Validating a sensor assembly using parameters of a sensor signal provided by the sensor assembly

Abstract

To provide a meter electronics for validating a sensor assembly using a parameter of a sensor signal provided by the sensor assembly.SOLUTION: The meter electronics includes an interface communicatively coupled to the sensor assembly and configured to receive the two sensor signals, and a processing system communicatively coupled to the interface. The processing system is configured to calculate a sensor signal parameter relationship value between the two sensor signals and compare the calculated sensor signal parameter relationship value between the two sensor signals to a baseline sensor signal parameter relationship value between the two sensor signals.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The embodiments described below relate to the verification of a sensor assembly in a vibration meter, and are more specific. More specifically, the sensor assembly is configured to use a sensor signal provided by the sensor assembly. It concerns verifying the [Background technology]

[0002] For example, Coriolis mass flowmeter, liquid density meter, gas density meter, liquid viscometer, gas / liquid specific gravity Vibration meters such as gas / liquid relative density meters, gas molecular weight meters, and so on are commonly known. Vibration meters are generally used to measure fluid parameters. The sensor assembly is communicatively connected to the meter electronics. The sensor assembly may be coupled to provide a sensor signal to the meter electronics. vibrates in response to a driving force imposed by an actuator that receives a drive signal from the device The actuator may include a conduit configured to be.

[0003] When a conduit is used in a sensor assembly, the conduit contains a material having a property to be measured. The material in one or more conduits of the sensor assembly may be filled with a material that The sensor assembly may be stationary or stationary. Used to measure one or more fluid parameters such as mass flow rate, density, or other properties of a material. More specifically, one or more sensors configured to convert vibrational motion into a sensor signal may be used. There may be one or more transducers attached to the upper conduit. The transducer is sometimes called a pick-off sensor. A pick-off sensor generally has the following characteristics: Located at the inlet and outlet portions of one or more conduits.

[0004] As previously mentioned, the vibratory meter may be a Coriolis flowmeter. A pipeline or other transport system connected in a straight line to transport material, e.g., fluid, within the system. , slurry and / or the like. Each conduit may, for example, Natural vibration modes including simple bending, torsional, radial, and coupled modes In Coriolis flow measurement applications, the conduit may be considered to have a set of As the material flows through the conduit, it is excited into one or more vibration modes, and the motion of the conduit is During the flow, the vibrating tube and the flowing mass are subjected to Coriolis forces. These tubes couple together, causing a phase difference in vibration between the ends of the tube. The phase difference is proportional to the mass flow rate. For example, the phase difference between the two sensor signals provided by the pickoff sensors and It may be measured as

[0005] For example, if the mass flow rate of a material is proportional to the phase difference or time delay between two sensor signals, where the time delay may include a phase difference divided by the frequency. The quantity may be, for example, a proportionality constant or calibration factor, sometimes called the flow calibration factor (FCF), for the time delay. The FCF can be determined by multiplying the material and mechanical properties of the flow tube. FCF recommends that flow meters be calibrated prior to installation in a pipeline or other conduit. The calibration process may be performed by pumping material through a conduit at a known flow rate. The proportionality constant between the phase difference or time delay and the flow rate is calculated and recorded as FCF. .

[0006] One advantage of Coriolis flow meters is that the accuracy of the measured mass flow rate is improved by the moving components in the flow meter. It is not affected by wear of the elements. More specifically, the only moving parts are vibrations. Any sensor or transducer attached to the conduit and vibrating conduit. However, there is a problem that the conduit may change over time. The changes can cause changes in the mechanical properties of the conduit. For example, the changes in the conduit The stiffness of the conduit shall be adjusted over the life of the flowmeter to the initial representative stiffness value (or the original measured stiffness). The change may be due to erosion, corrosion, coating, damage, etc. As a result, the initial factory calibration, sometimes called the reference factor or FCF value, The values ​​are measured over time as the conduit is corroded, eroded, or otherwise altered. This may cause burns.

[0007] Therefore, changes can be measured by calculating the stiffness value of the conduit and comparing it to the baseline stiffness value. This comparison is called verification of the meter or sensor assembly. The baseline stiffness value is determined at approximately the same time that the FCF is calculated. If the current stiffness value differs from the reference stiffness value, changes may have occurred in the conduit. Other conduit parameters such as residual flexibility, sensor mass and damping may be used as well. However, calculating the values ​​of these and other conduit parameters requires real-time This can make measurements difficult and may disrupt the customer's process to perform the calculations. The calculation of the value of the conduit parameter may involve changes in one or more conduits in the sensor assembly. This can be avoided by somehow using the parameters of the sensor signal to detect Therefore, to verify the sensor assembly, It is necessary to use the parameters of the sensor signal provided by Summary of the Invention

[0008] The sensor assembly is then configured to use the parameters of the sensor signal provided by the sensor assembly. According to one embodiment, meter electronics are provided for verifying the readiness of the meter. The sensor assembly includes an interface communicatively coupled to the sensor assembly, the interface communicatively coupled to the sensor assembly, and the interface communicatively coupled to the sensor assembly includes two sensors. an interface configured to receive a signal; and a processing system for detecting a sensor signal parameter between the two sensor signals. and calculates the calculated sensor signal parameter relationship value between the two sensor signals. and comparing the sensor signal parameter to a baseline sensor signal parameter relationship value between the two sensor signals. do.

[0009] of the sensor signal provided by the sensor assembly to verify the sensor assembly. A method is provided for using the parameters. According to one embodiment, the method comprises: Calculating a sensor signal parameter relationship value between the two sensor signals; The sensor signal parameter relationship value is calculated as the baseline sensor signal parameter between two sensor signals. and comparing the result with a relational value.

[0010] The sensor assembly is then configured to use the parameters of the sensor signal provided by the sensor assembly. According to one embodiment, meter electronics are provided for verifying the readiness of the meter. The instrument receives a left pickoff sensor signal and a right pickoff sensor signal from the meter assembly. and a processing system communicatively coupled to the interface. The processing system includes a current first sensor assembly verification value and a current second sensor assembly verification value. determining a sensor assembly verification value for the first base sensor assembly; and Determine the first sensor assembly validation shift by comparing with the line sensor assembly validation value. and converting the current second sensor assembly verification value to a second baseline sensor assembly verification value. determining a second sensor assembly verification shift compared to the first sensor assembly verification value; and a second sensor assembly configured to verify the shift and determine a condition of the conduit based on the shift. A current first sensor assembly verification value and a current second sensor assembly verification value are generated. At least one of the parameters comprises a sensor signal parameter relationship value.

[0011] The sensor assembly is then configured to use the parameters of the sensor signal provided by the sensor assembly. According to a first embodiment, a method is provided for verifying a battery, the method comprising: Determining a current first sensor assembly validation value and a current second sensor assembly validation value and comparing the current first sensor assembly verification value with the first baseline sensor assembly verification value. determining a first sensor assembly verification shift by comparing the first sensor assembly verification shift with the second sensor assembly verification shift; The second sensor assembly verification value is compared to a second baseline sensor assembly verification value. determining a first sensor assembly verification shift and a second sensor assembly verification shift; and determining a state of the conduit based on the assembly verification shift. and at least one of the current second sensor assembly verification value and the current second sensor assembly verification value. It consists of signal parameter related values.

[0012] The sensor assembly is then configured to use the parameters of the sensor signal provided by the sensor assembly. According to one embodiment, meter electronics are provided for verifying the readiness of the meter. The device stores a central tendency value of the sensor assembly validation values ​​and a variance value of the sensor assembly validation values. The processing system includes a storage system configured to: Obtain the central tendency value and dispersion value from the system, and calculate the central tendency value and dispersion value based on the central tendency value and dispersion value. to determine the probability that the central tendency value differs from the baseline sensor assembly validation value. The sensor assembly validation value is configured to detect a sensor signal parameter value. Made.

[0013] The sensor assembly is then configured to use the parameters of the sensor signal provided by the sensor assembly. According to one embodiment, a method is provided for verifying vibration. The central tendency value and the sensor assembly validation value are stored in the meter electronics of the meter. obtaining the variance value of the sensor assembly validation value, and calculating the probability based on the central tendency value and the variance value; to determine whether the central tendency values ​​differ from the baseline of sensor assembly validation values. The baseline sensor assembly validation values ​​include determining the sensor signal parameter values. Based on.

[0014] Aspects According to one aspect, a sensor assembly is provided using a parameter of the sensor signal. and meter electronics for validating the sensor assembly by communicating with the sensor assembly. an interface coupled to the sensor and configured to receive two sensor signals; and a processing system communicatively coupled to the interface. The system calculates the sensor signal parameter relationship value between the two sensor signals, and The calculated sensor signal parameter relationship between the two sensor signals is calculated as the baseline relationship between the two sensor signals. The sensor signal parameter is configured to be compared to a related value.

[0015] Preferably, the meter is adapted to calculate a sensor signal parameter relationship value between two sensor signals. The configuration of the controller electronics is shown by the left pickoff sensor signal voltage value and the right pickoff sensor signal voltage value. the meter electronics is configured to calculate a sensor signal parameter relationship value between the sensor signal voltage value and the This includes what has been done.

[0016] Preferably, the meter is adapted to calculate a sensor signal parameter relationship value between two sensor signals. The data electronics are configured to provide a correlation between the two sensor signal parameter values ​​of the two sensor signals. The meter electronics is configured to calculate one of a ratio and a difference of:

[0017] Preferably, the calculated sensor signal parameter relationship values ​​are used to calculate the baseline sensor signal parameters. The meter electronics is configured to compare the calculated sensor data with the data related value. Calculating the difference between the signal parameter relationship value and the baseline sensor signal parameter relationship value The meter electronics are configured so that

[0018] Preferably, the two sensor signals are a drive signal, a left pickoff sensor signal, and a right pickoff sensor signal. Includes two of the off sensor signals.

[0019] Preferably, the meter electronics calculates a calculated sensor signal parameter between the two sensor signals. The sensor algorithm is based on a comparison of the sensor signal parameter relationship values ​​with the baseline sensor signal parameter relationship values. It is further configured to determine the state of the assembly.

[0020] According to one aspect, a sensor assembly is provided using a parameter of the sensor signal. The method to verify the sensor assembly is to determine the sensor signal parameter relationship between the two sensor signals. calculating a correlation value between the two sensor signals; and and comparing the two sensor signals to a baseline sensor signal parameter relationship value. nothing.

[0021] Preferably, calculating a sensor signal parameter relationship value between two sensor signals comprises: Sensor signal parameter between the pickoff sensor signal voltage value and the right pickoff sensor signal voltage value This includes calculating data relation values.

[0022] Preferably, calculating a sensor signal parameter relationship value between two sensor signals comprises: calculating one of a ratio and a difference between two sensor signal parameter values ​​of the sensor signals of .

[0023] Preferably, the calculated sensor signal parameter relationship values ​​are used to calculate the baseline sensor signal parameters. Comparing the calculated sensor signal parameter relationship values ​​with the baseline sensor signal parameter relationship values ​​is a The method includes calculating the difference between the sensor signal parameter relationship value.

[0024] Preferably, the two sensor signals are a drive signal, a left pickoff sensor signal, and a right pickoff sensor signal. Includes two of the off sensor signals.

[0025] Preferably, the method further comprises: calculating a calculated sensor signal parameter relationship value between two sensor signals; The health of the sensor assembly based on a comparison with baseline sensor signal parameter relationships. and determining the

[0026] According to one aspect, a sensor assembly is provided using a parameter of the sensor signal. The meter electronics for verifying the sensor assembly is located a pitch to the left of the meter assembly. an interface configured to receive a right pick-off sensor signal and a right pick-off sensor signal; and a processing system communicatively coupled to the interface. determining a current first sensor assembly validation value and a current second sensor assembly validation value; , comparing the current first sensor assembly verification value to the first baseline sensor assembly verification value; and comparing the first sensor assembly to determine a verification shift and the current second sensor assembly. the second baseline sensor assembly verification value is compared to the second baseline sensor assembly verification value to verify the second sensor assembly. determining a first sensor assembly verification shift and a second sensor assembly verification shift; The current first sensor assembly is configured to determine a state of the conduit based on the signal shift. and / or the current second sensor assembly verification value is a sensor signal parameter. It consists of meter-related values.

