CN117129526B - High-precision transient dew point detection method in industrial environment - Google Patents
High-precision transient dew point detection method in industrial environment Download PDFInfo
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Abstract
The invention provides a high-precision transient dew point detection method in an industrial environment, which belongs to the technical field of industrial measurement and comprises the following steps: determining an air pressure measuring point and a water vapor content measuring point in the air accommodating space to be measured; acquiring real-time air pressure values at all air pressure measuring points and real-time water vapor content values at all water vapor content measuring points in the air accommodating space to be measured; respectively carrying out interpolation processing on the real-time air pressure values at all air pressure measuring points and the real-time water vapor content values at all water vapor content measuring points to obtain a transient air pressure value coverage model and a transient water vapor content value coverage model of the air accommodating space to be measured; determining dew point temperature data of the gas accommodating space to be detected based on the air pressure value, the relation coverage model between the water vapor content value and the dew point temperature, the transient air pressure value coverage model and the transient water vapor content value coverage model of the gas accommodating space to be detected, and determining the dew point temperature data of the gas accommodating space to be detected; the method is used for realizing high-precision detection of the transient dew point.
Description
Technical Field
The invention relates to the technical field of industrial measurement, in particular to a high-precision transient dew point detection method in an industrial environment.
Background
At present, the dew point is also called dew point temperature, which is the temperature to which gaseous water contained in air needs to be reduced to be saturated and condensed into liquid water under a fixed air pressure. The higher the air pressure, the higher the dew point; the higher the moisture content, the higher the dew point; both the air pressure and the moisture content of the air are positively correlated to the dew point. The existing dew point measuring method comprises the following steps: gravimetric, electrolytic, vibrational frequency, cold mirror, and the like.
However, the gravimetric method has the disadvantage that it is difficult to work in particular, a sufficient quantity of absorbed water mass (generally not less than 0.6 g) must be obtained, which is particularly difficult for low humidity gases, and the sample gas flow must be increased, with consequent increase of measurement time and errors (measured humidity is not instantaneous); while the electrolytic method and the vibration frequency method make up for the defects of the weight method, the electrolytic cell gas circuit needs to be dried before use, and has application limits such as higher requirements on corrosiveness and cleanliness of the gas; the disadvantage of the cold mirror method is that the response speed is slow, especially below the dew point of-60 ℃, the equilibrium time is even several hours, and the method has high requirements on the cleanliness and corrosiveness of the sample gas, otherwise the photoelectric detection effect is affected or the measurement error is caused by 'pseudo dew'. In summary, it is difficult to achieve high accuracy detection of the transient dew point temperature only by the prior art.
Therefore, the invention provides a high-precision transient dew point detection method in an industrial environment.
Disclosure of Invention
The invention provides a high-precision transient dew point detection method in an industrial environment, which is used for reasonably interpolating real-time air pressure values and real-time water vapor content values detected in real time at a plurality of positions in a gas accommodating space to be detected, constructing a data coverage model containing the real-time air pressure values and the real-time water vapor content values at different positions in the gas accommodating space to be detected, substituting the data model into a preset relation coverage model among the water vapor content values, the water vapor content values and the dew point temperature of the gas to be detected in the gas accommodating space, and determining the leakage point temperature data of the gas attached at different positions in the gas accommodating space to be detected.
The invention provides a high-precision transient dew point detection method in an industrial environment, which comprises the following steps:
S1: determining an air pressure measuring point and a water vapor content measuring point in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured;
S2: acquiring real-time air pressure values at all air pressure measuring points and real-time water vapor content values at all water vapor content measuring points in the air accommodating space to be measured;
S3: based on the gas accommodating space to be measured, respectively carrying out interpolation processing on the real-time gas pressure values at all the gas pressure measuring points and the real-time water vapor content values at all the water vapor content measuring points to obtain a transient gas pressure value coverage model and a transient water vapor content value coverage model of the gas accommodating space to be measured;
S4: and determining dew point temperature data of the gas accommodating space to be detected based on the air pressure value, the relation coverage model between the water vapor content value and the dew point temperature, the transient air pressure value coverage model and the transient water vapor content value coverage model of the gas accommodating space to be detected.
The method for detecting a high-precision transient dew point in an industrial environment according to claim 1, wherein the method comprises the following steps of: based on the three-dimensional size of the gas accommodation space to be measured, determining an air pressure measurement point and a water vapor content measurement point in the gas accommodation space to be measured, including:
S101: extracting the fluctuation position size characteristics of the air pressure value from the mass reference transient air pressure value coverage model, and extracting the fluctuation position size characteristics of the water vapor content value from the mass reference transient water vapor content value coverage model;
S102: determining a first air pressure measuring point meeting the size characteristic of the air pressure value fluctuation position in the air accommodating space to be measured, and determining a first water vapor content measuring point meeting the size characteristic of the water vapor content value fluctuation position in the air accommodating space to be measured;
s103: determining a second air pressure measuring point in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured and the normal measuring interval of the air pressure value, and determining a second water vapor content measuring point in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured and the normal measuring interval of the water vapor content value;
The air pressure measuring points comprise a first air pressure measuring point and a second air pressure measuring point;
The water vapor content measuring points comprise a first water vapor content measuring point and a second water vapor content measuring point.
