Method for monitoring the metrological performance of a measuring device

Abstract

With reference to Fig. 4, the method for monitoring metrological performance of a measuring device 300, wherein the measuring device provides a series of consecutive measurements of a physical parameter, can be summarized as follows: The method includes: obtaining an initial set of consecutive measurements of the series of consecutive measurements in a reference state of the parameter 310; calculating an initial standard deviation of the initial set of consecutive measurements 320; calculating an initial average of the initial set of consecutive measurements 330; then obtaining a monitoring set of consecutive measurements of the series of consecutive measurements in the reference state of the parameter 340; calculating a monitoring standard deviation of the monitoring set of consecutive measurements 350;Calculating a monitoring average of the monitoring set of consecutive measured values ​​360; Calculating a metrological distance of the monitoring set from the initial set based on the initial standard deviation, the monitoring standard deviation, the initial average, and the monitoring average 370; and Assessing the metrological performance of the measuring device based on the metrological distance of the monitoring set 380.

Description

The present invention relates to a method for monitoring a metrology performance of a measurement device, wherein the measurement device provides a series of consecutive measurement values of a physical parameter, e.g. a flow rate of a medium. A critical parameter for the measurement of the flow rate is the zero point or the zero flow value. Therefore, it is known to monitor the zero point as an aspect of the measurement performance. For example, publication WO 2022 / 256001 discloses a bias detection of a reference zero flow value, and publications WO 2022 / 256001 and WO 2022 / 255999 disclose how the criteria for zero verification are determined and selected depending on the media properties. However, while bias is an important consideration of zero point, limited analysis of bias provides incomplete analysis. In view of the foregoing, it is an object of the invention to provide a method for a more comprehensive analysis of the measurement performance.This object is achieved by the method according to independent claim 1.The method according to the invention is used for monitoring a metrological performance of a measuring device, wherein the measuring device provides a series of successive measured values of a physical parameter; wherein the method comprises the following:obtaining an initial set of consecutive measurement values of the series of consecutive measurement values in a reference state of the parameter;calculating an initial standard deviation of the initial set of consecutive measurement values;calculating an initial average of the initial set of consecutive measurement values;subsequently obtaining a monitoring set of consecutive measurement values of the series of consecutive measurement values in the reference state of the parameter;calculating a monitoring standard deviation of the monitoring set of consecutive measurement values;calculating a monitoring average of the monitoring set of consecutive measurement values;calculating a metrology distance of the monitoring set from the initial set based on the initial standard deviation, the monitoring standard deviation, the initial average, and the monitoring average; andassessing the metrology performance of the measurement device based on the metrology distance of the monitoring kit.According to a further development of the invention, the method further comprises:obtaining a probability for the monitoring set based on the metrology distance of the monitoring set;wherein the assessment of the metrological performance of the monitoring device is based on the probability of the monitoring set.According to a further development of the invention, the monitoring set comprises not less than three consecutive measured values, for example not less than thirty consecutive measured values, in particular not less than three hundred consecutive measured values.According to a further development of the invention, the probability density value is obtained by means of a model comprising a χ 2- distribution with two degrees of freedom, where p(d 2i), which is given as: where d 2i is the metrology distance.According to a further development of the invention, the probability density value is obtained by means of a model comprising a Weibull distribution w(d 2i) given as: wherein d 2i is the metrology distance, β is a shape parameter, η is a scale parameter, and γ is a location parameter.According to a further development of the invention, the parameters meet the following requirements:0,5 ≤β≤1, in particular 0.7≤β≤0.9 and / or2 ≤ η ≤ 4, in particular 2.5 ≤ η ≤ 3.5; and / orγ=0.γ=0.