[0027] Preferably, the first sensor assembly verification shift is between the driver and the left pickoff. The second sensor assembly verification shift represents a change in the physical stiffness of the conduit and is connected to the driver and right pitch. represents the change in physical stiffness of the conduit between the break and the

[0028] Preferably, the sensor signal parameter relationship value is a ratio of two sensor signal parameter values ​​and This is one side of the difference.

[0029] Preferably, the sensor signal parameter relationship value is a left pickoff sensor signal parameter, a right pickoff sensor signal parameter, and a Determined based on two of the pickoff sensor signal parameters and the drive signal parameters. will be done.

[0030] Preferably, the processing system is adapted to provide an alert based on the determined condition of the conduit. Further configured.

[0031] Preferably, the conduit condition is determined by measuring the erosion, corrosion, damage, and coating of the sensor assembly conduit. The method includes at least one of the following:

[0032] Preferably, the processing system is adapted to account for at least one of the stiffness, residual flexibility, damping, and mass of the conduit. The device is further configured to determine a condition of the conduit based on at least one of the signal strengths.

[0033] According to one aspect, a sensor assembly is provided using a parameter of the sensor signal. The method for validating the sensor assembly using a current first sensor assembly validation value and determining a current second sensor assembly verification value and a current first sensor assembly verification value; The verification value is compared to a first baseline sensor assembly verification value to obtain a first sensor assembly verification value. determining a verification shift and comparing the current second sensor assembly verification value with a second baseline sensor assembly verification value; determining a second sensor assembly verification shift relative to the sensor assembly verification value; a first sensor assembly verification shift and a second sensor assembly verification shift based on the first sensor assembly verification shift and the second sensor assembly verification shift; determining a current first sensor assembly validation value and a current second sensor assembly validation value; At least one of the sensor assembly validation values ​​comprises a sensor signal parameter relationship value.

[0034] Preferably, the first sensor assembly verification shift includes a driver and a left pickoff sensor. The second sensor assembly verification shift represents the change in the physical stiffness of the conduit between the driver and Represents the change in physical stiffness of the conduit between the right pickoff sensor and the left pickoff sensor.

[0035] Preferably, the sensor signal parameter relationship value is a ratio of two sensor signal parameter values ​​and This is one side of the difference.

[0036] Preferably, the sensor signal parameter relationship value is a left pickoff sensor signal parameter, a right pickoff sensor signal parameter, and a Determined based on two of the pickoff sensor signal parameters and the drive signal parameters. will be done.

[0037] Preferably, the method further comprises providing an alarm based on the determination of the condition of the conduit.

[0038] Preferably, the conduit condition includes erosion, corrosion, damage, and coating of the vibratory meter conduit. It includes at least one of the following:

[0039] According to one aspect, a sensor assembly is provided using a parameter of the sensor signal. The meter electronics for validating the sensor assembly using the A storage system configured to store a variance of cardiac tendency values ​​and sensor assembly validation values. The processing system includes a storage system for storing the central tendency and variance values. The central tendency value is obtained, and the probability is determined based on the central tendency value and the variance value. The base line sensor assembly is configured to detect whether the base line value differs from the verification value. The line sensor assembly validation values ​​are based on the sensor signal parameter values.

[0040] Preferably, the sensor assembly validation values ​​include an LPO / RPO voltage ratio value, a DRV / LPO voltage ratio value, and This is one of the DRV / RPO voltage ratio values.

[0041] Preferably, the processing system is configured to determine the probability based on the central tendency value and the variance value. What is done is to calculate a t-value and configure the processing system to use the t-value to calculate the probability. This includes the system being configured.

[0042] Preferably, the processing system is configured to determine the probability based on the central tendency value and the variance value. What is done is to calculate the degrees of freedom based on several sensor assembly validation measurements. The processing system is configured to:

[0043] Preferably, the processing system is configured to determine the probability based on the central tendency value and the variance value. This allows the processing system to calculate standard errors based on standard deviations and degrees of freedom. This includes the system being configured.

[0044] Preferably, the standard error is calculated using the following formula:

number

[0045] Preferably, the variance value is a function of the sensor assembly validation measurement and the baseline sensor assembly validation measurement. The pooled standard deviation includes the standard deviation of the validation measurements.

[0046] Preferably, the probabilities include confidence intervals for the central tendency values.

[0047] Preferably, the confidence interval is compared to 0, and if the confidence interval does not include 0, the central tendency value is the baseline. Detects if the line sensor assembly validation value is not equal to the confidence interval and includes 0. detects that the central tendency value is equal to the baseline sensor assembly validation value.

[0048] Preferably, the central tendency value is a sensor assembly validation value, and Confidence intervals are calculated using the following formula: CI=SV mean ±CI range ; where: CI is the confidence interval of the sensor assembly validation value, SV mean is the sensor assembly validation value retrieved from the storage system, CI range is the confidence interval range calculated based on the standard deviation and t-value.

[0049] Preferably, the confidence interval range is calculated using the following formula: CI range =stderror pooled ·t student,99.8 ; where: stderror pooled is the pooled standard error of the sensor assembly validation measurements, t student,99.8 is a number of sensor assembly validation measurements, including the sensor assembly validation value. The t-value is calculated based on the significance level and degrees of freedom determined from the t-value.

[0050] Preferably, the processing system is further configured to set a bias dead band, If the bias value is less than the bias deadband, the sensor assembly validation value is the baseline sensor. The subassembly verification value is not detected as different from the subassembly verification value.

[0051] Preferably, the processing system is configured to determine the probability based on the central tendency value and the variance value. The fact that the processing system is designed to determine confidence intervals based on central tendency and variance values ​​is a key factor. The stem is configured.

[0052] Preferably, the baseline sensor assembly validation value is Includes the central tendency and variance of the validation values.

[0053] Preferably, the central tendency value of the baseline sensor assembly validation value is is the mean of the baseline sensor assembly validation values, and the variance of the baseline sensor assembly validation values ​​is the 1 is the standard deviation of the line sensor assembly validation values.

[0054] Preferably, the central tendency value is determined to be different from the baseline sensor assembly validation value. The meter electronics are configured to output a probability based on the central tendency and variance. to determine whether the rate overlaps with the probability of the baseline sensor assembly validation value. The meter electronics are configured.

[0055] Preferably, the probability based on the central tendency value and the variance value is The probability of the baseline sensor assembly validation value is determined based on the confidence interval. The confidence interval is determined based on the sensor assembly validation measurements.

[0056] Preferably, the probability based on the central tendency value determines whether it duplicates with the probability of the baseline sensor assembly verification value, and the meter electronics is configured such that the following formula , that is, LHS = |μ measured - μ baseline |; RHS = 2 * (σ measured - σ baseline ); is calculated, and when LHS < RHS, it is determined that the probability of the central tendency value and the variance value obtained from the memory system duplicates with the probability of the baseline sensor assembly verification value, including that the meter electronics is configured as such.

[0057] Preferably, the baseline standard deviation is calculated according to the following formula. σ baseline = dead band * μ baseline

[0058] According to one aspect, a method for verifying a sensor assembly using the parameters of the sensor signal supplied by the sensor assembly includes obtaining the central tendency value of the sensor assembly verification value and the variance value of the sensor assembly verification value from the memory device in the meter electronics of the vibratory meter, and determining a probability based on the central tendency value and the variance value to determine whether the central tendency value is different from the baseline sensor assembly verification value. The baseline sensor assembly verification value is based on the sensor signal parameter value. Preferably, the sensor assembly verification value is one of the LPO / RPO voltage ratio value, the DRV / LPO voltage ratio value, and the DRV / RPO voltage ratio value.

[0059]

[0060] ​​​​Preferably, determining the probability based on the central tendency value and the variance value includes calculating a t-value. and using the t-value to calculate the probability.

[0061] Preferably, determining the probability based on the central tendency value and the variance value is performed for several sensors. Calculating the degrees of freedom based on the assembly validation measurements.

[0062] Preferably, determining the probability based on the central tendency value and the dispersion value is based on the standard deviation and the mean value. This involves calculating standard errors based on the degrees of freedom.

[0063] Preferably, the standard error is calculated using the following formula:

number

[0064] Preferably, the variance value is a function of the sensor assembly validation measurement and the baseline sensor assembly validation measurement. The pooled standard deviation includes the standard deviation of the validation measurements.

[0065] Preferably, the probabilities include confidence intervals for the central tendency values.

[0066] Preferably, the confidence interval is compared to 0, and if the confidence interval does not include 0, the central tendency value is the baseline. Detects if the line sensor assembly validation value is not equal to the confidence interval and includes 0. detects that the central tendency value is equal to the baseline sensor assembly validation value.

[0067] Preferably, the central tendency value is a sensor assembly validation value, and Confidence intervals are calculated using the following formula: CI=SV mean ±CI range ; where: CI is the confidence interval of the sensor assembly validation value, SV mean is the sensor assembly validation value retrieved from the storage system (204), CI range is the confidence interval range calculated based on the standard deviation and t-value.

[0068] Preferably, the confidence interval range is calculated using the following formula: CI range =stderror pooled ·t student,99.8 ; where: stderror pooled is the pooled standard error of the sensor assembly validation measurements, t student,99.8 is a number of sensor assembly validation measurements, including the sensor assembly validation value. The t-value is calculated based on the significance level and degrees of freedom determined from the t-value.

[0069] Preferably, the method further comprises setting a bias dead band, wherein the central tendency value is a bias If the sensor assembly validation value is less than the sensor deadband, the baseline sensor assembly It is not detected as different from the validation value.

[0070] Preferably, determining the probability based on the central tendency value and the variance value comprises determining the probability based on the central tendency value and the variance value. Determining a confidence interval based on the variance values.

[0071] Preferably, the baseline sensor assembly validation value is Includes the central tendency and variance of the validation values.

[0072] Preferably, the central tendency value of the baseline sensor assembly verification value is the average of the baseline sensor assembly verification values, and the variance value of the baseline sensor assembly verification value is the standard deviation of the baseline sensor assembly verification values.

[0073] Preferably, determining whether the central tendency value is different from the baseline sensor assembly verification value includes determining whether the probability based on the central tendency value and the variance value overlaps with the probability of the baseline sensor assembly verification value.

[0074] Preferably, the probability based on the central tendency value and the variance value includes a confidence interval determined based on the central tendency value and the variance value, and the probability of the baseline sensor assembly verification value includes a confidence interval determined based on the baseline sensor assembly verification measurement value.

[0075] Preferably, determining whether the probability based on the central tendency value and the variance value overlaps with the probability of the baseline sensor assembly verification value involves calculating the following formula, measured i.e., baseline LHS = |μ - μ measured |; baseline RHS = 2 * (σ - σ ); and, when LHS < RHS, determining that the probability of the central tendency value and the variance value obtained from the storage device overlaps with the probability of the baseline sensor assembly verification value.

