Accurate detection method for installation angle of rotor flowmeter

Abstract

The present application relates to the technical field of inclination detection, and specifically to a method for accurately detecting the installation inclination of a rotor flowmeter. The method comprises: collecting the flow value and installation inclination at each moment to form a sequence, and for the installation inclination sequence, obtaining the smoothness by smoothing the installation inclination difference and the deviation difference before and after; obtaining the interference by the installation inclination difference and the deviation difference of adjacent data points, obtaining the interference of the flow sequence, obtaining the flow influence based on the interference and sequence value of the two, and optimizing the interference; obtaining the processing effect of the smoothing factor based on the optimized interference and smoothness, and thereby obtaining the adjusted smoothing factor, smoothing the installation inclination by the adjusted smoothing factor, and completing the accurate detection. The present application improves the detection accuracy and efficiency of the installation inclination of the rotor flowmeter.

Description

Technical Field

[0001] The present application relates to the technical field of inclination detection, and in particular to a method for accurately detecting the installation inclination of a rotor flowmeter. Background Art

[0002] The rotor flowmeter measures fluid flow based on the throttling principle. It keeps the differential pressure above and below the rotor constant by changing the flow area of ​​the fluid, so it is also called a variable flow area constant differential pressure flowmeter. Traditional rotor flowmeters have high installation requirements and usually require vertical installation. However, in actual application, they are often limited by installation conditions, and the installation accuracy cannot meet the conditions, resulting in deviations in the measurement of the rotor flowmeter or even failure to work properly. Therefore, it is usually necessary to detect the installation inclination of the rotor flowmeter, and compensate the flow measurement value according to the installation inclination of the rotor flowmeter and the corresponding software. The detection accuracy of the installation inclination of the rotor flowmeter directly affects the compensation amount of the flow measurement value, that is, it affects the accuracy and efficiency of the rotor flowmeter in measuring flow.

[0003] When using a horizontal sensor to obtain the installation inclination angle of the rotor flowmeter, the accuracy of the collected installation inclination angle data is low due to the influence of the vibration and temperature changes around the rotor flow, which in turn makes the compensation accuracy of the rotor flowmeter low. Therefore, it is usually necessary to use a filtering algorithm to filter the inclination angle data collected by the horizontal sensor to improve the measurement accuracy and efficiency of the horizontal sensor. The exponentially weighted moving average filter is a common filtering algorithm, in which the selection of the smoothing factor is crucial to the performance of the filter. Too large a smoothing factor will make the filter too sensitive to noise, while too small a smoothing factor will make the filter react too slowly to data changes. Summary of the invention

[0004] In order to solve the technical problem of low installation inclination angle measurement accuracy, the present application provides an accurate detection method for the installation inclination angle of a rotor flowmeter. The technical solution adopted is as follows:

[0005] The present application proposes a method for accurately detecting the installation inclination angle of a rotor flowmeter, the method comprising the following steps:

[0006] Collect the flow value and installation inclination at each moment;

[0007] The flow value and the installation inclination angle constitute a flow sequence and an installation inclination angle sequence respectively. In the installation inclination angle sequence, the installation inclination angle sequence is smoothed by a preset smoothing factor to obtain the installation inclination angle after smoothing of the data point; the smoothness of each data point under different smoothing factors is obtained according to the difference in the installation inclination angle before and after smoothing and the difference in the degree of deviation of the same data point;

[0008] Obtain the neighborhood data points of each data point, and obtain the interference degree of the data point according to the difference in installation inclination between the data point and its neighborhood data points and the difference between the deviation degree of the data point and the average deviation degree of the neighborhood data points; in the flow sequence, obtain the interference degree of the data point in the flow sequence according to the difference in deviation degree and flow value between the data point and the neighborhood data points; obtain the flow influence degree of the data point according to the difference in interference degree of the same data point in different sequences and the difference between the installation inclination angle and the flow value; in the installation inclination sequence, optimize the interference degree according to the flow influence degree to obtain the optimized interference degree;

[0009] In the installation inclination sequence, the smoothness and optimized interference of the data point are compared with the smoothness and optimized interference of the remaining data points in the installation inclination sequence to obtain a processing effect value of the smoothing factor; the smoothing factor is adjusted according to the processing effect value, the smoothness and the optimized interference to obtain an adjusted smoothing factor;

[0010] The installation inclination angle is smoothed according to the adjusted smoothing factor, and the installation inclination angle is accurately detected.