Preferably, S101: extracting the fluctuation position size characteristics of the air pressure value in the mass reference transient air pressure value coverage model, and extracting the fluctuation position size characteristics of the water vapor content value in the mass reference transient water vapor content value coverage model, wherein the method comprises the following steps:
Determining the air pressure value fluctuation position in each reference transient air pressure value coverage model and the water vapor content value fluctuation position in each reference transient water vapor content value coverage model;
determining the relative position of each air pressure value fluctuation position and each conventional air pressure influence position in the corresponding reference transient air pressure value coverage model as a first relative position;
determining the relative position of each fluctuation position of the steam content value and each conventional steam content influence position in the corresponding reference transient steam content value coverage model as a second relative position;
and classifying and summarizing all the first relative positions to obtain the size characteristics of the fluctuation position of the air pressure value, and classifying and summarizing all the second relative positions to obtain the size characteristics of the fluctuation position of the water vapor content value.
Preferably, determining the air pressure value fluctuation position in each reference transient air pressure value coverage model and the water vapor content value fluctuation position in each reference transient water vapor content value coverage model includes:
Taking each reference transient air pressure value coverage model and each reference transient water vapor content value coverage model as target data coverage models;
Determining a circle area taking a single position point as a circle center and a corresponding normal measurement interval as a radius in each target data coverage model, and taking an area except for the position of the circle center in the circle area as a neighborhood of the position point of the circle center;
Calculating the fluctuation degree of each position point based on the target value of each position point in the target data coverage model and the target values of all position points in the corresponding neighborhood;
Taking a position point of which the fluctuation degree is not less than a fluctuation degree threshold value in the target data coverage model as a numerical fluctuation position;
When the target data coverage model is a reference transient air pressure value coverage model, the corresponding normal measurement interval is an air pressure value normal measurement interval, the corresponding target value is an air pressure value, and the corresponding value fluctuation position is an air pressure value fluctuation position;
When the target data coverage model is a reference transient water vapor content value coverage model, the corresponding normal measurement interval is the water vapor content value normal measurement interval, the corresponding target value is the water vapor content value, and the corresponding value fluctuation position is the water vapor content value fluctuation position.
Preferably, the classifying and summarizing are performed on all the first relative positions to obtain the size characteristics of the air pressure value fluctuation position, and meanwhile, the classifying and summarizing are performed on all the second relative positions to obtain the size characteristics of the water vapor content value fluctuation position, including:
classifying all corresponding relative positions based on the types of the conventional influence positions to obtain a relative position set of each conventional influence position;
Performing cluster analysis on the relative position set to obtain a plurality of final clusters of relative positions;
Summarizing each relative position cluster to obtain a fluctuation position size characteristic;
when the type of the conventional influencing position is the type of the conventional air pressure influencing position, all corresponding relative positions are all first relative positions, and the corresponding fluctuation position size characteristic is an air pressure fluctuation position size characteristic;
When the type of the conventional influencing location is the type of the conventional moisture content influencing location, then all corresponding relative locations are all second relative locations, and the corresponding fluctuation location dimension feature is a moisture content fluctuation location dimension feature.
Preferably, the clustering analysis is performed on the relative position set to obtain a plurality of final clusters of relative positions, including:
normalizing the relative positions to obtain a normalized relative position set;
Based on the number of each cluster in a preset cluster number table, carrying out multiple clustering analysis on the normalized relative position set to obtain multiple normalized relative position clusters in multiple clustering analysis processes of different cluster numbers;
based on all normalized relative position clusters in each cluster analysis process of the number of each cluster, calculating the comprehensive cluster aggregation degree of each cluster analysis process of the number of each cluster;
And regarding a plurality of normalized relative position clusters corresponding to the maximum comprehensive cluster aggregation degree in the comprehensive cluster aggregation degree in all cluster analysis processes of all cluster numbers as a plurality of relative position final clusters.
Preferably, S3: based on the gas accommodation space to be measured, respectively carrying out interpolation processing on the real-time air pressure values at all air pressure measuring points and the water vapor content values at all water vapor content measuring points to obtain a transient air pressure value coverage model and a transient water vapor content value coverage model of the gas accommodation space to be measured, comprising:
S301: determining an air pressure value interpolation selection range of each first position to be interpolated in an air pressure value to be interpolated region based on the air accommodating space to be detected, and determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated region;
S302: calculating an interpolation air pressure value of the first position to be interpolated based on the interval between the acquisition position of each real-time air pressure value in the air pressure value interpolation selection range and the corresponding first position to be interpolated, and calculating an interpolation water vapor content value of the second interpolation position based on the interval between the acquisition position of each real-time water vapor content value in the water vapor content value interpolation selection range and the corresponding second interpolation position;
S303: and obtaining a transient air pressure value coverage model and a transient water vapor content value coverage model of the gas accommodating space to be detected based on the interpolation air pressure values of all the first positions to be interpolated and the interpolation water vapor content values of all the second positions to be interpolated.
Preferably, S301: based on the gas accommodation space to be detected, determining an air pressure value interpolation selection range of each first position to be interpolated in the air pressure value to be interpolated area, and simultaneously determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated area, wherein the method comprises the following steps:
Taking the remaining areas except all the air pressure measuring points in the air accommodating space to be measured as air pressure value to-be-interpolated areas, and taking the remaining areas except all the water vapor content measuring points in the air accommodating space to be measured as water vapor content value to-be-interpolated areas;
and determining an air pressure value interpolation selection range of each first position to be interpolated in the air pressure value to be interpolated region based on the air pressure value normal measurement interval, and determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated region based on the water vapor content value normal measurement interval.
