0025] For the same processing flow in different acquisition times, the number of time units in the processing flow is counted respectively to obtain the total number of time units corresponding to the acquisition times, and the total number of time units of different acquisition times is compared to determine the number threshold of time units.

[0026] Preferably, the method of performing cellular simulation processing on the time unit and constructing the information cell of each time unit includes:

[0027] Determine the quantity status of the time unit, specifically including counting the number of time units in the current processing flow and taking it as the target number, comparing the target number with the quantity threshold, and if the target number is not greater than the quantity threshold, determining the parameter status of the parameter analysis value;

[0028] If the target quantity is greater than the quantity threshold, the time unit under the same processing flow in the target data is expanded to obtain an extended unit, the number of extended units is the difference between the target quantity and the quantity threshold, and the parameter analysis value of any type of polluted water parameter in the extended unit is calculated to be 0 based on the parameter analysis formula;

[0029] The method for determining the parameter status of the parameter analysis value includes:

[0030] Perform data comparison on the parameter analysis value and the parameter threshold. If the parameter analysis value is not lower than the parameter threshold, the parameter analysis value is judged to be normal; if the parameter analysis value is lower than the parameter threshold, the corresponding polluted water parameter type is marked as an abnormal parameter type;

[0031] An information cell is determined based on the processing flow to which each time unit belongs, the parameter status, and the time unit quantity status.

[0032] Preferably, the method for analyzing the infectivity of information cells comprises:

[0033] The state abnormality of the information cell is counted, and the cell characteristics of the information cell are determined using the feature definition model. The expression of the feature definition model is as follows:

[0034] ;

[0035] In the formula, S is the characteristic of the information cell, and N is the state abnormality of the information cell; S is normal, which means that the information cell is a normal cell; S is polluted, which means that the information cell is a polluted cell;

[0036] When the processing flow starts, the information cell is monitored. If the information cell is a normal cell, no operation is performed on the information cell. If the information cell is a polluted cell, whether there are continuous polluted cells is monitored.

[0037] If there are continuous contaminated cells, count the number of continuous contaminated cells, and determine whether the abnormal parameter type has hereditary characteristics in the continuous contaminated cells;

[0038] If the abnormal parameter type has a hereditary characteristic in the continuous contaminated cell, a first instruction is generated; if the abnormal parameter type does not have a hereditary characteristic in the continuous contaminated cell, a second instruction is generated.

[0039] Preferably, according to the first instruction, the genetic generation Y of the abnormal parameter type is counted and it is determined whether the abnormal parameter type has an infection characteristic;

[0040] Determine whether the abnormal parameter type has infection characteristics, including obtaining the number of abnormal parameters of consecutive contaminated cells and constructing the abnormal parameter sequence of consecutive contaminated cells: ;

[0041] In the formula, represents the number of abnormal parameters of the jth contaminated cell in the continuous contaminated cells, j is a positive integer; n is the number of continuous contaminated cells;

[0042] If the sequence elements of the exception parameter sequence satisfy the relation:

[0043] ;

[0044] Then the abnormal parameter type is judged to have the infection characteristic; otherwise, the abnormal parameter type is judged not to have the infection characteristic, based on the relationship: ; Calculate the infection value G of the abnormal parameter type;

[0045] Sum the genetic algebra Y of all abnormal parameter types in the contaminated cell, and use the calculation result as the first propagation parameter p1 of the contaminated cell to which it belongs. Sum the infection values G of all abnormal parameter types in the contaminated cell, and use the calculation result as the second propagation parameter p2 of the contaminated cell to which it belongs. Through the formula: Calculate the propagation value CB of the contaminated cell;

[0046] In the formula, w1 and w2 are the coefficients of the first propagation parameter p1 and the second propagation parameter p2 respectively;

[0047] According to the second instruction, count the total number of abnormal parameter types of the contaminated cell and use it as its propagation value.

