CN116662767A - Multi-sensor-based intelligent acquisition method for temperature data of evaporative cooling unit system - Google Patents
Multi-sensor-based intelligent acquisition method for temperature data of evaporative cooling unit system Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F5/00—Air-conditioning systems or apparatus not covered by F24F1/00 or F24F3/00, e.g. using solar heat or combined with household units such as an oven or water heater
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
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Abstract
The invention relates to the technical field of data processing, and provides an intelligent acquisition method for evaporating cooling unit system temperature data based on multiple sensors, which comprises the following steps: acquiring monitoring data and a water flow velocity change value; acquiring abnormal expression degree of the monitoring point difference on the monitoring data according to the temperature value difference of the monitoring data and the difference between the current moment and the historical water flow velocity; according to the distance from the monitoring point to the water inlet and the water flow velocity variation value, the water flow velocity deviation is obtained; acquiring the change moment of the water flow velocity, and acquiring monitoring data influenced by the water flow change according to the position of the monitoring point, the time interval, the water flow velocity deviation and the water flow velocity; acquiring the abnormal final expression degree of the difference of the monitoring points on the monitoring data according to the data change value, the abnormal expression degree and the influence of the water flow change of the monitoring data; and finishing data acquisition according to the abnormal final expression degree of the monitoring data by the difference of the monitoring points. The invention improves the accuracy of the abnormal expression of the difference of the monitoring points.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent acquisition method for evaporating cooling unit system temperature data based on multiple sensors.
Background
Evaporative cooling units are a common type of refrigeration that uses the heat exchange principle between water and air to reduce the indoor temperature by spraying the water onto a heat exchanger. The temperature data of the evaporative cooling unit system is a very important monitoring index to reflect the working efficiency, so that the temperature of the evaporative cooling unit system needs to be monitored, and a plurality of temperature monitoring points are usually required to be set for acquiring the temperature data in order to more comprehensively monitor the temperature of the evaporative cooling unit system. Because the sensor is affected by the environment, resulting in inaccurate data acquisition, cleaning is first required for the acquired temperature data. The cleaning of the temperature monitoring data mainly aims at the abnormal data of the acquisition process, and the temperatures at different positions in the evaporative cooling unit system are generally uniformly represented, so that the abnormal judgment is often directly carried out according to the deviation of the temperature data among different monitoring points. However, in the actual running process of the evaporative cooling unit, the water flow velocity influences heat transfer between monitoring points, so that the difference possibly exists between the monitoring points, and meanwhile, when the water flow velocity changes, the heat transfer responses of different monitoring points at different times are different, so that the temperature difference between the monitoring points is more obvious, and the temperature difference between the monitoring points cannot accurately reflect the abnormality of the monitoring data.
Disclosure of Invention
The invention provides an intelligent acquisition method of evaporative cooling unit system temperature data based on multiple sensors, which aims to solve the problem that the flow velocity of water flow affects heat transfer between monitoring points, and adopts the following technical scheme:
the embodiment of the invention provides an intelligent acquisition method for evaporating cooling unit system temperature data based on multiple sensors, which comprises the following steps:
acquiring all monitoring data and water flow velocity change values at each moment;
obtaining an abnormal monitoring point and a standard monitoring point, and obtaining abnormal expression degree of the difference of the abnormal monitoring point and the standard monitoring point on the monitoring data according to the temperature value of the standard monitoring point at the current time and the difference of the temperature value of the monitoring data, which is similar to the current water flow speed, in the history and the difference of the current water flow speed and the history water flow speed;
for each monitoring point, obtaining the current flow velocity deviation at the current moment according to the distance from the monitoring point to the water inlet and the current flow velocity change value; acquiring the change moment of the water flow velocity, and acquiring the influence of the water flow change on the monitoring data of the monitoring points at the current moment according to the position of each monitoring point, the time interval between the current moment and the current moment closest to the current moment, the water flow velocity deviation at the current moment and the water flow velocity at the current moment; obtaining the final abnormal expression degree of the difference of the abnormal monitoring points and the standard monitoring points on the monitoring data according to the difference of the data change value of the real-time monitoring data in the standard monitoring points and the data change value of the first monitoring data, the abnormal expression degree of the difference of the abnormal monitoring points and the standard monitoring points on the monitoring data and the difference of the ratio of the data change value of the real-time monitoring data of the abnormal monitoring points and the standard monitoring points to the influence of the water flow change;
and acquiring the abnormal degree of the real-time monitoring data of each monitoring point according to the final abnormal expression degree of the monitoring point difference on the monitoring data, and deleting the abnormal data according to the abnormal degree to complete data acquisition.
Preferably, the monitoring data is a temperature value acquired by each monitoring point at each moment, and the monitoring data acquired by each monitoring point at the current moment is real-time monitoring data.