[0076] ​​​​​​​​​[Brief explanation of the drawings]

[0077] The same reference numbers represent the same elements in all drawings. The drawings are not necessarily to scale. It should be understood that this is not the case. [Figure 1] 1 shows a vibratory meter 5 configured to verify a sensor assembly using parameters of a sensor signal provided by the sensor assembly. [Figure 2] 1 shows a block diagram of a vibratory meter 5, including a block diagram representation of meter electronics 20 configured to validate a sensor assembly using parameters of a sensor signal provided by the sensor assembly. [Figure 3] 1 illustrates meter electronics 20 configured to validate a sensor assembly using parameters of a sensor signal provided by the sensor assembly. [Figure 4] 4 shows a graph 400 illustrating the correspondence between the stiffness of the sensor assembly and the difference between the sensor signal parameters. [Figure 5] A method 500 for validating a sensor assembly, such as the sensor assembly 10 described above, using parameters of the sensor signal of the sensor assembly is shown. [Figure 6] 6 illustrates a method 600 for validating a sensor assembly using parameters of a sensor signal provided by the sensor assembly. [Figure 7] 7 illustrates a method 700 for validating a sensor assembly using parameters of a sensor signal provided by the sensor assembly. DETAILED DESCRIPTION OF THE INVENTION

[0078] 1-7 and the following description refer to the parameters of the sensor signals provided by the sensor assembly. and using the best mode of an embodiment to verify a sensor assembly using data Specific examples are provided to teach the method to those skilled in the art. Conventional aspects of the invention have been simplified or omitted. Those skilled in the art will recognize these concepts within the scope of this specification. Variations from the examples may be understood. Those skilled in the art will appreciate that the features described below may be implemented in various ways. and a sensor signal provided by the sensor assembly is used to Multiple variations can be made to detect changes in assembly. The disclosed embodiments are not limited to the specific examples described below, but are within the scope of the claims and the appended claims. This document is limited only by the terms of the applicable patent and its equivalents.

[0079] Figure 1 shows the sensor signal parameters provided by the sensor assembly. 1 shows a vibration meter 5 configured to verify the subassembly. The meter 5 includes a sensor assembly 10 and meter electronics 20. 0 is responsive to the mass flow rate and density of the process material. The meter electronics 20 receives the sensor signal 100. The sensor assembly 10 is connected to the sensor via leads carrying the signal. The sensor signals 100 include the RTD signal, the drive signal, and the left and right sensor signals. uses the sensor signal 100 to calculate and It may be configured to provide.

[0080] The sensor assembly 10 includes a pair of manifolds 150 and 150' and flange necks 110 and 111'. 10', a pair of parallel conduits 130 and 130', and a driver 180. , a resistance temperature detector (RTD) 190, and a pair of pick-off sensors 170l and 170r. 130′ and 130′ are two essentials that converge towards each other at the conduit mounting blocks 120 and 120′. The conduits 130, 130' have generally straight inlet legs 131, 131' and outlet legs 134, 134'. They bend at two symmetrical locations along their length and are essentially flat throughout their length. The brace bars 140 and 140' define axes W and W' about which each conduit 130, 130' vibrates. The legs 131, 131' and 134, 134' of the conduits 130, 130' function as conduit mounting The blocks 120 and 120' are fixedly attached to the manifold 150. and 150'. This allows for continuous closure through the sensor assembly 10. Resulting material pathway.

[0081] Flanges 103 and 103' having holes 102 and 102' are provided through an inlet end 104 and an outlet end 104'. , when connected to a process line (not shown) carrying the process material being measured, The air passes through an orifice 101 in a flange 103 into the inlet end 104 of the meter and flows through a manifold 150. The material is then introduced into a conduit mounting block 120 having a surface 121. is split and sent through conduits 130, 130'. Upon exiting conduits 130, 130', the process material are recombined into a single stream in block 120' having surface 121' and manifold 150'. and then connected to a process line (not shown) by a flange 103' with holes 102'. The flow is directed to an outlet end 104'.

[0082] Conduits 130, 130' are of substantially equal mass about bending axes WW and W'-W', respectively. The conduit mounting block 120, 1 20'. These bending axes pass through the brace bars 140, 140'. Insofar as Young's modulus of changes with temperature and this change affects the calculation of flow rate and density, An RTD 190 is attached to the conduit 130' to continuously measure the temperature of the conduit 130'. The temperature, and therefore the voltage appearing across the RTD 190 for a given current passing through it, is The temperature dependent voltage appearing across the RTD 190 is governed by the temperature of the material passing through the tube 130'. The pressure is adjusted to compensate for changes in the elastic modulus of the conduits 130, 130' due to any changes in the conduit temperature. , used by meter electronics 20 in a well-known manner. RTD 190 is connected to It is connected to the meter electronics 20 .

[0083] Both conduits 130, 130' are rotated by driver 180 about their respective bending axes W and W'. The vibration meter is driven in the opposite direction in the so-called first out-of-phase bending mode. The driver 180 is attached to the magnet attached to the conduit 130' and the conduit 130, and both conduits 130 , 130'. An appropriate drive signal 185 is applied by the meter electronics 20 to the relay. The voltage is applied to the driver 180 via a power line.

[0084] The meter electronics 20 receives the RTD temperature signal on lead 195 and the left and right sensor signals 165l, 165r. and the sensor signal 165 appearing on the lead 100 carrying the meter electronics 20. generates a drive signal 185 that appears on the leads to the driver 180, causing the conduits 130, 130' to vibrate. Meter electronics 20 receives left and right sensor signals 165l, 165r and the RTD signal from lead 195. The data is processed to calculate the mass flow rate and density of the material passing through the sensor assembly 10. The information, along with other information, is applied by meter electronics 20 as a signal via path 26. A more detailed description of the meter electronics 20 follows below.

[0085] Figure 2 shows the sensor signal parameters provided by the sensor assembly. 10 includes a block diagram representation of meter electronics 20 configured to verify the vibration 2 shows a block diagram of the automatic meter 5. As shown in FIG. 2, the meter electronics 20 includes a sensor assembly. As previously described with reference to FIG. 2, the sensor assembly 10 , left and right pickoff sensors 170l, 170r, a driver 180, and a temperature sensor 190. is communicatively coupled to meter electronics 20 via a set of leads 100 via a communication channel 112. are combined.

[0086] Meter electronics 20 provides drive signal 185 over lead 100. More specifically, The meter electronics 20 provides a drive signal 185 to a driver 180 in the sensor assembly 10. The sensor signals 165, including the left sensor signal 165l and the right sensor signal 165r, are transmitted to the sensor assembly 1. 0. More specifically, in the illustrated embodiment, the sensor signal 165 is provided by the sensor The left and right pickoff sensors 170l, 170r in the assembly 10 provide the necessary information. Thus, the sensor signals 165 are respectively provided to the meter electronics 20 via the communication channel 112. can be.

[0087] The meter electronics 20 can communicate with one or more signal processors 220 and one or more memories 230. The processor 210 also communicates with the user interface 30. The processor 210 communicates with the host through a communication port on port 26. The processor 210 is operably coupled to a power supply 214 and receives power through a power port 250. The processor may be a microprocessor, but any suitable processor may be used. The server 210 includes a multi-core processor, a serial communication port, and a peripheral interface (e.g., Subprocessors such as serial peripheral interfaces, on-chip memory, and I / O ports In these and other embodiments, the processor 210 may comprise a digitized signal. The receiver is configured to perform operations on received and processed signals, such as a digital signal.

[0088] The processor 210 receives digitized sensor signals from one or more signal processors 220. The processor 210 can also measure the phase difference, the characteristics of the fluid within the sensor assembly 10, and The processor 210 is configured to provide information such as the characteristics of the host computer via a communication port. The processor 210 may also communicate with one or more memories 230. The device may be configured to receive and / or store information in one or more memories 230, for example. , the processor 210 may set the calibration factor and / or the sensor assembly to zero (e.g., when the flow is 0). The calibration coefficients and / or sensor phase differences may be received from one or more memories 230. Each of the sensor assemblies 10 and 50 is connected to the vibration meter 5 and / or the sensor assembly 10. The processor 210 may use the calibration coefficients to calibrate one or more signal processors. The digitized sensor signals received from the sensor 220 may be processed.

[0089] One or more signal processors 220 include an encoder / decoder (CODEC) 222 and an analog-to-digital converter (ADC). One or more signal processors 220 are shown as comprising an analog-to-digital converter (ADC) 226. conditioning the analog signal, digitizing the conditioned analog signal, and / or The CODEC 222 can provide a filtered signal to the left and right pickoff sensors 170l, 170i, 170j, 170k, 170kb, 170kc, 170kb, 170kb. 70r. The CODEC 222 is also configured to receive the drive signal 185. to driver 180. In alternative embodiments, more or less Fewer signal processors can be used.

[0090] As shown, the sensor signal 165 is provided to the CODEC 222 via a signal conditioner 240. The driving signal 185 is supplied to the driver 180 through a signal conditioner 240. The signal conditioner 240 is a single Although shown as a block, the signal conditioner 240 may include two or more operational amplifiers, a low pass filter, The signal conditioning components may include filters such as filters, voltage-to-current amplifiers, and the like. For example, the sensor signal 165 may be amplified by a first amplifier, and the drive signal 185 may be a voltage The amplification may be performed by a current amplifier to ensure that the magnitude of the sensor signal 165 is equal to the full amplitude of the CODEC 222. It may be close to the scale range.

[0091] In the illustrated embodiment, the one or more memories 230 include a read-only memory (ROM) 232, a random access memory (RAM) 234, and a Random Access Memory (RAM) 234, and Ferroelectric Random Access Memory (FRAM However, in alternative embodiments, one or more memories 230 may be more Additionally or alternatively, one or more The memory 230 may be comprised of different types of memory (e.g., volatile, non-volatile, etc.). For example, erasable programmable read-only memory (EPROM) A different type of non-volatile memory may be employed in place of FRAM 236. The library 230 records process data such as drive or sensor signals, mass flow or density measurements, etc. The storage device may be configured to store the information.

[0092] Mass flow measurements can be generated according to the following equation:

number

number

[0093] The measured time delay Δt is, for example, a time delay related to the mass flow rate through the vibratory meter 5. Includes the time delay that exists between pickoff sensor signals if it is due to the Coriolis effect. Includes time delay values ​​derived (i.e., measured) by operation including the The extension Δt is a direct measure of the mass flow rate of the flowing material as it flows through the vibratory meter 5. The quantity time delay Δt0 includes the time delay at zero flow rate. The zero flow rate time delay Δt0 is set at the factory. is the zero flow value that can be determined and programmed into the vibratory meter 5. Zero flow time delay Δt 0 is an exemplary zero flow value. Other parameters such as phase difference, time difference, etc., determined at the zero flow condition A zero flow value may be used. The value of the zero flow time delay Δt0 is determined by the time when the flow conditions are changing. The mass flow rate of a substance flowing through the vibratory meter 5 may not change even if the The difference between the calculated time delay Δt and the reference zero flow value Δt0 is multiplied by the flow calibration factor FCF. The flow calibration factor FCF is proportional to the physical stiffness of the vibratory meter.

[0094] With respect to density, the resonant frequency at which each conduit 130, 130' can vibrate depends on the spring constant of the conduit 130, 130'. The mass of the conduit 130, 130' containing the material may be a function of the square root of the number divided by the total mass of the conduit 130, 130' containing the material. The total mass of the conduits 130, 130' is the mass of the conduits 130, 130' plus the mass of the material in the conduits 130, 130'. The mass of the material in the conduits 130, 130' is directly proportional to the density of the material. The density of this material varies as a function of the square of the period of vibration of the conduit 130, 130' containing the material. Therefore, the period during which the conduits 130, 130' vibrate can be determined by multiplying the spring constant of the conduits 130, 130'. and appropriately scaling the results to determine the material contained in the conduits 130, 130'. The meter electronics 20 can obtain an accurate measurement of the density of the sensor signal 165 and / or Alternatively, the drive signal 185 can be used to determine the period or resonant frequency. ' can vibrate in more than one vibration mode, as explained in more detail below. The meter electronics 20 may also perform verification of the sensor assembly.

