Determining a process related parameter based on two or more vibration modes

Abstract

A method of determining a process related parameter value from two or more vibration modes is provided. The method comprises vibrating, with a drive signal, a sensor assembly in a first vibration mode, vibrating, with the drive signal, the sensor assembly in a second vibration mode, and estimating a process related parameter value based on the first vibration mode and the second vibration mode.

Description

[0001] DETERMINING A PROCESS RELATED PARAMETER BASED ON TWO OR MORE VIBRATION MODES TECHNICAL FIELD The embodiments described below relate to vibratory meter measurements and, more particularly, to determining a process related parameter based on two or more vibration modes. BACKGROUND Vibratory meters, such as for example, Coriolis mass flowmeters, liquid density meters, gas density meters, liquid viscosity meters, gas / liquid specific gravity meters, gas / liquid relative density meters, and gas molecular weight meters, are generally known and are used for measuring characteristics of fluids. Generally, vibratory meters comprise a sensor assembly and a meter electronics. The material in or about the sensor assembly may be flowing or stationary. The vibratory meter may be used to measure a mass flow rate, density, or other properties of a material in or about the sensor assembly. In particular, the sensor assembly may vibrate a vibratory structure that moves the material in or about the sensor assembly. In sensor assemblies comprising one or more conduits containing the material, the vibratory structure may be defined by a length of the one or more conduits. A length of the one or more conduits defined by the fixed ends may be referred to as a vibratory portion of the one or more conduits of the vibratory structure. Vibration nodes are defined where the one or more conduits are fixed at each end. The vibratory portion of the sensor assembly may therefore have at least one vibration mode defined in part by two vibration nodes. The ends of the vibratory portion of the vibratory structure may be referred to as end nodes of a vibration mode. All vibration modes of the vibratory portion will have at least the two end nodes. The sensor assembly may have two or more vibration modes. That is, the vibratory portion may have a first, second, third, etc. vibration mode. In many sensor assemblies, the normal modes are comprised of various vibration mode shapes, including bend and twist modes of a conduit or vibratory portion of a sensor assembly. Bend modes are defined by symmetrical displacement of all points of the vibratory portion of the sensor assembly. Symmetrical displacement means that all locations of the conduit move in phase with each other. The twist mode may be defined by antisymmetric displacement of the vibratory portion of the sensor assembly. Antisymmetric displacement of a conduit means at least some locations of the conduit are not moving in phase with other locations of the conduit. For symmetrical structures of the vibratory portion, this may mean locations equidistant from a center location of the conduit are moving 180 degrees out-of-phase. Movement of the one or more conduits may be caused and / or sensed by a transducer. A transducer may be any device that converts between an electrical signal and a physical movement, which herein is a movement of the conduit. A transducer intended to cause the conduit to move can be referred to as a driver. A transducer intended to sense a movement may be referred to as a pickoff sensor. Other terms for a pickoff sensor may be employed, such as velocity or displacement sensor. The movement may be caused and / or sensed by a transducer coupled to the one or more conduits. The coupling may be direct and / or indirect, mechanical and / or electromechanical, etc. The vibratory motions may be driven or induced. The term “driven mode” or “driven vibration mode” means a vibration mode caused by a driver. That is, an electrical signal causes the transducer to apply a force to the conduit. The force may be referred to as a forcing function, where the forcing function has oscillation related parameters such as frequency or time-period, displacement and phase. An induced vibratory motion is caused by a force that is induced by the driven vibration mode. For example, a driven bend mode may cause a rotational angular velocity to be applied to a flowing material contained by a conduit, which induces a Coriolis force. The Coriolis force can cause an induced twisting of the conduit. The amount of twist, measured as a time delay or phase difference, is proportional to a mass flow rate of the material flowing through the conduit. The amount of twist can be used to measure a mass flow rate of the material with a suitable calibration. The conduit and / or the material contained by the conduit may have various parameters that are more desirably sensed and / or affected by particular vibration modes. However, no attempts have been made to exploit these benefits in a single vibratory meter. Additionally, various attempts that have been made used more than one vibratory sensor, employed complex electronics and / or sensor assemblies, or relied on induced vibration modes. There can also be benefits to being