Preferably, the method for acquiring the abnormal monitoring point and the standard monitoring point comprises the following steps:
all monitoring points are sequentially marked as one abnormal monitoring point, only one abnormal monitoring point can exist at the same time, monitoring data in the abnormal monitoring points are marked as abnormal monitoring data, all monitoring points except the abnormal monitoring points are sequentially marked as one standard monitoring point, and only one standard monitoring point can exist at the same time.
Preferably, the method for obtaining the abnormal performance degree of the difference between the abnormal monitoring point and the standard monitoring point on the monitoring data according to the difference between the temperature value of the standard monitoring point at the current time and the temperature value of the monitoring data in the history, which is similar to the current water flow velocity at the current time, and the difference between the current water flow velocity and the historical water flow velocity comprises the following steps:
acquiring the current water flow rate at the current moment, and finding the nearest preset number of data points in the current water flow rate at each moment in the history, wherein each data point only exists in one monitoring point at the same moment; and recording the acquired data points as running water data points, sequentially carrying out difference averaging on the temperature values of the running water data points and the temperature values of the data points of all monitoring points except the abnormal monitoring point at the same moment, sequentially carrying out difference averaging on the temperature values of the data points of all monitoring points except the abnormal monitoring point at the current moment, calculating the difference between the water flow velocity corresponding to each water flow data point and the water flow velocity of the current moment, and acquiring the abnormal expression degree of the difference of the abnormal monitoring point and the standard monitoring point on the monitoring data according to the average value of the two temperature values, the water flow velocity difference and the value of the current water flow velocity.
Preferably, the method for obtaining the abnormal expression degree of the difference between the abnormal monitoring point and the standard monitoring point on the monitoring data according to the average value of the two temperature value differences, the water flow speed difference and the current water flow speed value comprises the following steps:
in the method, in the process of the invention,mean value of temperature value differences of data points of the xth monitoring point at the t-th time and data points of all monitoring points except for the abnormal monitoring point, and +.>Mean value of temperature value difference representing the data point of the y-th water flow and the data point of all monitoring points except the abnormal monitoring point at the same moment, +.>Representing the difference of the current flow rate of the current time of the y-th water flow data point and the x-th monitoring point,/->Representing the number of water flow data points +.>Indicating the flow rate of the water flow at time t, < >>The abnormal expression degree of the difference between the ith monitoring point and the xth monitoring point for the real-time monitoring data of the ith monitoring point at the t moment is represented, wherein the ith monitoring point is the abnormal monitoring point, the xth monitoring point is the standard monitoring point, and the t moment is the current moment.
Preferably, the method for obtaining the current time water flow velocity deviation according to the distance from the monitoring point to the water inlet and the current time water flow velocity change value comprises the following steps:
and (3) obtaining the distance from the monitoring point to the water inlet, carrying out linear normalization on the distance from each monitoring point to the water inlet, and multiplying the distance normalized value obtained by each monitoring point by the current time water flow velocity change value to obtain the current time water flow velocity deviation of each monitoring point.
Preferably, the distance from the monitoring point to the water inlet is the path length from the position of the water pipe closest to the monitoring point to the water inlet of the water pipe along the opposite direction of water flow.
Preferably, the method for obtaining the influence of the water flow change on the monitoring data of the monitoring point at the current moment according to the position of each monitoring point, the time interval between the current moment and the moment of the water flow velocity change closest to the current moment, the water flow velocity deviation at the current moment and the water flow velocity at the current moment comprises the following steps:
in the method, in the process of the invention,represents the distance between the ith monitoring point and the water inlet, < ->Time interval of t time and the time of change of water flow velocity nearest to t time,/->Represents the flow rate of the water flow at time t +.>Indicating the deviation of the flow rate of the water flow at the ith monitoring point at the t-th moment,/for the monitoring point>The representation takes a positive function, ++>The monitoring data of the ith monitoring point at the t moment is influenced by the water flow change, wherein the ith monitoring point is abnormal monitoringAnd the t-th moment is the current moment.
