CN109813857B - Monitoring method based on Internet of things water quality monitoring system - Google Patents
Monitoring method based on Internet of things water quality monitoring system Download PDFInfo
- Publication number
- CN109813857B CN109813857B CN201910174660.4A CN201910174660A CN109813857B CN 109813857 B CN109813857 B CN 109813857B CN 201910174660 A CN201910174660 A CN 201910174660A CN 109813857 B CN109813857 B CN 109813857B
- Authority
- CN
- China
- Prior art keywords
- sensor
- module
- dissolved oxygen
- turbidity
- conductivity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Abstract
The invention discloses a monitoring method of a water quality monitoring system based on the Internet of things, which is used for solving the problems that water quality detection equipment ages along with the increase of the use time, the authenticity of detection data is influenced, and the reliability of the data is reduced; the system comprises a sample acquisition module, a sample detection module, an effective calculation module, an instrument acquisition module, an effective calculation module, a processor, a storage module, an early warning unit, a communication module, a server and a user side; the invention utilizes the formula
Obtaining an error proportionality coefficient WAi of the PH sensor; obtaining a true value HAi of the PH sensor by using a formula HAi ═ GAi (1+ WAi); therefore, the detection data is more real and reliable, and a formula is utilized
Obtaining a storage period Cai of the true value of the PH sensor; and deleting at regular time according to the storage time limit so as to ensure that the server stores effective water quality parameter data.
Description
Technical Field
The invention relates to the technical field of water quality monitoring, in particular to a water quality monitoring system based on the Internet of things.
Background
With the acceleration of the development of modern society, various pollution problems are continuously caused, and waste gas pollution, solid waste pollution and waste water pollution bring great influence to the life of people and reduce the life quality of people, so that people pay more and more attention to the environmental pollution problem.
In present water quality monitoring system, all adopt water quality testing equipment to carry out fixed point monitoring, though can realize the water quality monitoring to this place, water quality testing equipment increases along with the time of using, and some check out test set are ageing, influence the detection data authenticity, have reduced the reliability of its data.
Disclosure of Invention
The invention aims to provide a water quality monitoring system based on the Internet of things.
The technical problem to be solved by the invention is as follows:
(1) how to accurately calculate the true value of the water quality parameter and ensure the reliability of the data;
(2) how to judge according to the true value of the water quality parameter is convenient for alarming in time;
(3) how to delete the real value data of the water quality parameters regularly so as to store effective data.
The purpose of the invention can be realized by the following technical scheme: the water quality monitoring system based on the Internet of things comprises a sample acquisition module, a sample detection module, an effective calculation module, an instrument acquisition module, a processor, a storage module, an early warning module, a communication module, a server and a user side;
the sample acquisition module is used for acquiring a plurality of water samples of a water area of a monitoring point; the multiple water samples are formed by water samples at different positions and different depths of a water area of a monitoring point; the sample detection module is used for detecting the water quality parameters of a plurality of water samples collected by the sample collection module; the water quality parameters comprise PH value, temperature, dissolved oxygen, conductivity and turbidity; the sample detection module consists of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor; the PH sensor is used for detecting the PH value of the water sample; the temperature sensor is used for detecting the temperature of the water sample; the dissolved oxygen sensor is used for detecting the dissolved oxygen of the water sample; the conductivity sensor is used for detecting the conductivity of the water sample, and the turbidity sensor is used for detecting the turbidity of the water sample; the instrument acquisition module is used for counting the use times and the use time of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the instrument acquisition module comprises a time acquisition unit and a frequency counting unit; the time acquisition unit is used for counting the working start time and the working end time of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the frequency counting unit is used for counting the use frequency of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the specific statistical process of the instrument acquisition module is as follows:
a: setting the use times of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as Pa, Pb, Pc, Pd and Pe respectively; setting the use time Ta, Tb, Tc, Td and Te of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor; setting the pH value output by the pH sensor as GAi, wherein i is 1 … … n; setting the temperature value output by the temperature sensor as GBi, wherein i is 1 … … n; setting the dissolved oxygen value output by the dissolved oxygen sensor as GCi, wherein i is 1 … … n; setting the conductivity value output by the conductivity sensor as GDi, i is 1 … … n; setting the turbidity value output by the turbidity sensor to be GEi, wherein i is 1 … … n;