Preferably, S303: based on the interpolated air pressure values of all the first positions to be interpolated and the interpolated water vapor content values of all the second positions to be interpolated, a transient air pressure value coverage model and a transient water vapor content value coverage model of the air accommodating space to be measured are obtained, and the method comprises the following steps:
Fitting a transient air pressure value coverage model of the gas accommodating space to be measured based on the real-time air pressure values of all air pressure measuring points in the gas accommodating space to be measured and the interpolation air pressure values of all first positions to be interpolated in the air pressure value to be interpolated area;
fitting a transient water vapor content value coverage model of the gas accommodating space to be measured based on the real-time water vapor content values of all water vapor content measurement points in the gas accommodating space to be measured and the interpolation water vapor content values of all second positions to be interpolated in the water vapor content value interpolation area.
Preferably, S4: determining dew point temperature data of the gas accommodating space to be measured based on a relationship coverage model between the gas pressure value, the water vapor content value and the dew point temperature of the gas accommodating space to be measured, a transient gas pressure value coverage model, and a transient water vapor content value coverage model, comprising:
substituting the transient air pressure value coverage model and the transient water vapor content value coverage model into a relation coverage model between the water vapor content value and the water vapor content value-dew point temperature of the gas accommodating space to be detected to obtain dew point temperature data of the gas accommodating space to be detected.
The invention has the beneficial effects different from the prior art that: the method comprises the steps of reasonably interpolating real-time air pressure values and real-time water vapor content values detected in real time at a plurality of positions in a gas accommodating space to be detected, constructing a data coverage model containing the real-time air pressure values and the real-time water vapor content values at different positions in the gas accommodating space to be detected, substituting the data coverage model into a preset relation coverage model among the water vapor content values, the water vapor content values and the dew point temperatures of the gas accommodating space to be detected, and determining the leakage point temperature data of the gas attached to different positions in the gas accommodating space to be detected, wherein the application range of the detection method is not limited by the detection environment and the water vapor content of the gas to be detected, the time hysteresis of the traditional detection method is overcome, the dew point temperature of the gas in a certain space can be detected, and the detected leakage temperature covers the whole gas accommodating space to be detected, so that the dew point detection precision of the gas to be detected is improved
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objects and advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for high-precision transient dew point detection in an industrial environment according to an embodiment of the invention;
FIG. 2 is a flow chart of a method for high-precision transient dew point detection in yet another industrial environment in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart of a method for high-precision transient dew point detection in an industrial environment according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1:
the invention provides a high-precision transient dew point detection method in an industrial environment, which comprises the following steps of:
S1: based on the three-dimensional size of the gas accommodation space to be measured (i.e., the space for accommodating the gas to be measured, wherein the gas to be measured is the gas whose dew point temperature needs to be detected by the high-precision transient dew point detection method according to the embodiment), determining a gas pressure measurement point (i.e., the setting position of the pressure sensor) and a water vapor content measurement point (i.e., the setting position of the humidity sensor) in the gas accommodation space to be measured;
S2: acquiring real-time air pressure values (the real-time air pressure values are measured in real time based on the pressure sensors arranged at the corresponding air pressure measuring points) and real-time water vapor content values (the real-time water vapor content values are measured in real time based on the humidity sensors arranged at the corresponding water vapor content measuring points) at all the air pressure measuring points in the air accommodating space to be measured;
S3: based on the gas accommodating space to be measured, respectively carrying out interpolation processing on the real-time gas pressure values at all the gas pressure measuring points and the real-time water vapor content values at all the water vapor content measuring points to obtain a transient gas pressure value covering model of the gas accommodating space to be measured (namely, a model of the transient gas pressure values of all the position points in a container containing the gas accommodating space to be measured, which is formed by combining the transient gas pressure values of all the position points with a three-dimensional model of the gas accommodating space to be measured) and a transient water vapor content value covering model (namely, a model of the transient water vapor content values of all the position points in the container containing the gas accommodating space to be measured, which is formed by combining the transient water vapor content values of all the position points with the three-dimensional model of the gas accommodating space to be measured);
S4: based on the relation coverage model between the air pressure value, the water vapor content value and the dew point temperature of the to-be-detected gas accommodating space (namely, the pre-acquired corresponding relation model between the air pressure value and the water vapor content value of different position points in the container of the to-be-detected gas accommodating space and the dew point temperature of air nearby the position), the model is formed by combining the corresponding relation of all position points and the three-dimensional model of the to-be-detected gas accommodating space, wherein the air pressure value and the water vapor content value are independent variables of the corresponding relation, and the dew point temperature is a dependent variable of the corresponding relation), the transient air pressure value coverage model and the transient water vapor content value coverage model, and dew point temperature data of the to-be-detected gas accommodating space (the dew point temperature data of the to-be-detected gas accommodating space is the data of the transient dew point temperature of the gas nearby all position points in the container containing the to-be-detected gas accommodating space).
In this embodiment, the correspondence between the air pressure value and the moisture content value of the different position points in the container of the gas accommodation space to be measured and the dew point temperature of the air near the position is obtained by a plurality of test procedures in advance.
