CN117009771B - Water pollution degree detection method and system suitable for park city - Google Patents
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Abstract
The invention discloses a water pollution degree detection method and a system suitable for park cities, and particularly relates to the technical field of water pollution detection, wherein the reliability and the accuracy of water pollution data detected by water pollution detection equipment can be more comprehensively and quantitatively evaluated by calculating a reliability evaluation coefficient of the pollution detection equipment through normalization processing through an abnormal flow rate aggressive ratio, a flow rate time offset exceeding index and a data comprehensive transmission bumping reliability evaluation index; setting a credibility evaluation threshold value is helpful for classifying the water pollution data into credibility and non-credibility, and is helpful for better understanding the credibility and accuracy of the water pollution data; the comprehensive trust ratio is obtained by considering the data of the plurality of water pollution detection devices, and the data of the water pollution detection devices can be classified into trusted and untrusted by setting the threshold value of the comprehensive trust ratio, so that measures can be taken in time to solve the water quality problem possibly existing, and the efficiency and the effect of water quality monitoring are improved.
Description
Technical Field
The invention relates to the technical field of water pollution detection, in particular to a water pollution degree detection method and system suitable for parks and cities.
Background
Park cities are generally referred to as a concept of urban planning and design, and emphasize that a great number of natural elements such as public greenbelts, parks, green belts and the like are integrated in urban planning so as to provide places for people to take leisure, entertain, exercise and social activities and create a healthier and more suitable urban environment. In park cities, greenbelts and natural landscapes are considered part of the urban infrastructure, with important ecological, social and economic value. The water system of park city is an important component in city planning, and includes various elements and facilities related to water, aiming at creating healthy and suitable urban environment.
In a park city, a planned artificial water channel exists, so that the artificial water channel flows through green lands and parks, and natural elements of the city are enhanced; in order to ensure that the water quality of the artificial water channel is kept in a good state, a plurality of water pollution detection devices are usually arranged along the artificial water channel so as to monitor the water pollution condition of the artificial water channel in real time. However, the actual running state of the water pollution detection device has a great influence on the accuracy and the reliability of the water pollution degree detection, and the acquired water quality data may be inaccurate, so that the judgment of the water pollution degree is influenced.
In order to solve the above problems, a technical solution is now provided.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a method and a system for detecting water pollution level suitable for park cities, so as to solve the problems set forth in the above-mentioned background art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a water pollution degree detection method suitable for park cities comprises the following steps:
step S1: collecting water flow velocity change information corresponding to the water pollution detection equipment, and calculating a flow velocity abnormal excitation ratio and a flow velocity time offset exceeding index according to the water flow velocity change information;
step S2: the method comprises the steps of collecting complete information of water quality monitoring data corresponding to water pollution detection equipment, calculating a water pollution data fault ratio and a fault close relation ratio, weighting the water pollution data fault ratio and the fault close relation ratio, and calculating a data comprehensive transmission jolt credibility assessment index;
step S3: calculating a reliable evaluation coefficient of the pollution detection equipment through normalization processing on the flow speed abnormal aggressive ratio, the flow speed time offset exceeding index and the data comprehensive transmission bumping reliable evaluation index; generating a non-trusted signal of the pollution detection equipment or a trusted signal of the pollution detection equipment by comparing the trusted evaluation coefficient of the pollution detection equipment with a trusted evaluation threshold, and marking water pollution data detected by the water pollution detection equipment in a credibility monitoring interval as non-trusted water pollution data or trusted water pollution data;
step S4: acquiring marked conditions of water pollution data, and calculating a comprehensive trust ratio according to the marked conditions of the water pollution data; and generating a comprehensive untrustworthy signal or a comprehensive trust signal through comparison of the comprehensive trust ratio and the comprehensive trust ratio threshold value.
In a preferred embodiment, in step S1, a reliability monitoring interval is set;
acquiring the flow rate of the area of the artificial waterway in the credibility monitoring interval; setting a flow rate threshold;
calculating the time length of the actual flow rate in the credibility monitoring interval being greater than the flow rate threshold value, and marking the time length of the actual flow rate in the credibility monitoring interval being greater than the flow rate threshold value and the time length corresponding to the credibility monitoring interval as the abnormal flow rate excitation ratio; marking abnormal shock ratio of flow velocity as。
In a preferred embodiment, a time interval in which the actual flow rate in the reliability monitoring interval is greater than the flow rate threshold is obtained; setting a time interval exceeding a threshold value; acquiring the number of time intervals, in which the actual flow rate exceeds the flow rate threshold, of which the time length is greater than the time interval exceeding the threshold and the actual flow rate is greater than the flow rate threshold, corresponding to the time intervals, in which the actual flow rate is greater than the flow rate threshold, in the credibility monitoring interval, and calculating a flow rate time offset exceeding index, wherein the expression is as follows:wherein->The number of time intervals of which the time length is larger than the time interval of which the actual flow rate exceeds the flow rate threshold value and the number of time intervals of which the time length is larger than the time interval of which the actual flow rate exceeds the flow rate threshold value,，/>are positive integers greater than 1; />Respectively the flow velocity time offset exceeds the index, the +.>The time interval corresponding to the time interval when the actual flow velocity is larger than the flow velocity threshold value is longer than the time interval when the actual flow velocity exceeding the flow velocity threshold value is larger than the flow velocity threshold value; />Is a constant term.