Preferably, the method for obtaining the final abnormal expression degree of the difference between the abnormal monitoring point and the standard monitoring point on the monitoring data according to the difference between the data variation value of the real-time monitoring data in the standard monitoring point and the data variation value of the first monitoring data, the abnormal expression degree of the difference between the abnormal monitoring point and the standard monitoring point on the monitoring data and the difference between the ratio of the data variation value of the real-time monitoring data of the abnormal monitoring point and the standard monitoring point and the influence of the water flow variation comprises the following steps:
the method comprises the steps of recording the difference between the temperature of each monitoring point at the current moment and the temperature of the adjacent previous moment as a data change value of each monitoring point, finding the most similar preset number of monitoring data in historical data of each monitoring point for the influence of water flow change on real-time monitoring data of each monitoring point, recording the monitoring data as first monitoring data, enabling the data change value of the real-time monitoring data of a standard monitoring point and the data change values of all the first monitoring data in the standard monitoring point to be subjected to difference and mean value calculation, calculating the ratio of the data change value of the real-time monitoring data of the standard monitoring point to the influence of water flow change, calculating the ratio of the data change value of the real-time monitoring data of an abnormal monitoring point to the influence of water flow change, enabling the data change value of the real-time monitoring data of the standard monitoring point to be subjected to difference, and obtaining the abnormal final abnormal expression degree of the abnormal monitoring point and the difference of the standard monitoring point to the monitoring data according to the mean value, the difference and the abnormal expression degree.
Preferably, the method for obtaining the final abnormal performance degree of the monitored data by the difference between the abnormal monitoring point and the standard monitoring point according to the mean value, the difference and the abnormal performance degree comprises the following steps:
in the method, in the process of the invention,data change value representing the xth monitoring point at time t, < >>Represent the firstData change value of the s first monitoring data in the x monitoring points, +.>Data change value representing the ith monitoring point at time t,/>Monitoring data indicating the xth monitoring point at the t-th moment is influenced by the water flow change, ++>The monitoring data representing the ith monitoring point at time t is influenced by the water flow change, +.>Representing the abnormal expression degree of the difference between the ith monitoring point and the xth monitoring point at the t moment of the real-time monitoring data of the ith monitoring point, and +.>Representing the abnormal final expression degree of the difference between the ith monitoring point and the xth monitoring point at the t moment of the real-time monitoring data of the ith monitoring point; the ith monitoring point is an abnormal monitoring point, and the xth monitoring point is a standard monitoring point.
The beneficial effects of the invention are as follows: when the abnormal degree of the monitoring data is reflected by utilizing the data difference among the monitoring points, the normal temperature difference among the monitoring points caused by the water flow velocity and the water flow velocity change is considered, the error identification of the normal difference is avoided, the accuracy of the abnormal data reflected by the difference of the monitoring points is improved, the influence of different water flow velocities on the temperature relationship among the monitoring points is considered, the normal difference among the monitoring points under different water flow velocities is analyzed, the difference among the monitoring points under different water flow velocities has abnormal performance of the same scale, the abnormal performance error of the normal difference is avoided, the obtained abnormal accuracy is improved, the perception difference of the monitoring points on the water flow velocity change is considered finally, the water flow velocity deviation corresponding to different monitoring points is obtained, and the data difference of different monitoring points under the actual water flow velocity influence of different monitoring points after the water flow velocity change is avoided; meanwhile, according to the influence of the water flow velocity change on the data of the monitoring points, the consistent relation of the data change among the monitoring points is obtained, the misjudgment of the normal difference of the data of the monitoring points under the different influences of the water flow velocity change is avoided, and the accuracy of the abnormal representation of the difference of the monitoring points is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for intelligently collecting temperature data of an evaporative cooling unit system based on multiple sensors according to an embodiment of the 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.
In the process of cleaning the temperature monitoring data of the evaporative cooling unit, the abnormal degree of the deviation of the monitoring data of the monitoring points relative to the data of other monitoring points is reflected. The flow velocity of the water flow of the evaporative cooling unit has a great influence on the temperature difference between monitoring points. Therefore, the invention obtains the abnormal expression degree through the flow velocity and the flow velocity change of the water flow, and determines the final data abnormal degree by combining the difference between the monitoring points.
Referring to fig. 1, a flowchart of a method for intelligently collecting temperature data of an evaporative cooling unit system based on multiple sensors according to an embodiment of the invention is shown, and the method includes the following steps:
in step S001, all monitoring data are collected using a temperature sensor.
In the operation process of the evaporative cooling unit, a plurality of temperature sensors are installed in the system, the distance interval of each temperature sensor is 1m, the temperature of the evaporative cooling unit is collected by using the temperature sensors, the sampling interval of the sensors is set to be 5s, the position of each temperature sensor is a monitoring point, thus temperature data of each monitoring point at each moment is obtained, the temperature data are represented by a data point, and the data points are represented by time, position and temperature value together and are also represented as monitoring data. All the collected temperature data points are transmitted to a temperature monitoring system, and the temperature monitoring system is connected with an evaporative cooling unit control system and used for reading control parameters such as water flow velocity and water flow velocity change value at each moment.
So far, the temperature value of each monitoring point at each moment is obtained.
Step S002, calculating the abnormal degree of each monitoring data, and obtaining the abnormal expression degree of the monitoring point difference to the monitoring data according to the temperature difference between any monitoring points and the difference between the current water flow speed and the historical water flow speed at the current moment.