[0011] In the above scheme, in this application, the smoothness of the installation inclination data points is constructed by the deviation degree of the data points in the installation inclination sequence under the action of the smoothing factor and the change of the installation inclination, and at the same time, the interference degree of the installation inclination data points is constructed by the local data change and the deviation degree distribution characteristics of the installation inclination data points. The flow influence degree of the installation inclination data points and the flow data is constructed based on the influence of the fluid flow data measured by the rotor flowmeter on the installation inclination, the interference degree is optimized based on the flow influence degree, and the processing effect value of the smoothing factor is adaptively constructed based on the optimized interference degree and smoothness. The optimal smoothing factor is adaptively acquired based on the processing effect value, the optimized interference degree and the smoothness, thereby improving the filtering effect of the exponentially weighted moving average filter, and thereby improving the detection accuracy and efficiency of the installation inclination of the rotor flowmeter.

[0012] In one embodiment, the method for obtaining the smoothness of each data point under different smoothing factors according to the difference in the installation inclination angle and the difference in the degree of deviation before and after smoothing of the same data point is:

[0013] The difference in the Z score of each data point in the installation inclination angle sequence before and after smoothing is calculated as the difference in the degree of deviation of the installation inclination angle sequence;

[0014] The smoothness of the data points under the smoothing factor is obtained according to the difference in Z scores before and after smoothing and the difference in the installation inclination angle before and after smoothing;

[0015] The smoothness of the data points under the smoothing factor is positively correlated with the difference in Z scores before and after smoothing and the difference in mounting inclination angles before and after smoothing, and negatively correlated with the Z score after smoothing.

[0016] In one embodiment, the method of obtaining the neighborhood data points of each data point and obtaining the interference degree of the data point according to the difference in installation inclination between the data point and its neighborhood data points and the difference between the deviation degree of the data point and the mean deviation degree of the neighborhood data points is:

[0017] In the installation inclination sequence, for a data point, several data points closest to it are selected as its neighborhood data points;

[0018] Obtain the interference degree of the data point according to the difference between the Z score of the data point and the mean Z score of the neighboring data points and the difference in the installation inclination angle between the data point and the neighboring data points;

[0019] The interference degree of the data points was positively correlated with the difference in installation inclination angles, and the difference in Z scores and the mean Z scores of neighboring data points was negatively correlated.

[0020] In one embodiment, the method for obtaining the flow influence of a data point according to the difference in interference degree of the same data point in different sequences and the difference between the installation inclination angle and the flow value is:

[0021] , represents the interference degree of the qth data point in the installation inclination sequence, represents the interference degree of the qth data point in the traffic sequence, represents the normalized value of the installation inclination angle of the qth data point in the installation inclination angle sequence, Represents the normalized value of the flow value of the qth data point in the flow sequence, represents an exponential function with a natural constant as base, Indicates the traffic influence of the qth data point.

[0022] In one embodiment, in the installation inclination sequence, the method for optimizing the interference degree according to the flow influence degree to obtain the optimized interference degree is:

[0023] , It represents the interference degree after optimization of the qth data point in the installation inclination sequence, represents the traffic impact of the qth data point, Represents the interference degree of the qth data point in the installation inclination sequence.

[0024] In one embodiment, the method of comparing the smoothness and optimized interference of the data point with the smoothness and optimized interference of the remaining data points in the installation inclination sequence to obtain the processing effect value of the smoothing factor is:

[0025] , represents the smoothing effect value of the qth data point of the installed inclination sequence, It represents the maximum value of the processing effect of all data points in the installation inclination sequence under the smoothing factor. It represents the minimum value of the processing effect of all data points in the installation inclination sequence under the smoothing factor. represents the linear normalization function, It represents the treatment effect value of the qth data point of the installation inclination angle sequence under the smoothing factor.