In this embodiment, all the gas pressure measurement points and the moisture content measurement points are not limited to the inner wall of the gas accommodation space to be measured, and may be any position within the gas accommodation space to be measured.
Because the dew point temperature of the gas is affected by the air pressure value and the water vapor content value, and the air pressure value and the water vapor content value of the gas at different positions in the gas accommodating space are different in the industrial environment, the dew point temperature of the gas at different positions in the gas accommodating space is also different, and the detection mode in the embodiment can detect the transient dew point temperature of the gas near different positions in the gas accommodating space without waiting for a water absorption process and the like, compared with the traditional detection mode, the method of the embodiment has higher measurement precision, can detect the transient dew point temperature, and has less application range.
Example 2:
Based on example 1, S1: based on the three-dimensional dimensions of the gas accommodation space to be measured, determining a gas pressure measurement point and a water vapor content measurement point in the gas accommodation space to be measured, referring to fig. 2, including:
S101: extracting the size characteristics of the air pressure value fluctuation position (namely the size characteristics of the air pressure value fluctuation position) from a massive (for example 1000) reference transient air pressure value coverage model, wherein the air pressure value fluctuation position is a position point with a certain degree of numerical abnormality compared with the air pressure values of other positions nearby, and simultaneously extracting the size characteristics of the water vapor content value fluctuation position (namely the size characteristics of the water vapor content value fluctuation position) from a massive (for example 1000) reference transient water vapor content value coverage model, wherein the water vapor content value fluctuation position is a position point with a certain degree of numerical abnormality compared with the water vapor content values of other positions nearby;
S102: determining a first gas pressure measuring point meeting the size characteristic of the fluctuation position of the gas pressure value in the gas accommodating space to be measured (namely, the position of the size characteristic meeting the size characteristic of the fluctuation position of the gas pressure value in the gas accommodating space to be measured), and simultaneously determining a first water vapor content measuring point meeting the size characteristic of the fluctuation position of the water vapor content value in the gas accommodating space to be measured (namely, the position of the size characteristic meeting the size characteristic of the fluctuation position of the water vapor content value in the gas accommodating space to be measured);
S103: determining second air pressure measuring points (the second air pressure measuring points are distributed in the air accommodating space to be measured at intervals of air pressure value normal measuring distances) in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured and the air pressure value normal measuring intervals (namely, the preset second air pressure measuring points are arranged at intervals of the second air pressure measuring points), and determining second air pressure content measuring points (the second air pressure measuring points are distributed in the air accommodating space to be measured at intervals of the air pressure value normal measuring distances) in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured and the air pressure value normal measuring intervals (namely, the second air pressure measuring points are arranged at intervals of the air pressure value normal measuring distances);
The air pressure measuring points comprise a first air pressure measuring point and a second air pressure measuring point;
The water vapor content measuring points comprise a first water vapor content measuring point and a second water vapor content measuring point.
In this embodiment, the dimensional features are for example: is positioned in a certain range near the corner point.
The above-described process of determining the barometric pressure measurement point and the moisture content measurement point takes into account not only the conventional measurement distance thereof but also the position where the detection data easily fluctuates.
Example 3:
Based on example 2, S101: extracting the fluctuation position size characteristics of the air pressure value in the mass reference transient air pressure value coverage model, and extracting the fluctuation position size characteristics of the water vapor content value in the mass reference transient water vapor content value coverage model, wherein the method comprises the following steps:
Determining the air pressure value fluctuation position in each reference transient air pressure value coverage model and the water vapor content value fluctuation position in each reference transient water vapor content value coverage model;
Determining the relative position of each air pressure value fluctuation position and each conventional air pressure influence position (namely the position where the air pressure value of the position generally influences the air pressure values of other positions, such as the positions of an air inlet and an air outlet of a gas accommodating space to be detected or the corner of a pipeline, and the like) in a corresponding reference transient air pressure value coverage model, and taking the relative position as a first relative position;
Determining the relative position of each fluctuation position of the vapor content value and each conventional vapor content influence position (namely, the position where the vapor content value of the position generally influences the vapor content values of other positions, such as the position of a pipe orifice connected with a liquid storage chamber, and the like) in the corresponding reference transient vapor content value coverage model, and taking the relative position as a second relative position;
and classifying and summarizing all the first relative positions to obtain the size characteristics of the fluctuation position of the air pressure value, and classifying and summarizing all the second relative positions to obtain the size characteristics of the fluctuation position of the water vapor content value.
In this embodiment, the relative position may be represented in terms of direction plus pitch.
The relative positions between the air pressure value fluctuation position and the water vapor content value fluctuation position and the corresponding conventional air pressure influence position and water vapor content influence position are used for representing the size characteristics of the air pressure value fluctuation position and the water vapor content value fluctuation position, and the accurate extraction of the size characteristics of the air pressure value fluctuation position in the mass reference transient air pressure value coverage model and the size characteristics of the water vapor content value fluctuation position in the mass reference transient water vapor content value coverage model is realized.