In a preferred embodiment, in step S2, the number of times of occurrence of the water pollution data transmission failure in the reliability monitoring section is obtained, and each time point corresponding to the occurrence of the water pollution data transmission failure in the reliability monitoring section is obtained;
calculating a water pollution data fault ratio, wherein the water pollution data fault ratio is the ratio of the number of times of water pollution data transmission faults in a credibility monitoring interval to the time length corresponding to the credibility monitoring interval;
acquiring a time interval of adjacent time points of water pollution data transmission faults in a credibility monitoring interval; marking the time interval of adjacent time points, in which water pollution data transmission faults occur, in the reliability monitoring interval as a fault interval;
setting a fault interval threshold value; the method comprises the steps of obtaining the number of fault intervals in a reliability monitoring interval, and marking the ratio of the number of the fault intervals, in which the fault intervals are larger than a fault interval threshold, to the number of the fault intervals in the reliability monitoring interval as a fault close relation ratio;
the water pollution data fault ratio and the fault close relation ratio are weighted, and the data comprehensive transmission jolt credibility assessment index is calculated, wherein the expression is as follows:wherein->Respectively transmitting jolt credible evaluation indexes, water pollution data fault ratios and fault close relation ratios for the data; />Weights of water pollution data fault ratio and fault close relation ratio respectively>Are all greater than 0.
In a preferred embodiment, the expression of the reliability evaluation coefficient of the soil inspection device is:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>The method comprises the steps of (1) credible evaluation coefficients for pollution detection equipment; />Preset proportionality coefficients of flow speed abnormal aggressive ratio, flow speed time offset exceeding index and data comprehensive transmission jolt credibility assessment index respectively>Are all greater than 0;
setting a credibility evaluation threshold; when the credibility evaluation coefficient of the pollution detection equipment is larger than the credibility evaluation threshold, generating a non-credibility signal of the pollution detection equipment, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as non-credible water pollution data; when the credibility evaluation coefficient of the pollution detection equipment is smaller than or equal to the credibility evaluation threshold, generating a credibility signal of the pollution detection equipment, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as credible water pollution data.
In a preferred embodiment, in step S4, a plurality of water pollution detection devices are set in the artificial waterway uniformly, and each water pollution detection device corresponds to one water pollution data;
in the same credibility monitoring interval, acquiring the marked condition of the water pollution data corresponding to each water pollution detection device; calculating the ratio of the number of the water pollution data marked as unreliable to the total number of the water pollution data, and marking the ratio of the number of the water pollution data marked as unreliable to the total number of the water pollution data as a comprehensive trust ratio;
setting a comprehensive trust ratio threshold; when the comprehensive trust ratio is greater than the comprehensive trust ratio threshold, generating a comprehensive untrusted signal; and when the comprehensive trust ratio is smaller than or equal to the comprehensive trust ratio threshold, generating a comprehensive trust signal.
In a preferred embodiment, the water pollution degree detection system suitable for the park city comprises a data processing module, an information acquisition module, a credible judgment module, a data marking module and a comprehensive judgment module, wherein the information acquisition module, the credible judgment module, the data marking module and the comprehensive judgment module are in communication connection with the data processing module;
the information acquisition module acquires the water flow velocity change information, sends the water flow velocity change information to the data processing module, and calculates to obtain a flow velocity abnormal excitation ratio and a flow velocity time offset exceeding index;
the information acquisition module acquires the complete information of the water quality monitoring data, sends the complete information of the water quality monitoring data to the data processing module, and calculates to obtain a data comprehensive transmission jolt credibility assessment index;
the data processing module calculates a reliable evaluation coefficient of the pollution detection equipment through normalization processing on the abnormal flow rate aggressive ratio, the flow rate time offset exceeding index and the data comprehensive transmission bumping reliable evaluation index;
the credibility judgment module generates a non-credibility signal of the pollution detection device or a credibility signal of the pollution detection device through comparing the credibility evaluation coefficient of the pollution detection device with a credibility evaluation threshold value,
the data marking module marks the water pollution data as unreliable water pollution data or reliable water pollution data through the comparison of the reliable evaluation coefficient of the pollution detection device and the reliable evaluation threshold;
the comprehensive judgment module calculates the comprehensive trust ratio through the data processing module according to the marked condition of the acquired water pollution data; the comprehensive judgment module generates a comprehensive untrustworthy signal or a comprehensive trusted signal through comparison of the comprehensive trusted ratio and a comprehensive trusted ratio threshold.