[0026] In one embodiment, the method for adjusting the smoothing factor according to the processing effect value, the smoothness and the optimized interference degree to obtain the adjusted smoothing factor is:

[0027]

[0028] In the formula, Indicates the smoothness of the qth data point in the installation inclination sequence under the current smoothing factor, It represents the interference degree after optimization of the qth data point in the installation inclination sequence, It indicates the processing effect of the qth data point in the installation inclination sequence under the current smoothing factor. is the current smoothing factor, is the adjusted smoothing factor.

[0029] In one embodiment, the method for smoothing the installation inclination angle according to the adjusted smoothing factor is:

[0030] The installation inclination angle after smoothing is obtained by using the exponential moving weighted average method;

[0031] The inputs to the algorithm are the adjusted smoothing factor, the collected installation inclination angle, and the installation inclination angle after smoothing of the previous data point.

[0032] In one embodiment, the method for obtaining the smoothness of the data point under the smoothing factor according to the Z score difference before and after smoothing and the installation inclination angle difference before and after smoothing is:

[0033] , G represents the data points before smoothing, and E represents the data points after smoothing. represents the Z score of the data point before smoothing, represents the Z score of the smoothed data point, represents the installation inclination angle of the data point before smoothing, represents the installation inclination angle of the smoothed data point, Indicates the smoothness of the data point under the current smoothing factor.

[0034] In one embodiment, the method for obtaining the interference degree of a data point according to the difference between the Z score of the data point and the mean value of the Z scores of the neighboring data points and the difference in the installation inclination angle between the data point and the neighboring data points is:

[0035] , represents the Z score of the qth data point, represents the mean of the Z scores of all neighboring data points of the qth data point, represents the installation inclination angle of the qth data point, represents the installation inclination of the ith neighboring data point of the qth data point, represents the number of domain data points, Represents the interference degree of the qth data point.

[0036] The beneficial effects of the present application are as follows: in the present application, the smoothness of the installation inclination data points is constructed by the deviation degree of the data points in the installation inclination sequence under the action of the smoothing factor and the change of the installation inclination, and at the same time, the interference degree of the installation inclination data points is constructed by the local data change and the deviation degree distribution characteristics of the installation inclination data points, the flow influence degree of the installation inclination data points and the flow data is constructed based on the influence of the fluid flow data measured by the rotor flowmeter on the installation inclination, the interference degree is optimized based on the flow influence degree, the processing effect value of the smoothing factor is adaptively constructed based on the optimized interference degree and smoothness, and the optimal smoothing factor is adaptively acquired based on the processing effect value, the optimized interference degree and the smoothness, thereby improving the filtering effect of the exponentially weighted moving average filter, and thereby improving the detection accuracy and efficiency of the installation inclination of the rotor flowmeter. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A flow chart of a method for accurately detecting the installation inclination angle of a rotor flowmeter provided in one embodiment of the present application;

[0039] Figure 2 This is a schematic diagram of the installation of the rotor flowmeter and the tapered tube;

[0040] Figure 3 A comparison chart of the installation inclination angles in different situations for this application. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the precise detection method for the installation inclination angle of the rotor flowmeter proposed in the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0043] Embodiment of the method for accurately detecting the installation inclination angle of the rotor flowmeter:

[0044] The specific scheme of the method for accurately detecting the installation inclination angle of the rotor flowmeter provided by the present application is described in detail below with reference to the accompanying drawings.

[0045] See also Figure 1 , which shows a flow chart of a method for accurately detecting the installation inclination angle of a rotor flowmeter provided by an embodiment of the present application, the method comprising the following steps:

[0046] Step S001, collecting the flow value and installation inclination angle at each moment.