The water in the known evaporative cooling unit system can be sprayed into the filler layer to evaporate, so that the temperature distribution in the system is uniform, namely the temperatures in different positions in the system are uniform at the same moment, so that the temperature data points collected by different monitoring points at the same sampling moment have similarity, and the abnormal degree of the corresponding temperature data points can be reflected by utilizing the difference of the temperature data points among the different monitoring points.
Specifically, for the temperature difference between each time of each monitoring point and the other monitoring points at the same time, the abnormality degree of a single temperature data point is obtained, and the formula is as follows:
in the method, in the process of the invention,temperature value representing the ith monitoring point at the t-th moment,/>Temperature value at time t representing the remaining x-th monitoring point,/>Indicating the number of monitoring points->The degree of abnormality of the temperature data point at the t-th time of the i-th monitoring point is represented. />Representation->Relative to->The greater the difference in value of +.>The greater the degree of abnormality.
According to the steps, the degree of abnormality of the monitoring data is reflected by using the difference relation of the temperature data among the monitoring points, wherein each monitoring data represents all data contained in each data point. However, the analysis is based on uniform exchange of the current monitoring space temperature, but in practice, under different water flow rates, the water flow drives heat transfer at different speeds, so that the difference of different monitoring points is different, and therefore, the temperature difference between the monitoring points cannot accurately reflect the abnormal degree of the monitoring data. The present embodiment adjusts the degree of abnormality of the temperature data points according to the characteristics of the water flow.
Generally, during the operation of the evaporative cooling unit, the cooling water moves with heat, generally at a faster flow rate, and the heat may be transferred from one monitoring point to another more quickly, resulting in a smaller temperature difference. Whereas if the flow rate is slow, the rate of heat transfer in the system may be slow, possibly resulting in excessive or insufficient temperatures in certain areas, and the temperature differences between different monitoring points may increase.
Therefore, the abnormal expression degree of the temperature data difference between the monitoring points under different water flow rates in the abnormal process can be reflected by the temperature data difference between the monitoring points. Generally, the larger the flow speed of water flow is, the smaller the temperature difference between monitoring points is, so the larger the abnormal expression degree of the data difference of the monitoring points is, the smaller the flow speed of water flow is, the larger the temperature difference between the monitoring points is, and the smaller the abnormal expression degree of the data difference of the monitoring points is.
For each monitoring point, firstly, each monitoring point is marked as an abnormal monitoring point, monitoring data in the abnormal monitoring points are abnormal monitoring data, one abnormal monitoring point exists at the same time, in the comparison of difference between the temperature data of the abnormal monitoring point and the temperature data of data points except for the abnormal monitoring point at the same moment, the difference between the current data and the historical data of the monitoring points except for the abnormal monitoring point needs to be judged, the smaller the difference is, the data points are more consistent with the influence of the current water flow velocity, and the credibility of the data points of the abnormal monitoring point and the rest monitoring points is acquired by utilizing the influence of the current water flow velocity on the data points of the monitoring points except for the abnormal monitoring point.
For each monitoring point except for the abnormal monitoring point, marking the monitoring point as a standard monitoring point, wherein one standard monitoring point exists at the same time, acquiring the temperature value of the standard monitoring point at the current time, calculating the average value of the temperature value difference values of the standard monitoring point and all monitoring points except for the abnormal monitoring point at the same time, acquiring the current water flow velocity, and finding the water flow velocity closest to the current water flow velocity in the historical dataData points corresponding to the flow rates of the water flow, wherein the data points can only acquire one data point at each moment and each monitoring point, in the embodiment, the water flow rate is +.>The data point closest to the current water flow velocity is recorded as water flow data point, and for each water flow data point, the data point is calculated and the data point except for abnormal monitoringCalculating the average value of the difference values of the temperature values of all the data points of all the monitoring points outside the measuring point at the same moment, calculating the difference of the water flow velocity of each water flow data point at the current moment and the standard monitoring point, and obtaining the abnormal credibility of the standard monitoring point according to the temperature difference of the standard monitoring point and the rest monitoring points, the temperature difference of the water flow data point at the same moment, the difference of the water flow velocity of the water flow data point at the current moment and the standard monitoring point and the whole water flow velocity at the current moment, wherein for each abnormal monitoring point, the abnormal credibility of the standard monitoring point is the abnormal expression degree of the abnormal monitoring point and the standard monitoring point, and the formula is as follows:
in the method, in the process of the invention,mean value of temperature value differences of data points of the xth monitoring point at the t-th time and data points of all monitoring points except for the abnormal monitoring point, and +.>Mean value of temperature value difference representing the data point of the y-th water flow and the data point of all monitoring points except the abnormal monitoring point at the same moment, +.>Representing the difference of the current flow rate of the current time of the y-th water flow data point and the x-th monitoring point,/->Representing the number of water flow data points +.>Indicating the flow rate of the water flow at time t, < >>Real-time monitoring data representing the difference between the ith monitoring point and the xth monitoring point for the ith monitoring pointThe abnormal expression degree at the t moment, wherein the i-th monitoring point is an abnormal monitoring point, the x-th monitoring point is a standard monitoring point, and the t moment is the current moment.