The invention relates to a water pollution degree detection method and a water pollution degree detection system suitable for park cities, which have the technical effects and advantages that:
1. the credibility and accuracy of the water pollution data detected by the water pollution detection equipment can be more comprehensively and quantitatively estimated by calculating the credibility evaluation coefficient of the pollution detection equipment through normalization processing through the flow speed abnormal aggressive ratio, the flow speed time offset exceeding index and the data comprehensive transmission bumping credibility evaluation index; setting the confidence assessment threshold helps to separate the water pollution data into two levels of confidence and non-confidence, helping to better understand the confidence and accuracy of the water pollution data.
2. By considering the data of a plurality of water pollution detection devices, the water quality condition of the artificial water channel can be more comprehensively estimated, errors possibly existing only depending on a single device are avoided, and the data credibility and accuracy of the water pollution detection devices are comprehensively considered by calculating the comprehensive trust ratio, so that the estimation is more comprehensive and accurate; by setting the comprehensive trust ratio threshold, the data of the water pollution detection equipment can be divided into trusted and untrusted, so that measures can be taken in time to solve the water quality problem possibly existing, water resources and environment are better protected, and the efficiency and effect of water quality monitoring are improved.
Drawings
FIG. 1 is a schematic diagram of a method for detecting water pollution level applicable to a park city;
fig. 2 is a schematic structural diagram of a water pollution level detection system suitable for use in a park city according to 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.
Example 1
Fig. 1 shows a method for detecting water pollution level suitable for a park city, which comprises the following steps:
step S1: and acquiring water flow velocity change information corresponding to the water pollution detection equipment, and calculating a flow velocity abnormal excitation ratio and a flow velocity time offset exceeding index according to the water flow velocity change information.
Step S2: and acquiring complete information of water quality monitoring data corresponding to the water pollution detection equipment, calculating a water pollution data fault ratio and a fault close relation ratio, weighting the water pollution data fault ratio and the fault close relation ratio, and calculating a data comprehensive transmission jolt credibility assessment index.
Step S3: calculating a reliable evaluation coefficient of the pollution detection equipment through normalization processing on the flow speed abnormal aggressive ratio, the flow speed time offset exceeding index and the data comprehensive transmission bumping reliable evaluation index; and generating a non-trusted signal of the pollution detection equipment or a trusted signal of the pollution detection equipment by comparing the trusted evaluation coefficient of the pollution detection equipment with a trusted evaluation threshold, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as non-trusted water pollution data or trusted water pollution data.
Step S4: acquiring marked conditions of water pollution data, and calculating a comprehensive trust ratio according to the marked conditions of the water pollution data; and generating a comprehensive untrustworthy signal or a comprehensive trust signal through comparison of the comprehensive trust ratio and the comprehensive trust ratio threshold value.
In step S1, a reliability monitoring section is set for determining the reliability and accuracy of the water pollution data detected by the water pollution detection device in the reliability monitoring section by analyzing the information in the reliability monitoring section.
The time length corresponding to the reliability monitoring interval is set by a person skilled in the art according to actual conditions, and the time length corresponding to the frequency monitoring interval is unchanged.
The water pollution data refer to data for detecting the water quality of the artificial water channel.
The water flow velocity change information corresponding to the water pollution detection equipment is collected, and reflects the influence of the water flow velocity change of the artificial water channel on the credibility and accuracy of water pollution data detected by the water pollution detection equipment.
Reasons for the excessive rate of flow in artificial waterways include, but are not limited to, heavy rainfall causing significant amounts of rain to run into the waterway, thereby rapidly increasing the flow rate, and abrupt changes in flow rate may be caused by artificial operations such as opening a sluice gate, directing the flow of water, etc.
Because the frequency of the water pollution detection equipment for monitoring the water quality of the artificial water channel is usually fixed, when the flow speed of the water flow of the water channel is too fast, the sampling of the water quality parameters is disturbed, so that the monitoring data is distorted or inaccurate, and especially under the condition of the fixed frequency sampling of the sensor, the instantaneous change of the water quality can not be captured; fast flowing water may dilute the contaminants in the water to a reduced concentration, thereby affecting accurate monitoring of the water quality, which may result in underestimation of low concentrations of contaminants.
In the credibility monitoring interval, analyzing the flow rate of the monitored area of the artificial water channel corresponding to the single water pollution detection equipment:
the flow rate of the area of the artificial waterway within the confidence monitoring interval is obtained.
