CN116975767B - Intelligent water affair monitoring system and disaster deduction method based on big data analysis - Google Patents
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Abstract
The invention discloses an intelligent water affair monitoring system and a disaster deduction method based on big data analysis, comprising a pipe network acquisition unit, a pipe monitoring unit, a pipe analysis unit and an abnormality display unit. According to the intelligent water service monitoring system and the disaster deduction method based on big data analysis, the pipeline analysis unit is used for analyzing the water drain pipe data in various modes to obtain abnormal signals of the corresponding water drain pipes, so that the running state of the whole urban water drain pipe network is mastered globally in real time, the abnormal problems of the water drain pipes are effectively identified, data support is provided for formulating a water drain management treatment scheme, the defects and problems existing in the running of the water drain pipes can be timely found and diagnosed, the water accumulation deduction analysis is carried out on a designated area, and further flood disasters can be intuitively displayed, and therefore the prevention and treatment effect on the flood disasters can be improved, and personnel and property damage in the area caused by the water accumulation problem can be avoided.
Description
Technical Field
The invention relates to the technical field of water affair monitoring, in particular to an intelligent water affair monitoring system and a disaster deduction method based on big data analysis.
Background
The construction of the existing urban water service monitoring system is relatively lagged, the monitoring means used by the existing early warning system are not scientific enough, the early warning result error is large, the abnormal condition of the urban drainage pipe network cannot be truly reflected, and the method has great influence on the establishment of disaster prevention and reduction measures.
Therefore, the establishment of the urban drainage pipe network water service monitoring system provides a management platform for urban drainage pipe managers to observe the water level change of the drainage pipe network in real time and analyze the dynamic running condition of the drainage pipe network, and has become an urgent requirement for modern urban drainage management.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent water affair monitoring system and a disaster deduction method based on big data analysis, which solve the problems in the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: an intelligent water affair monitoring system and a disaster deduction method based on big data analysis comprise the following steps:
the pipe network acquisition unit is used for acquiring the pipeline distance of each drain pipe in the urban drainage pipe network and then sending the pipeline distance to the pipeline analysis unit;
the pipeline monitoring unit is used for monitoring inflow and outflow of each drain pipe in real time in the urban drain pipe network and monitoring the water flow rate in the drain pipe in real time, then sending all the detected results to the pipeline analysis unit, wherein the inflow is represented as inflow of the drain pipe, the outflow is represented as outflow of the drain pipe, and the water flow rate is represented as speed of water flowing in the drain pipe;
the pipeline analysis unit is used for analyzing and obtaining abnormal signals of the corresponding drainage pipes according to the pipeline distance, the water flow rate, the inflow flow rate and the outflow flow rate of each drainage pipe, and then sending the abnormal signals to the abnormal display unit;
and the abnormal display unit is used for marking the corresponding drain pipe in the urban drain pipe network according to the early warning signal and displaying the marked water to the manager.
Preferably, the specific detection mode of the pipeline monitoring unit is as follows: and selecting one drain pipe between two inspection wells, acquiring the inflow flow and the outflow flow of the drain pipe in real time through a flowmeter at the inflow end and the outflow end of the drain pipe, and simultaneously acquiring a plurality of water flow rates in real time through a plurality of flow rate sensors arranged at different positions inside the drain pipe.
Preferably, the analysis mode of the pipeline analysis unit is as follows:
SA1, taking a drain pipe between two inspection wells as an example, and acquiring a plurality of water flow rates in the drain pipe at a designated time point;
SA2, calculating the discrete degree of all water flow rates, comparing the discrete degree with a preset discrete threshold value, deleting a group of water flow rates with the largest value according to the comparison result if the discrete degree is larger than the discrete threshold value, calculating the discrete degree of the rest water flow rates until the discrete degree is smaller than or equal to the discrete threshold value, and then calculating the average value of all undeleted water flow rates and recording the average value as an analysis flow rate;
SA3, calculating the pipeline distance and the analysis flow rate according to a speed calculation formula to obtain the time from the inflow end to the outflow end of the water body, and recording the time as the flowing time Ts;
SA4, obtaining the outflow flow of the drain pipe in a specific time period T1, and obtaining the corresponding inflow flow in a time period T0 before the specific time point of the drain pipe, wherein T0 is set according to Ts, and a gap Ts is reserved between T0 and T1;
SA5, carrying out difference calculation on the outflow flow and the inflow flow obtained in the step SA4, marking the obtained difference as CC, and then comparing |CC| with a preset comparison threshold CY, wherein |CC| is expressed as an absolute value of CC, and "||" is an absolute value sign, and judging an abnormal signal of the drainage pipeline according to the comparison result.