[0048] Preferably, the method for data analysis of the propagation value of the information cell to determine the automatic monitoring method of water treatment includes:

[0049] Monitor and obtain the propagation value CB of all information cells, and perform data analysis on the propagation value CB of all information cells. The propagation value CB of the information cell is compared with the preset first risk threshold Z1 and the second risk threshold Z2 respectively, where Z1 < Z2;

[0050] If the propagation value CB satisfies CB ≤ Z1, send the information that the water treatment system is operating normally;

[0051] If the propagation value CB satisfies Z1 < CB ≤ Z2, send that the water treatment system has a slight abnormality and needs to be adjusted;

[0052] If the propagation value CB satisfies CB > Z2, send that the water treatment system has a serious abnormality and notify the technical personnel to repair the water treatment system in time.

[0053] The present invention also discloses a mine water treatment automation and remote monitoring system, which applies the above-mentioned mine water treatment automation and remote monitoring method, and specifically includes:

[0054] A data acquisition module, used to obtain the treatment process of mine water, collect data based on the execution process of the treatment process by the water treatment system, and obtain sample data;

[0055] A data processing module, taking the sample data as the target data, performing data processing on the target data, determining the time unit sequence of each treatment process, obtaining the target sub-data corresponding to the time unit in the time unit sequence, and performing data analysis on the target sub-data to determine the parameter analysis value of the time unit;

[0056] The monitoring and processing module is used to monitor the mine water in real time, obtain monitoring data, use the monitoring data as target data, perform data processing on the target data, determine the parameter state of the parameter analysis value, perform cellular simulation processing on the time unit based on the parameter analysis value and the corresponding parameter state, and construct the information cell of each time unit;

[0057] The monitoring and analysis module is used to perform infectiousness analysis on information cells, determine the propagation value of each information cell and perform data analysis on the propagation value of the information cell, determine the automated monitoring method for water treatment, and supervise the water treatment system based on the automated monitoring method for water treatment.

[0058] Compared with the prior art, the above technical solution of the present invention has the following beneficial technical effects:

[0059] Data is collected during the execution of the treatment flow to obtain sample data, which is then processed to determine the time unit sequence of the treatment flow and the parameter analysis values ​​of the time units. The parameter states of the parameter analysis values ​​are determined through analysis of the monitoring data. Cellular simulation is performed on the time units based on the parameter analysis values ​​and parameter states, and information cells for each time unit are constructed. The automated monitoring method for water treatment is determined by calculating and analyzing the propagation values ​​of the information cells, thus achieving monitoring at each treatment flow level executed by the water treatment automation system and solving the problem of difficulty in performing rational monitoring at the treatment flow level. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a flow chart of the method of embodiment 1 proposed by the present invention. DETAILED DESCRIPTION

[0061] Embodiment 1, as Figure 1 As shown, a mine water treatment automation and remote monitoring method proposed by the present invention comprises the following steps:

[0062] Obtain the treatment process of mine water, collect data on the execution process of the treatment process based on the water treatment system, and obtain sample data; the sample data consists of the number of collections, the treatment process, the treatment timestamp, and several polluted water parameters; for example, the number of collections is 3, which includes the first collection, the second collection, and the third collection, and the treatment processes, treatment timestamps, and several polluted water parameters corresponding to the three collections;

[0063] The sample data is used as the target data, data processing is performed on the target data, the time unit sequence of each processing flow is determined, the target sub-data corresponding to the time unit in the time unit sequence is obtained, data analysis is performed on the target sub-data, and the parameter analysis value of the time unit is determined;

[0064] The method for processing the target data also includes data preprocessing. The method for data preprocessing is as follows:

[0065] Perform data cleaning on multiple water pollution parameters and remove invalid data; perform interpolation and normalization on the cleaned parameters to obtain polluted water parameters;

[0066] Methods for processing target data include:

[0067] Divide the processing timestamp of each processing flow into time periods to obtain a time unit sequence for each processing flow;

[0068] Methods for data analysis of target sub-data include:

[0069] For the same number of collections, the time unit sequence is traversed, and the time units are marked as target units in turn. It is periodically determined whether the polluted water parameter types contained in the target units all have corresponding parameter analysis values. If the target unit has a parameter analysis value, the mark of the target unit is canceled and the next time unit is marked.