The flow rate threshold is set by a person skilled in the art according to the frequency of monitoring the water quality of the artificial water channel by the water pollution detection device and other practical conditions such as the requirement standard for water quality monitoring, and will not be described here.
When the actual flow rate is greater than the flow rate threshold, the reliability and accuracy of the water pollution data detected by the water pollution detection device may be lowered.
Calculating the time length of the actual flow rate in the credibility monitoring interval being greater than the flow rate threshold value, and marking the time length of the actual flow rate in the credibility monitoring interval being greater than the flow rate threshold value and the time length corresponding to the credibility monitoring interval as the abnormal flow rate excitation ratio; marking abnormal shock ratio of flow velocity as。
The greater the abnormal shock ratio of the flow rate, the worse the reliability and accuracy of the water pollution data detected by the water pollution detection device in the reliability monitoring section.
There may be multiple time intervals within the confidence monitoring interval when the actual flow rate is greater than the flow rate threshold.
Setting a time interval exceeding a threshold value; the time interval exceeding the threshold is set by a person skilled in the art according to the size of the time interval when the actual flow rate is greater than the flow rate threshold and other practical situations such as a requirement standard for the time length corresponding to the time interval when the actual flow rate is greater than the flow rate threshold, and will not be repeated here.
When the time length corresponding to the time interval when the actual flow rate is greater than the flow rate threshold value is greater than the time interval when the actual flow rate exceeds the flow rate threshold value, the more serious the continuous condition that the actual flow rate is greater than the flow rate threshold value, the worse the credibility and the accuracy of water pollution data detected by the water pollution detection equipment are caused.
Acquiring the number of time intervals, in which the actual flow rate exceeds the flow rate threshold, of the actual flow rate which exceeds the flow rate threshold and the actual flow rate which exceeds the flow rate threshold, corresponding to the time intervals, in which the actual flow rate exceeds the flow rate threshold, of the actual flow rate which exceeds the flow rate threshold, and the specific time of the time interval, in which the actual flow rate which exceeds the flow rate threshold, corresponding to the time interval, in which the actual flow rate exceeds the flow rate threshold, in the credibility monitoring intervalThe degree is analyzed, and the flow velocity time offset exceeding index is calculated, wherein the expression is as follows:wherein->The number of time intervals of which the actual flow rate is greater than the flow rate threshold value and the time intervals of which the actual flow rate is greater than the flow rate threshold value are respectively the number of the time intervals of which the actual flow rate is greater than the flow rate threshold value and the time intervals of which the actual flow rate is greater than the flow rate threshold value, and the time intervals of which the actual flow rate is greater than the flow rate threshold value are respectively the number of the time intervals of which the actual flow rate is greater than the flow rate threshold value>，/>Are positive integers greater than 1; />Respectively the flow velocity time offset exceeds the index, the +.>The time interval corresponding to the time interval when the actual flow velocity is larger than the flow velocity threshold value is longer than the time interval when the actual flow velocity exceeding the flow velocity threshold value is larger than the flow velocity threshold value; />The constant term is a fixed value, and the situation that the number of time intervals, of which the time length is larger than the time interval exceeding the threshold value and the actual flow rate is larger than the flow rate threshold value, corresponding to the time interval of which the actual flow rate is larger than the flow rate threshold value is 0 is prevented.
The greater the flow velocity time offset exceeding index, the more serious the time length corresponding to the time interval of which the actual flow velocity is greater than the flow velocity threshold value is greater than the degree of exceeding the threshold value in the credibility monitoring interval, which means that the actual flow velocity exceeds a certain flow velocity threshold value in the credibility monitoring interval, and the longer the duration of the condition is, the more serious the condition of abnormal flow velocity is indicated; the worse the reliability and accuracy of the water pollution data detected by the water pollution detection device in the reliability monitoring section.
In step S2, the integrity information of the water quality monitoring data corresponding to the water pollution detection device is collected, and the integrity information of the water pollution data corresponding to the water pollution detection device reflects the integrity of the water pollution data when the water pollution detection device detects the water pollution data.
The integrity of water pollution data can be affected by the following factors:
the quality of the communication channel of the data transmission is one of the key factors, and unstable network connection, signal interference or communication interruption can cause interruption or loss of the water-contaminated data transmission. Sensor reliability: the reliability and stability of the sensors of the water pollution detection device used directly affect the integrity of the water pollution data, and faulty or inaccurate calibration sensors may produce erroneous water pollution data. Environmental conditions: environmental conditions during data transmission may also affect data integrity, for example, transmission lines of water pollution detection devices may be damaged under severe weather conditions, resulting in data loss.