Preferably, the drainage pipeline abnormality signal is determined as follows:
if |CC| > CY, the drain pipe is abnormal, and an abnormal signal is generated; otherwise, no abnormal signal is generated.
Preferably, the analysis mode of the pipe analysis unit is as follows:
SB1, taking a drain pipe between two inspection wells as an example, acquiring a plurality of water flow rates in the drain pipe at a designated time point, and sequencing the water flow rates according to the arrangement sequence of flow rate sensors from the inflow end to the outflow end of the drain pipe to obtain a corresponding flow rate sequence table;
SB2, slave flowExtracting the water flow rate arranged at the head in the flow rate table as a reference flow rate value, sequentially calculating the difference between the reference flow rate value and the other water flow rates in the flow rate table from front to back, and recording the difference as a flow rate difference SC i I=1, 2, … …, n-1, n represents the number of flow velocity sensors in the drain, n-1 represents the number of adjacent differences in flow velocity in the drain, i represents the number of flow velocity adjacent differences, SC i Indicating what flow rate difference is in the drain pipe;
SB3, subsequent treatment of the respective flow velocity differences SC i Respectively with a preset flow speed difference threshold value SC y Comparing with SC i ＞SC y And SC (SC) i ≤SC y And then judging the abnormal position of the lower pipeline according to the comparison result and generating an abnormal signal.
Preferably, the determination method of the pipe line abnormal position and the abnormal signal is as follows:
SC is obtained one by one according to the sequence from front to back of the flow velocity sequence table i ＞SC y Is a comparison of the results of (a):
if there is no SC in the flow rate sequence table i ＞SC y Indicating that the drain pipe is draining normally;
if SC exists in the flow rate sequence table i ＞SC y The abnormal drainage of the drain pipe is indicated, and the first SC is obtained according to the flow velocity sequence table i ＞SC y Corresponding SC i Then according to the SC i And acquiring a corresponding flow velocity sensor, wherein the position of the flow velocity sensor is an abnormal position, and generating an abnormal signal.
Preferably, the analysis mode of the pipeline analysis unit is as follows:
SC1, taking a drain pipe between two inspection wells as an example, acquiring a plurality of water flow rates in the drain pipe at a designated time point, and sequencing the water flow rates according to the arrangement sequence of flow rate sensors from the inflow end to the outflow end of the drain pipe to obtain a corresponding flow rate sequence table;
SC2, calculating the flow velocity between two adjacent water bodies sequentially from front to back in the flow velocity sequence tableThe difference is recorded as the flow velocity adjacent difference LC i I=1, 2, … …, n-1, n represents the number of flow velocity sensors in the drain, n-1 represents the number of adjacent differences in flow velocity in the drain, i represents the number of adjacent differences, LC i Indicating what flow velocity is adjacent to the difference in the drain;
SC3, acquisition of individual LC i And acquiring and connecting a plurality of LC according to the flow velocity sequence table i LC of positive value i And compares it with a preset neighbor difference threshold LC y Comparing, if at least one LC is present i ＞LC y Indicating that the drainage pipeline is abnormal, and acquiring LC i ＞LC y Corresponding LC i Then according to the SC i And acquiring a corresponding flow velocity sensor, wherein the position of the flow velocity sensor is an abnormal position, and generating an abnormal signal.
The disaster deduction method based on big data analysis is realized by the intelligent water affair monitoring system based on big data analysis, and comprises the following steps:
step one, acquiring the positions of all inspection wells according to an urban drainage pipe network, and simultaneously acquiring the maximum water storage volume of all inspection wells;
step two, simultaneously acquiring a drain pipe generating an abnormal signal from the urban drain pipe network;
simultaneously obtaining the analysis flow rate of the drain pipe, then calculating the maximum water storage volume and the analysis flow rate of the inspection well, obtaining the time of the inspection well for discharging the water body with the corresponding volume, and recording the time as the analysis time;
step three, obtaining rainfall in a designated period in weather forecast, then calculating a multiple value between analysis time and the designated period, and multiplying the multiple value by the rainfall in the designated period to obtain total rainfall in the analysis time;
step four, comparing the total rainfall with the water storage volume:
if the total rainfall is greater than or equal to the water storage volume, the situation that the corresponding inspection well position has water accumulation risk is indicated, and an early warning signal is generated; otherwise, the corresponding inspection well position can normally drain rainwater, and an early warning signal is not generated;
and fifthly, corresponding personnel make an adaptive scheme according to the early warning signal.