able to selectively operate a vibratory meter in two or more operating modes. There is a need therefore for determining a process related parameter based on two or more vibration modes. There is also a need for determining the process related parameters based on the two or more vibration modes without complex electronics and / or sensor assemblies. SUMMARY A method of determining a process related parameter value from two or more vibration modes is provided. According to an embodiment, the method comprises vibrating, with a drive signal, a sensor assembly in a first vibration mode, vibrating, with the drive signal, the sensor assembly in a second vibration mode, and estimating a process related parameter value based on the first vibration mode and the second vibration mode. A method of determining a process related parameter from two or more vibration modes is provided. According to an embodiment, the method comprises vibrating, with a drive signal, a sensor assembly in a first vibration mode, vibrating, with the drive signal, the sensor assembly in a second vibration mode, and determining a relationship between a process related parameter and the first vibration mode and the second vibration mode. A method of determining a process-related parameter based on two or more vibration modes is provided. According to an embodiment, the method comprises vibrating, with a drive signal, a sensor assembly of a vibratory meter in a first vibration mode, vibrating, with the drive signal, the sensor assembly of the vibratory meter in a second vibration mode, and determining at least one meter verification parameter based on the first vibration mode and the second vibration mode. A vibratory meter configured to determine a process-related parameter based on two or more vibration modes is provided. According to an embodiment, the vibratory meter comprises a sensor assembly comprising a conduit and a driver disposed on the conduit and a meter electronics communicatively coupled to the sensor assembly, the meter electronics being configured to perform a method according to the foregoing. ASPECTS According to an aspect, a method of determining a process related parameter value from two or more vibration modes comprises vibrating, with a drive signal, a sensor assembly in a first vibration mode, vibrating, with the drive signal, the sensor assembly in a second vibration mode, and estimating a process related parameter value based on the first vibration mode and the second vibration mode. Preferably, the first vibration mode and the second vibration mode are normal modes of the sensor assembly. Preferably, the first vibration mode is a first bend mode and the second vibration mode is one of a second bend mode and a first twist mode. Preferably, estimating the process related parameter value based on the first vibration mode and the second vibration mode comprises estimating the process related parameter based on a mode relationship between the first vibration mode and the second vibration mode. Preferably, the mode relationship between the first vibration mode and the second vibration mode comprises a relationship between parameters of the first vibration mode and the second vibration mode. Preferably, the mode relationship comprises one of a ratio and a difference between the first vibration mode and the second vibration mode. Preferably, the mode relationship between the first vibration mode and the second vibration mode is comprised of a frequency, time-period, and / or an amplitude of the first and second vibration mode. Preferably, estimating the process related parameter comprises estimating the process related parameter based on a relationship between the process related parameter and a plurality of other process related parameters. Preferably, the relationship between a process related parameter and the plurality of other process related parameters comprises a function relationship between the process related parameter and the plurality of other process related parameters. Preferably, the function relationship determines a pressure P according to:^ = ^^^^, ^, ^^;where:^ is an internal pressure or pressure inside a conduit of a sensor assembly;^^ is a frequency ratio between the first and second vibration modes;^is a density of a material contained by the conduit; and^ is a temperature of the conduit.Preferably, the function relationship is defined as:^ ≅ ^ ^ ^ ^^^ ^ ^^ ^ ^ ^ ^^ ^ ^ ^ ^ ^ ^^ ^ ^ ^ ^ ^^ ^^^^ ^ ^ ^ ^ ^ ^^^ ^^ ^ ^^^^ ^^,^^^^ ^ ^^^^^^ ^ ^^^^ ^ ^^,^^^^ ^ ^^^;where: ^is an estimated pressure;^^, ^, ^ are the independent variables, which herein are process-relatedvariables;^^^, ^^, ^^, ^^^^, ^^,^^, ^^,^^ are coefficients referred to sensitivities tochanges in the independent variables; and^^^, ^^, ^^ are nominal values of the independent variables.Preferably, the function relationship has the form of:^ = ^^^^, ^^ , … ^^ , … , ^^^ ^^; for j=1 to NVAR;^^ is a jth process related parameter; andNVAR is the number of other process related parameters. Preferably, the function relationship has the form of:^ = ^^ ^ ^^^^ ^ … ^ ^^^^ ^ ⋯ ^ ^^^ ^^"^ ^, for j = 1 to NVAR;where: ^is a response variable;^^ is a jth predictor variable;^^ is the average effect on ^ of an increase in ^^ predictor variable, holding allother predictors fixed; and