Disclosure of Invention
The invention aims to: to the problem that prior art exists, provide a flow detection system with data analysis and internet data sharing function, solve current water supply and drainage flow detection more need manual operation, and the inconvenient problem of data storage.
The invention aims to be realized by the following technical scheme:
a flow detection system with data analysis and internet data sharing functions comprises:
the measuring host is used for sending measuring data to the mobile terminal or receiving an operating instruction of the mobile terminal through a short-distance wireless communication technology;
the cloud server is used for storing the measurement data uploaded by the mobile terminal;
and the mobile terminal is used for uploading the measured data to the cloud server, checking and downloading the data stored by the cloud server from the cloud server, analyzing the measured flow data and judging whether the current flow value is normal or not.
As a further technical scheme, the specific steps of analyzing the measured flow data and judging whether the current flow value is normal by the mobile terminal include:
(1) the mobile terminal acquires operation pipeline information;
(2) measurements on working linesThe host sends the current measured value u to the mobile terminal in real timeCurrent measured valueComparing the current measured value uCurrent measured valueAnd uRated valueObtaining a set of difference values, if the set of difference values are not larger than the corresponding threshold value TuRated valueIf so, the flow is normal; otherwise, the flow rate is abnormal.
As a further technical scheme, u isCurrent measured valueAs uHistorical valueStoring in a database, and determining the u of the measured operation pipeline in the databaseHistorical valueWhen the quantity of the measured operation pipeline reaches the set quantity, calculating the probability of occurrence of the abnormal flow of the measured operation pipeline through linear regression, drawing a trend curve, and predicting the possible abnormal flow.
As a further technical solution, a specific method for predicting a possible flow abnormality is as follows: when the trend line is suddenly changed, the phenomenon of abnormal flow of the measured drainage system is judged; when the trend line shows monotonous decrease, the phenomenon of abnormal flow of the measured drainage system is judged.
As a further technical solution, the trend line is obtained as follows:
putting the time and the flow value into a Cartesian coordinate system, wherein the flow value fluctuates along with the change of the time, and the linear relation is set as follows: (x) ax + b;
the error of each point can be expressed as: e ═ f (x)i)-yi)2;
The square of the total error is:
different a and b will make the value of tau different, and according to the multiple calculus, when:
then taking the minimum value;
solving the above equation system to obtain a, b, and obtaining the equation f (x) of the trend line.
As a further technical scheme, if the a or b quantity changes to be larger than a certain rated value, the pipeline flow is abnormal; if the absolute value of a is larger than a set rated value, the pipeline flow is abnormal.
As a further technical solution, the method for the mobile terminal to obtain the operation pipeline information includes:
if the operation pipeline information is recorded into the mobile terminal for the first time, the operation pipeline information is stored into a local database and is also stored into a cloud server for sharing after the operation pipeline information is recorded into the mobile terminal for the first time;
if not, the mobile terminal selects one of the following modes to obtain:
(1) the method comprises the steps of checking locally at a cloud server or a mobile terminal, manually screening out required pipeline information, downloading and then automatically inputting;
(2) the two-dimension code of the scanning measurement site is automatically screened out from a local database or a cloud server to download the pipeline information of the corresponding pipeline and then is automatically input, and the information contained in the two-dimension code comprises the same information as the input pipeline information.
As a further technical scheme, the flow data is stored to be shared by the cloud server.
As a further technical scheme, the information of the operation pipeline is manually input into the mobile terminal, other parameters of the pipeline are automatically input after one parameter of the pipeline is input, and the parameters of each pipeline accord with the national standard of the pipeline.
Compared with the prior art, the invention has the following advantages:
1. the flow data sharing of the detected pipeline is realized through the mobile terminal, the measurement host and the cloud server;
2. all the pipeline information is manually input once before the first measurement operation, and then the pipeline information is not required to be manually input again no matter the same mobile terminal is used for repeated measurement or different mobile terminals are used for measurement;
3. the data can be analyzed in real time, and whether the current flow is abnormal or not is judged;
4. and calculating the occurrence probability of the abnormal flow of the measured drainage system through linear regression, drawing a trend curve, and predicting the possible abnormal flow.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Example 1
As shown in fig. 1 to 6, the present embodiment provides a traffic detection system with data analysis and internet data sharing functions, which includes: the measuring host is used for sending measuring data to the mobile terminal or receiving an operating instruction of the mobile terminal through a short-distance wireless communication technology; the cloud server is used for storing the measurement data uploaded by the mobile terminal; and the mobile terminal is used for uploading the measured data to the cloud server, checking and downloading the data stored by the cloud server from the cloud server, analyzing the measured flow data and judging whether the current flow value is normal or not.