[0095] FIG. 3 illustrates the use of parameters of the sensor signal 100 provided by the sensor assembly 10. Meter electronics 20 is shown configured to verify sensor assembly 10. As shown in FIG. As such, meter electronics 20 includes an interface 301 and a processing system 302. The device 20 receives a vibration response from a sensor assembly, such as the sensor assembly 10 described above. The meter electronics 20 processes the vibration response to determine the flow rate through the sensor assembly 10. The meter electronics 20 also provides the flow characteristics of the flow material. Perform checks, verifications, calibration routines, etc. to ensure accurate measurements. It is possible.

[0096] The interface 301 receives a signal from one of the pickoff sensors 170l, 170r shown in FIGS. The interface 301 can also receive the sensor signal 165, e.g., the signal conditioner 24 0. The drive signal 185 is sent to the signal conditioner 240. Although shown as being supplied by vibration of the conduit 130 within the sensor assembly 10, As a result, back EMF may be supplied from the sensor assembly 10 to the meter electronics 20. Therefore, the interface 301 may be configured to receive the sensor signal 100 shown in FIG. can be done.

[0097] The interface 301 can be used for any type of formatting, amplification, buffering, etc. Alternatively, some or all of the signal conditioning may be performed. can be executed by the processing system 302. Furthermore, the interface 301 can The interface 301 may be any suitable interface. The interface 301 may be capable of electronic, optical, or wireless communication in any manner. The interface 301 can provide information based on the answer. and the sensor signal includes an analog sensor signal. The digitizer samples and digitizes the analog sensor signal. A signal is generated.

[0098] The processing system 302 performs the operations of the meter electronics 20 and processes the flow from the sensor assembly 10. The processing system 302 executes one or more processing routines to The processing system 302 processes the flow measurements to generate one or more flow characteristics. communicatively coupled to interface 301 and configured to receive information from interface 301. It is done.

[0099] The processing system 302 may be a general-purpose computer, a microprocessing system, a logic circuit, or or any other general purpose or customized processing device. Additionally or alternatively, the processing system 302 may be distributed across multiple processing devices. The processing system 302 may be integrated or stand-alone in any manner, such as with a storage system 304. It may also include electronic storage media.

[0100] The storage system 304 stores the vibratory meter parameters and data, software routines, constants, and In one embodiment, the storage system 304 can store numerical values ​​and variable values. 3. The processing system 302 includes routines executed by the processing system 302, such as routine 310. 302 executes other routines such as a zero calibration routine and a zero verification routine for the vibration meter 5. The storage system may further be configured to perform the following: It is also possible to store statistical values ​​such as intervals.

[0101] The operating routine 310 calculates the mass based on the sensor signals received by the interface 301. A mass flow value 312 and a density value 314 can be determined. The mass flow value 312 is frequency independent. The mass flow value 312 may be a measured mass flow value, a directly measured mass flow value, etc. The time delay between the right pickoff sensor signal and the left pickoff sensor signal is determined from the sensor signals. The density value 314 can also be determined, for example, by determining whether one or both of the left and right pickoff sensor signals are present. may be determined from the sensor signal by determining the frequency from both.

[0102] As previously mentioned, a sensor assembly such as the sensor assembly 10 described with reference to FIGS. The assembly determines the conduit parameters such as stiffness, mass, damping, and residual flexibility of the sensor assembly. and comparing the calculated conduit parameter values ​​to the baseline conduit parameter values. However, such calculations are difficult to perform in real time. This can make it difficult to calculate pipeline parameter values ​​and can result in disruption to the customer's process. Some calculations, such as the gain attenuation method, can be used to calculate the system noise and This allows the sensor assembly verification routine to be run in a timely manner and can be sensitive to changes in process conditions. Low or no flow conditions or insufficient flow for calculation of conduit parameter values. As explained in more detail below, these and other and other problems using the parameters of the sensor signals provided by the sensor assembly. This can be avoided by validating the sensor assembly.

[0103] Still referring to FIG. 3, the storage system 304 may include sensor signal parameter values ​​320. As shown in FIG. 3, the sensor signal parameter values ​​320 may include, for example, drive voltage values ​​322, LPO The drive voltage value 322, the LPO voltage value 324, and the RPO voltage value 326. and / or the RPO voltage value 326 may be reset, for example, during a customer process, during calibration using a known fluid, etc. Therefore, the drive voltage value 322, the LPO voltage value 324, and and / or RPO voltage value 326 is used to calculate mass flow value 312 and / or density value 314. As can be appreciated, the drive voltage values 322, LPO voltage value 324, and / or RPO voltage value 326 are measured, determined, obtained, and / or recorded substantially simultaneously. and / or can be calculated.

[0104] The sensor signal parameter values ​​320 are used to generate one or more current can be used to calculate the sensor assembly validation value 330. The electronics 20, or more specifically the processing system 302, receives the drive voltage value 322 of the sensor signal, LPO configured to determine a sensor signal parameter value, such as a voltage value 324 and / or an RPO voltage value 326. The sensor signal parameter may be the amplitude of the sensor signal, but may also be any Any suitable sensor signal parameters may be used. As can be appreciated, the amplitude of the sensor signal The amplitude may be voltage, current or power, although any suitable amplitude may be used. The meter electronics 20 or processing system 302 also calculates the sensor signal from the sensor signal parameter values. The meter electronics 20, or more specifically, the Specifically, the processing system 302 processes the sensor signal parameter relationship values ​​into the current sensor assembly validation. The value 330 may be configured to be stored in the storage system 304 .

[0105] As shown in FIG. 3, the current sensor assembly validation value 330 is calculated based on the current LPO / RPO voltage ratio value 332. , the current DRV / LPO voltage ratio value 334, and the current DRV / RPO voltage ratio value 336. more or fewer current sensor assembly validation values ​​330, including data-related values, The illustrated meter electronics 20 or alternative meter electronics measure, determine, obtain, calculate, and As can be appreciated, the current LPO / RPO voltage ratio value 332, the current D The RV / LPO voltage ratio value 334 and the current DRV / RPO voltage ratio value 336 are sensor signal electrical parameters. For example, alternative meter electronics may provide the current LPO / RPO voltage ratio value 332 as Use a profile that is not similar to the calibration state from which the baseline sensor assembly validation value is calculated. It is possible to reliably detect a significant number, e.g., most, of the changes to the conduit under process conditions. Therefore, pickoff sensor signal related values ​​such as the current LPO / RPO voltage ratio value 332 can be measured and determined. It may be configured to only acquire, calculate, and / or store.

[0106] As an example, the baseline LPO / RPO voltage ratio value is calculated during calibration of the FCF of a given vibration meter. After the vibration meter is installed at the customer site, the Therefore, customers must ensure that the vibration meter is in a state where the baseline LPO / RPO voltage ratio value is calculated. While measuring the mass flow rate and / or density of the process fluid under different process conditions, A sensor assembly verification routine can be performed.

[0107] The gain decay method for calculating the stiffness value of the conduit is as follows:

number

[0108] As mentioned above, stiffness measurement can be difficult to achieve in real time, and customers may need to It requires calculations that may require the process to be interrupted. To determine the appropriate stiffness ratio, the following can be used: do.

number

[0109] As can be seen, some terms in equation [4] cancel out. More specifically, the drive current and The tube frequency terms cancel. Pickoff and driver sensitivity terms BL PO , B.L. DR are assumed to be the same This may be determined in advance or compensated for later, resulting in the following relationship:

number

[0110] Equation [5] is the ratio of the voltages of the left and right pickoff signals, V LPO / V RPO is the inverse of the ratio of stiffness to damping (ζ R / ζ L )K R / K L Therefore, the left and right pipe damping or the left and right pipe stiffness A change in either of these will result in a change that is detected by taking the ratio of the pickoff voltages As mentioned above, the sensor signal parameters can be the amplitude of the sensor signal, Therefore, equation [5] can be expressed as, for example, the amplitude of the sensor signal (e.g., voltage, current, power etc.), i.e., A LPO / A RPOcan be generalized to

[0111] As can be seen, the voltages of the left and right pickoff sensor signals are determined by the parameters of the sensor signals. and therefore are needed to calculate conduit parameter values ​​such as the stiffness of the conduit Furthermore, the above equation [5] does not require the same calculations as the previous one to detect stiffness changes. This shows that the ratio of the voltages of the left and right pickoff sensor signals can be used to detect The change may be limited to an asymmetric change in the left-right stiffness of the conduit. More specifically, the change in the conduit If a proportional change in left-right stiffness occurs, the voltage ratio may not detect the change. .

[0112] Whether the voltage of the left sensor signal or the voltage of the right sensor signal has changed relative to the baseline value Symmetrical changes to the duct can be detected by determining whether the left The ratio of the voltage of the pick-off sensor signal to the drive signal, and the voltage of the right pick-off sensor signal to the drive signal The ratio of the voltage of the dynamic signal to the respective baseline values ​​can be compared. Therefore, such a comparison is necessary to ensure that the condition of the sensor assembly is the same as when the baseline value is determined. Therefore, the parameters of the sensor signal may be used to determine the amplitude. Customer processes must be interrupted to detect symmetrical changes in the conduit of a dynamic meter. However, the calculations required for stiffness values ​​can be avoided.

[0113] Still referring to FIG. 3, the storage system may include a baseline sensor assembly validation value 340. The baseline sensor assembly validation value 340 can be calculated by calculating the baseline sensor signal. For example, as shown in FIG. The assembly verification value 340 is the baseline LPO / RPO voltage ratio value 342, the baseline DRV / LPO voltage baseline sensor signal parameters such as ratio value 344, and baseline DRV / RPO voltage ratio value 346 The "DRV" term is the value of the voltage of the drive signal supplied to the driver. may be the same as the drive voltage value 322, but may be any suitable sensor signal parameter. Similarly, the terms "LPO" and "RPO" refer to the left and right pickoffs, respectively. voltage value, which may be the same as the LPO and RPO voltage values ​​324, 326, but may be any Any suitable sensor signal parameters may be employed.

[0114] The baseline sensor assembly verification value 340 may be calculated during factory calibration, customer calibration, or after or by any other suitable routine that establishes a reference value against which values ​​can be compared. The baseline sensor assembly validation value 340 can be calculated by The flow calibration value used in the flow measurement (e.g., operational FCF) determined simultaneously with the flow verification value 340. Therefore, the operating FCF and the baseline sensor assembly Changing one or more conduits after the revalidation value 340 is determined may result in an inaccurate measurement. There is a gender.

[0115] Using the LPO / RPO voltage ratio value, such as the current LPO / RPO voltage ratio value 332 described above with reference to FIG. , the sensor assembly can detect changes in the conduit. The verification value shift can be used to detect changes in the conduit of the sensor assembly. For example, a ratio shift, such as a voltage ratio shift, occurs when the current LPO / RPO voltage ratio value 332 is changed from the baseline LPO / RP The ratio shift may be defined as the difference between the baseline LPO / RPO voltage ratio value 342. It can be expressed as a percentage of the voltage ratio value 342.

[0116] As can be appreciated, a viable sensor assembly verification is performed to ensure that no changes have occurred to the conduit. It should be possible to understand that one or more ducts may not have undergone any changes. So, this is where verification of the sensor assembly can be performed during process flow conditions. This should be true at different flow rates. The table below shows the voltage ratio shift across the entire flow range. More specifically, each flowmeter type has a zero-flow The LPO / RPO voltage ratio value at no flow and maximum flow conditions were measured for each type of flow meter. The percentage shift between the LPO / RPO voltage ratio values ​​at maximum flow conditions was calculated. The results are tabulated. The results are shown in Table 1 below.

[0117] [Table 1]

[0118] As can be appreciated, the percentage value of the voltage ratio shift will be greater if a change occurs in one or more conduits. Very small across a variety of flowmeter types exposed to unmodified no-flow and maximum-flow conditions This means that the change in the LPO / RPO voltage ratio is likely not due to a difference in flow rate. Therefore, the LPO / RPO voltage ratio is a reliable indicator of the condition of one or more conduits. For example, the change in the LPO / RPO voltage ratio relative to the baseline LPO / RPO voltage ratio can be The change is unlikely to be due to a change in the flow rate of material flowing through one or more conduits.