Example 4:
on the basis of embodiment 3, determining the air pressure value fluctuation position in each reference transient air pressure value coverage model and the water vapor content value fluctuation position in each reference transient water vapor content value coverage model includes:
Taking each reference transient air pressure value coverage model and each reference transient water vapor content value coverage model as target data coverage models;
Determining a circle area taking a single position point as a circle center and a corresponding normal measurement interval as a radius in each target data coverage model, and taking an area except for the position of the circle center in the circle area as a neighborhood of the position point of the circle center;
Calculating the fluctuation degree of each position point based on the target value of each position point in the target data coverage model and the target values of all position points in the corresponding neighborhood;
taking the position point of which the fluctuation degree in the target data coverage model is not less than a fluctuation degree threshold (namely a preset screening threshold for screening the fluctuation degree of the numerical fluctuation position) as the numerical fluctuation position;
When the target data coverage model is a reference transient air pressure value coverage model, the corresponding normal measurement interval is an air pressure value normal measurement interval, the corresponding target value is an air pressure value at a corresponding position in the reference transient air pressure value coverage model, and the corresponding value fluctuation position is an air pressure value fluctuation position;
When the target data coverage model is a reference transient water vapor content value coverage model, the corresponding normal measurement interval is the water vapor content value normal measurement interval, the corresponding target value is the water vapor content value of the corresponding position in the reference transient water vapor content value coverage model, and the corresponding value fluctuates at the water vapor content value fluctuation position.
In this embodiment, calculating the fluctuation degree of each location point based on the target value of each location point in the target data coverage model and the target values of all location points in the corresponding neighborhood includes:
taking the ratio of the difference value between the target value of the single position point and the target value of the single position point in the corresponding neighborhood to the average value as the sub-fluctuation degree;
The mean value of the wavelet dynamics of the single location point and all the location points in the corresponding neighborhood is taken as the fluctuation degree of the single location point.
According to the method, the neighborhood is determined through normal measurement intervals, the fluctuation degree of each position point is calculated based on the target data covering each position in the model and the target values of all position points in the corresponding neighborhood, and the calculated fluctuation degree is compared with the fluctuation degree threshold value, so that the accurate determination of the fluctuation position of the air pressure value and the fluctuation position of the water vapor content value is realized.
Example 5:
On the basis of embodiment 3, all the first relative positions are classified and summarized to obtain the size characteristics of the air pressure value fluctuation position, and all the second relative positions are classified and summarized to obtain the size characteristics of the water vapor content value fluctuation position, including:
Classifying all corresponding relative positions based on the types of the conventional influence positions to obtain a relative position set of each conventional influence position (namely, a set containing relative positions with a single conventional influence position);
Performing cluster analysis on the relative position set to obtain a plurality of final clusters of relative positions (namely clusters containing a plurality of normalized relative positions);
Summarizing each relative position cluster to obtain a fluctuation position size characteristic (namely, a value range of the relative position formed by all positions in the relative position cluster);
when the type of the conventional influencing position is the type of the conventional air pressure influencing position, all corresponding relative positions are all first relative positions, and the corresponding fluctuation position size characteristic is an air pressure fluctuation position size characteristic;
When the type of the conventional influencing location is the type of the conventional moisture content influencing location, then all corresponding relative locations are all second relative locations, and the corresponding fluctuation location dimension feature is a moisture content fluctuation location dimension feature.
Based on the above process, the first relative position and the second relative position are respectively classified according to the types of the conventional influence positions, and then are secondarily classified based on the clustering analysis, and the accurate generalization of the size characteristics of the fluctuation position is realized based on the range formed by the relative positions in the results after the two classifications.
Example 6:
on the basis of embodiment 5, a cluster analysis is performed on the set of relative positions to obtain a plurality of final clusters of relative positions, including:
normalizing the relative positions to obtain a normalized relative position set (namely, a set containing all normalized relative positions in the relative position set);
Performing multiple clustering analysis on the normalized relative position set based on each cluster number in a preset cluster number table (for example, the cluster numbers are 2,3, 4, 5 and … …) to obtain multiple normalized relative position clusters (for example, 2 normalized relative position clusters obtained in multiple clustering analysis processes, 3 normalized relative position clusters obtained in multiple clustering analysis processes and 4 normalized relative position clusters obtained in multiple clustering analysis processes, … …) of multiple clustering analysis processes with different cluster numbers;
Based on all normalized relative position clusters of each cluster analysis process of each cluster number, calculating the comprehensive cluster aggregation degree of each cluster analysis process of each cluster number (namely, the numerical value representing the similarity degree of all numerical values in the clusters of a plurality of normalized relative position clusters obtained in each cluster analysis process);
And regarding a plurality of normalized relative position clusters corresponding to the maximum comprehensive cluster aggregation degree in the comprehensive cluster aggregation degree in all cluster analysis processes of all cluster numbers as a plurality of relative position final clusters.
In this embodiment, normalizing the relative position includes:
taking the ratio of the difference between each distance in a single relative position and the minimum value of the distances in all relative positions to the difference between the maximum value and the minimum value of the distances in all relative positions as a normalized distance;
taking the ratio of the difference value between each azimuth angle in a single relative position and the minimum value in all azimuth angles of all relative positions to the difference value between the maximum value and the minimum value in all azimuth angles of all relative positions as a normalized azimuth angle;
the normalized distance and the normalized azimuth angle of the single relative position are regarded as normalized relative positions.