The specific steps of analyzing the measured flow data and judging whether the current flow value is normal by the mobile terminal include:
(1) the mobile terminal acquires the operation pipeline information.
The method for acquiring the operation pipeline information by the mobile terminal comprises the following steps:
if the operation pipeline information is recorded into the mobile terminal for the first time, the operation pipeline information is stored into a local database and is also stored into a cloud server for sharing after the operation pipeline information is recorded into the mobile terminal for the first time;
if not, the mobile terminal selects one of the following modes to obtain:
(11) the method comprises the steps of checking locally at a cloud server or a mobile terminal, manually screening out required pipeline information, downloading and then automatically inputting;
(12) the two-dimension code of the scanning measurement site is automatically screened out from a local database or a cloud server to download the pipeline information of the corresponding pipeline and then is automatically input, and the information contained in the two-dimension code comprises the same information as the input pipeline information.
(2) The measurement host arranged on the operation pipeline sends the current measurement value u to the mobile terminal in real timeCurrent measured valueComparing the current measured value uCurrent measured valueAnd uRated valueObtaining a set of difference values, if the set of difference values are not larger than the corresponding threshold value TuRated valueIf so, the flow is normal; otherwise, the flow rate is abnormal.
(3) Will uCurrent measured valueAs uHistorical valueStoring in a database, and determining the u of the measured operation pipeline in the databaseHistorical valueWhen the quantity of the measured operation pipeline reaches the set quantity, calculating the probability of occurrence of the abnormal flow of the measured operation pipeline through linear regression, drawing a trend curve, and predicting the possible abnormal flow.
The trend line is obtained as follows:
putting the time and the flow value into a Cartesian coordinate system, wherein the flow value fluctuates along with the change of the time, and the linear relation is set as follows: (x) ax + b;
the error of each point can be expressed as: e ═ f (x)i)-yi)2;
The square of the total error is:
different a and b will make the value of tau different, and according to the multiple calculus, when:
then taking the minimum value;
solving the above equation system to obtain a, b, and obtaining the equation f (x) of the trend line.
If the a or b quantity changes to be larger than a certain rated value, the pipeline flow is abnormal; if the absolute value of a is larger than a set rated value, the pipeline flow is abnormal.
And the traffic data is stored to the cloud server for sharing. The information of the operation pipeline is manually input into the mobile terminal, other parameters of the pipeline are automatically input after one parameter of the pipeline is input, and each pipeline parameter meets the national standard of the pipeline.
Example 2
The embodiment provides a portable drainage system flow detection system with data analysis and internet data sharing functions, and the system is composed of a portable measurement host, a cloud server, a mobile terminal and matched mobile terminal software. The measurement host sends measurement data to the mobile terminal or receives an operation instruction of the mobile terminal through a short-distance wireless communication technology (such as Bluetooth, WiFi and the like), the mobile terminal uploads the measurement data to the cloud server or checks and downloads data stored by the cloud server from the cloud server, and a system topological diagram is shown in fig. 1.
The functions which can be realized by the system comprise:
1. data analysis
The flow detection system analyzes the measured flow data and judges whether the current flow value is normal.
2. Data sharing
(1) Pipeline information sharing
The pipeline information is stored in the local database and also stored in the cloud server side for sharing after being recorded into the mobile terminal for the first time, and the control room host and all the mobile terminals can check and download the pipeline information and the pipeline flow data from the cloud server side. All the pipeline information is manually input once before the first measurement operation, and then the pipeline information is not required to be manually input again no matter the same mobile terminal is used for repeated measurement or different mobile terminals are used for measurement. When the information of the measuring operation pipeline is input (not for the first time), the mobile terminal can carry out the following two pipeline information acquisition modes through mobile terminal software:
the method comprises the steps of checking and manually screening required pipeline information at a cloud service end or a mobile terminal locally, and then automatically inputting the information.