γ=0.According to a further development of the invention, the metrology distance of the monitoring set is calculated as wherein x i. is a monitoring average of an i-th monitoring set of consecutive measurement values, σ i is a monitoring standard deviation of an i-th monitoring set of consecutive measurement values, x ref is the initial average of the initial set of consecutive measurement values, σ ref is an initial standard deviation of the initial set of consecutive measurement values, and m is the number of consecutive measurement values in each set.According to a further development of the invention, the method further comprises:calculating a quotient of a difference between the monitoring standard deviation and the initial standard deviation divided by a difference between the monitoring average and the initial average; andcalculating a monitoring angle as a function of the quotient, in particular as an arctangent of the quotient; andwherein the assessment of the metrological performance of the monitoring device is further based on the monitoring angle,in particular, possible causes for the metrological distance of the monitoring set being examined based on the monitoring angle.According to a further development of the invention, the method further comprises:installing the measuring device at a measuring site, wherein the initial set is obtained from the installed measuring device.According to a further development of the invention, the measuring device comprises a flowmeter, wherein the parameter is a flow rate, wherein the reference state of the parameter is a flow rate of zero, and wherein the assessment of the metrological performance of the monitoring device relates to a stability of a zero point, wherein the zero point comprises the monitoring set.According to a further development of the invention, the assessment of the metrological performance of the monitoring device comprises the following:comparing the probability value of the monitoring set with a probability threshold;when the probability of the monitoring set is below a probability threshold, comparing the monitoring angle to a first monitoring angle threshold;when the monitoring angle is less than the first monitoring angle threshold, examining likely causes of a bias effect; and / orwhen the probability of the monitoring set is below a probability threshold, comparing the monitoring angle to a second monitoring angle threshold;when the monitoring angle is greater than the second monitoring angle threshold, examining likely causes of lack of repeatability;in particular wherein the first monitoring angle threshold value is between 20° and 30°, in particular 25°, and / or the second monitoring angle threshold value is between 50° and 60°, in particular 55°.According to a further development of the invention, the method further comprises:Examining the causes of a bias effect and the causes of lack of repeatability when the monitoring angle is between the first monitoring angle threshold and the second monitoring angle threshold.According to a further development of the invention, the method further comprises:comparing a monitoring vector comprising an average difference as a first component and the monitoring standard deviation as a second component with a boundary curve, the boundary curve being defined by a set of boundary vectors, the boundary vectors comprising a difference to the initial average as a first component and a standard deviation boundary as a second component; andoutputting a signal when the monitor set is outside a range bounded by the boundary curve; wherein the average difference is defined as the difference between the monitor average and the initial average; and wherein the standard deviation boundary is defined as a function of the difference between the initial average and a boundary for the average difference.According to a further development of the invention, the limit curve is given as where k is a constant greater than 1, for example k=2.According to a further development of the invention method, the method further comprises checking whether the sum of the square of k times the monitoring standard deviation and the square of the average difference is less than or equal to the square of a boundary for the average difference, wherein k is a constant greater than 1, for example k=2; and outputting a signal if not.According to a further development of the invention, the limit of the average difference depends on a temperature measurement value which represents the temperature of the measuring device.According to a further development of the invention, the method further comprises:providing a status signal related to the measurement performance to the measurement device when the probability of the monitoring set is below a probability threshold.According to a further development of the invention, the status signal represents causes or groups of causes which are identified by the examination of causes.Embodiments of the invention will be discussed below with reference to the accompanying drawings, wherein FIG. 1 shows a diagram of metrological distances of monitoring sets in a framework of probabilities and limit curves; FIG. 2 shows a probability representation for monitoring sets based on their measurement distance; FIG. 3 shows a block diagram of an embodiment of the method according to the present invention; and Figure 4 shows a block diagram of another embodiment of the method according to the present invention.In the embodiments discussed below, the physical parameter in question is the zero point of a flowmeter, i.e. the offset measured at a reference state of zero flow, which reference state can be obtained, for example, by closing a valve in the pipe towards the flowmeter. When installing a flowmeter at a measurement site, e.g., in a processing plant, a factory zero point may require initial correction for various reasons, e.g., mechanical stresses on the flowmeter. To this effect, an initial set of successive zero point readings is obtained immediately after installation of the flowmeter at a reference state of the parameter, i.e., a zero flow. An initial average of the initial set of consecutive measurements is calculated and this average is set as a null value for the installed flowmeter. Moreover, an initial standard deviation of the initial set of consecutive