[0070] If the target unit contains different types of polluted water parameters and corresponding parameter analysis values, perform the following operations:

[0071] Determine whether the target unit has a previous time unit, and if the target unit has a previous time unit, determine whether the previous time unit and the target time unit belong to the same processing flow;

[0072] If the previous time unit and the target unit belong to the same treatment process, the polluted water parameters of the previous time unit are obtained and marked as reference parameters; if the previous time unit and the target unit do not belong to the same treatment process, it is determined that there is no previous time unit;

[0073] If the target unit does not have a previous time unit, the polluted water parameters at the beginning of the treatment process are obtained and marked as reference parameters; the polluted water parameters at the end of the treatment process are obtained and marked as treatment result parameters;

[0074] Obtain the change value of the polluted water parameter in the target unit, and calculate the parameter analysis value of the polluted water parameter of the target unit through the parameter analysis formula , the parameter analysis formula is as follows:

[0075] ;

[0076] In the formula, k is the time unit number, and k is a positive integer; is the change value of water pollution parameter; is the reference parameter; is the processing result parameter; i is the water pollution parameter number, i is a positive integer; c is a constant;

[0077] For the same time unit in different acquisition times, the parameter analysis values ​​of the same parameter type are Perform data comparison to determine the parameter range of the parameter type; specifically, obtain the minimum and maximum values ​​of the parameter analysis values, and use them as the lower and upper limits of the parameter range, respectively;

[0078] For the same processing flow in different acquisition times, the number of time units in the processing flow is counted to obtain the total number of time units corresponding to the acquisition times, and the total number of time units of different acquisition times is compared to determine the number threshold of time units;

[0079] Monitor the mine water in real time to obtain monitoring data, use the monitoring data as target data, perform data processing on the target data, determine the parameter state of the parameter analysis value, perform cellular simulation processing on the time unit based on the parameter analysis value and the corresponding parameter state, and construct the information cell of each time unit;

[0080] The method of performing cellular simulation processing on the time unit and constructing the information cell of each time unit includes:

[0081] Determine the quantity status of the time unit, specifically including counting the number of time units in the current processing flow and taking it as the target number, comparing the target number with the quantity threshold, and if the target number is not greater than the quantity threshold, determining the parameter status of the parameter analysis value;

[0082] If the target quantity is greater than the quantity threshold, the time unit under the same processing flow in the target data is expanded to obtain an extended unit, the number of extended units is the difference between the target quantity and the quantity threshold, and the parameter analysis value of any type of polluted water parameter in the extended unit is calculated to be 0 based on the parameter analysis formula;

[0083] The method for determining the parameter status of the parameter analysis value includes:

[0084] Perform data comparison on the parameter analysis value and the parameter threshold. If the parameter analysis value is not lower than the parameter threshold, the parameter analysis value is judged to be normal; if the parameter analysis value is lower than the parameter threshold, the corresponding polluted water parameter type is marked as an abnormal parameter type;

[0085] Determine an information cell based on the processing flow, parameter status and time unit quantity status to which each time unit belongs;

[0086] Conduct infectivity analysis on information cells, determine the propagation value of each information cell and conduct data analysis on the propagation value of the information cell, determine the automated monitoring method for water treatment, and supervise the water treatment system based on the automated monitoring method for water treatment;

[0087] Methods for infectivity analysis of information cells include:

[0088] The state abnormality of the information cell is counted, and the cell characteristics of the information cell are determined using the feature definition model. The expression of the feature definition model is as follows:

[0089] ;

[0090] In the formula, S is the characteristic of the information cell, and N is the state abnormality of the information cell; S is normal, which means that the information cell is a normal cell; S is polluted, which means that the information cell is a polluted cell;

[0091] When the processing flow starts, the information cell is monitored. If the information cell is a normal cell, no operation is performed on the information cell. If the information cell is a polluted cell, whether there are continuous polluted cells is monitored.