Advantageous effects
The invention provides an intelligent water affair monitoring system and a disaster deduction method based on big data analysis. Compared with the prior art, the method has the following beneficial effects:
the system acquires the drain pipe data of the selected area by utilizing the pipe network acquisition unit and the pipe monitoring unit, analyzes the drain pipe data in a plurality of modes by utilizing the pipe analysis unit to obtain abnormal signals of the corresponding drain pipe, provides effective data for the operation and maintenance of the drain system, realizes the overall real-time mastering of the running state of the whole urban drain pipe network, effectively identifies the abnormal problem of the drain pipe, provides data support for formulating a drain pipe treatment scheme, and can timely find and diagnose the defects and problems existing in the operation of the drain pipe;
according to the method, based on the result obtained by the intelligent water affair monitoring system for big data analysis, the accumulated water deduction analysis is carried out on the designated area, so that a deduction result analysis report is obtained, and further, the flood disaster can be visually displayed, the control effect on the flood disaster can be improved, the damage to personnel and property in the area caused by the accumulated water problem is avoided, and the emergency flood prevention capability of the drainage system is improved.
Drawings
FIG. 1 is a system block diagram of the present invention;
fig. 2 is a flow chart of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As an embodiment of the invention
Referring to fig. 1, the present invention provides the following technical solutions: an intelligent water affair monitoring system and a disaster deduction method based on big data analysis comprise the following steps:
the pipe network acquisition unit is used for acquiring the pipeline distance of each drain pipe in the urban drainage pipe network and then sending the pipeline distance to the pipeline analysis unit;
the pipeline monitoring unit is used for monitoring the inflow flow and the outflow flow of each drain pipe in the urban drain pipe network in real time and monitoring the water flow velocity in the drain pipe in real time, and then sending all the detected results to the pipeline analysis unit;
the specific detection mode of the pipeline monitoring unit is as follows: taking a drain pipe between two inspection wells as an example, acquiring the inflow flow and the outflow flow of the drain pipe in real time through a flowmeter at the inflow end and the outflow end of the drain pipe, and simultaneously acquiring a plurality of water flow rates in real time through a plurality of flow rate sensors arranged at different positions in the drain pipe;
the pipeline analysis unit is used for analyzing and obtaining abnormal signals of the corresponding drainage pipes according to the pipeline distance, the water flow rate, the inflow flow rate and the outflow flow rate of each drainage pipe, and then sending the abnormal signals to the abnormal display unit;
the analysis mode of the pipeline analysis unit is as follows:
SA1, taking a drain pipe between two inspection wells as an example, and acquiring a plurality of water flow rates in the drain pipe at a designated time point;
in the embodiment, the underground pipeline is mostly linear, when the steering is needed, the inspection well is arranged at the steering position, so that the linear pipeline is not easy to block, and the pipeline is easy to install, and therefore, the analysis is performed by taking a drain pipe between two inspection wells as an example;
SA2, calculating the discrete degree of all water flow rates, comparing the discrete degree with a preset discrete threshold value, deleting a group of water flow rates with the largest value according to the comparison result if the discrete degree is larger than the discrete threshold value, calculating the discrete degree of the rest water flow rates until the discrete degree is smaller than or equal to the discrete threshold value, and then calculating the average value of all undeleted water flow rates and recording the average value as an analysis flow rate;
the discrete degree calculating mode is a common technical means for the person skilled in the art, and the specific mode is as follows:
first byObtaining discrete values L of all water flow rates, wherein S j Indicates the water flow rate obtained by monitoring the flow rate sensors in the drain pipe, j=1, 2, … …, n indicates the number of the flow rate sensors in the drain pipe, S p Representing the average value of all water flow rates in the drain pipe;
then comparing the calculated L with L0, if L > L0, the discrete value L is considered to be too large, according to |S i -S p The corresponding S is sequentially removed from the order of the big to the small i The value is correspondingly calculated to the residual discrete value L until L is less than or equal to L0, and then all S which is not removed is obtained i The value L0 is a preset discrete threshold value;
SA3, calculating the pipeline distance and the analysis flow rate according to a speed calculation formula to obtain the time from the inflow end to the outflow end of the water body, and recording the time as the flowing time Ts;