In this embodiment, based on all normalized relative position clusters in each cluster analysis process of each cluster number, a comprehensive cluster aggregation degree in each cluster analysis process of each cluster number is calculated, including:
Determining the average value of the distances in all the relative positions in the normalized relative position cluster in the current cluster analysis process, and taking the average value of the ratio of the distances in each relative position in the normalized relative position cluster to the corresponding average value as the first difference degree of the normalized relative position cluster;
Determining the average value of azimuth angles in all relative positions in a normalized relative position cluster in the current cluster analysis process, and taking the average value of the ratio of the azimuth angle in each relative position in the normalized relative position cluster to the corresponding average value as a second difference degree of the normalized relative position cluster;
taking the sum of the first difference degree and the second difference degree as the difference degree of the normalized relative position cluster;
Taking the difference value of 1 and the difference degree as the cluster aggregation degree of the normalized relative position cluster;
And taking the average value of the cluster aggregation degree of all the normalized relative position clusters obtained in the current cluster analysis process as the comprehensive cluster aggregation degree of the cluster analysis process.
According to the process, the screening standard of the comprehensive cluster aggregation degree is adopted, and the cluster analysis result with the largest comprehensive cluster aggregation degree is screened out from the cluster analysis results of different cluster analysis processes with different cluster numbers to serve as a plurality of relative position final clusters, so that the similarity between the intra-cluster data of the relative position final clusters obtained by dividing is higher, and the accurate size characteristics can be summarized conveniently.
Example 7:
Based on example 1, S3: based on the gas accommodation space to be measured, respectively performing interpolation processing on the real-time gas pressure values at all the gas pressure measurement points and the water vapor content values at all the water vapor content measurement points to obtain a transient gas pressure value coverage model and a transient water vapor content value coverage model of the gas accommodation space to be measured, referring to fig. 3, including:
S301: determining an air pressure value interpolation selection range (namely a range formed by acquiring the air pressure value according to the current interpolation process) of each first position to be interpolated in an air pressure value interpolation region (namely a region formed by position points of the real-time air pressure value of which the position is required to be determined based on interpolation processing) based on the air accommodating space to be detected, and determining a water vapor content value interpolation selection range (namely a range formed by acquiring the water vapor content value according to the current interpolation process) of each second position to be interpolated in an air pressure value interpolation region (namely a region formed by position points of the real-time water vapor content value of which the position is required to be determined based on interpolation processing);
S302: calculating an interpolation air pressure value of a first interpolation position (namely taking the reciprocal of the interval corresponding to the acquisition position of each real-time air pressure value as a corresponding interpolation duty ratio, taking the sum of products of all real-time air pressure values and interpolation duty ratios in the air pressure value interpolation selection range as an interpolation air pressure value of the first interpolation position) based on the interval between the acquisition position of each real-time air pressure value and the corresponding first interpolation position in the air pressure value interpolation selection range, and simultaneously calculating an interpolation air pressure value of a second interpolation position (namely taking the reciprocal of the interval corresponding to the acquisition position of each real-time air pressure value as a corresponding interpolation duty ratio, taking the sum of products of all real-time air pressure values and interpolation duty ratios in the air pressure value interpolation selection range as an interpolation air pressure value of the second interpolation position) based on the interval between the acquisition position of each real-time air pressure value and the corresponding second interpolation position in the air pressure value interpolation selection range;
S303: and obtaining a transient air pressure value coverage model and a transient water vapor content value coverage model of the gas accommodating space to be detected based on the interpolation air pressure values of all the first positions to be interpolated and the interpolation water vapor content values of all the second positions to be interpolated.
And determining an air pressure value interpolation selection range of each first position to be interpolated in the air pressure value to be interpolated area and a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated area based on the process quasi, and respectively completing interpolation processing of the corresponding first position to be interpolated and the corresponding second position to be interpolated based on the air pressure value interpolation selection range and the water vapor content value interpolation selection range.
Example 8:
Based on example 7, S301: based on the gas accommodation space to be detected, determining an air pressure value interpolation selection range of each first position to be interpolated in the air pressure value to be interpolated area, and simultaneously determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated area, wherein the method comprises the following steps:
Taking the remaining areas except all the air pressure measuring points in the air accommodating space to be measured as air pressure value to-be-interpolated areas, and taking the remaining areas except all the water vapor content measuring points in the air accommodating space to be measured as water vapor content value to-be-interpolated areas;
And determining an air pressure value interpolation selection range of each first position to be interpolated in the air pressure value to be interpolated region (namely, a region except the circle center in a circle region taking the first position to be interpolated as the circle center and taking the air pressure value normal measurement interval as the radius) based on the air pressure value normal measurement interval, and simultaneously determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated region (namely, a region except the circle center in a circle region taking the second position to be interpolated as the circle center and taking the water vapor content value normal measurement interval as the radius) based on the water vapor content value normal measurement interval.
The process completes the determination of the air pressure value to-be-interpolated area and the water vapor content value to-be-interpolated area, and the determination of the air pressure value interpolation selection range and the water vapor content value interpolation selection range by taking the normal measurement interval of the air pressure value as the radius, thereby ensuring the data quantity of the air pressure value and the water vapor content value according to the interpolation.