By utilizing the steps, the abnormal expression degree of the difference between the monitoring points is determined according to the influence of the water flow velocity. The influence of different water flow rates on the temperature relation between the monitoring points is considered, and the normal difference between the monitoring points under different water flow rates is analyzed, so that the difference between the monitoring points under different water flow rates has abnormal performance of the same scale, abnormal performance errors of the normal difference are avoided, and the accuracy of the obtained abnormality is improved.
Thus, the abnormal expression degree of the difference between the standard monitoring point and the abnormal monitoring point on the monitoring data at the current time is obtained.
Step S003, obtaining the water flow speed deviation according to the positions of the monitoring points, further obtaining the influence of the water flow change on the monitoring data by combining the difference between the time of the water flow speed change and the current time, and obtaining the abnormal final expression degree of the monitoring point difference on the real-time monitoring data according to the influence of the water flow change on the monitoring data of different monitoring points and the abnormal expression degree.
In the actual operation process of the evaporative cooling unit, in order to meet the actual demand, the flow speed of water needs to be adjusted, when the flow speed of water changes, the heat transfer of water changes, and the corresponding relation of the temperature difference between the flow speed of water and the monitoring points is caused to have deviation, so that the abnormal expression degree of the difference between the monitoring points under the flow speed of water is caused to be inaccurate.
Because the positions of the monitoring points are different, the time for water to reach different monitoring points after passing through the pipeline or the equipment is also different, when the flow rate of the water flow changes, other monitoring points can sense the change only by a certain time delay, so that the difference exists between the actual flow rate of the water flow corresponding to each monitoring point and the read flow rate of the water flow, the larger the distance between the monitoring point and the water inlet is, the larger the deviation of the flow rate of the water flow at the corresponding position is, and the distance between the monitoring point and the water inlet is the length of the route from the position of the water pipe closest to the monitoring point to the water inlet of the water pipe along the opposite direction of the water flow.
According to the distance between the monitoring point and the water inlet and the current time water flow velocity change value, obtaining the current time water flow velocity deviation of each monitoring point, wherein the formula is as follows:
in the method, in the process of the invention,represents the distance between the ith monitoring point and the water inlet, < ->Indicating the flow rate variation value, < >>Representing a linear normalization function, ++>Indicating the deviation of the flow velocity of the water flow at the t-th moment of the ith monitoring point.
Because the water flow has a delay effect at different positions at the same moment, the flow velocity of the changed water flow can be transmitted to the position of each monitoring point from the water inlet when passing through one section, the deviation of the flow velocity of the water flow at the monitoring points can be continuously reduced along with the water flow transmission, after the flow velocity of the water flow changes, the deviation of the flow velocity of the water flow corresponding to different monitoring points at different times is different, and the abnormal data representation of the monitoring data corresponding to different monitoring points at different times is affected by the flow velocity of the water flow.
When the water flow speed changes, the time of the water flow speed change is obtained, the time interval between the current time and the time of the water flow speed change closest to the current time is obtained, and the influence of the water flow change on each monitoring point at the current time is obtained according to the position of the monitoring point, the water flow speed deviation of each monitoring point at the current time, the current water flow speed and the time interval between the current time and the time of the water flow speed change closest to the current time, wherein the formula is as follows:
in the method, in the process of the invention,represents the distance between the ith monitoring point and the water inlet, < ->Time interval of t time and the time of change of water flow velocity nearest to t time,/->Represents the flow rate of the water flow at time t +.>Indicating the deviation of the flow rate of the water flow at the ith monitoring point at the t-th moment,/for the monitoring point>The representation takes a positive function, ++>The monitoring data representing the ith monitoring point at the t moment is influenced by the water flow change.
Wherein the method comprises the steps ofThe expression means that if the value in the function is positive, the function value is unchanged, if the value in the function is not positive, the function value is 0, +.>Reflecting the decrease in the response distance of the water flow change, +.>Indicating the response distance of the current moment to the change of the water flow, < >>Indicating the current time relative to the current flow velocity change time and the current change of the water received by the ith monitoring pointDegree of influence of the chemical reaction.
The influence of water flow change on different style monitoring points at different times is determined. The sensing difference of the monitoring points on the water flow velocity change is considered, the water flow velocity deviation corresponding to different monitoring points is obtained, the data difference of different monitoring points under the influence of the actual water flow velocity of different monitoring points after the water flow velocity change is avoided, and the accuracy of the water flow velocity on the abnormal expression degree reflected by the monitoring data difference is improved.