SA4, obtaining the outflow flow of the drain pipe in a specific time period T1, and obtaining the corresponding inflow flow in a time period T0 before the specific time point of the drain pipe, wherein T0 is set according to Ts, and a gap Ts is reserved between T0 and T1;
SA5, calculating the difference value between the outflow flow and the inflow flow obtained in the step four, marking the obtained difference value as CC, and comparing |CC| with a preset comparison threshold value CY, wherein |CC| is expressed as an absolute value of CC, and "||" is an absolute value sign, and judging an abnormal signal of the drainage pipeline according to the comparison result, wherein the specific judging mode is as follows:
if |CC| > CY, the drain pipe is abnormal, and an abnormal signal is generated; otherwise, no abnormal signal is generated;
in this embodiment, the abnormal signal obtained by the analysis of the pipe analysis unit indicates that the corresponding drain pipe has abnormal problems such as defect or blockage;
when |CC| > CY and the value of CC is negative, the outflow flow of the inflow end of the corresponding drain pipe is smaller than the inflow flow of the outflow end, firstly, the outflow flow of the inflow end is smaller than the inflow flow of the outflow end possibly caused by the defect of the drain pipe when groundwater or other water flows into the drain pipe, secondly, the drain pipe is blocked in the early stage possibly, a quantitative water body is contained in the drain pipe during analysis, and the water flow of the drain pipe in the time period washes out a blocking object to the corresponding inspection well, so that the outflow flow of the inflow end of the drain pipe is smaller than the inflow flow of the outflow end;
when |CC| > CY and the value of CC is positive, the outflow flow of the inflow end of the corresponding drain pipe is larger than the inflow flow of the outflow end, firstly, the outflow flow of the inflow end is larger than the inflow flow of the outflow end possibly because of defect of the drain pipe, and secondly, the outflow flow of the inflow end of the drain pipe is smaller than the inflow flow of the outflow end possibly because of blockage of the drain pipe due to the inclusion of impurities in the water body in the drain pipe during analysis;
and the abnormal display unit is used for marking the corresponding drain pipe in the urban drain pipe network according to the early warning signal and displaying the marked water to the manager.
According to the embodiment, by adopting the technical scheme, the pipe network acquisition unit and the pipeline monitoring unit are utilized to acquire the drain pipe data of the selected area, the pipeline analysis unit is used for analyzing the drain pipe data to obtain the abnormal signal of the corresponding drain pipe, effective data is provided for operation and maintenance of a drainage system, the operation state of the whole urban drain pipe network is mastered globally in real time, the abnormal problem of the drain pipe is effectively identified, and data support is provided for formulating a drain pipe treatment scheme.
As embodiment II of the present invention
In this embodiment, compared to the first embodiment, the pipe analysis unit of this embodiment further provides an analysis method, which is as follows:
SB1, taking a drain pipe between two inspection wells as an example, acquiring a plurality of water flow rates in the drain pipe at a designated time point, and sequencing the water flow rates according to the arrangement sequence of flow rate sensors from the inflow end to the outflow end of the drain pipe to obtain a corresponding flow rate sequence table;
SB2, extracting the water flow rate arranged at the first position from the flow rate sequence table, taking the water flow rate as a reference flow rate value, sequentially calculating the difference value between the reference flow rate value and the other water flow rates from front to back in the flow rate sequence table, and recording the difference value as a flow rate difference SC i I=1, 2, … …, n-1, n represents the number of flow velocity sensors in the drain, n-1 represents the number of adjacent differences in flow velocity in the drain, i represents the number of flow velocity adjacent differences, SC i Indicating what flow rate difference is in the drain pipe;
SB3, subsequent treatment of the respective flow velocity differences SC i Respectively with a preset flow speed difference threshold value SC y Comparing with SC i ＞SC y And SC (SC) i ≤SC y Then judging the abnormal position of the lower pipeline according to the comparison result and generating an abnormal signal;
the judging mode is as follows:
SC is obtained one by one according to the sequence from front to back of the flow velocity sequence table i ＞SC y Is a comparison of the results of (a):
if there is no SC in the flow rate sequence table i ＞SC y Indicating that the drain pipe is draining normally;
if SC exists in the flow rate sequence table i ＞SC y The abnormal drainage of the drain pipe is indicated, and the first SC is obtained according to the flow velocity sequence table i ＞SC y Corresponding SC i Then according to the SC i And acquiring a corresponding flow velocity sensor, wherein the position of the flow velocity sensor is an abnormal position, and generating an abnormal signal.