The method comprises the steps of obtaining the times of occurrence of water pollution data transmission faults in a credibility monitoring interval, and obtaining each time point corresponding to the occurrence of the water pollution data transmission faults in the credibility monitoring interval.
And calculating the water pollution data fault ratio, wherein the water pollution data fault ratio is the ratio of the number of times of water pollution data transmission faults in the credibility monitoring interval to the time length corresponding to the credibility monitoring interval.
The larger the water pollution data fault ratio is, the higher the unreliability of the water pollution data transmission in the credibility monitoring interval is, and the problem that the water pollution data is lost or the transmission is interrupted possibly exists, namely the lower the credibility and the accuracy of the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval are.
The more the distance between the time points corresponding to the water pollution data transmission faults is short in the credibility monitoring interval, the more serious the situation that the water pollution data transmission channel is unstable is indicated by the short distance between the time points of the short faults, and the more adverse effects on the accuracy and credibility of the water pollution data are caused.
The time intervals of adjacent time points, such as n time points, of water pollution data transmission faults in the reliability monitoring interval are acquired, and the number of the time intervals is n-1.
And marking the time interval of adjacent time points in which the water pollution data transmission faults occur in the reliability monitoring interval as the fault interval.
The fault interval threshold is set by a person skilled in the art according to the fault interval and other practical situations such as the requirement standard of the time interval in the water pollution data transmission fault, and will not be repeated here.
The method comprises the steps of obtaining the number of fault intervals in a reliability monitoring interval, and marking the ratio of the number of the fault intervals, in which the fault intervals are larger than a fault interval threshold, to the number of the fault intervals in the reliability monitoring interval as a fault close relation ratio.
The larger the fault close relation ratio is, the smaller the time interval between the time points of the water pollution data transmission faults is, namely the water pollution data transmission faults are denser, and the accuracy and the credibility of the water pollution data of the water pollution detection equipment can be adversely affected.
The water pollution data fault ratio and the fault close relation ratio are weighted, and the data comprehensive transmission jolt credibility assessment index is calculated, wherein the expression is as follows:wherein->Respectively transmitting jolt credible evaluation indexes, water pollution data fault ratios and fault close relation ratios for the data; />Weights of water pollution data fault ratio and fault close relation ratio respectively>Are all greater than 0, and->The size of (2) is set by a person skilled in the art according to the actual situation, and will not be described here.
The larger the data comprehensive transmission jolt reliability evaluation index is, the lower the stability and the reliability of the water pollution data transmission are, and the accuracy and the reliability of the water pollution data detection by the water pollution detection equipment are adversely affected. Unreliable water pollution data is detrimental to the accuracy and reliability of water pollution monitoring.
In step S3, calculating a reliable evaluation coefficient of the pollution detection equipment by normalizing the abnormal flow rate excitation ratio, the flow rate time offset exceeding index and the data comprehensive transmission jolt reliable evaluation index.
Judging the credibility and accuracy of water pollution data detected by the water pollution detection equipment in a credibility monitoring interval through a credibility evaluation coefficient of the pollution detection equipment; the expression of the credibility evaluation coefficient of the pollution detection device is as follows:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>The method comprises the steps of (1) credible evaluation coefficients for pollution detection equipment; />Preset proportionality coefficients of flow speed abnormal aggressive ratio, flow speed time offset exceeding index and data comprehensive transmission jolt credibility assessment index respectively>Are all greater than 0.
The greater the credibility evaluation coefficient of the pollution detection device is, the worse the credibility and accuracy of the water pollution data detected by the water pollution detection device in the credibility monitoring interval are, the greater the credibility evaluation coefficient of the pollution detection device is, the lower the credibility and accuracy of the water pollution data are, the inaccurate detection result is caused, the inaccurate water pollution data can lead to misleading results, if the water pollution data of the water pollution detection device are not credible, a misleading decision maker can take inappropriate actions, the pollution degree of the water body of the artificial water channel cannot be truly reflected, and the real water pollution problem cannot be timely dealt with.
And setting a credibility evaluation threshold, and judging the credibility and accuracy of the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval through the comparison of the credibility evaluation coefficient of the pollution detection equipment and the credibility evaluation threshold.
When the credibility evaluation coefficient of the pollution detection equipment is larger than the credibility evaluation threshold, generating a non-credibility signal of the pollution detection equipment, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as non-credible water pollution data.
When the credibility evaluation coefficient of the pollution detection equipment is smaller than or equal to the credibility evaluation threshold, generating a credibility signal of the pollution detection equipment, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as credible water pollution data.
The setting of the credibility evaluation threshold is performed by a person skilled in the art according to the credibility evaluation coefficient of the pollution detection device and other practical situations such as the requirement standard for the detection of the water pollution detection device, and will not be repeated here.