[0092] If there are continuous contaminated cells, count the number of continuous contaminated cells, and determine whether the abnormal parameter type has hereditary characteristics in the continuous contaminated cells;

[0093] If the abnormal parameter type has a hereditary characteristic in the continuous contaminated cell, a first instruction is generated; if the abnormal parameter type does not have a hereditary characteristic in the continuous contaminated cell, a second instruction is generated;

[0094] According to the first instruction, the genetic generation Y of the abnormal parameter type is counted and whether the abnormal parameter type has an infection characteristic is determined; it should be noted that the genetic characteristic of the abnormal parameter type means that in continuous contaminated cells, if there is an abnormal parameter type in any contaminated cell, all contaminated cells after the contaminated cell have the same abnormal parameter type;

[0095] For example, the genetic generation is described as follows: for example, continuous contaminated cells are a1, a2, a3, a4, and a5, where there is an abnormal parameter type b1 in the contaminated cell a1, and there are abnormal parameter types b1 in a1, a3, and a4. Then, the genetic generation of the abnormal parameter type b1 in the contaminated cell a1 is 3, and the genetic generation of the contaminated cell a2 is 2;

[0096] Determine whether the abnormal parameter type has infection characteristics, including obtaining the number of abnormal parameters of consecutive contaminated cells and constructing the abnormal parameter sequence of consecutive contaminated cells: ;

[0097] In the formula, represents the number of abnormal parameters of the jth contaminated cell in the continuous contaminated cells, j is a positive integer; n is the number of continuous contaminated cells;

[0098] If the sequence elements of the exception parameter sequence satisfy the relation:

[0099] ;

[0100] Then it is determined that the abnormal parameter type has an infectious characteristic; otherwise, it is determined that the abnormal parameter type does not have an infectious characteristic. Based on the relational expression: ; Calculate the infection value G of the abnormal parameter type;

[0101] Sum up the genetic algebra Y of all abnormal parameter types in the contaminated cell and use the calculation result as the first propagation parameter p1 of the affiliated contaminated cell. Sum up the infection values G of all abnormal parameter types in the contaminated cell and use the calculation result as the second propagation parameter p2 of the affiliated contaminated cell. Through the formula: Calculate the propagation value CB of the contaminated cell;

[0102] In the formula, w1 and w2 are the coefficients of the first propagation parameter p1 and the second propagation parameter p2 respectively;

[0103] According to the second instruction, count the total number of abnormal parameter types in the contaminated cell and use it as its propagation value;

[0104] Perform data analysis on the propagation values of the information cells. The methods for determining the automated monitoring method of water treatment include:

[0105] Monitor and obtain the propagation values CB of all information cells, and perform data analysis on the propagation values CB of all information cells. The propagation values CB of the information cells are respectively compared with a preset first risk threshold Z1 and a second risk threshold Z2, where Z1 < Z2;

[0106] If the propagation value CB satisfies CB ≤ Z1, send information indicating that the water treatment system is operating normally;

[0107] If the propagation value CB satisfies Z1 < CB ≤ Z2, send information indicating that the water treatment system has a mild abnormality and needs to be adjusted;

[0108] If the propagation value CB satisfies CB > Z2, send information indicating that the water treatment system has a severe abnormality and notify the technical personnel to promptly repair the water treatment system.

[0109] Embodiment 2. A mine water treatment automation and remote monitoring system proposed by the present invention is applied to a mine water treatment automation and remote monitoring method proposed in Embodiment 1, and specifically includes:

[0110] A data acquisition module, which is used to obtain the treatment process of mine water, collect data based on the execution process of the treatment process by the water treatment system, and obtain sample data;

[0111] The data processing module takes the sample data as the target data, performs data processing on the target data, determines the time unit sequence of each processing flow, obtains the target sub-data corresponding to the time unit in the time unit sequence, performs data analysis on the target sub-data, and determines the parameter analysis value of the time unit;

[0112] The monitoring and processing module is used to monitor the mine water in real time, obtain monitoring data, use the monitoring data as target data, perform data processing on the target data, determine the parameter state of the parameter analysis value, perform cellular simulation processing on the time unit based on the parameter analysis value and the corresponding parameter state, and construct the information cell of each time unit;

[0113] The monitoring and analysis module is used to perform infectiousness analysis on information cells, determine the propagation value of each information cell and perform data analysis on the propagation value of the information cell, determine the automated monitoring method for water treatment, and supervise the water treatment system based on the automated monitoring method for water treatment.