In the embodiment, the abnormal signal obtained by the analysis of the pipeline analysis unit is expressed as that the corresponding drain pipe has abnormal problems such as blockage and the like, and the obtained abnormal position is the blockage section of the blockage in the drain pipe;
according to the embodiment, by adopting the technical scheme, the pipeline analysis unit is utilized to analyze the data of the drainage pipe according to another mode to obtain the abnormal signal of the corresponding drainage pipe, so that the running state of the whole urban drainage pipe network is further mastered globally in real time, the abnormal problem of the drainage pipe is effectively identified, and data support is provided for formulating a drainage management treatment scheme.
Embodiment III as the present invention
In this embodiment, compared to the first embodiment, the pipe analysis unit of this embodiment further provides an analysis method, which is as follows:
SC1, taking a drain pipe between two inspection wells as an example, acquiring a plurality of water flow rates in the drain pipe at a designated time point, and sequencing the water flow rates according to the arrangement sequence of flow rate sensors from the inflow end to the outflow end of the drain pipe to obtain a corresponding flow rate sequence table;
SC2, calculating the difference between the flow rates of two adjacent water bodies sequentially from front to back in the flow rate sequence table, and recording the difference as a flow rate adjacent difference LC i I=1, 2, … …, n-1, n represents the number of flow velocity sensors in the drain, n-1 represents the number of adjacent differences in flow velocity in the drain, i represents the number of adjacent differences, LC i Indicating what flow velocity is adjacent to the difference in the drain;
SC3, acquisition of individual LC i And acquiring and connecting a plurality of LC according to the flow velocity sequence table i LC of positive value i And compares it with a preset neighbor difference threshold LC y Comparing, if at least one LC is present i ＞LC y Indicating that the drainage pipeline is abnormal, and acquiring LC i ＞LC y Corresponding LC i Then according to the SC i And acquiring a corresponding flow velocity sensor, wherein the position of the flow velocity sensor is an abnormal position, and generating an abnormal signal.
In the embodiment, the abnormal signal obtained by the analysis of the pipeline analysis unit is expressed as that the corresponding drain pipe has abnormal problems such as blockage and the like, and the obtained abnormal position is the blockage section of the blockage in the drain pipe;
according to the embodiment, by adopting the technical scheme, the pipeline analysis unit is utilized to analyze the data of the drainage pipe according to another mode to obtain the abnormal signal of the corresponding drainage pipe, so that the running state of the whole urban drainage pipe network is further mastered globally in real time, the abnormal problem of the drainage pipe is effectively identified, and data support is provided for formulating a drainage management treatment scheme.
Fourth embodiment of the invention
This embodiment will be described in conjunction with the first to third embodiments.
Referring to fig. 2, the present invention further provides the following technical solutions: the disaster deduction method based on big data analysis is realized through the intelligent water affair monitoring system based on big data analysis, and comprises the following steps:
step one, acquiring the positions of all inspection wells according to an urban drainage pipe network, and simultaneously acquiring the maximum water storage volume of all inspection wells;
step two, simultaneously acquiring a drain pipe generating an abnormal signal from the urban drain pipe network;
simultaneously obtaining the analysis flow rate of the drain pipe, then calculating the maximum water storage volume and the analysis flow rate of the inspection well, obtaining the time of the inspection well for discharging the water body with the corresponding volume, and recording the time as the analysis time;
step three, obtaining rainfall in a designated period in weather forecast, then calculating a multiple value between analysis time and the designated period, and multiplying the multiple value by the rainfall in the designated period to obtain total rainfall in the analysis time;
step four, comparing the total rainfall with the water storage volume:
if the total rainfall is greater than or equal to the water storage volume, the situation that the corresponding inspection well position has water accumulation risk is indicated, and an early warning signal is generated; otherwise, the corresponding inspection well position can normally drain rainwater, and an early warning signal is not generated;
and fifthly, corresponding personnel make an adaptive scheme according to the early warning signal.