b: counting the use times of Pa, Pb, Pc, Pd and Pe; specifically, for the Pa value, when the PH sensor output GA1, Pa is 1; when the output value of the PH sensor is GA 8; then Pa is 8; similarly, counting the use times of Pb, Pc, Pd and Pe;
c: setting the operation start time of the PH sensor to be tAaiAnd the end time of the work is recorded as tAbi(ii) a Setting the start time of operation of the temperature sensor to tBaiThe end of work time is denoted tBbi(ii) a Setting the start time of the operation of the dissolved oxygen sensor as tCaiAnd the end time of the work is recorded as tCbi(ii) a Setting the start time of operation of the conductivity sensor to tDaiAnd the end time of the job is recorded as tDbi(ii) a The start time of operation of the turbidity sensor is set to be tEaiAnd the end time of the job is recorded as tEbi；
d: using formulas
Obtaining the use time Ta value of the PH sensor; in the same way, using the formula
And
obtaining Tb, Tc, Td and Te;
the sample detection module and the instrument acquisition module send the PH values, the temperature values, the dissolved oxygen values, the conductivity values and the turbidity values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor and the service time of corresponding service times to the effective calculation module; the effective calculation module receives and calculates the data of the PH values, temperature values, dissolved oxygen values, conductivity values and turbidity values of the PH sensors, the temperature sensors, the dissolved oxygen sensors, the conductivity sensors and the turbidity sensors and the use time data of corresponding use times, which are sent by the sample detection module and the instrument acquisition module; the effective calculation module comprises the following calculation steps:
the method comprises the following steps: setting preset coefficient values for Pa and Ta, Pb and Tb, Pc and Tc, Pd and Td, and Pe and Te;
step two: setting the preset coefficient of Pa as Ja1 and the preset coefficient of Ta as Ja 2; setting the preset coefficient of Pb as Jb1 and the preset coefficient of Tb as Jb 2; setting the preset coefficient of Pc as Jc1 and the preset coefficient of Tc as Jc 2; setting the preset coefficient of Pd as Jd1 and the preset coefficient of Td as Jd 2; setting the preset coefficient of Pe as Je1 and the preset coefficient of Te as Je 2;
step three: using formulas
Obtaining an error proportionality coefficient WAi of the PH sensor; wherein ua is interference factor, and formula is used in the same way
Obtaining WBi error proportion coefficient of temperature sensor;
obtaining an error proportion coefficient WCi of the dissolved oxygen sensor;
obtaining an error proportionality coefficient WDi of the conductivity sensor; wherein ub, uc and ud are interference factors;
obtaining an error proportion coefficient WEi of the turbidity sensor; wherein ue is an interference factor;
step four: obtaining a true value HAi of the PH sensor by using a formula HAi ═ GAi (1+ WAi); similarly, the true value HBi of the temperature sensor is obtained from HBi ═ GBi (1+ WBi); obtaining the true value HCi of the dissolved oxygen sensor by GCi (1+ WCi); acquiring an actual value HDi of the conductivity sensor by GDi (1+ WDi); obtaining an actual value HEi of the turbidity sensor by GEi (1+ WEi);
the effective calculation module sends the calculated actual values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the processor; the processor receives real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor which are sent by the effective calculation module and sends the data to the storage module for storage; the processor sends real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the server through the communication module; the server receives and stores real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, which are sent by the processor; and the user side is used for accessing real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor which are stored in the server.
Preferably, the early warning module is used for sending alarm instruction information to a manager terminal; the storage module further comprises a detection unit, the detection unit is used for detecting real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, and the specific detection process is as follows:
a: setting allowable values of a pH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as YA, YB, YC, YD and YE respectively;
b: the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor are compared with the allowable values; specifically, when HAi is greater than YA, the detection unit sends an alarm instruction '000' to the early warning module, and the early warning module sends the alarm instruction to the manager terminal; similarly, when the HBi is greater than the YB, the detection unit sends an alarm instruction '001' to the early warning module; when HCi is more than YC, the detection unit sends an alarm instruction '010' to the early warning module; when HDi is greater than YD, the detection unit sends an alarm instruction '100' to the early warning module; when HEi is YE, the detection unit sends an alarm instruction '101' to the early warning module.