Further, when the flow rate of the water flow changes, the heat transfer is changed at first, so that the temperature of a single monitoring point changes, the temperature changes corresponding to different monitoring points after the flow rate of the water flow changes are different because the responses of the different monitoring points to the flow rate of the water flow change are different, and the abnormal expression degree of the differences among the monitoring points is different under the influence of the flow rate change because the monitoring points are affected differently by the flow rate of the water flow at different moments.
The more consistent the influence of the water flow change among the known monitoring points is, the more consistent the monitoring data change is, and the more consistent the monitoring data change is relative to the influence relation of the water flow change is, the higher the abnormal expression degree of the difference among the monitoring points is. The more stable the monitoring data change relation is after the water flow change for one monitoring point, the higher the credibility of the monitoring data change relation is as comparison data. The stability of the monitored data change relationship is also obtained from historical data.
Firstly, calculating the difference between the temperature of each monitoring point at the current moment and the temperature of the adjacent previous moment, recording the difference as a data change value of each monitoring point, finding out N0 monitoring data which are closest to each monitoring point in the historical data of each monitoring point and are influenced by the water flow change of the monitoring data at the current moment, recording the selected monitoring data as first monitoring data, and obtaining the abnormal final expression degree of the abnormal monitoring point and the standard monitoring point according to the difference between the current monitoring data of the standard monitoring point and the data change value of the first monitoring data, the ratio of the data change values of the standard monitoring point and the abnormal monitoring point to the influence of the water flow change of the monitoring data and the abnormal expression degree of the standard monitoring point and the abnormal monitoring point at the current moment, wherein the formula is as follows:
in the method, in the process of the invention,data change value representing the xth monitoring point at time t, < >>Data change value representing the s first monitoring data in the x monitoring point, ++>Data change value representing the ith monitoring point at time t,/>Monitoring data indicating the xth monitoring point at the t-th moment is influenced by the water flow change, ++>The monitoring data representing the ith monitoring point at time t is influenced by the water flow change, +.>Representing the abnormal expression degree of the difference between the ith monitoring point and the xth monitoring point at the t moment of the real-time monitoring data of the ith monitoring point, and +.>And the abnormal final expression degree of the difference between the ith monitoring point and the xth monitoring point at the t moment of the real-time monitoring data of the ith monitoring point is represented. The ith monitoring point is an abnormal monitoring point, and the xth monitoring point is a standard monitoring point.
，/>Representing the corresponding relation between the monitoring data change and the influence of the water flow change of the corresponding monitoring point at the current moment,the smaller the value of the difference representing the corresponding relation is, the more the corresponding relation between the data changes of the two monitoring points is consistent, the higher the abnormal expression degree of the difference of the monitoring data is, and the more the difference is ∈ ->The smaller the value of the difference representing the current change relative to the historical change, the more stable the current data change of the xth monitoring point is, +.>Representing the selected +.>The greater the value of the change stability of the current data of the current x-th monitoring point is reflected by the historical data, the higher the change stability is, so that the higher the reliability of the change stability as comparison data is.
By utilizing the steps, the final abnormal performance degree among the monitoring points is obtained, and the accuracy of the obtained data abnormal degree is improved. When the water flow speed changes, the data change consistency relation between the monitoring points is obtained according to the influence of the water flow speed changes on the data of the monitoring points, so that misjudgment of normal difference of the data of the monitoring points under different influences of the water flow speed changes is avoided, and the accuracy of the difference of the monitoring points on abnormal representation of the difference of the monitoring points is improved.
So far, the final abnormal expression degree of the difference of the abnormal monitoring points and the standard monitoring points on the abnormal monitoring data is obtained.
And S004, eliminating abnormal data according to the final abnormal expression degree of the abnormal monitoring data by the difference of the abnormal monitoring points and the standard monitoring points to complete the acquisition of normal data.
Obtaining the abnormal degree of the current time data point of each monitoring point according to the obtained final abnormal expression degree, wherein the formula is as follows:
in the method, in the process of the invention,temperature value representing the ith monitoring point at the t-th moment,/>Temperature value at time t representing the remaining x-th monitoring point,/>Indicating the number of monitoring points->Indicating the degree of abnormality of the temperature data point at the t-th moment of the i-th monitoring point, ++>And the final abnormal performance degree of the ith monitoring point and the xth monitoring point at the t moment is represented.