Example 9:
Based on example 7, S303: based on the interpolated air pressure values of all the first positions to be interpolated and the interpolated water vapor content values of all the second positions to be interpolated, a transient air pressure value coverage model and a transient water vapor content value coverage model of the air accommodating space to be measured are obtained, and the method comprises the following steps:
Fitting a transient air pressure value coverage model of the gas accommodating space to be measured based on the real-time air pressure values of all air pressure measuring points in the gas accommodating space to be measured and the interpolation air pressure values of all first positions to be interpolated in the air pressure value to be interpolated area;
fitting a transient water vapor content value coverage model of the gas accommodating space to be measured based on the real-time water vapor content values of all water vapor content measurement points in the gas accommodating space to be measured and the interpolation water vapor content values of all second positions to be interpolated in the water vapor content value interpolation area.
The above process completes the data supplement of the position to be interpolated in the transient air pressure value coverage model and the transient water vapor content value coverage model of the air accommodating space to be detected.
Example 10:
Based on example 1, S4: determining dew point temperature data of the gas accommodating space to be measured based on a relationship coverage model between the gas pressure value, the water vapor content value and the dew point temperature of the gas accommodating space to be measured, a transient gas pressure value coverage model, and a transient water vapor content value coverage model, comprising:
substituting the transient air pressure value coverage model and the transient water vapor content value coverage model into a relation coverage model between the water vapor content value and the water vapor content value-dew point temperature of the gas accommodating space to be detected to obtain dew point temperature data of the gas accommodating space to be detected.
Based on the above calculation process, the transient dew point temperature of the gas near different positions in the gas accommodating space to be measured can be determined with higher accuracy.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (4)
1. The high-precision transient dew point detection method in the industrial environment is characterized by comprising the following steps of:
S1: determining an air pressure measuring point and a water vapor content measuring point in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured;
S2: acquiring real-time air pressure values at all air pressure measuring points and real-time water vapor content values at all water vapor content measuring points in the air accommodating space to be measured;
S3: based on the gas accommodating space to be measured, respectively carrying out interpolation processing on the real-time gas pressure values at all the gas pressure measuring points and the real-time water vapor content values at all the water vapor content measuring points to obtain a transient gas pressure value coverage model and a transient water vapor content value coverage model of the gas accommodating space to be measured;
S4: determining dew point temperature data of the gas accommodating space to be detected based on the air pressure value, the relation coverage model between the water vapor content value and the dew point temperature, the transient air pressure value coverage model and the transient water vapor content value coverage model of the gas accommodating space to be detected;
s1: based on the three-dimensional size of the gas accommodation space to be measured, determining an air pressure measurement point and a water vapor content measurement point in the gas accommodation space to be measured, including:
S101: extracting the fluctuation position size characteristics of the air pressure value from the mass reference transient air pressure value coverage model, and extracting the fluctuation position size characteristics of the water vapor content value from the mass reference transient water vapor content value coverage model;
S102: determining a first air pressure measuring point meeting the size characteristic of the air pressure value fluctuation position in the air accommodating space to be measured, and determining a first water vapor content measuring point meeting the size characteristic of the water vapor content value fluctuation position in the air accommodating space to be measured;
s103: determining a second air pressure measuring point in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured and the normal measuring interval of the air pressure value, and determining a second water vapor content measuring point in the air accommodating space to be measured based on the three-dimensional size of the air accommodating space to be measured and the normal measuring interval of the water vapor content value;
The air pressure measuring points comprise a first air pressure measuring point and a second air pressure measuring point;
the water vapor content measuring points comprise a first water vapor content measuring point and a second water vapor content measuring point;
S101: extracting the fluctuation position size characteristics of the air pressure value in the mass reference transient air pressure value coverage model, and extracting the fluctuation position size characteristics of the water vapor content value in the mass reference transient water vapor content value coverage model, wherein the method comprises the following steps:
Determining the air pressure value fluctuation position in each reference transient air pressure value coverage model and the water vapor content value fluctuation position in each reference transient water vapor content value coverage model;
determining the relative position of each air pressure value fluctuation position and each conventional air pressure influence position in the corresponding reference transient air pressure value coverage model as a first relative position;
determining the relative position of each fluctuation position of the steam content value and each conventional steam content influence position in the corresponding reference transient steam content value coverage model as a second relative position;
Classifying and summarizing all the first relative positions to obtain the size characteristics of the fluctuation position of the air pressure value, and classifying and summarizing all the second relative positions to obtain the size characteristics of the fluctuation position of the water vapor content value;
S3: based on the gas accommodation space to be measured, respectively carrying out interpolation processing on the real-time air pressure values at all air pressure measuring points and the water vapor content values at all water vapor content measuring points to obtain a transient air pressure value coverage model and a transient water vapor content value coverage model of the gas accommodation space to be measured, comprising:
S301: determining an air pressure value interpolation selection range of each first position to be interpolated in an air pressure value to be interpolated region based on the air accommodating space to be detected, and determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated region;
S302: calculating an interpolation air pressure value of the first position to be interpolated based on the interval between the acquisition position of each real-time air pressure value in the air pressure value interpolation selection range and the corresponding first position to be interpolated, and calculating an interpolation water vapor content value of the second interpolation position based on the interval between the acquisition position of each real-time water vapor content value in the water vapor content value interpolation selection range and the corresponding second interpolation position;