[0114] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto, and various changes can be made within the knowledge scope of technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A mine water treatment automation and remote monitoring method, characterized in that: The following steps are involved: Obtain the treatment process of mine water, collect data on the execution process of the treatment process based on the water treatment system, and obtain sample data; The sample data is used as the target data, data processing is performed on the target data, the time unit sequence of each processing flow is determined, the target sub-data corresponding to the time unit in the time unit sequence is obtained, data analysis is performed on the target sub-data, and the parameter analysis value of the time unit is determined; Monitor the mine water in real time to obtain monitoring data, use the monitoring data as target data, perform data processing on the target data, determine the parameter state of the parameter analysis value, perform cellular simulation processing on the time unit based on the parameter analysis value and the corresponding parameter state, and construct the information cell of each time unit; The method of performing cellular simulation processing on the time unit and constructing the information cell of each time unit includes: Determine the quantity status of the time unit, specifically including counting the number of time units in the current processing flow and taking it as the target number, comparing the target number with the quantity threshold, and if the target number is not greater than the quantity threshold, determining the parameter status of the parameter analysis value; If the target quantity is greater than the quantity threshold, the time unit under the same processing flow in the target data is expanded to obtain an extended unit, the number of extended units is the difference between the target quantity and the quantity threshold, and the parameter analysis value of any type of polluted water parameter in the extended unit is calculated to be 0 based on the parameter analysis formula; The method for determining the parameter status of the parameter analysis value includes: Perform data comparison on the parameter analysis value and the parameter threshold. If the parameter analysis value is not lower than the parameter threshold, the parameter analysis value is judged to be normal; if the parameter analysis value is lower than the parameter threshold, the corresponding polluted water parameter type is marked as an abnormal parameter type; Determine an information cell based on the processing flow, parameter status and time unit quantity status to which each time unit belongs; Conduct infectivity analysis on information cells, determine the propagation value of each information cell and perform data analysis on the propagation value of the information cell, determine the automated monitoring method for water treatment, and supervise the water treatment system based on the automated monitoring method for water treatment.

2. A mine water treatment automation and remote monitoring method according to claim 1, characterized in that: The sample data consists of the number of collections, processing flow, processing timestamp, and several contaminated water parameters.

3. A mine water treatment automation and remote monitoring method according to claim 2, characterized in that: Methods for processing target data include: Divide the processing timestamp of each processing flow into time periods to obtain a time unit sequence for each processing flow; Methods for data analysis of target sub-data include: For the same number of collections, the time unit sequence is traversed, and the time units are marked as target units in turn. It is periodically determined whether the polluted water parameter types contained in the target unit all have corresponding parameter analysis values. If the polluted water parameter types contained in the target unit all have corresponding parameter analysis values, the mark of the target unit is canceled and the next time unit is marked; If the target unit contains different types of polluted water parameters and corresponding parameter analysis values, perform the following operations: Mark the contaminated water parameter types without parameter analysis values as selected parameter types, and determine whether there is a previous time unit for the target unit. If there is a previous time unit for the target unit, then determine whether the previous time unit and the target time unit belong to the same treatment process; If the previous time unit and the target unit belong to the same treatment process, obtain the contaminated water parameters of the selected parameter types in the previous time unit and mark them as reference parameters; if the previous time unit and the target unit do not belong to the same treatment process, then determine that there is no previous time unit; If there is no previous time unit for the target unit, obtain the contaminated water parameters of the selected parameter types at the start of the treatment process and mark them as reference parameters.

4. A mine water treatment automation and remote monitoring method according to claim 3, characterized in that: Obtain the contaminated water parameters at the end of this treatment process and mark them as treatment result parameters; Obtain the change value of the polluted water parameter in the target unit, and calculate the parameter analysis value of the polluted water parameter of the target unit through the parameter analysis formula , the parameter analysis formula is as follows: ； In the formula, k is the time unit number, and k is a positive integer; is the change value of water pollution parameter; is the reference parameter; is the processing result parameter; i is the water pollution parameter number, i is a positive integer; c is a constant.

5. A mine water treatment automation and remote monitoring method according to claim 4, characterized in that: For the same time unit in different acquisition times, the parameter analysis values ​​of the same parameter type are Perform data comparison to determine the parameter range of the parameter type; For the same treatment process in different collection times, respectively count the number of time units in the treatment process to obtain the total number of time units corresponding to the collection times, and compare the total number of time units in different collection times to determine the quantity threshold of time units.