[0047] Place the rotor flowmeter in the common conical tube of the rotor flowmeter, place the level sensor on the bottom of the conical tube, and make sure the rotor center of gravity of the rotor flowmeter coincides with the axis of the conical tube. Figure 2 As shown, Figure 2 1 is the rotor of the rotor flowmeter, 2 is the level sensor, and 3 is the conical tube of the rotor flowmeter. The installation inclination of the rotor flowmeter can be obtained through the level sensor, and the flow value can be collected in real time through the rotor flowmeter. The flow value at this time is the uncompensated flow value. The installation inclination and flow value are collected every five seconds.

[0048] At this point, the flow value and installation inclination angle at each moment are obtained.

[0049] Step S002, the flow value and the installation inclination angle are respectively used to form a flow sequence and an installation inclination angle sequence, and the installation inclination angle sequence is smoothed by a preset smoothing factor to obtain the smoothed installation inclination angle of the data point in the installation inclination angle sequence; the smoothness of each data point in the installation inclination angle sequence under different smoothing factors is obtained according to the difference in the installation inclination angle before and after smoothing and the difference in the degree of deviation of the same data point in the installation inclination angle sequence.

[0050] For the collected installation inclination and flow values, one day is taken as a cycle, so that all the installation inclination and flow values ​​collected from the beginning of each day to the current time constitute a sequence, which are respectively recorded as the installation inclination sequence and the flow sequence.

[0051] Due to the excessive fluid flow, the pipeline pressure is too high, resulting in local deformation or pipeline vibration, which will cause the installation inclination angle to fluctuate around a fixed value, making the collected installation inclination angle inaccurate. Therefore, the installation inclination angle needs to be smoothed. The change of the installation inclination angle before and after smoothing can be adaptively constructed to characterize the change of the installation inclination angle under the action of the filter, and then the smoothing factor parameters can be adjusted based on the smoothness.

[0052] Since both the installation inclination angle sequence and the flow rate sequence are time series, the initial smoothing factor of the exponentially weighted moving average filter is first set. In this embodiment, the initial smoothing factor is 0.3, and the initial smoothing factor is the smoothing factor of the first data point in the sequence. The smoothing factor of each data point is adjusted based on the smoothing factor of the previous data point. The installation inclination angle sequence is smoothed by the exponentially weighted moving average method, and the smoothed installation inclination angle of each data point in the installation inclination angle sequence is obtained after smoothing; wherein, the exponentially weighted moving average method is a well-known technology and will not be described in detail in this application.

[0053] Calculate the Z score of each data point in the installation inclination sequence before and after smoothing. The calculation of the Z score is a well-known technique, and its function is to obtain the degree of deviation of each data point relative to the average value. The greater the difference in the degree of deviation before and after smoothing, the more it indicates that the installation inclination with large fluctuations has been corrected, and the smoothing effect is better. The greater the difference in the installation inclination before and after smoothing, the greater the smoothing influence. Based on this, the smoothness of each data point under the smoothing factor is obtained.

[0054] The smoothness of the data points under the smoothing factor is positively correlated with the difference in Z scores before and after smoothing and the difference in mounting inclination angles before and after smoothing, and negatively correlated with the Z score after smoothing.

[0055] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the two variables change in the same direction. When one variable changes from large to small or from small to large, the other variable also changes from large to small or from small to large. The specific relationship is determined by actual application and this application does not impose any special restrictions.

[0056] It should be noted that negative correlation means that when one variable increases, the other variable decreases accordingly, and the two variables change in opposite directions. When one variable changes from large to small or from small to large, the other variable also changes from small to large or from large to small. The specific relationship is determined by actual application and this application does not impose any special restrictions.

[0057] Preferably, in this embodiment, the expression of smoothness under the current smoothing factor is:

[0058] , where G represents the data point before smoothing and E represents the data point after smoothing. represents the Z score of the data point before smoothing, represents the Z score of the smoothed data point, represents the installation inclination angle of the data point before smoothing, represents the installation inclination angle of the smoothed data point, Indicates the smoothness of the data point under the current smoothing factor.