Thereby obtaining the abnormal degree of the monitoring data at the current moment of each monitoring point, the monitoring data at the current moment of the monitoring point is called as real-time monitoring data, and the abnormal degree of all the real-time monitoring data is subjected to linear normalization to obtain a normalization resultSetting an abnormality threshold +.>When->When the real-time monitoring data at this time is judged to be abnormal data, otherwise, the real-time monitoring data is judged to be normal data, and in the embodiment, the abnormal threshold value is +.>。
After the abnormal data in the collected temperature data is determined, the abnormal data is eliminated, and then the temperature data capable of reflecting the operation state of the evaporative cooling unit is obtained.
Thus, the acquisition of the temperature data of the evaporative cooler, which normally reflects, is completed.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. The intelligent acquisition method for the evaporative cooling unit system temperature data based on the multiple sensors is characterized by comprising the following steps of:
acquiring all monitoring data and water flow velocity change values at each moment;
obtaining an abnormal monitoring point and a standard monitoring point, and obtaining abnormal expression degree of the difference of the abnormal monitoring point and the standard monitoring point on the monitoring data according to the temperature value of the standard monitoring point at the current time and the difference of the temperature value of the monitoring data, which is similar to the current water flow speed, in the history and the difference of the current water flow speed and the history water flow speed;
for each monitoring point, obtaining the current flow velocity deviation at the current moment according to the distance from the monitoring point to the water inlet and the current flow velocity change value; acquiring the change moment of the water flow velocity, and acquiring the influence of the water flow change on the monitoring data of the monitoring points at the current moment according to the position of each monitoring point, the time interval between the current moment and the current moment closest to the current moment, the water flow velocity deviation at the current moment and the water flow velocity at the current moment;
obtaining the final abnormal expression degree of the difference of the abnormal monitoring points and the standard monitoring points on the monitoring data according to the difference of the data change value of the real-time monitoring data in the standard monitoring points and the data change value of the first monitoring data, the abnormal expression degree of the difference of the abnormal monitoring points and the standard monitoring points on the monitoring data and the difference of the ratio of the data change value of the real-time monitoring data of the abnormal monitoring points and the standard monitoring points to the influence of the water flow change;
and acquiring the abnormal degree of the real-time monitoring data of each monitoring point according to the final abnormal expression degree of the monitoring point difference on the monitoring data, and deleting the abnormal data according to the abnormal degree to complete data acquisition.
2. The intelligent acquisition method for the temperature data of the evaporative cooling unit system based on the multiple sensors according to claim 1, wherein the monitoring data are temperature values acquired at each moment by each monitoring point, and the monitoring data acquired at the current moment of each monitoring point are real-time monitoring data.
3. The intelligent acquisition method for the evaporative cooling unit system temperature data based on the multiple sensors according to claim 1, wherein the method for acquiring the abnormal monitoring points and the standard monitoring points is as follows:
any one monitoring point is marked as an abnormal monitoring point, monitoring data in the abnormal monitoring points are marked as abnormal monitoring data, and any monitoring point except the abnormal monitoring point is marked as a standard monitoring point.
4. The intelligent acquisition method for the temperature data of the evaporative cooling unit system based on the multiple sensors according to claim 1, wherein the method for acquiring the abnormal expression degree of the difference between the abnormal monitoring point and the standard monitoring point on the monitoring data according to the difference between the temperature value of the standard monitoring point at the current time and the temperature value of the monitoring data similar to the current water flow rate in the history and the difference between the current water flow rate and the historical water flow rate is as follows:
acquiring the current water flow rate at the current moment, and finding the nearest preset number of data points in the current water flow rate at each moment in the history, wherein each data point only exists in one monitoring point at the same moment; and recording the acquired data points as running water data points, sequentially carrying out difference averaging on the temperature values of the running water data points and the temperature values of the data points of all monitoring points except the abnormal monitoring point at the same moment, sequentially carrying out difference averaging on the temperature values of the data points of all monitoring points except the abnormal monitoring point at the current moment, calculating the difference between the water flow velocity corresponding to each water flow data point and the water flow velocity of the current moment, and acquiring the abnormal expression degree of the difference of the abnormal monitoring point and the standard monitoring point on the monitoring data according to the average value of the two temperature values, the water flow velocity difference and the value of the current water flow velocity.
5. The intelligent acquisition method for the temperature data of the evaporative cooling unit system based on the multiple sensors according to claim 4 is characterized in that the method for acquiring the abnormal expression degree of the difference between the abnormal monitoring point and the standard monitoring point on the monitoring data according to the average value of the two temperature value differences, the water flow speed difference and the current water flow speed value is as follows:
in the method, in the process of the invention,mean value of temperature value differences of data points of the xth monitoring point at the t-th time and data points of all monitoring points except for the abnormal monitoring point, and +.>Mean value of temperature value difference representing the data point of the y-th water flow and the data point of all monitoring points except the abnormal monitoring point at the same moment, +.>Representing the difference of the current flow rate of the current time of the y-th water flow data point and the x-th monitoring point,/->Representing the number of water flow data points +.>Represents the t-th timeThe flow rate of the water flow engraved down,the abnormal expression degree of the difference between the ith monitoring point and the xth monitoring point for the real-time monitoring data of the ith monitoring point at the t moment is represented, wherein the ith monitoring point is the abnormal monitoring point, the xth monitoring point is the standard monitoring point, and the t moment is the current moment.