measurement values is calculated. The initial average and standard deviation of the zero point define the origin of the graph in Figures 1 and 2. subsequent monitor sets are obtained to verify the zero point during operation.The points in FIGS. 1 and 2 represent monitoring sets for each of which a set of successive measurement values is subsequently obtained when the flow through the flowmeter is to be zero. For each monitoring set, a monitoring standard deviation of the monitoring set from successive measurement values and a monitoring average of the monitoring set of successive measurement values are calculated. The deviation of the monitor average from the initial average defines the horizontal position of the monitor set in the plots, while the vertical position is defined by the corresponding difference of the standard deviations.The dashed lines in the diagrams of Figures 1 and 2 define levels of equal metrology distances d i2 to the origin of the diagram, i.e. from the mean and standard deviation of the original set. The metrology distance d i2 may be calculated using the equations of the following: where x i is a monitor average of an ith monitoring set of consecutive measurements, σ i is a monitor default deviation of an ith monitoring set of consecutive measurements, x ref is the initial average of the initial set of consecutive measurements, σ ref is an initial standard deviation of the initial set of consecutive measurements, and m is the number of consecutive measurements in each set. Based on the metrology distance d i2 and a proper distribution function, a probability is calculated for each of the monitoring sets. A suitable distribution may be a χ 2- distribution with two degrees of freedom. The corresponding probability density p(d 2i), given as: where d 2i is the metrology distance. The dashed lines of equal measurement distance are also lines of equal probability density. The integrated probability densities for metrology distances from 0 to the metrology distance of a dashed line define the probability for a monitoring set to fall within the range bounded by the dashed line when the flowmeter and its operating conditions remain unchanged.The choice of the proper distribution function requires verification for the specific arrangement of the method, e.g. type of flowmeter, number of consecutive values and the like. While the χ 2- distribution works well for many situations, a Weibull distribution provides more parameters to adapt to a particular situation. Thus, according to a further embodiment of the invention, the probability density value is obtained by means of a model comprising a Weibull distribution w(d 2i) given as: wherein d 2i is the metrology distance, β is a shape parameter, η is a scale parameter, and γ is a location parameter. The parameters meet the following requirements: 0.5 ≤ β ≤ 1, in particular 0.7 ≤ β ≤ 0.9; 2 ≤ η ≤ 4, in particular 2.5 ≤ η ≤ 3.5; and γ = 0.The percentages corresponding to the curves in Figure 1 indicate the complement to the probabilities, i.e. the probability for a monitor sentence to fall outside the range bounded by the respective dashed line in an unchanged system. For example, the 32% at the inner dashed line indicates that 68% of all monitoring sets should fall within the range bounded by the inner dashed line, with unchanged metrology conditions. Similarly, the 5% line indicates that 95% should be bounded by the line and that the probability for a monitor set to fall outside this curve is only 5% with unchanged conditions. However, it is apparent that a significant number of monitor sets fall outside the 5% curve, indicating a need for analysis, the details of which are discussed further below.The diagram in FIG. 1 further includes two curves labeled L and 2L. These curves are not equal span curves with respect to the initial survey set. Instead, they limit ranges for the monitor sets resulting from a predetermined limit for the zero point (L) and from the double limit (2L). At their respective intersections with the lower horizontal line corresponding to a standard deviation of zero, the curve L corresponds to the predetermined limit. For smaller differences between the average of a monitor set and the average of the initial set, the standard deviation of a monitor set may increase. More specifically, the boundary curve L is defined by pairs of average differences and corresponding standard deviations, the corresponding standard deviations σ L being given as:The factor 1⁄2 is instantiated by considering that only about 34% of all monitor sets statistically fall within the interval of one standard deviation, while about 95% fall within the interval of two standard deviations. Thus, the limitation by the factor 1⁄2 ensures a significantly tighter monitoring that the predetermined limit matches when a monitor set is checked against the limit curve.As shown in Figure 1, a significant number of the monitor sets are outside the range bounded by the 95% probability curve. While all the monitoring sets are still within the curve L, which results from a predetermined and / or required limit for the zero point. This means that the flowmeter can continue to operate, but changes can be detected and analyzed early at the beginning of the metrology performance to prevent operation of the flowmeter outside its specification.Another aspect of the method of the invention is discussed with reference to Figure 2, wherein the graph shows the same curves of equal probability density as the graph in Figure 1. In addition, the plotted monitoring sets are marked with a total probability in % and with a monitoring