[0059] Preferably, in another embodiment of the present application, the expression of smoothness under the current smoothing factor is: .

[0060] The larger the Z score of the smoothed data point in the installation inclination angle sequence, the greater the deviation of the smoothed data point and the worse the smoothing effect. The greater the difference in the Z scores of the data points before and after smoothing, the better the smoothing effect of the installation inclination angle under the current smoothing factor. The greater the difference in the installation inclination angle before and after smoothing, the greater the change in the smoothed data point, which means the better the smoothing effect.

[0061] At this point, the smoothness of each data point under the current smoothing factor is obtained.

[0062] Step S003, obtain the neighborhood data points of each data point, and obtain the interference degree of the data point according to the difference in installation inclination between the data point and its neighborhood data points and the difference between the deviation degree of the data point and the average deviation degree of the neighborhood data points; in the flow sequence, obtain the interference degree of the data point in the flow sequence according to the difference in deviation degree and flow value between the data point and the neighborhood data points; obtain the flow influence degree of the data point according to the difference in interference degree of the same data point in different sequences and the difference between the installation inclination and the flow value; in the installation inclination sequence, optimize the interference degree according to the flow influence degree to obtain the optimized interference degree.

[0063] Through the above steps, the smoothness of each data point in the installation inclination sequence under the current smoothing factor is obtained. Since for different data points, the larger the smoothness, the better. When the data point in the installation inclination sequence is a normal data point (that is, a data point with less interference), the larger the smoothness, the more the influence weight of the historical data in the current filter is too large, which leads to the current normal data point being over-smoothed. When the data point in the installation inclination sequence is an abnormal data point (that is, a data point with greater interference), the larger the smoothness, the better the noise removal effect of the current filter.

[0064] Therefore, it is necessary to analyze the data points in the installation inclination angle sequence and obtain the interference degree of each data point in the installation inclination angle sequence based on the difference in installation inclination angle between the data point and the data points in its neighborhood and the difference in Z scores.

[0065] For each data point in the installation inclination sequence, select the M data points closest to the data point in the installation inclination sequence as neighborhood data points. If there are no M data points in the installation inclination sequence, take all data points, and the value of M is 11.

[0066] The interference degree of the data points is positively correlated with the difference in the installation inclination angle and the difference in the Z score.

[0067] Preferably, in this embodiment, the interference degree of the data points in the installation inclination sequence is:

[0068] , represents the Z score of the qth data point, represents the mean of the Z scores of all neighboring data points of the qth data point, represents the installation inclination angle of the qth data point, represents the installation inclination of the ith neighboring data point of the qth data point, represents the number of domain data points, Represents the interference degree of the qth data point.

[0069] Preferably, in another embodiment of the present application, the interference degree of the data points in the installation inclination sequence is:

[0070] .

[0071] The larger the Z score of a data point is, and the smaller the average Z score of all neighboring data points is, that is, the greater the difference in Z score between a data point and its neighboring data points, the greater the deviation of the data point from its neighboring data points, that is, the greater the independence of the data point, and the more likely the change in the installation inclination angle of the data point is to be an independent change, the greater the interference to the data point. The greater the difference between the installation inclination angle of a data point and that of its neighboring data points, the greater the mutation of the installation inclination angle of the data point, and the greater the difference in the installation inclination angle of the data point compared to the normal fluctuation, and the greater the interference to the data point.

[0072] The above steps are used to obtain the interference degree of each data point in the installation inclination sequence. Then, for each flow sequence, the interference degree of each data point in the flow sequence is obtained through the difference between the Z score of the data point in the flow sequence and the flow value of its neighboring data points and the mean of the Z score.

[0073] Since the installation inclination angle will be affected by the flow rate of the fluid during collection, when the flow rate is too large, the pressure of the fluid on the pipeline will change, which will cause the local load of the pipeline to be too large and local deformation to occur. Therefore, when the flow rate is too large, the installation inclination angle will change significantly, resulting in excessive interference of data points in the installation inclination angle sequence.