The credibility and accuracy of the water pollution data detected by the water pollution detection equipment can be more comprehensively and quantitatively estimated by calculating the credibility evaluation coefficient of the pollution detection equipment through normalization processing through the flow speed abnormal aggressive ratio, the flow speed time offset exceeding index and the data comprehensive transmission bumping credibility evaluation index; setting the confidence assessment threshold helps to separate the water pollution data into two levels of confidence and non-confidence, helping to better understand the confidence and accuracy of the water pollution data. And the water quality monitoring and pollution handling are better managed.
In step S4, a plurality of water pollution detection devices are set in the artificial waterway uniformly, and each water pollution detection device corresponds to one water pollution data. The water pollution detection equipment is uniformly distributed along the artificial water channel.
And acquiring the marked condition of the water pollution data corresponding to each water pollution detection device in the same credibility monitoring interval.
Calculating the ratio of the number of the water pollution data marked as the unreliable water to the total number of the water pollution data, and marking the ratio of the number of the water pollution data marked as the unreliable water to the total number of the water pollution data as the comprehensive trust ratio.
The larger the comprehensive trust ratio is, the poorer the credibility and the accuracy of water pollution data corresponding to the water pollution detection equipment in the artificial water channel are.
Setting a comprehensive trust ratio threshold; and comparing the comprehensive trust ratio with a comprehensive trust ratio threshold value to judge the reliability and accuracy of water pollution data of the overall water pollution detection equipment in the artificial water channel, and generating a comprehensive untrusted signal or a comprehensive trusted signal.
When the comprehensive trust ratio is larger than the comprehensive trust ratio threshold value, a comprehensive untrusted signal is generated, and the reliability and the accuracy of water pollution data corresponding to the water pollution detection equipment in the artificial water channel are relatively poor at the moment.
When the comprehensive trust ratio is smaller than or equal to the comprehensive trust ratio threshold value, a comprehensive trust signal is generated, and the existing conditions of poor reliability and accuracy of the water pollution data of the water pollution detection equipment in the artificial water channel are in an acceptable range, and the conditions of poor reliability and accuracy of the water pollution data corresponding to the water pollution detection equipment in the artificial water channel are normal, and the reliability and accuracy of the water pollution data of the overall water pollution detection equipment in the artificial water channel are normal.
The comprehensive trust ratio threshold is set by a person skilled in the art according to the magnitude of the comprehensive trust ratio and other practical situations such as a requirement standard for water quality detection in an artificial water channel in practice, and is not described herein.
By considering the data of a plurality of water pollution detection devices, the water quality condition of the artificial water channel can be more comprehensively evaluated, and errors which can exist only depending on a single device are avoided. The data credibility and accuracy of the water pollution detection equipment are comprehensively considered by calculating the comprehensive trust ratio, so that the evaluation is more comprehensive and accurate; by setting the comprehensive trust ratio threshold, the data of the water pollution detection equipment can be divided into trusted and untrusted, which is helpful to take measures in time to solve the water quality problem possibly existing. Is beneficial to better protecting water resources and environment and improving the efficiency and effect of water quality monitoring.
It is noted that the water pollution detection device of the present invention may be, for example, an on-line water quality detector; an on-line water quality detector is an instrument and equipment capable of monitoring water quality indexes in real time. The working principle of the online water quality detector is that various indexes in a water sample are converted into electric signals by utilizing an advanced sensor technology, and accurate and reliable water quality monitoring results are provided through data processing and analysis. The specific working principle steps comprise the following aspects:
the on-line water quality detector is internally provided with a sensor, and can collect various parameters in the water sample, namely water pollution data. Water pollution data includes, but is not limited to, dissolved oxygen, pH, turbidity, conductivity, temperature, and the like.
The sensor converts the acquired parameter information into an electrical signal, typically represented using an analog signal or a digital signal. The analog signal conversion is to convert the sensor signal into voltage or current through resistor, capacitor and other elements. Digital signal conversion is the conversion of an analog signal into digital form using an analog-to-digital converter (ADC).
Example 2
The difference between the embodiment 2 and the embodiment 1 of the present invention is that the present embodiment describes a water pollution level detection system suitable for use in a park city.
Fig. 2 shows a schematic structural diagram of a water pollution level detection system suitable for a park city according to the present invention, and the water pollution level detection system suitable for a park city includes a data processing module, and an information acquisition module, a trusted judgment module, a data marking module and a comprehensive judgment module which are communicatively connected with the data processing module.
The information acquisition module acquires the water flow velocity change information, sends the water flow velocity change information to the data processing module, and calculates to obtain the abnormal flow velocity excitation ratio and the flow velocity time offset exceeding index.