Secondly, scanning and measuring a field two-dimensional code (the information contained in the two-dimensional code comprises information which is the same as the input pipeline information, such as routing inspection serial numbers, positions and the like), automatically screening the pipeline information of the corresponding pipeline from a local database or a cloud service terminal, downloading the pipeline information, and then automatically inputting the pipeline information.
(2) Pipeline flow data sharing
The flow data is stored in the cloud server for sharing, and a user can log in the cloud server through various terminals with browsers to check and download the flow data of each pipeline in real time through the browsers.
(3) When the pipeline parameters are input, other parameters of the pipeline are automatically input after one parameter of the pipeline is input (for example, after the drift diameter of the pipeline is input, the parameters of the outer diameter, the thickness and the like of the pipeline are automatically input), and each pipeline parameter accords with the national standard of the pipeline.
The system realizes the specific technical method that:
1. data analysis
The flow detection system displays flow data in real time in a form of a line graph, a flow regression line and a rated flow line are simultaneously displayed in a display interface and are distinguished according to different line types, current widths or colors, and a target line graph can be displayed or hidden by clicking a legend of each broken line in the line graph. The data analysis method is as follows:
the data transmitted to the mobile terminal is processed by means of mobile terminal software, and the mobile terminal software completes analysis on whether the current measured flow state is normal or not by using a statistical method. The method comprises the following concrete steps:
the method comprises the following steps: preset setpoint value uRated valueAnd its corresponding threshold value TuRated value;
Step two: comparing the current measured value uCurrent measured valueAnd uRated valueObtaining a group of difference values, and if the group of difference values are not larger than the corresponding threshold value, the flow is normal; otherwise, the flow rate is abnormal. Namely:
when uCurrent measured value-uRated value|≤TuRated valueWhen the flow is normal;
when uCurrent measured value-uRated value|>TuRated valueThe flow rate is abnormal.
Then u is putCurrent measured valueAs uHistory ofValue ofStoring in a database, u of the measured drainage systemHistorical valueWhen the number of the second step reaches the set number, entering a third step;
step three: and calculating the occurrence probability of the abnormal flow of the measured drainage system through linear regression, drawing a trend curve, and predicting the possible abnormal flow.
As shown in fig. 2, when the trend line is changed steeply, it is determined that the drainage system to be tested has an "abnormal flow rate" phenomenon;
as shown in fig. 3, when the trend line shows monotone decreasing, it is determined that the "abnormal flow" phenomenon occurs in the drainage system to be tested.
Wherein, the trend line obtaining process is as follows:
putting the time and the flow value into a Cartesian coordinate system (the time is the horizontal axis x, and the flow value is the vertical axis y), wherein the flow value fluctuates along with the change of the time and is similar to a certain linear relation, and the linear relation is set as follows:
f(x)=ax+b
the error of each point can be expressed as:
ε=(f(xi)-yi)2
the square of the total error is:
different a and b will cause the value of tau to be different, and according to the multiple calculus, when:
at this point the minimum value is taken.
For a and b, the above equation system is a linear equation system, and a and b can be solved, so that an equation f (x) of the trend line can be obtained.
Ideally, the trend line is kept unchanged all the time in the measurement process, but in the actual measurement process, a and b slightly change under the influence of external factors (such as field voltage change, air bubble amount change in a water pipe and the like) under normal conditions, and if the a or b amount change is larger than a certain rated value, the pipeline flow is abnormal.
Because the field voltage changes very little, the water pump power is basically invariable, and the value of a of the trend line is close to 0, if the absolute value of a is greater than a certain set rated value, the pipeline flow is abnormal.
The system realizes data sharing as follows:
(1) the pipeline information sharing technique is shown in fig. 4;
(2) the traffic data sharing technique is shown in fig. 5;
(3) according to the related national standard of the pipeline, the parameters of the pipeline with different types are stored in a mobile terminal software database and a cloud server terminal database, when the pipeline information is recorded, after one parameter of the pipeline is input, the mobile terminal software automatically searches other parameters of the pipeline from the database and fills the other parameters into the corresponding position, and the specific implementation method is as shown in fig. 6.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, it should be noted that any modifications, equivalents and improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.