[0074] Based on the above analysis, the present application further analyzes the flow values ​​collected by the rotor flowmeter. Since the flow values ​​and installation inclination angles are collected at every moment, at the same moment, the data points in the installation inclination angle sequence and the data points in the flow sequence are one-to-one corresponding. Therefore, the flow influence of each data point is obtained based on the difference in interference degrees of corresponding data points in different sequences and the difference in installation inclination angle and flow value of the data point.

[0075] Preferably, in this embodiment, the normalized value of the installation inclination angle and the flow value of each data point is first obtained, and the expression of the flow influence is:

[0076] , represents the interference degree of the qth data point in the installation inclination sequence, represents the interference degree of the qth data point in the traffic sequence, represents the normalized value of the installation inclination angle of the qth data point in the installation inclination angle sequence, Represents the normalized value of the flow value of the qth data point in the flow sequence, represents an exponential function with a natural constant as base, Indicates the traffic influence of the qth data point.

[0077] When the flow data is too large, the local load of the pipeline is too large and local deformation occurs, which will cause the installation inclination angle to change. Therefore, the flow impact reflects the possibility that the abnormal installation inclination angle is affected by the flow data. If the difference between the interference degree of the corresponding data points of the installation inclination angle sequence and the flow sequence is smaller, the flow impact is greater. At this time, the change of the installation inclination angle and the flow value is reflected as a whole, and the change of the numerical value is ignored. Therefore, the flow impact of the data point is obtained by combining the difference in the numerical value.

[0078] The interference degree of the data points in the installation inclination sequence is optimized through the flow influence of the data points, and the optimized interference degree is obtained, and its expression is: , It represents the interference degree after optimization of the qth data point in the installation inclination sequence.

[0079] At this point, the optimized interference degree of each data point in the installation inclination angle sequence is obtained.

[0080] Step S004: In the installation inclination sequence, the smoothness and optimized interference of the data point are compared with the smoothness and optimized interference of the remaining data points in the installation inclination sequence to obtain a processing effect value of the smoothing factor; the smoothing factor is adjusted according to the processing effect value, smoothness and optimized interference to obtain an adjusted smoothing factor.

[0081] Through the above steps, the smoothness of the data points and the optimized interference degree are obtained, and the processing effect of the smoothing factor is constructed based on the smoothness and the optimized interference degree.

[0082] For each data point, the smoothness of the data point indicates that the data point has a large change under the influence of the smoothing factor. The optimized interference degree of the data point indicates that the data point is more likely to be a data point collected with interference. The product of the smoothness of each data point and the optimized interference degree is calculated and recorded as the smoothing effect value. The smoothing effect value represents the processing effect of the smoothing factor. When the smoothing effect value is large, it means that the smoothing effect of the installation inclination angle data point is large when it is interfered with, and the smoothing effect is good. When the smoothing effect value is small, it means that the smoothing effect of the installation inclination angle is small when it is not interfered with, and more content is retained after smoothing.

[0083] The treatment effect value of the smoothing factor is obtained by fitting the smoothing effect value for each data point in the dip series.

[0084] Preferably, in this embodiment, the expression of the processing effect value of the smoothing factor is:

[0085] , represents the smoothing effect value of the qth data point of the installed inclination sequence, It represents the maximum value of the processing effect of all data points in the installation inclination sequence under the smoothing factor. It represents the minimum value of the processing effect of all data points in the installation inclination sequence under the smoothing factor. represents the linear normalization function, It represents the treatment effect value of the qth data point of the installation inclination angle sequence under the smoothing factor.

[0086] Through the above steps, the processing effect value of each data point in the installation inclination sequence under the smoothing factor is obtained. Based on this processing effect value, the smoothing factor is adaptively adjusted in the following way:

[0087]

[0088] In the formula, Indicates the smoothness of the qth data point in the installation inclination sequence under the current smoothing factor, It represents the interference degree after optimization of the qth data point in the installation inclination sequence, It indicates the processing effect of the qth data point in the installation inclination sequence under the current smoothing factor. is the current smoothing factor, is the adjusted smoothing factor.