The information acquisition module acquires the complete information of the water quality monitoring data, sends the complete information of the water quality monitoring data to the data processing module, and calculates to obtain the data comprehensive transmission jolt credibility assessment index.
And the data processing module calculates the credible evaluation coefficient of the pollution detection equipment through normalization processing according to the abnormal flow rate aggressive ratio, the flow rate time offset exceeding index and the data comprehensive transmission bumping credible evaluation index.
The credibility judgment module generates a non-credibility signal of the pollution detection device or a credibility signal of the pollution detection device through comparing the credibility evaluation coefficient of the pollution detection device with a credibility evaluation threshold value,
the data marking module marks the water pollution data as unreliable water pollution data or reliable water pollution data through the comparison of the credibility evaluation coefficient of the pollution detection device and the credibility evaluation threshold value.
The comprehensive judgment module calculates the comprehensive trust ratio through the data processing module according to the marked condition of the acquired water pollution data; the comprehensive judgment module generates a comprehensive untrustworthy signal or a comprehensive trusted signal through comparison of the comprehensive trusted ratio and a comprehensive trusted ratio threshold.
The above formulas are all formulas with dimensionality removed and numerical calculation, the formulas are formulas with the latest real situation obtained by software simulation through collecting a large amount of data, and preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system, apparatus and module may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (5)
1. The water pollution degree detection method suitable for the park city is characterized by comprising the following steps of:
step S1: collecting water flow velocity change information corresponding to the water pollution detection equipment, and calculating a flow velocity abnormal excitation ratio and a flow velocity time offset exceeding index according to the water flow velocity change information;
step S2: the method comprises the steps of collecting complete information of water quality monitoring data corresponding to water pollution detection equipment, calculating a water pollution data fault ratio and a fault close relation ratio, weighting the water pollution data fault ratio and the fault close relation ratio, and calculating a data comprehensive transmission jolt credibility assessment index;
step S3: calculating a reliable evaluation coefficient of the pollution detection equipment through normalization processing on the flow speed abnormal aggressive ratio, the flow speed time offset exceeding index and the data comprehensive transmission bumping reliable evaluation index; generating a non-trusted signal of the pollution detection equipment or a trusted signal of the pollution detection equipment by comparing the trusted evaluation coefficient of the pollution detection equipment with a trusted evaluation threshold, and marking water pollution data detected by the water pollution detection equipment in a credibility monitoring interval as non-trusted water pollution data or trusted water pollution data;
step S4: acquiring marked conditions of water pollution data, and calculating a comprehensive trust ratio according to the marked conditions of the water pollution data; generating a comprehensive untrustworthy signal or a comprehensive trust signal through comparison of the comprehensive trust ratio and a comprehensive trust ratio threshold;
in step S1, a reliability monitoring section is set;
acquiring the flow rate of the area of the artificial waterway in the credibility monitoring interval; setting a flow rate threshold;
calculating the length of time that the actual flow velocity is greater than the flow velocity threshold value in the credibility monitoring interval, wherein the actual flow velocity is greater in the credibility monitoring intervalMarking the time length corresponding to the time length of the flow speed threshold value and the credibility monitoring interval as a flow speed abnormal excitation ratio; marking abnormal shock ratio of flow velocity as；
In step S2, the number of times of occurrence of the water pollution data transmission failure in the reliability monitoring interval is obtained, and each time point corresponding to the occurrence of the water pollution data transmission failure in the reliability monitoring interval is obtained;
calculating a water pollution data fault ratio, wherein the water pollution data fault ratio is the ratio of the number of times of water pollution data transmission faults in a credibility monitoring interval to the time length corresponding to the credibility monitoring interval;
acquiring a time interval of adjacent time points of water pollution data transmission faults in a credibility monitoring interval; marking the time interval of adjacent time points, in which water pollution data transmission faults occur, in the reliability monitoring interval as a fault interval;
setting a fault interval threshold value; the method comprises the steps of obtaining the number of fault intervals in a reliability monitoring interval, and marking the ratio of the number of the fault intervals, in which the fault intervals are larger than a fault interval threshold, to the number of the fault intervals in the reliability monitoring interval as a fault close relation ratio;
the water pollution data fault ratio and the fault close relation ratio are weighted, and the data comprehensive transmission jolt credibility assessment index is calculated, wherein the expression is as follows:wherein->Respectively transmitting jolt credible evaluation indexes, water pollution data fault ratios and fault close relation ratios for the data; />Weights of water pollution data fault ratio and fault close relation ratio respectively>Are all greater than 0.