According to the embodiment, based on the result obtained by the intelligent water affair monitoring system for big data analysis, accumulated water deduction analysis is carried out on a designated area, and a deduction result analysis report is obtained; and further, the flood disasters can be intuitively displayed, so that the control effect on the flood disasters can be improved, and the damage to personnel and property in the area caused by the water accumulation problem is avoided.
And all that is not described in detail in this specification is well known to those skilled in the art.
The foregoing describes one embodiment of the present invention in detail, but the disclosure is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (7)
1. Intelligent water affair monitoring system based on big data analysis, its characterized in that includes:
the pipe network acquisition unit is used for acquiring the pipeline distance of each drain pipe in the urban drainage pipe network and then sending the pipeline distance to the pipeline analysis unit;
the pipeline monitoring unit is used for monitoring inflow and outflow of each drain pipe in real time in the urban drain pipe network and monitoring the water flow rate in the drain pipe in real time, then sending all the detected results to the pipeline analysis unit, wherein the inflow is represented as inflow of the drain pipe, the outflow is represented as outflow of the drain pipe, and the water flow rate is represented as speed of water flowing in the drain pipe;
the pipeline analysis unit is used for analyzing and obtaining abnormal signals of the corresponding drainage pipes according to the pipeline distance, the water flow rate, the inflow flow rate and the outflow flow rate of each drainage pipe, and then sending the abnormal signals to the abnormal display unit;
the analysis mode of the pipeline analysis unit is as follows:
SA1, taking a drain pipe between two inspection wells as an example, and acquiring a plurality of water flow rates in the drain pipe at a designated time point;
SA2, calculating the discrete degree of all water flow rates, comparing the discrete degree with a preset discrete threshold value, deleting a group of water flow rates with the largest value according to the comparison result if the discrete degree is larger than the discrete threshold value, calculating the discrete degree of the rest water flow rates until the discrete degree is smaller than or equal to the discrete threshold value, and then calculating the average value of all undeleted water flow rates and recording the average value as an analysis flow rate;
SA3, calculating the pipeline distance and the analysis flow rate according to a speed calculation formula to obtain the time from the inflow end to the outflow end of the water body, and recording the time as the flowing time Ts;
SA4, obtaining the outflow flow of the drain pipe in a specific time period T1, and obtaining the corresponding inflow flow in a time period T0 before the specific time point of the drain pipe, wherein T0 is set according to Ts, and a gap Ts is reserved between T0 and T1;
SA5, carrying out difference calculation on the outflow flow and the inflow flow obtained in the step SA4, marking the obtained difference as CC, and then comparing |CC| with a preset comparison threshold value CY, wherein |X| is expressed as an absolute value, and judging an abnormal signal of the drainage pipeline according to a comparison result;
and the abnormal display unit is used for marking the corresponding drain pipe in the urban drain pipe network according to the early warning signal and displaying the marked water to the manager.
2. The intelligent water service monitoring system based on big data analysis of claim 1, wherein: the specific detection mode of the pipeline monitoring unit is as follows: and selecting one drain pipe between two inspection wells, acquiring the inflow flow and the outflow flow of the drain pipe in real time through a flowmeter at the inflow end and the outflow end of the drain pipe, and simultaneously acquiring a plurality of water flow rates in real time through a plurality of flow rate sensors arranged at different positions inside the drain pipe.
3. The intelligent water service monitoring system based on big data analysis of claim 1, wherein: the abnormal signal of the drainage pipeline is judged as follows:
if |CC| > CY, the drain pipe is abnormal, and an abnormal signal is generated; otherwise, no abnormal signal is generated.