[0119] A reliable indication of a change in one or more conduits of the sensor assembly also provides a function of one or more conduits. It may be necessary to correlate with mechanical properties. For example, changes in one or more conduits may cause LPO / RPO The LPO / RPO voltage ratio is the ratio of one or more conduits to the stiffness when the voltage ratio has a rate of change equal to the rate of change of stiffness. The table below shows the effect of changes in one or more conduits on each type of membrane. The ratio shift may be caused by the etching agent in one or more conduits of the This indicates that it is present in various types of meters.

[0120] [Table 2]

[0121] As can be seen, a shift in the LPO / RPO voltage ratio is equivalent to a shift in the LPO / RPO stiffness ratio. As can also be appreciated, the shift may be determined by a meter electronic attached to the sensor assembly. Similar results were obtained with different sensor assemblies, as shown in Table 3 below. can be done.

[0122] [Table 3]

[0123] Therefore, the LPO / RPO voltage ratio value of the sensor signal provided by the sensor assembly, etc. The parameter can detect changes in one or more conduits of the sensor assembly. As can be seen, the sensor signal from the sensor assembly may be based on current, power, resistance, etc. Other parameters can be used, including the sensor signal. Other parameter relationships can be used, such as the difference between the parameters of the driving signal. Parameters of signals other than the sensor signal, such as the voltage of the signal, may also be used. The data is not calculated and the sensor assembly is unable to consistently detect changes in one or more conduits. can.

[0124] Figure 4 shows the correspondence between the stiffness of the sensor assembly and the difference between the sensor signal parameters. As shown in FIG. 4, the graph 400 includes a corrosion path axis 410, a pickoff voltage dimension 420, and a The corrosion path axis 410 is unitless and includes the pickoff The voltage delta axis 420 is in units of volts and the stiffness delta axis 430 is in units of newton meters per radian. Although the units are in units of amperes, any suitable units may be used. 4 includes a sensor assembly validation value delta plot 440. The delta plot 440 includes a stiffness delta plot 442 and a pickoff delta plot 444 .

[0125] As can be seen, the stiffness delta plot 442 and the pickoff delta plot 444 are It is approximately linear with respect to the eclipse path axis 410. Also, as can be seen, the stiffness delta plot 4 42 and pickoff delta plot 444 are roughly equivalent, albeit with different abscissa scaling. Therefore, there is a linear relationship between the pickoff voltage delta and the stiffness delta. A relationship can exist where the pickoff voltage delta causes a stiffness shift This suggests that the sensor assembly may be able to reliably detect changes within the conduit. is doing.

[0126] As previously described with reference to FIG. 3, a current sensor assembly validation value 330, such as one of The current sensor assembly validation value and one of 340 baseline sensor assembly validation values Using one or more comparisons between the baseline sensor assembly validation values, such as those described above Changes in a sensor assembly, such as the sensor assembly 10, can be detected and identified. For example, the sensor assembly validation value can be based on a sensor signal parameter. As such, the sensor assembly validation value is the LPO / RPO voltage ratio, the DRV / LPO voltage ratio, or the DRV / RPO voltage ratio. It may be a pressure ratio, but any suitable sensor signal parameter ratio may be used. Additionally or alternatively, differences between sensor signal parameters can be used. For example, the current sensor assembly verification value 330 and the baseline sensor assembly verification value 330 The value 340 may be based on sensor signal parameters such as the LPO voltage, the RPO voltage, and / or the DRV voltage. This can be done.

[0127] As explained above, the sensor assembly validation value shift is used to More specifically, the foregoing description is directed to sensors that can detect and identify changes in the sensor assembly. It explains that changes in the sensor signal parameters correlate with changes in the stiffness of the sensor assembly. Therefore, sensor assembly validation values ​​based on sensor signal parameters are used to verify the sensor. Changes in the subassembly can be detected and identified.

[0128] The correlation between the stiffness of the sensor assembly may also be location specific. For example, DRV / LPO The voltage ratio is relative to the stiffness of the conduit between the left pickoff sensor location and the driver location on the conduit. The stiffness of the conduit between the left pickoff location and the driver location can be related to the LPO stiffness. Therefore, under similar or the same process conditions, the LPO stiffness is As the conduit decreases over time for a given drive current, it becomes larger at the left pickoff sensor location. This larger LPO displacement can be called the LPO displacement. Displacement can induce higher LPO voltage values. As a result, the DRV / L The PO voltage ratio may decrease. A similar correlation exists between the DRV / RPO voltage ratio and RPO stiffness. There can be.

[0129] As previously mentioned, asymmetric changes in the conduit cause asymmetric changes in the LPO and RPO voltages. Similar asymmetric changes can occur in other sensor signal parameters such as power and current. Asymmetric changes in the LPO and RPO voltages can occur due to the current LPO / RPO voltage ratio value 332 and the base This can be quantified by using the baseline LPO / RPO voltage ratio value 342. For example, the current LPO / RPO voltage ratio value 332 may be compared to a baseline LPO / RPO voltage ratio value 342. (e.g., subtraction, division, etc.).

[0130] Symmetrical changes in the sensor assembly conduit are used to baseline the current sensor assembly validation values. This can be detected by comparing the sensor assembly verification value. The current DRV / LPO voltage ratio value 334 can be compared to a baseline DRV / LPO voltage ratio value 344. Additionally or alternatively, a 2DRV / (LPO*RPO) voltage ratio may also be used to determine the symmetrical distribution of the conduit. A change can be detected because a symmetric decrease in the stiffness of the conduit causes the left pickoff sensor This is because it can cause larger displacements on both the right and left pickoff sensors. However, to detect symmetrical changes in the conduit, one of the drive signal or sensor signal The above ratios, using only the above, assume that the process conditions are the same as when the baseline ratio values ​​were determined. Additionally or alternatively, the calculated stiffness value of the conduit may be used. This ensures that the conditions are the same as when the baseline stiffness value was calculated. These and other current sensor assembly validation values ​​may not require can be used separately to detect symmetric and asymmetric changes and It can even distinguish between the underlying conditions that cause changes in sensor signal parameters. It is not possible to identify it.

[0131] A shift or change in the sensor assembly verification value may occur if a change occurs within the conduit of the sensor assembly. The current and baseline sensor assembly validation values ​​indicate that This shift or change in the sensor assembly validation value can be defined as a comparison between may be specified as "low" or "decreasing," "high" or "increasing," or "null" or "static," etc. Additionally or alternatively, quantitative values ​​may be used. Using a combination of sensor assembly validation value shifts or changes, the underlying condition of the conduit can be determined. It can be identified.

[0132] For example, as previously mentioned, a "low" DRV / LPO voltage ratio shift is This may indicate a decrease in the physical stiffness of the conduits 130, 130' between the off-sensor 170l. A "high" DRV / RPO voltage ratio shift is caused by the conduction between the driver 180 and the right pickoff sensor 170l. It can be seen that the physical stiffness of the tubes 130, 130' has increased. The combination of the "high" DRV / RPO voltage ratio shift and the corrosion of the conduit adjacent to the entrance of the conduit. and certain conditions, such as processes that cause coating of the conduit adjacent to the outlet of the conduit. It can be correlated.

[0133] The processing system 302 further processes these values ​​to determine the position of the driver 180 and the left pickoff sensor 17. Produces a toggle indicator that indicates only an increase or decrease in the physical stiffness of the conduit 130, 130' between 0 and 1. These values ​​and / or toggle indicators can be set as shown in the following truth table: , can be utilized to determine fundamental changes in the conduits 130, 130'.

[0134] [Table 4]

[0135] As can be seen from the figure, the combination of LPO / RPO voltage ratio, LPO stiffness change, and RPO stiffness change can be used to distinguish between different possible variations of the conduits 130, 130'. For example, Both J and N have an LPO / RPO voltage ratio that is "bottom right" and an RPO stiffness change that is "low." However, the LPO stiffness change in Case J is "low" and the LPO stiffness change in Case N is "high." Case J is shown as possible erosion / corrosion of the conduits 130, 130', and Case N is shown as possible erosion / corrosion of the conduits 130, 130'. 130, 130' are shown as possible coatings.

[0136] The above table uses the LPO stiffness change, RPO stiffness change, and It utilizes the LPO / RPO voltage ratio, but the table of alternatives, logic, object, relationship, circuit, processor, rule The conditions within the conduit can be determined using any suitable means, such as a flowmeter. For example, the condition of the conduits 130, 130' can be determined using only the LPO stiffness change and the RPO stiffness change. However, as can be seen, by utilizing the LPO / RPO voltage ratio, A more specific determination of the condition of the conduits 130, 130' may be possible.

[0137] Additionally or alternatively, instead of a toggle indicator, LPO stiffness change, RPO stiffness change, and / or Alternatively, the actual value of the LPO / RPO voltage ratio can be used to determine the condition of the conduit, e.g. ,The state determined by the above table is, for example, "Right Low" when the LPO / RPO voltage ratio is relatively small. If so, further steps are taken to determine that Case J is more likely to be corrosion than erosion. That is, a relatively small "right low" LPO / RPO voltage ratio can be This may be due to the more uniform nature of the corrosion compared to erosion which may be more prevalent at the entrance. do.

[0138] Statistical methods that calculate the probability of an outcome can be used to detect changes in vibration meters. However, due to their complexity, they could not be performed by the meter electronics 20. For example, P and T statistics can be used to determine whether the null hypothesis is met for a given data set. Rejecting the null hypothesis means that the vibration meter has a state. It does not determine whether the sensor is present or not, but the absence of the state is false. In the case of assembly validation, the null hypothesis is that the current sensor assembly validation results are This null hypothesis can be defined as "the sensor assembly validation results have the same mean." If not proven, the average of the current sensor assembly verification results due to changes in the vibration meter It can be assumed that σ is not the same as the baseline sensor assembly validation result.

[0139] As an example, in a t-test, the t-value can be calculated using the following formula:

number

number

[0140] In the context of sensor assembly validation, μ0 is used to calculate a baseline measurement, such as the baseline LPO / RPO voltage ratio value. The sensor assembly validation measurements are the baseline sensor assembly validation values. Sample averages for comparison with sensor assembly validation values

number

[0141] As mentioned earlier, a t-test can be used to test the null hypothesis, which is that the For assembly validation, sample average

number

[0142] However, it is difficult to calculate the P value with limited computing resources. For example, P The values ​​are calculated using a computer workstation equipped with an operating system and statistical software. It can be calculated on a computer, but it is not easily calculated on an embedded system. The meter electronics 20 described above may be embedded with limited computing resources. Furthermore, the null hypothesis may be calculated in real time on the meter electronics. The ability to dismiss the alarm can prevent the meter electronics 20 from sending false alarms. At the same time, changes in the conduits 130, 130' can be accurately detected using predetermined alarm limits. This is a significant improvement over using

[0143] To this end, the limited computing resources of the meter electronics 20 are utilized. The confidence intervals are used instead of the P-values. As a result, the confidence intervals are For example, the meter electronics 20 can calculate The current sensor assembly validation value and the standard deviation of the current sensor assembly validation value are calculated using two As can be seen, the above t-values ​​can be calculated using the significance level α and By using the degrees of freedom, the current sensor assembly validation values ​​can be used to calculate As an example, the significance level α may be set to 0.01, which is a 99% confidence level. The number of times for some sensor assembly verification tests can be set to 5. Therefore, the pooled degrees of freedom are determined to be 2·(5-1)=8. The two-tailed Student's t-value is , the significance level α and the pooled degrees of freedom are used to calculate the Student t-value function as follows: can be calculated as follows.

number

[0144] Pooled sensor assembly validation values ​​associated with left and right pickoff sensors 170l and 170r Standard deviation can also be used. In the general case, calculating the pooled standard deviation is complicated. However, it is possible that the meter electronics 20 will register the standard deviation of the sensor assembly validation values. Due to the storage of data in the database, the pooled standard deviation is simply the stored standard deviation. A pooled standard error can also be calculated, which is defined as will be done.

number

[0145] The confidence interval range can be calculated using the standard error and t-value determined above as follows: This can be done. CI range =stderror pooled ·t student,99.8 ;[9] CI range =stderror pooled 3.36 Finally, the confidence interval is calculated using the mean and confidence interval range of the sensor assembly validation measurements. This can be calculated as shown in the following formula: CI=SV mean ±CI range ;

[10]

[0146] Confidence intervals test the null hypothesis by determining whether the confidence interval contains 0.0. If the confidence interval includes 0.0, the null hypothesis is not rejected and the If the confidence interval does not include 0.0, the null hypothesis is rejected. A sensor assembly verification failure may be transmitted.