2. The method for detecting the water pollution level applicable to the city of the park according to claim 1, wherein the method comprises the following steps: acquiring a time interval in which the actual flow velocity in the credibility monitoring interval is larger than a flow velocity threshold value; setting a time interval exceeding a threshold value; acquiring the number of time intervals, in which the actual flow rate exceeds the flow rate threshold, of which the time length is greater than the time interval exceeding the threshold and the actual flow rate is greater than the flow rate threshold, corresponding to the time intervals, in which the actual flow rate is greater than the flow rate threshold, in the credibility monitoring interval, and calculating a flow rate time offset exceeding index, wherein the expression is as follows:wherein->The number of time intervals of which the actual flow rate is greater than the flow rate threshold value and the time intervals of which the actual flow rate is greater than the flow rate threshold value are respectively the number of the time intervals of which the actual flow rate is greater than the flow rate threshold value and the time intervals of which the actual flow rate is greater than the flow rate threshold value, and the time intervals of which the actual flow rate is greater than the flow rate threshold value are respectively the number of the time intervals of which the actual flow rate is greater than the flow rate threshold value>，/>Are positive integers greater than 1; />Respectively the flow velocity time offset exceeds the index, the +.>The time interval corresponding to the time interval when the actual flow velocity is larger than the flow velocity threshold value is longer than the time interval when the actual flow velocity exceeding the flow velocity threshold value is larger than the flow velocity threshold valueThe interval exceeds a threshold; />Is a constant term.
3. The method for detecting the water pollution level applicable to the city of the park according to claim 1, wherein the method comprises the following steps: the expression of the credibility evaluation coefficient of the pollution detection device is as follows:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>The method comprises the steps of (1) credible evaluation coefficients for pollution detection equipment; />Preset proportionality coefficients of flow speed abnormal aggressive ratio, flow speed time offset exceeding index and data comprehensive transmission jolt credibility assessment index respectively>Are all greater than 0;
setting a credibility evaluation threshold; when the credibility evaluation coefficient of the pollution detection equipment is larger than the credibility evaluation threshold, generating a non-credibility signal of the pollution detection equipment, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as non-credible water pollution data; when the credibility evaluation coefficient of the pollution detection equipment is smaller than or equal to the credibility evaluation threshold, generating a credibility signal of the pollution detection equipment, and marking the water pollution data detected by the water pollution detection equipment in the credibility monitoring interval as credible water pollution data.
4. The method for detecting the water pollution level applicable to the city of the park according to claim 1, wherein the method comprises the following steps: in step S4, setting a plurality of water pollution detection devices uniformly arranged in the artificial water channel, wherein each water pollution detection device corresponds to one water pollution data;
in the same credibility monitoring interval, acquiring the marked condition of the water pollution data corresponding to each water pollution detection device; calculating the ratio of the number of the water pollution data marked as unreliable to the total number of the water pollution data, and marking the ratio of the number of the water pollution data marked as unreliable to the total number of the water pollution data as a comprehensive trust ratio;
setting a comprehensive trust ratio threshold; when the comprehensive trust ratio is greater than the comprehensive trust ratio threshold, generating a comprehensive untrusted signal; and when the comprehensive trust ratio is smaller than or equal to the comprehensive trust ratio threshold, generating a comprehensive trust signal.
5. A water pollution level detection system suitable for use in a park city for implementing a water pollution level detection method suitable for use in a park city as claimed in any one of claims 1 to 4, characterized in that: the system comprises a data processing module, an information acquisition module, a trusted judgment module, a data marking module and a comprehensive judgment module, wherein the information acquisition module, the trusted judgment module, the data marking module and the comprehensive judgment module are in communication connection with the data processing module;
the information acquisition module acquires the water flow velocity change information, sends the water flow velocity change information to the data processing module, and calculates to obtain a flow velocity abnormal excitation ratio and a flow velocity time offset exceeding index;
the information acquisition module acquires the complete information of the water quality monitoring data, sends the complete information of the water quality monitoring data to the data processing module, and calculates to obtain a data comprehensive transmission jolt credibility assessment index;
the data processing module calculates a reliable evaluation coefficient of the pollution detection equipment through normalization processing on the abnormal flow rate aggressive ratio, the flow rate time offset exceeding index and the data comprehensive transmission bumping reliable evaluation index;
the credibility judgment module generates a non-credibility signal of the pollution detection device or a credibility signal of the pollution detection device through comparison of the credibility evaluation coefficient of the pollution detection device and a credibility evaluation threshold;
the data marking module marks the water pollution data as unreliable water pollution data or reliable water pollution data through the comparison of the reliable evaluation coefficient of the pollution detection device and the reliable evaluation threshold;
the comprehensive judgment module calculates the comprehensive trust ratio through the data processing module according to the marked condition of the acquired water pollution data; the comprehensive judgment module generates a comprehensive untrustworthy signal or a comprehensive trusted signal through comparison of the comprehensive trusted ratio and a comprehensive trusted ratio threshold.
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