Preferably, the server further comprises a statistical module, a pre-storage calculation module and a deletion module; the statistical module is used for counting the times of accessing the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor by a user side, and the pre-storage calculating module is used for calculating the storage period of the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the deleting module is used for deleting real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, and the deleting module specifically comprises the following processing steps:
s1: setting the times of the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor as Nai, Nbi, Nci, Ndi and Nei respectively; 1, 1 … … n;
s2: using formulas
Obtaining a storage period Cai of the true value of the PH sensor; in the same way, using the formula
Acquiring a storage period Cbi of the true value of the temperature sensor; the storage period Cci of the true value of the dissolved oxygen sensor; the storage life Cdi of the actual value of the conductivity sensor; storage life Cei for the turbidity sensor; wherein K is a preset basic storage period fixed value;
s3: setting storage dates of real values of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as LAi, LBi, LCi, LDi and LEi respectively; setting a server system date Mi; matching the storage period with the system date; specifically, when LAi + Cai ═ Mi; the actual value data HA1 of the PH sensor is deleted.
A monitoring method based on an Internet of things water quality monitoring system comprises the following steps:
s1: collecting a water sample through a sample collection module;
s2: the sample detection module is used for detecting the water quality parameters of the collected water sample to obtain an initial measurement value; specifically, the initial measurement value of the pH sensor is GAi;
s3: according to the using time and using times of the statistical sample detection module, using a formula
Calculating an error scaling factor WAi;
s4: calculating the value corresponding to the initial measurement value and the error proportion coefficient by using a formula HAi which is GAi (1+ WAi), so as to obtain the true value of the PH value in the water quality parameter;
s5: and the processor sends the calculated real value of the water quality parameter to a server for storage.
The invention has the beneficial effects that:
(1) the method comprises the steps of collecting a plurality of water samples of a water area of a monitoring point through a sample collecting module; then detecting a basic value of a water quality parameter through a sample detection module, and counting the use time and the use times of a sensor in the sample detection module through an instrument acquisition module; using formulas
Obtaining an error proportionality coefficient WAi of the PH sensor; obtaining a true value HAi of the PH sensor by using a formula HAi ═ GAi (1+ WAi); therefore, the detection data is more real and reliable;
(2) the invention sends the alarm instruction information to the manager terminal through the early warning module; the real value is compared with the allowable value, so that the alarm is judged, and managers can receive the water quality parameter information of the alarm in time so as to process in time;
(3) the invention stores the true values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor through the server, and then utilizes the formula
Obtaining a storage period Cai of the true value of the PH sensor; and deleting at regular time according to the storage time limit so as to ensure that the server stores effective water quality parameter data.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of a water quality monitoring system based on the internet of things.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to a water quality monitoring system based on the internet of things, which comprises a sample acquisition module, a sample detection module, an effective calculation module, an instrument acquisition module, a processor, a storage module, an early warning module, a communication module, a server and a user side;
the sample acquisition module is used for acquiring a plurality of water samples of a water area of a monitoring point; the multiple water samples are formed by water samples at different positions and different depths of a water area of a monitoring point; the sample detection module is used for detecting the water quality parameters of a plurality of water samples collected by the sample collection module; the water quality parameters comprise PH value, temperature, dissolved oxygen, conductivity and turbidity; the sample detection module consists of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor; the PH sensor is used for detecting the PH value of the water sample; the temperature sensor is used for detecting the temperature of the water sample; the dissolved oxygen sensor is used for detecting the dissolved oxygen of the water sample; the conductivity sensor is used for detecting the conductivity of the water sample, and the turbidity sensor is used for detecting the turbidity of the water sample; the instrument acquisition module is used for counting the use times and the use time of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the instrument acquisition module comprises a time acquisition unit and a frequency counting unit; the time acquisition unit is used for counting the working start time and the working end time of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the frequency counting unit is used for counting the use frequency of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the specific statistical process of the instrument acquisition module is as follows:
a: setting the use times of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as Pa, Pb, Pc, Pd and Pe respectively; setting the use time Ta, Tb, Tc, Td and Te of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor; setting the pH value output by the pH sensor as GAi, wherein i is 1 … … n; setting the temperature value output by the temperature sensor as GBi, wherein i is 1 … … n; setting the dissolved oxygen value output by the dissolved oxygen sensor as GCi, wherein i is 1 … … n; setting the conductivity value output by the conductivity sensor as GDi, i is 1 … … n; setting the turbidity value output by the turbidity sensor to be GEi, wherein i is 1 … … n;
b: counting the use times of Pa, Pb, Pc, Pd and Pe; specifically, for the Pa value, when the PH sensor output GA1, Pa is 1; when the output value of the PH sensor is GA 8; then Pa is 8; similarly, counting the use times of Pb, Pc, Pd and Pe;
c: setting the operation start time of the PH sensor to be tAaiAnd the end time of the work is recorded as tAbi(ii) a Setting the start time of operation of the temperature sensor to tBaiThe end of work time is denoted tBbi(ii) a Setting the start time of the operation of the dissolved oxygen sensor as tCaiAnd the end time of the work is recorded as tCbi(ii) a Setting the conductivity sensorThe work start time is recorded as tDaiAnd the end time of the job is recorded as tDbi(ii) a The start time of operation of the turbidity sensor is set to be tEaiAnd the end time of the job is recorded as tEbi；
d: using formulas
Obtaining the use time Ta value of the PH sensor; in the same way, using the formula
And
obtaining Tb, Tc, Td and Te;
the sample detection module and the instrument acquisition module send the pH value, the temperature value, the dissolved oxygen value, the conductivity value, the turbidity value and the service time of corresponding service times of the pH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the effective calculation module; the effective calculation module receives and calculates the data of the PH values, temperature values, dissolved oxygen values, conductivity values and turbidity values of the PH sensors, the temperature sensors, the dissolved oxygen sensors, the conductivity sensors and the turbidity sensors and the use time data of corresponding use times, which are sent by the sample detection module and the instrument acquisition module; the effective calculation module comprises the following calculation steps:
the method comprises the following steps: setting preset coefficient values for Pa and Ta, Pb and Tb, Pc and Tc, Pd and Td, and Pe and Te;
step two: setting the preset coefficient of Pa as Ja1 and the preset coefficient of Ta as Ja 2; setting the preset coefficient of Pb as Jb1 and the preset coefficient of Tb as Jb 2; setting the preset coefficient of Pc as Jc1 and the preset coefficient of Tc as Jc 2; setting the preset coefficient of Pd as Jd1 and the preset coefficient of Td as Jd 2; setting the preset coefficient of Pe as Je1 and the preset coefficient of Te as Je 2;
step three: using formulas
Is obtained to obtainError scaling factor for PH sensor WAi; wherein ua is interference factor, and formula is used in the same way
Obtaining WBi error proportion coefficient of temperature sensor;
obtaining an error proportion coefficient WCi of the dissolved oxygen sensor;
obtaining an error proportionality coefficient WDi of the conductivity sensor; wherein ub, uc and ud are interference factors;
obtaining an error proportion coefficient WEi of the turbidity sensor; wherein ue is an interference factor; the sample detection module is used for a long time, and the detection error of the sample detection module is larger along with the increase of the use times and the use time, so that the error proportion coefficient of the sensor in the sample acquisition module is calculated by the use times and the use time according to the relationship between the use times, the use time and the error, and the measured true value is more accurate by increasing the error value;
step four: obtaining a true value HAi of the PH sensor by using a formula HAi ═ GAi (1+ WAi); similarly, the true value HBi of the temperature sensor is obtained from HBi ═ GBi (1+ WBi); obtaining the true value HCi of the dissolved oxygen sensor by GCi (1+ WCi); acquiring an actual value HDi of the conductivity sensor by GDi (1+ WDi); obtaining an actual value HEi of the turbidity sensor by GEi (1+ WEi);
the effective calculation module sends the calculated actual values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the processor; the processor receives real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor which are sent by the effective calculation module and sends the data to the storage module for storage; the processor sends real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the server through the communication module; the server receives and stores real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, which are sent by the processor; and the user side is used for accessing real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor which are stored in the server.
The early warning module is used for sending the alarm instruction information to a manager terminal; the storage module further comprises a detection unit, the detection unit is used for detecting real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, and the specific detection process is as follows:
a: setting allowable values of a pH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as YA, YB, YC, YD and YE respectively;
b: the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor are compared with the allowable values; specifically, when HAi is greater than YA, the detection unit sends an alarm instruction '000' to the early warning module, and the early warning module sends the alarm instruction to the manager terminal; similarly, when the HBi is greater than the YB, the detection unit sends an alarm instruction '001' to the early warning module; when HCi is more than YC, the detection unit sends an alarm instruction '010' to the early warning module; when HDi is greater than YD, the detection unit sends an alarm instruction '100' to the early warning module; when HEi is YE, the detection unit sends an alarm instruction '101' to the early warning module.