angle in °. The total probability indicates the probability for the monitor set to be outside the range bounded by an equal probability density curve passing through the position of the monitor set. The monitoring angle is calculated as an arctangent of a quotient of a difference between the monitoring standard deviation and the initial standard deviation divided by a difference between the monitoring average and the initial average. The monitoring angle is a simple means of indicating tendencies for causes of deviations in the zero point. High monitoring angles indicate problems of short term variations and noise repeatability, while low angles indicate bias problems and long term zero drift, therefore it is advantageous to take into account the monitoring angle in the analysis of root causes of the metrology distance of a monitoring set to the initial set.The embodiment of the method 100 shown in FIG. 3 begins by generating the origin 110 of the metrology distance curves shown in FIGS. 1 and 2, comprising data acquisition for an initial set of consecutive measurements for the zero point of a newly installed knife, obtaining an initial average set as the new zero point, and obtaining an initial standard deviation of the initial set of consecutive measurements.During subsequent operation of the flowmeter, the method 100 includes a subsequent zero point verification 120 comprising: obtaining a probability value 122 for a monitoring set of consecutive measurements based on its metrology distance to the initial set, and comparing the probability value to a threshold 124 set to 95% in the embodiment. If the test is passed, the zero point verification 120 is complete and may be repeated at any given time. However, if the probability for the monitor set is too low, the causes must be analyzed. This begins with a comparison of a monitoring angle 140 of the monitoring set in question with at least one threshold value, here an angle of 25°. If the monitoring angle is below 25°, bias related problem analysis 160 is started. If the angle is above 25° or above a second, higher threshold angle, which can be checked in a second test (not shown here), an analysis for causes of the repetition problems 180 is started. The angles between the two aspects can be taken into account.The bias related problem analysis 160 begins by examining bias root causes 162 that can cover changes in both the flowmeter and the measurement installation of which the flowmeter is a part. The basic causes can be leaks, in particular leaking valves, sensor asymmetry in Coriolis flow meters, structure on the walls of the measuring tubes, changed mechanical stresses which act on the sensor, and the like.When a root cause is identified, a test 164 is performed to determine whether the root cause is due to the flowmeter. If so, a test 168 is performed to determine whether the flowmeter needs replacement or whether the flowmeter can be repaired. Depending on the decision, different further actions 200 are initiated. For example, a request for replacement 202 or repair 204 is issued. If the root cause is not due to the flowmeter, another test 166 is performed to determine if a repair is an option, e.g., by remedying a leaky valve, or if a new zero point adjustment is advisable. In this case, a request is issued to this effect 206.The analysis for problems related to repeatability 180 begins by examining the root causes of repeatability 182 that may cover inhomogeneous media turbulence, entrained gas bubbles, vibrations or pressure changes in the environment of the flowmeter, irregular leak rates, and the like.When a root cause of repeatability is identified, a test 184 is performed to determine whether it can be resolved. Further measures 200 are initiated by issuing a request for repair 204. However, if the override is not an option, a decision 186 is made to leave the zero point at its previous value further and to repeat the verification process at the appropriate time.Referring to FIG. 4, the method for monitoring metrology performance of a measurement device 300, the measurement device providing a series of consecutive measurement values of a physical parameter, may be summarized as follows: the method comprises: obtaining an initial set of consecutive measurement values of the series of consecutive measurement values in a reference state of the parameter 310; calculating an initial standard deviation of the initial set of consecutive measurement values 320; calculating an initial average of the initial set of consecutive measurement values 330; subsequently obtaining a monitoring set of consecutive measurement values of the series of consecutive measurement values in the reference state of the parameter 340; calculating a monitoring standard deviation of the monitoring set of consecutive measurement values 350; calculating a monitoring average of the monitoring set of consecutive measurement values 360; calculating a metrology distance of the monitoring set from the initial set based on the initial standard deviation, the monitoring standard deviation, the initial average, and the monitoring average 370; and assessing metrology performance of the measurement device based on the metrology distance of the monitoring set 380.References included in the specificationThis list of documents cited by the applicant has been produced in an automated manner and is only included for the better information of the reader. The list is not part of the German patent application or utility model application. The DPMA does not take any adhesion for any faults or omissions.Patent Literature citedWO 2022 / 256001