4. The intelligent water service monitoring system based on big data analysis of claim 1, wherein: the analysis mode of the pipeline analysis unit is as follows:
SB1, taking a drain pipe between two inspection wells as an example, acquiring a plurality of water flow rates in the drain pipe at a designated time point, and sequencing the water flow rates according to the arrangement sequence of flow rate sensors from the inflow end to the outflow end of the drain pipe to obtain a corresponding flow rate sequence table;
SB2, extracting the water flow rate arranged at the first position from the flow rate sequence table, taking the water flow rate as a reference flow rate value, sequentially calculating the difference value between the reference flow rate value and the other water flow rates from front to back in the flow rate sequence table, and recording the difference value as a flow rate difference SC i I=1, 2, … …, n-1, n represents the number of flow velocity sensors in the drain, n-1 represents the number of adjacent differences in flow velocity in the drain, i represents the number of flow velocity adjacent differences, SC i Indicating what flow rate difference is in the drain pipe;
SB3, subsequent treatment of the respective flow velocity differences SC i Respectively with a preset flow speed difference threshold value SC y Comparing with SC i ＞SC y And SC (SC) i ≤SC y And then judging the abnormal position of the lower pipeline according to the comparison result and generating an abnormal signal.
5. The intelligent water service monitoring system based on big data analysis of claim 4, wherein: judging modes of abnormal positions and abnormal signals of the pipeline:
SC is obtained one by one according to the sequence from front to back of the flow velocity sequence table i ＞SC y Is a comparison of the results of (a):
if there is no SC in the flow rate sequence table i ＞SC y Indicating that the drain pipe is draining normally;
if SC exists in the flow rate sequence table i ＞SC y The abnormal drainage of the drain pipe is indicated, and the first SC is obtained according to the flow velocity sequence table i ＞SC y Corresponding SC i Then according to the SC i Acquiring a corresponding flow rate sensor, and the flow rate sensorThe position is an abnormal position and generates an abnormal signal.
6. The intelligent water service monitoring system based on big data analysis of claim 1, wherein: the analysis mode of the pipeline analysis unit is as follows:
SC1, taking a drain pipe between two inspection wells as an example, acquiring a plurality of water flow rates in the drain pipe at a designated time point, and sequencing the water flow rates according to the arrangement sequence of flow rate sensors from the inflow end to the outflow end of the drain pipe to obtain a corresponding flow rate sequence table;
SC2, calculating the difference between the flow rates of two adjacent water bodies sequentially from front to back in the flow rate sequence table, and recording the difference as a flow rate adjacent difference LC i I=1, 2, … …, n-1, n represents the number of flow velocity sensors in the drain, n-1 represents the number of adjacent differences in flow velocity in the drain, i represents the number of adjacent differences, LC i Indicating what flow velocity is adjacent to the difference in the drain;
SC3, acquisition of individual LC i And acquiring and connecting a plurality of LC according to the flow velocity sequence table i LC of positive value i And compares it with a preset neighbor difference threshold LC y Comparing, if at least one LC is present i ＞LC y Indicating that the drainage pipeline is abnormal, and acquiring LC i ＞LC y Corresponding LC i Then according to the SC i And acquiring a corresponding flow velocity sensor, wherein the position of the flow velocity sensor is an abnormal position, and generating an abnormal signal.
7. The disaster deduction method based on big data analysis is characterized in that the method is realized by the intelligent water service monitoring system based on big data analysis according to any one of claims 1-6, and the method comprises the following steps:
step one, acquiring the positions of all inspection wells according to an urban drainage pipe network, and simultaneously acquiring the maximum water storage volume of all inspection wells;
step two, simultaneously acquiring a drain pipe generating an abnormal signal from the urban drain pipe network;
simultaneously obtaining the analysis flow rate of the drain pipe, then calculating the maximum water storage volume and the analysis flow rate of the inspection well, obtaining the time of the inspection well for discharging the water body with the corresponding volume, and recording the time as the analysis time;
step three, obtaining rainfall in a designated period in weather forecast, then calculating a multiple value between analysis time and the designated period, and multiplying the multiple value by the rainfall in the designated period to obtain total rainfall in the analysis time;
step four, comparing the total rainfall with the water storage volume:
if the total rainfall is greater than or equal to the water storage volume, the situation that the corresponding inspection well position has water accumulation risk is indicated, and an early warning signal is generated; otherwise, the corresponding inspection well position can normally drain rainwater, and an early warning signal is not generated;
and fifthly, corresponding personnel make an adaptive scheme according to the early warning signal.
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