S303: obtaining a transient air pressure value coverage model and a transient water vapor content value coverage model of the gas accommodating space to be detected based on the interpolation air pressure values of all the first positions to be interpolated and the interpolation water vapor content values of all the second positions to be interpolated;
s301: based on the gas accommodation space to be detected, determining an air pressure value interpolation selection range of each first position to be interpolated in the air pressure value to be interpolated area, and simultaneously determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated area, wherein the method comprises the following steps:
Taking the remaining areas except all the air pressure measuring points in the air accommodating space to be measured as air pressure value to-be-interpolated areas, and taking the remaining areas except all the water vapor content measuring points in the air accommodating space to be measured as water vapor content value to-be-interpolated areas;
Determining an air pressure value interpolation selection range of each first position to be interpolated in an air pressure value to be interpolated region based on an air pressure value normal measurement interval, and determining a water vapor content value interpolation selection range of each second position to be interpolated in the water vapor content value to be interpolated region based on a water vapor content value normal measurement interval;
S303: based on the interpolated air pressure values of all the first positions to be interpolated and the interpolated water vapor content values of all the second positions to be interpolated, a transient air pressure value coverage model and a transient water vapor content value coverage model of the air accommodating space to be measured are obtained, and the method comprises the following steps:
Fitting a transient air pressure value coverage model of the gas accommodating space to be measured based on the real-time air pressure values of all air pressure measuring points in the gas accommodating space to be measured and the interpolation air pressure values of all first positions to be interpolated in the air pressure value to be interpolated area;
Fitting a transient water vapor content value coverage model of the gas accommodating space to be measured based on the real-time water vapor content values of all water vapor content measurement points in the gas accommodating space to be measured and the interpolation water vapor content values of all second positions to be interpolated in the water vapor content value interpolation area;
s4: determining dew point temperature data of the gas accommodating space to be measured based on a relationship coverage model between the gas pressure value, the water vapor content value and the dew point temperature of the gas accommodating space to be measured, a transient gas pressure value coverage model, and a transient water vapor content value coverage model, comprising:
substituting the transient air pressure value coverage model and the transient water vapor content value coverage model into a relation coverage model between the water vapor content value and the water vapor content value-dew point temperature of the gas accommodating space to be detected to obtain dew point temperature data of the gas accommodating space to be detected.
2. The method of high accuracy transient dew point detection in an industrial environment of claim 1, wherein determining a barometric pressure value fluctuation location in each reference transient barometric pressure value coverage model and a vapor content value fluctuation location in each reference transient vapor content value coverage model comprises:
Taking each reference transient air pressure value coverage model and each reference transient water vapor content value coverage model as target data coverage models;
Determining a circle area taking a single position point as a circle center and a corresponding normal measurement interval as a radius in each target data coverage model, and taking an area except for the position of the circle center in the circle area as a neighborhood of the position point of the circle center;
Calculating the fluctuation degree of each position point based on the target value of each position point in the target data coverage model and the target values of all position points in the corresponding neighborhood;
Taking a position point of which the fluctuation degree is not less than a fluctuation degree threshold value in the target data coverage model as a numerical fluctuation position;
When the target data coverage model is a reference transient air pressure value coverage model, the corresponding normal measurement interval is an air pressure value normal measurement interval, the corresponding target value is an air pressure value, and the corresponding value fluctuation position is an air pressure value fluctuation position;
When the target data coverage model is a reference transient water vapor content value coverage model, the corresponding normal measurement interval is the water vapor content value normal measurement interval, the corresponding target value is the water vapor content value, and the corresponding value fluctuation position is the water vapor content value fluctuation position.
3. The method for high-precision transient dew point detection in an industrial environment according to claim 1, wherein classifying and summarizing all first relative positions to obtain a size characteristic of a fluctuation position of an air pressure value, and classifying and summarizing all second relative positions to obtain a size characteristic of a fluctuation position of an air moisture content value, comprises:
classifying all corresponding relative positions based on the types of the conventional influence positions to obtain a relative position set of each conventional influence position;
Performing cluster analysis on the relative position set to obtain a plurality of final clusters of relative positions;
Summarizing each relative position cluster to obtain a fluctuation position size characteristic;
when the type of the conventional influencing position is the type of the conventional air pressure influencing position, all corresponding relative positions are all first relative positions, and the corresponding fluctuation position size characteristic is an air pressure fluctuation position size characteristic;
When the type of the conventional influencing location is the type of the conventional moisture content influencing location, then all corresponding relative locations are all second relative locations, and the corresponding fluctuation location dimension feature is a moisture content fluctuation location dimension feature.
4. The method for high-precision transient dew point detection in an industrial environment according to claim 3, wherein performing cluster analysis on a set of relative positions to obtain a plurality of final clusters of relative positions comprises:
normalizing the relative positions to obtain a normalized relative position set;
Based on the number of each cluster in a preset cluster number table, carrying out multiple clustering analysis on the normalized relative position set to obtain multiple normalized relative position clusters in multiple clustering analysis processes of different cluster numbers;
based on all normalized relative position clusters in each cluster analysis process of the number of each cluster, calculating the comprehensive cluster aggregation degree of each cluster analysis process of the number of each cluster;
And regarding a plurality of normalized relative position clusters corresponding to the maximum comprehensive cluster aggregation degree in the comprehensive cluster aggregation degree in all cluster analysis processes of all cluster numbers as a plurality of relative position final clusters.
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