[0001] WO 2022 / 255999

[0001]

Claims

A method (300) of monitoring metrology performance of a measurement device, the measurement device providing a series of consecutive measurement values of a physical parameter, the method (300) comprising: obtaining an initial set of consecutive measurement values of the series of consecutive measurement values in a reference state of the parameter (310); calculating an initial standard deviation of the initial set of consecutive measurement values (320); calculating an initial average of the initial set of consecutive measurement values (330); subsequently obtaining a monitoring set of consecutive measurement values of the series of consecutive measurement values in the reference state of the parameter (340); calculating a monitoring standard deviation of the monitoring set of consecutive measurement values (350); calculating a monitoring average of the monitoring set of consecutive measurement values (360); calculating a metrology distance of the monitoring set from the initial set based on the initial standard deviation, the monitoring standard deviation, the initial average, and the monitoring average (370); and assessing metrology performance of the measurement device based on the metrology distance of the monitoring set (380).The method of claim 1, further comprising: obtaining a probability for the monitoring set based on the metrology distance of the monitoring set; wherein the assessing the metrology performance of the monitoring device is based on the probability of the monitoring set.Method according to claim 1, wherein the monitoring set comprises not less than three consecutive measurement values, for example not less than thirty consecutive measurement values, in particular not less than three hundred consecutive measurement values.Method according to claim 2 or 3, wherein a probability density value is obtained by means of a model comprising a χ 2- distribution with two degrees of freedom, wherein p(d 2i), which is given as: p ( d 2 i ) = 1 2 e - d 2 i 2, wherein d 2i is the metrology distance.The method according to claim 2 or 3, wherein the probability density value is obtained by means of a model comprising a Weibull distribution w(d 2i) given as: w ( d 2 i ) = β η ( d 2 i - γ η ) β - 1 e - ( d 2 i - γ η ) β. wherein d 2i is the metrology distance, β is a shape parameter, η is a scale parameter, and γ is a location parameter.The method according to claim 5, wherein 0.5 ≤ β ≤ 1, in particular 0.7 ≤ β ≤ 0.9 and / or 2 ≤ η ≤ 4, in particular 2.5 ≤ 11 ≤ 3.5; and / or γ = 0.The method of any preceding claim, wherein the metrology distance of the monitoring set is calculated as d 2 i = f ( x i, x r e f, σ r e f ) 2 + g ( σ i, σ r e f ) 2, where f ( x i, x r e f, σ r e f ) = m x i - x r e f σ r e f, where g ( σ i, σ r e f ) = 2 ( m - 1) l n ( σ i σ r e f ), where +x i is a monitoring average of an i-th monitoring set of consecutive measurement values, σ i is a monitoring standard deviation of an i-th monitoring set of consecutive measurement values, x ref is the initial average of the initial set of consecutive measurement values, σ ref is an initial standard deviation of the initial set of consecutive measurement values, and m is the number of consecutive measurement values in each set.Method according to one of the preceding claims, further comprising: calculating a quotient of a difference between the monitoring standard deviation and the initial standard deviation divided by a difference between the monitoring average and the initial average, and calculating a monitoring angle as a function of the quotient, in particular as arctangent of the quotient; and wherein the assessment of the metrological performance of the monitoring device is further based on the monitoring angle, in particular wherein possible causes for the metrological distance of the monitoring set are examined based on the monitoring angle.The method of any preceding claim, further comprising: installing the measurement device at a measurement site, wherein the initial set is obtained from the installed measurement device.The method of any preceding claim, wherein the measurement device comprises a flowmeter, wherein the parameter is a flow rate, wherein the reference state of the parameter is a flow rate of zero, and wherein evaluating the metrology performance of the monitoring device relates to stability of a zero point, wherein the zero point comprises the monitoring set.The method of claims 2 and 8, or any claim depending on these claims, wherein assessing metrology performance of the monitoring device comprises: comparing the probability value of the monitoring set to a probability threshold; if the probability of the monitoring set is below a probability threshold, comparing the monitoring angle to a first monitoring angle threshold; if the monitoring angle is less than the first monitoring angle threshold, examining likely causes for a bias effect; and / or if the probability of the monitoring set is below a probability threshold, comparing the monitoring angle to a second monitoring angle threshold; if the monitoring angle is greater than the second monitoring angle threshold, examining likely causes for a lack of repeatability; in particular wherein the first monitoring angle threshold value is between 20° and 30°, in particular 25°, and / or the second monitoring angle threshold value is between 50° and 60°, in particular 55°.The method of claim 11 or any preceding claim, further comprising: examining the causes of a bias effect and the causes of a lack of repeatability if the monitoring angle is between the first monitoring angle threshold and the second monitoring angle threshold.The method of any preceding claim, further comprising: comparing a monitor vector comprising an average difference as a first component and the monitor default deviation as a second component to a boundary curve, wherein the boundary curve is defined by a set of boundary vectors, wherein the boundary vectors comprise a difference to the initial average as a first component and a standard deviation boundary as a second component; and outputting a signal when the monitor set is outside a range bounded by the boundary curve; wherein the average difference is defined as the difference between the monitor average and the initial average; and wherein the standard deviation boundary is defined as a function of the difference between the initial average and a boundary for the average difference.Method according to claim 13, wherein the limit curve is given as standard deviation limit = 1 k ⋅ ( limit f u%0020̈ r the average difference ) 2 - ( average difference ) 2 wherein k is a constant greater than 1, for example k = 2.The method according to any one of claims 1 to 12, further comprising: checking whether the sum of the square of k times the monitoring standard deviation and the square of the average difference is less than or equal to the square of a boundary for the average difference, wherein k is a constant greater than 1, for example k = 2; and outputting a signal if not.Method according to claims 13 to 15, wherein the limit of the average difference depends on a temperature measurement value representing the temperature of the measuring device.The method of any preceding claim, further comprising: providing a status signal related to the measurement performance to the measurement device when the probability of the monitoring set is below a probability threshold.A method according to claim 16 and 12 or any claim dependent on claim 12, wherein the status signal represents causes or groups of causes identified by the investigation of causes.

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