[0147] The meter electronics 20 measures the sensor assembly validation value and the standard deviation of the sensor assembly validation value. By using confidence intervals instead of storing P values, the calculation is relatively simple and This can be done using embedded code. For example, if you have enough data to calculate a P value, Meter electronics 20, which may not have computing resources, may provide on-the-fly or real-time Confidence intervals can be calculated to perform statistical analysis. , the confidence interval can be used to test the null hypothesis at a desired confidence level.

[0148] In addition to the confidence interval, to account for bias in the sensor assembly validation value measurements, A bias deadband can be defined around 0. Assume that the vibration meter mounting, density, etc. may affect the sensor assembly validation measurements. , temperature gradients, or other conditions. This bias deadband in the t-test is value, otherwise small with small variations that would cause the confidence interval check to reject the hypothesis. The bias does not reject the hypothesis. Therefore, this bias deadband is This can be set to a value that reduces the number of false alarms sent by

[0149] In the example of a confidence interval compared to 0, the bias deadband is the range around 0, where 0 is the confidence interval If the confidence interval is not within the bias dead zone, but part of the bias dead zone is within the confidence interval, then the null hypothesis is not rejected. Mathematically, this test is sometimes called the sensor assembly validation average. This can be expressed as whether the average value of the pre-verification measurements is less than the bias deadband. Or, using the nomenclature discussed above, i.e.

number

[0150] Bias deadbands can be implemented alone or in combination with other deadbands. For example, a bias deadband can be implemented in conjunction with a variable deadband. vari ation =db bias / t student,99. The fluctuation dead band can be determined from variatio n is the fluctuation deadband. The fluctuation deadband is compared to the standard deviation of the sensor assembly validation values ​​to determine the resulting It can be determined whether the null hypothesis should be rejected. In one example, the bias deadband is and the fluctuation deadband may be compared to the standard deviation as follows: That is,

number

number

number

[0151] The preferred method for testing the null hypothesis is a two-confidence test that does not rely on the pooled standard deviation. The standard deviation of the baseline measurements can be used to validate the sensor assembly. If the standard deviation of the measurements cannot be assumed to be the same, two confidence intervals should be used. It may be preferable to use a first confidence interval (e.g., a baseline confidence interval) A second confidence interval (e.g., a measurement) may consist of a baseline mean and a baseline standard deviation. or meter validation confidence interval) is the measurement mean and The standard deviation of the measurements can be calculated.

[0152] In this example, the first confidence interval was an exemplary baseline sensor assembly validation value. Although any suitable value, including a probability value, may be the baseline sensor assembly validation value. The second confidence interval may be determined from the measured mean and the measured standard deviation. It can be a probability; that is, as explained below, the measurement mean can be a central tendency value. Instead, the measurement standard deviation is calculated by comparing the probability to the baseline sensor assembly validation value. and a distributed ion beam used to validate a sensor assembly, such as the sensor assembly 10 described above. It may be a value.

[0153] For two overlapping confidence intervals, if the first and second confidence intervals overlap, the change (e.g. If the two are identical, the difference (no damage) may not be detected. Otherwise, the difference is detected. The overlap of the confidence intervals can be determined using any suitable method. For example, The overlap of the confidence intervals is the difference between the measured mean and the baseline mean, and the difference between the measured mean and the baseline mean. It can be determined by comparing the difference between the standard deviation value and the baseline standard deviation value. Comparisons simply involve terms called the computed left-hand side (LHS) value and the computed right-hand side (RHS) value. The LHS value is less than the RHS value, although any suitable term can be used. If so, then there is an overlap and damage can be detected accordingly; otherwise, there is no overlap. Therefore, damage may go undetected. The following equations

[11] -

[13] are used to Here is an example: LHS=|μ measured -μ baseline |;

[11] RHS=2*(σ measured -σ baseline ); and

[12] LHS <RHS

[13] where: μ measured is the mean value (i.e., the exemplary central tendency) of the measurements of the sensor assembly validation value), and μ baseline is the average of the baseline values ​​performed for subsequent sensor assembly validation values ​​(i.e., exemplary central tendency values), σ measured is the standard deviation value (i.e., the exemplary variance) of the measurements of the sensor assembly validation value), and σ baseline is the standard measured baseline value for subsequent sensor assembly verification. is the deviation value (i.e., an exemplary dispersion value).

[0154] A factor of 2 was used in calculating the RHS value to allow for a 95% probability in both confidence intervals. Other values ​​may be used. As can be appreciated, the sensor assembly verification measurements The mean of the baseline values ​​and the baseline values ​​can be determined by any suitable method. In equation

[14] , the standard deviation of the baseline value is the average value of the baseline value multiplied by the dead band value. is determined by multiplying σ baseline =dead band*μ baseline

[14]

[0155] However, once calculated, when confidence interval checks are performed, the null hypothesis is may not be rejected due to bias in the subassembly validation measurements.

[0156] FIG. 5 illustrates a sensor, such as the sensor assembly 10 described above, for verifying the sensor assembly. 5 illustrates a method 500 for using parameters of a sensor signal of an assembly. 500 calculates a sensor signal parameter relationship value between two sensor signals in step 510. The sensor signal in step 510 is the sensor signal 100 described above with reference to FIGS. In step 520, the sensor signal may be a signal from the sensor, but any suitable sensor signal may be used. The method 500 calculates a calculated sensor signal parameter relationship value between two sensor signals. The comparison is performed using the process described above. This may be performed by system 302, although any suitable processor or processing system may be used. may be used.

[0157] In step 510, a sensor signal parameter relationship value between two sensor signals is calculated. The difference between the left pick-off sensor signal voltage value and the right pick-off sensor signal voltage value is the sensor signal voltage. The method may further include calculating a signal parameter relationship between the two sensor signals. Calculating the sensor signal parameter relationship value is a method of calculating the two sensor signal parameters of the two sensor signals. For example, the method may include calculating one of a ratio and a difference between sensor signal parameters. The meter relationship can include the above equation [5], but the left pickoff sensor signal voltage and the right The difference between the pickoff and sensor signal voltages can be used. The signal parameter relationship is the left pickoff when the right pickoff sensor signal voltage is in the numerator. It may be the ratio between the sensor signal voltage and the right pickoff sensor signal voltage.

[0158] Additionally or alternatively, the calculated sensor signal parameter relationship values ​​may be compared with the baseline sensor signal. Comparing the calculated sensor signal parameter relationship value with the base The method may include calculating a difference between the line sensor signal parameter relationship value. For example, if the sensor signal parameter relationship is greater than equation [5], the comparison may be performed using, for example, the following The sensor signal parameter relationship may be between:

number

number

number

number

[0159] The above sensor signal parameter relationship value delta

number

number

[0160] As mentioned above, the two sensor signals are the drive signal, the left pickoff sensor signal, and the right pickoff sensor signal. For example, in equation [5] above, The two sensor signals are left and right pickoff sensor signals, and the sensor signal parameters are left and right The voltage of the pickoff sensor signal. Alternatively, for example, the two sensor signals are the drive signal and , or one of the left and right sensor signals. However, as mentioned above, the ratio of the drive signal Using the ratio of the voltage to the left pickoff sensor signal voltage, the customer's process is completed and the conditions used to calculate the sensor signal parameter relationship values ​​are The sensor signal parameters must be the same as the state used to obtain the related values. You may need to get.

[0161] The method 500 includes calculating the electrical parameter relationship and determining a baseline between two or more sensor signals. determining the status of the sensor assembly based on a comparison with the relevant electrical parameter values; For example, a non-zero sensor signal parameter between the left and right sensor signals may be The meter value delta can indicate that an asymmetric change has occurred. This may be due to uniform etching, erosion, etc. As can be appreciated, the sensor signal parameters If the relationship delta is 0 or within the acceptable range, conclude that there is no change or that a symmetric change has occurred. Thus, the method 500 may, for example, terminate a customer process and The sensor signal parameter relationship between the signal and the left or right pickoff sensor signal is the baseline Determine whether a symmetric change has occurred by determining whether a change has occurred relative to Additionally or alternatively, method 500 can further include To further determine the state of the tube, values ​​based on conduit parameters such as stiffness, damping, etc. were varied. It can further be determined that:

[0162] As previously mentioned, two or more comparisons between sensor assembly validation values ​​can be used. Additionally, sensor assembly validation value changes can also be employed. For example, As shown, the sensor assembly verification shift combination is used to verify the conduit in the sensor assembly. The following conditions can be detected and identified:

[0163] Figure 6 shows the sensor signal parameters provided by the sensor assembly. 6 illustrates a method 600 for verifying a subassembly. As shown in FIG. 6, the method 600 begins at step 610. In step 620, method 600 determines a current first sensor assembly validation value. compares the current first sensor assembly verification value with the first baseline sensor assembly verification value The method 600 also includes step 630. and comparing the current second sensor assembly verification value with a second baseline sensor assembly verification value. and comparing the first sensor assembly verification shift to the first sensor assembly verification shift. 600 is derived based on the first sensor assembly verification shift and the second sensor assembly verification shift. Determine the state of the tube. At least one of the validation values ​​comprises a sensor signal parameter relationship value. , may be executed on meter electronics, such as meter electronics 20 described above. may also include additional steps and / or various substeps.

[0164] For example, the first sensor assembly verification shift is the conduit between the driver and the left pickoff. The second sensor assembly verification shift can represent a change in the physical stiffness of the driver and This represents the change in the physical stiffness of the conduit between the driver and the driver's right pickoff. The change in the physical stiffness of the conduit between the driver and the left pickoff sensor correlates with the DRV / LPO voltage ratio value. can be calculated (e.g., a linear relationship) and the physical stiffness of the conduit between the driver and the right pickoff can be correlated (eg, linearly related) with the DRV / LPO voltage ratio value.

[0165] The sensor signal parameter relation value is one of the ratio and difference of two sensor signal parameter values. Additionally, the conduit sensor signal parameter relationship may be determined based on the left pickoff sensor signal parameter. Based on two of the following parameters: meter, right pickoff sensor signal parameter, and drive signal parameter. For example, the DRV / LPO voltage ratio value and / or the DRV / LPO voltage ratio value may be used. However, the difference between the DRV / LPO voltage difference value and the DRV / RPO voltage difference value can be The value of the ratio does not depend on the common factor of the numerator and denominator. It is possible, but the common factor can effectively scale the difference value, so the ratio is It can be advantageous.

[0166] The method 600 may also provide an alert based on the determination of the condition of the conduit. The meter electronics 20 described above can send messages via the port 26 described above. Additionally or alternatively, the method 600 may include a user interface connected to the meter electronics. A message can be displayed on the face. As mentioned above, the state of the conduit is determined by the vibration The damage includes at least one of erosion, corrosion, damage, and coating of the meter conduit. As can be seen from the foregoing description, the state is determined by the current sensor assembly validation value and the base and a sensor assembly validation determined based on a comparison between the line sensor assembly validation value and the line sensor assembly validation value. The shifts can be detected and identified by using a combination of shifts. As indicated, this may be any suitable comparison, including a statistical comparison, and may be combined with other comparisons. A combination of methods may or may not be used, and statistical methods may or may not be used.