The server also comprises a statistical module, a pre-storage calculation module and a deletion module; the statistical module is used for counting the times of accessing the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor by a user side, and the pre-storage calculating module is used for calculating the storage period of the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the deleting module is used for deleting real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, and the deleting module specifically comprises the following processing steps:
s1: setting the times of the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor as Nai, Nbi, Nci, Ndi and Nei respectively; 1, 1 … … n;
s2: using formulas
Obtaining a storage period Cai of the true value of the PH sensor; in the same way, using the formula
Acquiring a storage period Cbi of the true value of the temperature sensor; the storage period Cci of the true value of the dissolved oxygen sensor; the storage life Cdi of the actual value of the conductivity sensor; storage life Cei for the turbidity sensor; wherein K is a preset basic storage period fixed value;
s3: setting storage dates of real values of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as LAi, LBi, LCi, LDi and LEi respectively; setting a server system date Mi; matching the storage period with the system date; specifically, when LA1+ Ca1 is Mi; the actual value data HA1 of the PH sensor is deleted.
A monitoring method based on an Internet of things water quality monitoring system comprises the following steps:
s1: collecting a water sample through a sample collection module;
s2: the sample detection module is used for detecting the water quality parameters of the collected water sample to obtain an initial measurement value; specifically, the initial measurement value of the pH sensor is GAi;
s3: according to the using time and using times of the statistical sample detection module, using a formula
Calculating an error scaling factor WAi;
s4: calculating the value corresponding to the initial measurement value and the error proportion coefficient by using a formula HAi which is GAi (1+ WAi), so as to obtain the true value of the PH value in the water quality parameter;
s5: and the processor sends the calculated real value of the water quality parameter to a server for storage.
The working principle of the invention is as follows:
collecting a plurality of water samples of a water area of a monitoring point through a sample collecting module; then detecting a basic value of a water quality parameter through a sample detection module, and counting the use time and the use times of a sensor in the sample detection module through an instrument acquisition module; using formulas
Obtaining an error proportionality coefficient WAi of the PH sensor; obtaining a true value HAi of the PH sensor by using a formula HAi ═ GAi (1+ WAi); therefore, the detection data is more real and reliable; sending alarm instruction information to a manager terminal through an early warning module; the real value is compared with the allowable value, so that the alarm is judged, and managers can receive the water quality parameter information of the alarm in time so as to process in time; storing the actual values of the pH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor by the server, and then using the formula
Obtaining a storage period Cai of the true value of the PH sensor; and deleting at regular time according to the storage time limit so as to ensure that the server stores effective water quality parameter data.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. The water quality monitoring system based on the Internet of things is characterized by comprising a sample acquisition module, a sample detection module, an effective calculation module, an instrument acquisition module, a processor, a storage module, an early warning module, a communication module, a server and a user side;
the sample acquisition module is used for acquiring a plurality of water samples of a water area of a monitoring point; the multiple water samples are formed by water samples at different positions and different depths of a water area of a monitoring point; the sample detection module is used for detecting the water quality parameters of a plurality of water samples collected by the sample collection module; the water quality parameters comprise PH value, temperature, dissolved oxygen, conductivity and turbidity; the sample detection module consists of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor; the PH sensor is used for detecting the PH value of the water sample; the temperature sensor is used for detecting the temperature of the water sample; the dissolved oxygen sensor is used for detecting the dissolved oxygen of the water sample; the conductivity sensor is used for detecting the conductivity of the water sample, and the turbidity sensor is used for detecting the turbidity of the water sample; the instrument acquisition module is used for counting the use times and the use time of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the instrument acquisition module comprises a time acquisition unit and a frequency counting unit; the time acquisition unit is used for counting the working start time and the working end time of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the frequency counting unit is used for counting the use frequency of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the specific statistical process of the instrument acquisition module is as follows:
a: setting the use times of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as Pa, Pb, Pc, Pd and Pe respectively; setting the use time Ta, Tb, Tc, Td and Te of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor; setting the pH value output by the pH sensor as GAi, wherein i is 1 … … n; setting the temperature value output by the temperature sensor as GBi, wherein i is 1 … … n; setting the dissolved oxygen value output by the dissolved oxygen sensor as GCi, wherein i is 1 … … n; setting the conductivity value output by the conductivity sensor as GDi, i is 1 … … n; setting the turbidity value output by the turbidity sensor to be GEi, wherein i is 1 … … n;
b: counting the use times of Pa, Pb, Pc, Pd and Pe; specifically, for the Pa value, when the PH sensor output GA1, Pa is 1; when the output value of the PH sensor is GA 8; then Pa is 8; similarly, counting the use times of Pb, Pc, Pd and Pe;
c: setting the operation start time of the PH sensor to be tAaiAnd the end time of the work is recorded as tAbi(ii) a Setting the start time of operation of the temperature sensor to tBaiThe end of work time is denoted tBbi(ii) a Setting the start time of the operation of the dissolved oxygen sensor as tCaiAnd the end time of the work is recorded as tCbi(ii) a Setting the start time of operation of the conductivity sensor to tDaiAnd the end time of the job is recorded as tDbi(ii) a The start time of operation of the turbidity sensor is set to be tEaiAnd the end time of the job is recorded as tEbi；
d: using formulas
Obtaining the use time Ta value of the PH sensor; in the same way, using the formula
And
obtaining Tb, Tc, Td and Te;
the sample detection module and the instrument acquisition module send the PH values, the temperature values, the dissolved oxygen values, the conductivity values and the turbidity values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor and the service time of corresponding service times to the effective calculation module; the effective calculation module receives and calculates the data of the PH values, temperature values, dissolved oxygen values, conductivity values and turbidity values of the PH sensors, the temperature sensors, the dissolved oxygen sensors, the conductivity sensors and the turbidity sensors and the use time data of corresponding use times, which are sent by the sample detection module and the instrument acquisition module; the effective calculation module comprises the following calculation steps:
the method comprises the following steps: setting preset coefficient values for Pa and Ta, Pb and Tb, Pc and Tc, Pd and Td, and Pe and Te;
step two: setting the preset coefficient of Pa as Ja1 and the preset coefficient of Ta as Ja 2; setting the preset coefficient of Pb as Jb1 and the preset coefficient of Tb as Jb 2; setting the preset coefficient of Pc as Jc1 and the preset coefficient of Tc as Jc 2; setting the preset coefficient of Pd as Jd1 and the preset coefficient of Td as Jd 2; setting the preset coefficient of Pe as Je1 and the preset coefficient of Te as Je 2;
step three: using formulas
Obtaining an error proportionality coefficient WAi of the PH sensor; wherein ua is interference factor, and formula is used in the same way
Obtaining WBi error proportion coefficient of temperature sensor;
obtaining an error proportion coefficient WCi of the dissolved oxygen sensor;
obtaining an error proportionality coefficient WDi of the conductivity sensor; wherein ub, uc and ud are interference factors;
obtaining an error proportion coefficient WEi of the turbidity sensor; wherein ue is an interference factor;
step four: obtaining a true value HAi of the PH sensor by using a formula HAi ═ GAi (1+ WAi); similarly, the true value HBi of the temperature sensor is obtained from HBi ═ GBi (1+ WBi); obtaining the true value HCi of the dissolved oxygen sensor by GCi (1+ WCi); acquiring an actual value HDi of the conductivity sensor by GDi (1+ WDi); obtaining an actual value HEi of the turbidity sensor by GEi (1+ WEi);
the effective calculation module sends the calculated actual values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the processor; the processor receives real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor which are sent by the effective calculation module and sends the data to the storage module for storage; the processor sends real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor to the server through the communication module; the server receives and stores real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, which are sent by the processor; and the user side is used for accessing real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor which are stored in the server.
2. The water quality monitoring system based on the Internet of things of claim 1, wherein the early warning module is used for sending alarm instruction information to a manager terminal; the storage module further comprises a detection unit, the detection unit is used for detecting real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, and the specific detection process is as follows:
a: setting allowable values of a pH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as YA, YB, YC, YD and YE respectively;
b: the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor are compared with the allowable values; specifically, when HAi is greater than YA, the detection unit sends an alarm instruction '000' to the early warning module, and the early warning module sends the alarm instruction to the manager terminal; similarly, when the HBi is greater than the YB, the detection unit sends an alarm instruction '001' to the early warning module; when HCi is more than YC, the detection unit sends an alarm instruction '010' to the early warning module; when HDi is greater than YD, the detection unit sends an alarm instruction '100' to the early warning module; when HEi is YE, the detection unit sends an alarm instruction '101' to the early warning module.