6. The intelligent acquisition method for the evaporative cooling unit system temperature data based on the multiple sensors according to claim 1 is characterized in that the method for obtaining the current time water flow speed deviation according to the distance from the monitoring point to the water inlet and the current time water flow speed change value is as follows:
and (3) obtaining the distance from the monitoring point to the water inlet, carrying out linear normalization on the distance from each monitoring point to the water inlet, and multiplying the distance normalized value obtained by each monitoring point by the current time water flow velocity change value to obtain the current time water flow velocity deviation of each monitoring point.
7. The intelligent acquisition method for the evaporative cooling unit system temperature data based on the multiple sensors according to claim 1, wherein the distance from the monitoring point to the water inlet is the path length from the water pipe position closest to the monitoring point to the water inlet of the water pipe along the opposite direction of water flow.
8. The intelligent acquisition method for the evaporative cooling unit system temperature data based on the multiple sensors according to claim 1 is characterized in that the method for acquiring the influence of the water flow change on the monitoring data of the monitoring point at the current moment according to the position of each monitoring point, the time interval between the current moment and the moment of the water flow rate change nearest to the current moment, the water flow rate deviation at the current moment and the water flow rate at the current moment is as follows:
in the method, in the process of the invention,represents the distance between the ith monitoring point and the water inlet, < ->Time interval of t time and the time of change of water flow velocity nearest to t time,/->Represents the flow rate of the water flow at time t +.>Indicating the deviation of the flow rate of the water flow at the ith monitoring point at the t-th moment,/for the monitoring point>The representation takes a positive function, ++>The monitoring data of the ith monitoring point at the t moment is influenced by the water flow change, wherein the ith monitoring point is an abnormal monitoring point, and the t moment is the current moment.
9. The intelligent acquisition method for the evaporative cooling unit system temperature data based on multiple sensors according to claim 1, wherein the method for acquiring the abnormal final expression degree of the difference of the abnormal monitoring point and the standard monitoring point on the monitoring data according to the difference of the data change value of the real-time monitoring data and the data change value of the first monitoring data in the standard monitoring point, the abnormal expression degree of the difference of the abnormal monitoring point and the standard monitoring point on the monitoring data and the difference of the ratio of the data change value of the real-time monitoring data of the abnormal monitoring point and the standard monitoring point to the influence of the water flow change is as follows:
the method comprises the steps of recording the difference between the temperature of each monitoring point at the current moment and the temperature of the adjacent previous moment as a data change value of each monitoring point, finding the most similar preset number of monitoring data in historical data of each monitoring point for the influence of water flow change on real-time monitoring data of each monitoring point, recording the preset number of monitoring data as first monitoring data, enabling the data change value of the real-time monitoring data of a standard monitoring point and the data change values of all the first monitoring data in the standard monitoring point to be the difference and calculate the average value, calculating the ratio of the data change value of the real-time monitoring data of the standard monitoring point to the influence of the water flow change, calculating the ratio of the data change value of the real-time monitoring data of an abnormal monitoring point to the influence of the water flow change, enabling the data change value of the real-time monitoring data of the abnormal monitoring point to be the difference, and obtaining the abnormal final abnormal representation degree of the monitoring point and the difference of the standard monitoring point according to the average value, the difference and the abnormal representation degree.
10. The intelligent acquisition method for the temperature data of the evaporative cooling unit system based on the multiple sensors according to claim 9, wherein the method for acquiring the final abnormal expression level of the monitoring data by the difference between the abnormal monitoring points and the standard monitoring points according to the mean value, the difference and the abnormal expression level is as follows:
in the method, in the process of the invention,data change value representing the xth monitoring point at time t, < >>Data change value representing the s first monitoring data in the x monitoring point, ++>Data change value representing the ith monitoring point at time t,/>Indicating that the xth monitoring point is at the tThe monitoring data of the moment is influenced by the change of the water flow, < + >>The monitoring data representing the ith monitoring point at time t is influenced by the water flow change, +.>Representing the abnormal expression degree of the difference between the ith monitoring point and the xth monitoring point at the t moment of the real-time monitoring data of the ith monitoring point, and +.>Representing the abnormal final expression degree of the difference between the ith monitoring point and the xth monitoring point at the t moment of the real-time monitoring data of the ith monitoring point; the ith monitoring point is an abnormal monitoring point, and the xth monitoring point is a standard monitoring point.
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