[0167] Figure 7 shows the sensor signal parameters provided by the sensor assembly. 7 illustrates a method 700 for verifying a subassembly. As shown in FIG. 7, the method 700 begins at step 710. The method 700 obtains the central tendency and variance values ​​from the storage system. 0. Thus, the aforementioned processing system 302 The processing system, such as the one shown in FIG. 1, may acquire central tendency values ​​from a storage system, such as the storage system 304 described above. In step 720, the method 700 calculates the central tendency and the variance based on the central tendency and the variance. Based on this, a probability is determined to detect whether the central tendency value differs from the baseline value.

[0168] In the method 700, the sensor assembly validation value may be based on the sensor signal parameter value. For example, the sensor assembly verification values ​​are the LPO / RPO voltage ratio and DRV / LPO voltage ratio values ​​mentioned above. The sensor signal parameter value may be one of the following: a value of the previous The sensor signal may be from a sensor assembly such as the sensor assembly 10 described above. Therefore, the sensor assembly validation value may be used to verify the accuracy of the sensor assembly 10 or any suitable sensor. It can be used to verify the assembly.

[0169] The method 700 can also determine probabilities based on central tendency and variance values, and calculate t-values. This includes calculating the central tendency and probability using the t-value. Determining the probability based on the variance may be based on several sensor assembly validation measurements. Determining the probability based on the meter stiffness can include calculating the degrees of freedom. , which may include calculating the standard error based on the standard deviation and degrees of freedom, as previously mentioned. For example, the standard error can be calculated using the above formula [8]. A pool containing the standard deviation of the assembly validation measurements and the baseline sensor assembly validation measurements. The probability may be a confidence interval calculated using formula

[10] above. , which may be a confidence interval for the central tendency value.

[0170] As mentioned above, more than one probability can be used, e.g., a first confidence interval, etc. The first probability can be based on a baseline sensor assembly validation measurement, and the second probability can be based on a The second probability, such as the reliability interval, is based on measurements taken to validate the sensor assembly. Illustratively, the first confidence interval can be calculated by dividing the mean of the baseline sensor assembly validation values ​​by and standard deviation. For example, the baseline sensor assembly validation value The average of may be the average of the baseline sensor assembly validation measurements, The standard deviation of the in-sensor assembly validation values ​​is the standard deviation of the baseline sensor assembly validation measurements. It may also be a standard deviation value.

[0171] Therefore, the method 700 determines the confidence interval based on the central tendency value and the variance value. Therefore, the probability can be determined based on the central tendency value and the variance value. As shown, the baseline sensor assembly validation value is The central tendency and variance values ​​can be included. The trend value may be the average of the baseline sensor assembly validation values, The variance of the sensor assembly validation values ​​is the standard deviation of the baseline sensor assembly validation values. It is also possible.

[0172] The method 700 calculates a probability based on a central tendency value and a variance value for the baseline sensor assembly verification. The central tendency values ​​are calculated by determining whether they overlap with the probability of the baseline central tendency. It is possible to detect whether the sample assembly differs from the validation value. The probability is calculated based on the central tendency value. The variance value may include a confidence interval determined based on the central tendency value and the variance value. , the probability of the baseline sensor assembly validation value is The method 700 includes a confidence interval determined based on a constant value. The probability of the central tendency and variance values ​​obtained from the The method 700 can determine that the baseline overlaps with the baseline using equation

[14] above. The in-standard deviation can be determined.

[0173] The vibratory meter 5, meter electronics 20, and methods 500-700 described above are based on a sensor assembly. Validate the sensor assembly using the sensor signal parameters provided by For example, the method 500 executed on the meter electronics 20 may include determining the current sensor signal parameter relationships.

number

number

[0174] The method 500 also includes the parameter relationships between the drive signal and the pickoff sensor signal, the conduit Additional information, such as those based on determining parameter values ​​(e.g., stiffness, residual flexibility, mass, etc.) Additional verification can be performed to further determine the conditions causing the change in the sensor assembly. For example, additional verification of the sensor assembly can be performed by checking the parameters of the pickoff sensor signal. Even if asymmetric changes are not detected using only the In another example, additional verification of the sensor assembly can determine whether In this example, it is possible to determine what type of asymmetric change has occurred. The sensor signal alone is used to determine if an asymmetric change has occurred in the sensor assembly. Additional testing can determine which condition caused the asymmetric change. For example, etching can only cause asymmetric changes, while immersion Eclipses can cause both asymmetric and symmetric changes.

[0175] Methods 500-700 may also perform additional steps based on the verification, such as , the method 500 may be implemented by providing a sensor assembly, such as the sensor assembly 10 described above, with a state Additionally or alternatively, the method 500 may determine whether the state is This can result in a diagnosis that includes information about what is likely to happen. The method 500 may include transmitting the meter electronics 20 through the port 26 to the customer network, the terminal, the computer, and the like. A remote computing resource, such as a computer station, detects the condition and A message appears indicating that the condition detected is likely a corrosion of the conduit within the sensor assembly. Additionally or alternatively, meter electronics 20 may transmit a meter voltage message. The sensor assembly is communicatively coupled to a display of the slave device 20 or to the meter electronics. A message, window, text banner, and / or status indicating that the condition has been detected You can display information about:

[0176] The sensor signal parameter values ​​can be determined with relatively few computing resources. This allows for more efficient use of the resources of the meter electronics 20. , the sensor signal parameter relationship values ​​may be calculated without terminating the customer process. As explained above, the sensor signal parameter related values, especially the pickoff sensor signal parameters, Meter related values ​​are consistent at zero flow and maximum flow for a given, unchanging sensor assembly. Furthermore, statistical methods can be used which require fewer computational resources. Additionally, sensor signal parameter relationship values, such as pickoff sensor signal parameter relationship values, are calculated. When the sensor assembly and / or meter electronics are ) is the sensor assembly and The condition of the meter electronics and / or the metering equipment does not have to be the same.

[0177] The detailed description of the above embodiments is intended to be all that the inventors consider to be within the scope of this specification. This is not an exhaustive description of all embodiments. Indeed, those skilled in the art will recognize that the foregoing embodiments may be Various combinations or exclusions of specific elements of the forms provide further embodiments. and such further embodiments are within the scope and teachings of this specification. As is apparent from the above, the above embodiments may be combined in whole or in part to fall within the scope of this specification. and may result in additional embodiments within the teachings.

[0178] Accordingly, certain embodiments are described herein for illustrative purposes, but are not intended to be limiting unless otherwise recognized by those skilled in the art. As will be appreciated, various equivalent modifications are possible within the scope of this specification. The teachings herein apply not only to the embodiments described above and shown in the accompanying drawings, but also to the sensor assembly. Other methods for validating the sensor assembly using the sensor signal parameters provided by the The present invention can be applied to vibration meters and meter electronic equipment methods. The scope of the embodiments should be determined from the claims that follow.

Claims

1. The sensor assembly (10) is used to measure the parameters of the sensor signal.

2. A meter electronics system for verifying a sensor assembly, comprising: an interface (301) communicatively coupled to the sensor assembly (10); an interface (301) configured to receive two sensor signals (100); a processing system (302) communicatively coupled to the interface (301), calculating a sensor signal parameter relationship value between the two sensor signals (100); The calculated sensor signal parameter relationship value between the two sensor signals (100) is comparing the two sensor signals (100) to a baseline sensor signal parameter relationship value; A processing system (302) configured to meter electronics (20).

2. a sensor signal parameter relationship value between the two sensor signals (100) The meter electronics (20) is configured to measure the left pickoff sensor signal voltage value and the right pickoff sensor signal voltage value. and calculating a relationship value between the sensor signal parameter and the check-off sensor signal voltage value.

10. The meter electronics of claim 1, wherein the meter electronics (20) is configured （20）。

3. a sensor signal parameter relationship value between the two sensor signals (100) The meter electronics (20) is configured to detect two of the two sensor signals (100). the meter electronics (20) to calculate one of a ratio and a difference between sensor signal parameter values. The meter electronics (20) of claim 1, comprising:

4. The calculated sensor signal parameter relationship value is then calculated using the baseline sensor signal parameter The meter electronics (20) is configured to compare the calculated between the acquired sensor signal parameter relationship value and the baseline sensor signal parameter relationship value.

10. The method of claim 1, wherein the meter electronics (20) is configured to calculate a difference between The meter electronic device (20) according to claim 1.

5. The two sensor signals (100) are the drive signal (185) and the left pickoff sensor signal (165l). , and a right pickoff sensor signal (165r). Equipment (20).

6. The meter electronics (20) calculates the calculated sensor signal between the two sensor signals (100). said comparison of said sensor signal parameter relationship values ​​with said baseline sensor signal parameter relationship values. and determining a state of the sensor assembly (10) based on the Item 1. The meter electronics (20) according to item 1.

7. A parameter of the sensor signal provided by the sensor assembly is used to A method for verifying assembly, comprising: Calculating a sensor signal parameter relationship value between the two sensor signals; The calculated sensor signal parameter relationship value between the two sensor signals is calculated based on the two sensor signal parameters. and comparing the sensor signal parameter relationship to a baseline sensor signal parameter relationship between the sensor signals. A method comprising:

8. Calculating the sensor signal parameter relationship value between the two sensor signals includes: The sensor signal parameter between the right pickoff sensor signal voltage value and the left pickoff sensor signal voltage value.

8. The method of claim 7, further comprising calculating a data relationship value.

9. Calculating the sensor signal parameter relationship value between the two sensor signals includes: calculating one of a ratio and a difference between two sensor signal parameter values ​​of the sensor signals of 8. The method of claim 7.

10. The calculated sensor signal parameter relationship value is compared with a baseline sensor signal parameter relationship Comparing the calculated sensor signal parameter relationship value with the baseline sensor signal parameter relationship value.

8. The method of claim 7, further comprising calculating a difference between the sensor signal parameter relationship value and the sensor signal parameter relationship value.

11. The two sensor signals are a drive signal, a left pickoff sensor signal, and a right pickoff sensor signal. The method of claim 7, including two of the signals.

12. The calculated sensor signal parameter relationship value between the two sensor signals and the baseline a state of the sensor assembly based on said comparison with said sensor signal parameter relationship value; The method of claim 7, further comprising determining:

13. The sensor assembly (10) is used to measure the parameters of the sensor signal.

2. A meter electronics system for verifying a sensor assembly, comprising: Receives left and right pick-off sensor signals from the meter assembly (10). an interface (301) configured to receive A processing system (302) communicably coupled to the interface (301), determining a current first sensor assembly verification value and a current second sensor assembly verification value, and comparing the current first sensor assembly verification value with a first baseline sensor assembly verification value to determine a first sensor assembly verification shift, comparing the current second sensor assembly verification value with a second baseline sensor signal parameter relationship value to determine a second sensor assembly verification shift, determining the state of the conduit (130, 130') based on the first sensor assembly verification shift and the second sensor assembly verification shift, a processing system (302) configured as such, and comprising wherein at least one of the current first sensor assembly verification value and the current second sensor assembly verification value is composed of sensor signal parameter relationship values, a meter electronic device (20).

14. The first sensor assembly verification shift represents a physical rigidity change of the conduit (130, 130') between the driver (180) and the left pickoff, The second sensor assembly verification shift represents a physical rigidity change of the conduit (130, 130') between the driver (180) and the right pickoff, The meter electronic device (20) according to claim 13.

15. The sensor signal parameter relationship value is one of the ratio and difference of two sensor signal parameter values, The meter electronic device (20) according to claim 13 or 14.

16. The sensor signal parameter relationship value is determined based on two of the left pickoff sensor signal parameter, the right pickoff sensor signal parameter, and the drive signal parameter, The meter electronic device (20) according to any one of claims 13 to 15.