3. The Internet of things-based water quality monitoring system according to claim 1, wherein the server further comprises a statistical module, a pre-storage calculation module and a deletion module; the statistical module is used for counting the times of accessing the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor by a user side, and the pre-storage calculating module is used for calculating the storage period of the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor; the deleting module is used for deleting real value data of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor, and the deleting module specifically comprises the following processing steps:
s1: setting the times of the real values of the PH sensor, the temperature sensor, the dissolved oxygen sensor, the conductivity sensor and the turbidity sensor as Nai, Nbi, Nci, Ndi and Nei respectively; 1, 1 … … n;
s2: using formulas
Obtaining a storage period Cai of the true value of the PH sensor; in the same way, using the formula
Acquiring a storage period Cbi of the true value of the temperature sensor; the storage period Cci of the true value of the dissolved oxygen sensor; the storage life Cdi of the actual value of the conductivity sensor; storage life Cei for the turbidity sensor; wherein K is a preset basic storage period fixed value;
s3: setting storage dates of real values of a PH sensor, a temperature sensor, a dissolved oxygen sensor, a conductivity sensor and a turbidity sensor as LAi, LBi, LCi, LDi and LEi respectively; setting a server system date Mi; matching the storage period with the system date; specifically, when LAi + Cai ═ Mi; the actual value data HA1 of the PH sensor is deleted.
4. A monitoring method based on an Internet of things water quality monitoring system is characterized by comprising the following steps:
s1: collecting a water sample through a sample collection module;
s2: the sample detection module is used for detecting the water quality parameters of the collected water sample to obtain an initial measurement value; specifically, the initial measurement value of the pH sensor is GAi;
s3: according to the using time and using times of the statistical sample detection module, using a formula
Calculating an error scaling factor WAi; the number of times of use of the PH sensor is recorded as Pa; ua is an interference factor; the preset coefficient of Pa is Ja1, and the preset coefficient of Ta is Ja 2; ta is the value of the use time of the PH sensor; wherein the operation start time of the PH sensor is set to be tAaiAnd the end time of the work is recorded as tAbi(ii) a Using formulas
Obtaining the use time Ta value of the PH sensor;
s4: calculating the value corresponding to the initial measurement value and the error proportion coefficient by using a formula HAi which is GAi (1+ WAi), so as to obtain the true value of the PH value in the water quality parameter;
s5: and the processor sends the calculated real value of the water quality parameter to a server for storage.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910174660.4A CN109813857B (en) | 2019-03-08 | 2019-03-08 | Monitoring method based on Internet of things water quality monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910174660.4A CN109813857B (en) | 2019-03-08 | 2019-03-08 | Monitoring method based on Internet of things water quality monitoring system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109813857A CN109813857A (en) | 2019-05-28 |
| CN109813857B true CN109813857B (en) | 2021-07-13 |
Family
ID=66608417
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910174660.4A Active CN109813857B (en) | 2019-03-08 | 2019-03-08 | Monitoring method based on Internet of things water quality monitoring system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109813857B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110987875B (en) * | 2019-12-24 | 2022-08-12 | 上海蓝长自动化科技有限公司 | Water turbidity detection method for spatial fusion based on support degree and confidence degree |
| CN112070393B (en) * | 2020-09-07 | 2021-06-01 | 宜昌湖蓝科技开发有限公司 | Wastewater quality detection system that industry and agriculture production discharged |
| CN112114109A (en) * | 2020-09-23 | 2020-12-22 | 安徽元通水处理设备有限公司 | Reverse osmosis water quality standard exceeding detection protection system |
| CN113450546A (en) * | 2021-06-30 | 2021-09-28 | 湖北大眼界企业管理有限公司 | Standardized service terminal for sewage discharge |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS61251769A (en) * | 1985-03-29 | 1986-11-08 | Chikiyuu Kagaku Kk | Continuous monitoring method for water quality using fish |
| CN103728891A (en) * | 2013-12-25 | 2014-04-16 | 力合科技（湖南）股份有限公司 | Method and device for controlling water quality on-line monitoring data |
| US8958917B2 (en) * | 1998-12-17 | 2015-02-17 | Hach Company | Method and system for remote monitoring of fluid quality and treatment |