6. A mine water treatment automation and remote monitoring method according to claim 5, characterized in that: The method for performing infectivity analysis on information cells includes: Count the amount of abnormal states of information cells, and use the feature definition model to determine the cell features of information cells. The expression of the feature definition model is as follows: ； In the formula, S is the feature of the information cell, and N is the amount of abnormal states of the information cell; among them, S being normal indicates that the information cell is a normal cell; S being contaminated indicates that the information cell is a contaminated cell; When monitoring information cells at the start of the treatment process, if the information cell is a normal cell, no operation is performed on the information cell; if the information cell is a contaminated cell, then monitor whether there are consecutive contaminated cells; If there are consecutive contaminated cells, count the number of consecutive contaminated cells, and sequentially determine whether the abnormal parameter type has a genetic characteristic in the consecutive contaminated cells; If the abnormal parameter type has a genetic characteristic in the consecutive contaminated cells, generate a first instruction; if the abnormal parameter type does not have a genetic characteristic in the consecutive contaminated cells, generate a second instruction.

7. A mine water treatment automation and remote monitoring method according to claim 6, characterized in that: According to the first instruction, count the genetic generation Y of the abnormal parameter type and determine whether the abnormal parameter type has an infective characteristic; Determine whether the abnormal parameter type has infection characteristics, including obtaining the number of abnormal parameters of continuous contaminated cells and constructing the abnormal parameter sequence of continuous contaminated cells. ; In the formula, represents the number of abnormal parameters of the jth contaminated cell in the continuous contaminated cells, j is a positive integer; n is the number of continuous contaminated cells; If the sequence elements of the abnormal parameter sequence satisfy the relationship: ； Then the abnormal parameter type is judged to have the infection characteristic; otherwise, the abnormal parameter type is judged not to have the infection characteristic, based on the relational expression Calculate the infection value G of the abnormal parameter type; The genetic algebra Y of all abnormal parameter types in the contaminated cell is summed up and the calculation result is used as the first propagation parameter p1 of the contaminated cell. The infection value G of all abnormal parameter types in the contaminated cell is summed up and the calculation result is used as the second propagation parameter p2 of the contaminated cell. Calculate the propagation value CB of the polluted cell; In the formula, w1 and w2 are the coefficients of the first propagation parameter p1 and the second propagation parameter p2 respectively; According to the second instruction, count the total number of abnormal parameter types of contaminated cells and use it as its propagation value.

8. A mine water treatment automation and remote monitoring method according to claim 7, characterized in that: The method for performing data analysis on the propagation value of information cells to determine the automatic monitoring method for water treatment includes: Monitor and obtain the propagation value CB of all information cells, and perform data analysis on the propagation value CB of all information cells. The propagation value CB of the information cell is respectively compared with a preset first risk threshold Z1 and a second risk threshold Z2, where Z1 < Z2; If the propagation value CB satisfies CB ≤ Z1, send information that the water treatment system is operating normally; If the propagation value CB satisfies Z1 < CB ≤ Z2, send that the water treatment system is slightly abnormal and needs adjustment; If the propagation value CB satisfies CB > Z2, send that the water treatment system is severely abnormal and notify the technical personnel to promptly repair the water treatment system.

9. A mine water treatment automation and remote monitoring system, applied to a mine water treatment automation and remote monitoring method as claimed in any one of claims 1 to 8, characterized in that: Specifically include: The data acquisition module is used to obtain the treatment process of mine water, collect data on the execution process of the treatment process based on the water treatment system, and obtain sample data; The data processing module takes the sample data as the target data, performs data processing on the target data, determines the time unit sequence of each processing flow, obtains the target sub-data corresponding to the time unit in the time unit sequence, performs data analysis on the target sub-data, and determines the parameter analysis value of the time unit; The monitoring and processing module is used to monitor the mine water in real time, obtain monitoring data, use the monitoring data as target data, perform data processing on the target data, determine the parameter state of the parameter analysis value, perform cellular simulation processing on the time unit based on the parameter analysis value and the corresponding parameter state, and construct the information cell of each time unit; The monitoring and analysis module is used to perform infectiousness analysis on information cells, determine the propagation value of each information cell and perform data analysis on the propagation value of the information cell, determine the automated monitoring method for water treatment, and supervise the water treatment system based on the automated monitoring method for water treatment.

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