17. The processing system (302) is further configured to provide an alarm based on the determined state of the conduit (130, 130'), The meter electronic device (20) according to any one of claims 13 to 16.

18. The state of the conduit (130, 130') includes at least one of erosion, corrosion, damage, and coating of the conduit (130 , 130') of the sensor assembly (10), The meter electronic device (20) according to any one of claims 13 to 17.

19. ​ The processing system (302) determines the stiffness, residual flexibility, damping, and and determining the condition of the conduit (130, 130') based on at least one of the mass and 19. The meter electronics (20) of any one of claims 13 to 18, further configured to:

20. A parameter of the sensor signal provided by the sensor assembly is used to 1. A method for verifying assembly, comprising: Determining a current first sensor assembly validation value and a current second sensor assembly validation value And, Comparing the current first sensor assembly verification value with a first baseline sensor assembly verification value determining a first sensor assembly verification shift compared to Comparing the current second sensor assembly verification value with a second baseline sensor assembly verification value determining a second sensor assembly verification shift compared to the first sensor assembly verification shift; based on the first sensor assembly verification shift and the second sensor assembly verification shift determining a condition of the conduit based on the Including, the current first sensor assembly validation value and the current second sensor assembly validation value at least one of which is comprised of sensor signal parameter relationship values; method.

21. The first sensor assembly verification shift is the front shift between the driver and the left pickoff sensor. represents the change in physical stiffness of the vessel, The second sensor assembly verification shift is between the driver and the right pickoff sensor. represents a change in the physical stiffness of the conduit.

21. The method of claim 20.

22. The sensor signal parameter relationship value is one of a ratio and a difference of two sensor signal parameter values.

22. The method according to claim 20 or 21, wherein

23. The sensor signal parameter relationship values ​​include left pickoff sensor signal parameters, right pickoff sensor signal parameters, and determined based on two of the sensor signal parameter and the drive signal parameter.

23. The method of any one of claims 20 to 22.

24. 21. The method of claim 20, further comprising providing an alert based on the determination of the condition of the conduit.

23. The method according to any one of claims 1 to 23.

25. The condition of the conduit may include erosion, corrosion, damage, and coating of the conduit of the vibratory meter.

25. The method of any one of claims 20 to 24, comprising at least one of the following:

26. The sensor assembly (10) is used to measure the parameters of the sensor signal.

1. A meter electronics (20) for verifying a sensor assembly (10), comprising: storing a central tendency value of the sensor assembly validation values ​​and a variance value of the sensor assembly validation values; a processing system (302) including a storage system (304) configured to perform the processing The system (302) obtaining the central tendency value and the variance value from the storage system (304); A probability is determined based on the central tendency value and the variance value, and the central tendency value is determined based on the baseline probability. Detect whether the in-sensor assembly is different from the verification value; It is configured as follows: the baseline sensor assembly validation value is based on sensor signal parameter values; Meter electronics (20).

27. The sensor assembly validation values ​​include an LPO / RPO voltage ratio value, a DRV / LPO voltage ratio value, and a DRV / RPO 27. The meter electronics (20) of claim 26, wherein the voltage ratio value is one of:

28. the processing system to determine the probability based on the central tendency value and the variance value. (302) is configured to calculate a t value and use the t value to calculate the probability.

28. The method of claim 26 or 27, wherein the processing system (302) is configured to Meter electronics (20).

29. the processing system to determine the probability based on the central tendency value and the variance value. (302) is configured based on several sensor assembly validation measurements.

27. The method of claim 26, wherein the processing system (302) is configured to calculate a 29. The meter electronics (20) of any one of claims 1 to 28.

30. the processing system to determine the probability based on the central tendency value and the variance value. (302) is constructed to calculate the standard error based on the standard deviation and the degrees of freedom.

30. The meter of claim 29, wherein the processing system (302) is configured to: Electronic equipment (20).

31. The standard error is calculated using the following formula: [Equation 23] where: stddev pooled is the standard deviation, n DOF is the degree of freedom, 31. The meter electronics (20) of claim 30.

32. The variance is calculated by dividing the sensor assembly validation measurement and the baseline sensor assembly validation measurement by the variance.

32. The method of claim 26, wherein the standard deviation is a pooled standard deviation including the standard deviation of the constants. On-board meter electronics (20).

33. 33. The method of any one of claims 26 to 32, wherein the probability comprises a confidence interval for the central tendency value. Meter electronics (20).

34. The confidence interval is compared to 0; If the confidence interval does not include 0, the central tendency value is Detects that the value is not equal to the revalidation value, If the confidence interval includes 0, the central tendency value is Detect that the value is equal to the revalidation value.

34. The meter electronics (20) of claim 33.

35. the central tendency value is a sensor assembly validation value, Confidence intervals are calculated using the following formula: CI=SV mean ±CI range ; where: CI is the confidence interval of the sensor assembly validation value; SV mean is the sensor assembly validation value obtained from the storage system (204). the law of nature, CI range is the confidence interval range calculated based on the standard deviation and t-value, 35. The meter electronics (20) of claim 33 or 34.

36. The confidence interval range is calculated using the following formula: CI range =stderror pooled ・t student,99.8 ; stderror pooled is the pooled standard error of the sensor assembly validation measurements the law of nature, t student,99.8 is a number of the sensor assemblies including the sensor assembly validation value. is the t-value calculated based on the significance level and degrees of freedom determined from the validation measurements, 36. The meter electronics (20) of claim 35.

37. The processing system (302) is further configured to set a bias dead band, If the cardiac tendency value is less than the bias deadband, the sensor assembly validation value is 26 to 28.

36. The meter electronics (20) of any one of claims 36 to 36.

38. the processing system to determine the probability based on the central tendency value and the variance value. (302) is configured to calculate a confidence interval based on the central tendency value and the variance value.

28. The method of claim 26 or 27, wherein the processing system (302) is configured to determine The meter electronic device (20) according to claim 1.

39. The baseline sensor assembly validation value is 39. The meter electronics (20) of claim 38, including a central tendency value and a variance value of the values.

40. The central tendency value of the baseline sensor assembly validation value is the mean of the baseline sensor assembly validation values, 40. The method of claim 39, wherein the value is the standard deviation of the baseline sensor assembly validation values. Data electronics (20).

41. The meter electronic device (20) is configured to detect whether the central tendency value is different from the baseline sensor assembly verification value which includes that the meter electronic device (20) is configured to determine whether the probability based on the central tendency value and the variance value overlaps with the probability of the baseline sensor assembly verification value, The meter electronic device (20) according to claim 26 or 27.

42. The probability based on the central tendency value and the variance value includes a confidence interval determined based on the central tendency value and the variance value, and the probability of the baseline sensor assembly verification value includes a confidence interval determined based on the baseline sensor assembly verification measurement value, The meter electronic device (20) according to claim 41.

43. That the meter electronic device (20) is configured to determine whether the probability based on the central tendency value overlaps with the probability of the baseline sensor assembly verification value means calculating the following formula, that is, and when LHS < RHS, determining that the probability of the central tendency value and the variance value obtained from the memory system (304) overlaps with the probability of the baseline sensor assembly verification value, The meter electronic device (20) according to claim 41, which includes that the meter electronic device (20) is configured as such.

44. LHS=|μ measured -m baseline |; RHS=2*(σ measured -s baseline ); The baseline standard deviation is calculated according to the following formula, The meter electronic device (20) according to claim 43. A method for verifying the sensor assembly using parameters of a sensor signal supplied by the sensor assembly, comprising: obtaining a central tendency value of a sensor assembly verification value and a variance value of the sensor assembly verification value from a storage device in a meter electronic device of a vibratory meter; determining a probability based on the central tendency value and the variance value to determine whether the central tendency value is different from a baseline sensor assembly verification value; and where the baseline sensor assembly verification value is based on sensor signal parameter values. s baseline =dead band*μ baseline Method

46. The sensor assembly verification value is one of an LPO / RPO voltage ratio value, a DRV / LPO voltage ratio value, and a DRV / RPO voltage ratio value, The method according to claim 45. Determining the probability based on the central tendency value and the variance value includes calculating a t-value ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ and calculating the probability using the t-value. method.

48. Determining the probability based on the central tendency value and the variance value may involve several sensors.

48. Any of claims 45 to 47, including calculating degrees of freedom based on assembly validation measurements.

1. The method according to claim 1.

49. Determining the probability based on the central tendency value and the variance value includes determining the standard deviation and prior 49. The method of claim 48, comprising calculating a standard error based on the degrees of freedom.

50. The standard error is calculated using the following formula: [0000] where: stddev pooled is the standard deviation, n DOF is the degree of freedom, 50. The method of claim 49.

51. The variance is calculated by dividing the sensor assembly validation measurement and the baseline sensor assembly validation measurement by the variance.

51. The method of claim 45, wherein the standard deviation is a pooled standard deviation including the standard deviation of the constants. How to post.

52. 52. The method of any one of claims 45 to 51, wherein the probability comprises a confidence interval for the central tendency value. method.

53. The confidence interval is compared to 0; If the confidence interval does not include 0, the central tendency value is Detects that the value is not equal to the revalidation value, If the confidence interval includes 0, the central tendency value is Detect that the value is equal to the revalidation value.

53. The method of claim 52.

54. the central tendency value is the sensor assembly validation value, The confidence interval is calculated using the following formula: CI=SV mean ±CI range ; where: CI is the confidence interval of the sensor assembly validation value; SV mean is the sensor assembly validation value obtained from the storage system (204). the law of nature, CI range is the confidence interval range calculated based on the standard deviation and t-value, 54. The method of claim 52 or 53.

55. The confidence interval range is calculated using the following formula: CI range =stderror pooled ・t student,99.8 ; where: stderror pooled is the pooled standard error of the sensor assembly validation measurements the law of nature, t student,99.8 is a number of the sensor assemblies including the sensor assembly validation value. is the t-value calculated based on the significance level and degrees of freedom determined from the validation measurements, 55. The method of claim 54.

56. further comprising setting a bias deadband, wherein the central tendency value is smaller than the bias deadband. If t is smaller than t, the sensor assembly verification value is 56. The method of any one of claims 45 to 55, wherein the value is not detected as different from the value.

57. Determining the probability based on the central tendency value and the variance value is and determining a confidence interval based on the variance value. 。

58. The baseline sensor assembly verification value is the baseline sensor assembly verification value including a central tendency value and a variance value, the method according to claim 57. **Claim 59** The central tendency value of the baseline sensor assembly verification value is the average of the baseline sensor assembly verification values, and the variance value of the baseline sensor assembly verification value is the standard deviation of the baseline sensor assembly verification values, the method according to claim 58. **Claim 60** Detecting whether the central tendency value is different from the baseline sensor assembly verification value includes determining whether the probability based on the central tendency value and the variance value overlaps with the probability of the baseline sensor assembly verification value, the method according to claim 45 or 46. **Claim 61** The probability based on the central tendency value and the variance value includes a confidence interval determined based on the central tendency value and the variance value, and the probability of the baseline sensor assembly verification value includes a confidence interval determined based on the baseline sensor assembly verification measurement value, the method according to claim 59. **Claim 62** Determining whether the probability based on the central tendency value and the variance value does not overlap with the probability of the baseline sensor assembly verification value includes calculating the following formula, that is, and when LHS < RHS, determining that the probability of the central tendency value and the variance value obtained from the storage device overlaps with the probability of the baseline sensor assembly verification value. **Claim 63** The standard deviation of the baseline system assembly verification value is calculated according to the following formula, the method according to claim 61. ​ ​ ​ ​ ​ LHS=|μ measured -m baseline |; RHS=2*(σ measured -s baseline ); ​ ​ ​ ​ ​ ​ ​ ​ s baseline =dead band*μ baseline ​

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