| CN106290772A (en) * | 2016-10-10 | 2017-01-04 | 深圳万发创新进出口贸易有限公司 | A kind of sewage monitoring system |
| CN106530140A (en) * | 2016-12-12 | 2017-03-22 | 上海歆峥智能科技有限公司 | Online monitoring system of water quality |
| CN106918684A (en) * | 2017-02-17 | 2017-07-04 | 清华大学 | A kind of water quality pollution early warning method |
| CN108846423A (en) * | 2018-05-29 | 2018-11-20 | 中国农业大学 | Water quality prediction method and system |
| CN109212153A (en) * | 2018-10-16 | 2019-01-15 | 深圳美特优科技有限公司 | A kind of water quality monitoring system based on wireless sensor network |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10900921B2 (en) * | 2015-01-20 | 2021-01-26 | Masco Corporation | Multi-functional water quality sensor |
-
2019
- 2019-03-08 CN CN201910174660.4A patent/CN109813857B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS61251769A (en) * | 1985-03-29 | 1986-11-08 | Chikiyuu Kagaku Kk | Continuous monitoring method for water quality using fish |
| US8958917B2 (en) * | 1998-12-17 | 2015-02-17 | Hach Company | Method and system for remote monitoring of fluid quality and treatment |
| CN103728891A (en) * | 2013-12-25 | 2014-04-16 | 力合科技（湖南）股份有限公司 | Method and device for controlling water quality on-line monitoring data |
| CN106290772A (en) * | 2016-10-10 | 2017-01-04 | 深圳万发创新进出口贸易有限公司 | A kind of sewage monitoring system |
| CN106530140A (en) * | 2016-12-12 | 2017-03-22 | 上海歆峥智能科技有限公司 | Online monitoring system of water quality |
| CN106918684A (en) * | 2017-02-17 | 2017-07-04 | 清华大学 | A kind of water quality pollution early warning method |
| CN108846423A (en) * | 2018-05-29 | 2018-11-20 | 中国农业大学 | Water quality prediction method and system |
| CN109212153A (en) * | 2018-10-16 | 2019-01-15 | 深圳美特优科技有限公司 | A kind of water quality monitoring system based on wireless sensor network |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109813857A (en) | 2019-05-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109813857B (en) | Monitoring method based on Internet of things water quality monitoring system | |
| CN109668607B (en) | Method for monitoring tiny leakage of gas meter | |
| CN113783272A (en) | Safety control method based on super capacitor monitoring management system | |
| CA3043600A1 (en) | A system for remote groundwater monitoring | |
| CN108876175A (en) | A kind of npp safety shell slip calculates appraisal procedure and system | |
| CN111999318A (en) | Soil moisture content monitoring system and method based on cosmic ray neutrons | |
| CN109060888A (en) | A kind of sampling method and device | |
| CN115638718A (en) | Big data-based displacement detection device operation environment detection system | |
| CN105425004B (en) | Electric energy measuring equipment and its stealing event detecting method, device | |
| CN117664281B (en) | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of Things | |
| CN117503204B (en) | Ultrasonic AI digital diagnosis and treatment system | |
| CN212433949U (en) | Electric energy meter with working environment detection function | |
| CN116399402B (en) | Fault early warning system of wireless sensor for ecological environment monitoring | |
| CN112539810A (en) | Intelligent water meter operation error calibration method | |
| CN111695735A (en) | Railway bow net real-time early warning method, system and device based on flow calculation | |
| CN208140040U (en) | Laser avenges depth gauge and its measuring system | |
| CN110410057B (en) | Method and system for detecting polished rod suspension point dead point of pumping well | |
| CN208847636U (en) | A kind of steel tower reinforced concrete foundation reinforcement corrosion degree detection device | |
| CN213142201U (en) | Ballast tank corrosion monitoring system | |
| CN113333304B (en) | Environment-friendly coiled material detection, evaluation and sorting system based on Internet | |
| CN110244253B (en) | Provincial metering center standard quantity transmission online control method | |
| CN212747877U (en) | Digital bridge detection system | |
| CN112734211A (en) | Coal quality consistency evaluation method, device, equipment and readable storage medium | |
| CN104991222A (en) | Measurement automation terminal quality evaluation system | |
| CN218383263U (en) | Electric energy metering management terminal with state online monitoring function |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210630 Address after: 330000 3rd floor, Guiyuan Avenue, Nanchang Economic and Technological Development Zone, Nanchang City, Jiangxi Province Applicant after: Jiangxi Telecom Information Industry Co.,Ltd. Address before: 312513 Zhejiang province Shaoxing city Xinchang County South Township Shi Xi Village Applicant before: XINCHANG COUNTY YILIN ENVIRONMENTAL PROTECTION TECHNOLOGY Co.,Ltd. |
|
| TA01 | Transfer of patent application right |