[0089] When the processing effect of the data point under the smoothing factor is weak, the smoothing factor needs to be corrected. When the optimized interference degree is greater than or equal to the smoothing degree, it means that the data point in the installation inclination sequence is subject to greater interference. At this time, the installation inclination adjusted by the previous data point is more important, and the current smoothing factor needs to be reduced. When the optimized interference degree is less than the smoothing degree, it means that the data point in the current installation inclination sequence is over-smoothed. At this time, more attention needs to be paid to the installation inclination collected by the data point itself, so the smoothing factor needs to be increased.

[0090] At this point, the adjusted smoothing factor is obtained.

[0091] Step S005, smoothing the installation inclination angle according to the adjusted smoothing factor, and accurately detecting the installation inclination angle.

[0092] For each data point in the installation inclination sequence, the smoothing factor of the previous data point is used as the current smoothing factor, and the current smoothing factor is adjusted through the above steps. The smoothed installation inclination is obtained by the exponential moving weighted average method through the adjusted smoothing factor, and the accurate detection of the installation inclination is completed. Its input is the adjusted smoothing factor, the collected installation inclination, and the installation inclination after the previous data point is smoothed. The comparison of the unfiltered installation inclination, the original filtered installation inclination, and the optimized filtered installation inclination of this application is shown in the figure below. Figure 3 shown.

[0093] It should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

[0094] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for accurately detecting the installation inclination angle of a rotor flowmeter, characterized in that: The method comprises the following steps: Collect the flow value and installation inclination at each moment; The flow value and the installation inclination angle constitute a flow sequence and an installation inclination angle sequence respectively. In the installation inclination angle sequence, the installation inclination angle sequence is smoothed by a preset smoothing factor to obtain the installation inclination angle after smoothing of the data point; the smoothness of each data point under different smoothing factors is obtained according to the difference in the installation inclination angle before and after smoothing and the difference in the degree of deviation of the same data point; Obtain the neighborhood data points of each data point, and obtain the interference degree of the data point according to the difference in installation inclination between the data point and its neighborhood data points and the difference between the deviation degree of the data point and the average deviation degree of the neighborhood data points; in the flow sequence, obtain the interference degree of the data point in the flow sequence according to the difference in deviation degree and flow value between the data point and the neighborhood data points; obtain the flow influence degree of the data point according to the difference in interference degree of the same data point in different sequences and the difference between the installation inclination angle and the flow value; in the installation inclination sequence, optimize the interference degree according to the flow influence degree to obtain the optimized interference degree; In the installation inclination sequence, the smoothness and optimized interference of the data point are compared with the smoothness and optimized interference of the remaining data points in the installation inclination sequence to obtain a processing effect value of the smoothing factor; the smoothing factor is adjusted according to the processing effect value, the smoothness and the optimized interference to obtain an adjusted smoothing factor; The installation inclination angle is smoothed according to the adjusted smoothing factor, and the installation inclination angle is accurately detected.

2. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 1, characterized in that: The method for obtaining the smoothness of each data point under different smoothing factors according to the difference in the installation inclination angle and the difference in the degree of deviation before and after smoothing of the same data point is: The difference in the Z score of each data point in the installation inclination angle sequence before and after smoothing is calculated as the difference in the degree of deviation of the installation inclination angle sequence; The smoothness of the data points under the smoothing factor is obtained according to the difference in Z scores before and after smoothing and the difference in the installation inclination angle before and after smoothing; The smoothness of the data points under the smoothing factor is positively correlated with the difference in Z scores before and after smoothing and the difference in mounting inclination angles before and after smoothing, and negatively correlated with the Z score after smoothing.

3. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 2, characterized in that: The method for obtaining the neighborhood data points of each data point and obtaining the interference degree of the data point according to the difference in the installation inclination angle between the data point and its neighborhood data points and the difference between the deviation degree of the data point and the mean deviation degree of the neighborhood data points is: In the installation inclination sequence, for a data point, several data points closest to it are selected as its neighborhood data points; Obtain the interference degree of the data point according to the difference between the Z score of the data point and the mean Z score of the neighboring data points and the difference in the installation inclination angle between the data point and the neighboring data points; The interference degree of the data points was positively correlated with the difference in installation inclination angles, and the difference in Z scores and the mean Z scores of neighboring data points was negatively correlated.

4. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 1, characterized in that: The method for obtaining the flow influence of a data point according to the difference in interference degree of the same data point in different sequences and the difference between the installation inclination angle and the flow value is: , represents the interference degree of the qth data point in the installation inclination sequence, represents the interference degree of the qth data point in the traffic sequence, represents the normalized value of the installation inclination angle of the qth data point in the installation inclination angle sequence, Represents the normalized value of the flow value of the qth data point in the flow sequence, represents an exponential function with a natural constant as base, Indicates the traffic influence of the qth data point.

5. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 1, characterized in that: In the installation inclination sequence, the method for optimizing the interference degree according to the flow influence degree to obtain the optimized interference degree is: , It represents the interference degree after optimization of the qth data point in the installation inclination sequence, represents the flow influence of the qth data point, Represents the interference degree of the qth data point in the installation inclination sequence.

6. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 1, characterized in that: The method for obtaining the processing effect value of the smoothing factor by comparing the smoothness and optimized interference of the data point with the smoothness and optimized interference of the remaining data points in the installation inclination sequence is: , represents the smoothing effect value of the qth data point of the installed inclination sequence, It represents the maximum value of the processing effect of all data points in the installation inclination sequence under the smoothing factor. It represents the minimum value of the processing effect of all data points in the installation inclination sequence under the smoothing factor. represents the linear normalization function, It represents the treatment effect value of the qth data point of the installation inclination angle sequence under the smoothing factor.

7. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 1, characterized in that: The method for adjusting the smoothing factor according to the processing effect value, the smoothness and the optimized interference degree to obtain the adjusted smoothing factor is: In the formula, Indicates the smoothness of the qth data point in the installation inclination sequence under the current smoothing factor, It represents the interference degree after optimization of the qth data point in the installation inclination sequence, It indicates the processing effect of the qth data point in the installation inclination sequence under the current smoothing factor. is the current smoothing factor, is the adjusted smoothing factor.

8. The accurate detection method for the installation inclination angle of a rotor flowmeter according to claim 1, characterized in that: The method for smoothing the installation inclination angle according to the adjusted smoothing factor is: The installation inclination angle after smoothing is obtained by using the exponential moving weighted average method; The inputs to the algorithm are the adjusted smoothing factor, the collected installation inclination angle, and the installation inclination angle after smoothing of the previous data point.

9. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 2, characterized in that: The method for obtaining the smoothness of the data point under the smoothing factor according to the Z score difference before and after smoothing and the installation inclination angle difference before and after smoothing is: , G represents the data points before smoothing, and E represents the data points after smoothing. represents the Z score of the data point before smoothing, represents the Z score of the smoothed data point, represents the installation inclination angle of the data point before smoothing, represents the installation inclination angle of the smoothed data point, Indicates the smoothness of the data point under the current smoothing factor.

10. The accurate detection method for the installation inclination angle of the rotor flowmeter according to claim 3, characterized in that: The method for obtaining the interference degree of a data point according to the difference between the Z score of the data point and the mean value of the Z score of the neighboring data points and the difference in the installation inclination angle between the data point and the neighboring data points is: , represents the Z score of the qth data point, represents the mean of the Z scores of all neighboring data points of the qth data point, represents the installation inclination angle of the qth data point, represents the installation inclination of the ith neighboring data point of the qth data point, represents the number of domain data points, Represents the interference degree of the qth data point.

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