NVAR is the number of predictor variables. Preferably, estimating the process related parameter value based on the first vibration mode and the second vibration mode comprises calculating the process related parameter value based on a predetermined measured process related parameter value and the first vibration mode and the second vibration mode. Preferably, calculating the process related parameter value based on a predetermined measured process related parameter value and the first vibration mode and the second vibration mode comprises calculating the process related parameter value based on interpolations between the process related parameter values and vibration mode parameter values. Preferably, estimating the process related parameter value comprises estimating one of a pressure value and a temperature value. According to an aspect, a method of determining a process related parameter from two or more vibration modes comprises vibrating, with a drive signal, a sensor assembly in a first vibration mode, vibrating, with the drive signal, the sensor assembly in a second vibration mode, and determining a relationship between a process related parameter and the first vibration mode and the second vibration mode. Preferably, determining the relationship between the process related parameter and the first vibration mode and the second vibration mode comprises minimizing an error # between a model of the relationship between the process related parameter and the first vibration mode and the second vibration mode and a plurality of data points determined based on the first vibration mode and the second vibration mode. Preferably, minimizing the error # between a model of the relationship between the process related parameter and the first vibration mode and the second vibration mode and a plurality of data points determined based on the first vibration mode and the second vibration mode comprises minimizing the error # in a multiple linear regressionaccording to:^ = ^^ ^ ^^^^ ^ ⋯ ^ ^^^^ ^ ⋯ ^ ^^^ ^^^^ ^ ^ #, for j = 1 to NVAR;where: ^is a response variable;^^ is a jth predictor variable;^^ is the average effect on ^ of an increase in ^^ predictor variable, holding allother predictors fixed; NVAR is the number of predictor variables; and#is an error term.Preferably, each data point of the plurality of data points comprises an ordered sequence of the response variable ^ and the predictor variables ^^. Preferably, determining the relationship between a process related parameter and the first vibration mode and the second vibration mode comprises obtaining a plurality of samples of the process related parameters. Preferably, the plurality of samples of the process related parameters comprises a plurality of samples of the pressure, frequency ratio, density, and temperature (P, FR, ρ, T) data points. Preferably, the plurality of samples of the process related parameters is obtained from one of an analysis of a finite element model or measurements of the sensor assembly. According to an aspect, a method of determining a process-related parameter based on two or more vibration modes comprises vibrating, with a drive signal, a sensor assembly of a vibratory meter in a first vibration mode, vibrating, with the drive signal, the sensor assembly of the vibratory meter in a second vibration mode, and determining at least one meter verification parameter based on the first vibration mode and the second vibration mode. Preferably, nodes of the first vibration mode and nodes of the second vibration mode are located at symmetric positions of a conduit of the sensor assembly. Preferably, the sensor assembly further comprises a driver symmetrically disposed on a conduit of the sensor assembly. Preferably, the driver being symmetrically disposed on the conduit of the sensor assembly comprises the driver being disposed equidistance between brace bars coupled to the conduit. Preferably, the brace bars define end nodes of the nodes of the first vibration mode and the nodes of the second vibration mode. Preferably, the driver being symmetrically disposed on the conduit comprises the driver being disposed at a node of the nodes of the second vibration mode. Preferably, the sensor assembly further comprises a pickoff sensor disposed on the conduit of the sensor assembly, wherein the drive signal is provided to one of the driver and the pickoff sensor. Preferably, vibrating the sensor assembly in the first vibration mode comprises providing the drive signal to the sensor assembly at a fundamental frequency of the first vibration mode and vibrating the sensor assembly in the second vibration mode comprises providing the drive signal to the sensor assembly at a fundamental frequency of the second vibration mode. Preferably, the first vibration mode is a first bend mode and the second vibration mode is one of a second bend mode and a first twist mode. Preferably, the driver being symmetrically disposed on the conduit of the sensor assembly comprises the driver being symmetrically disposed between two or more pickoff sensors disposed on the conduit of the sensor assembly. Preferably, the driver symmetrically disposed on the conduit of the sensor assembly is comprised of a single driver affixed to the conduit at a center of a longitudinal length of the conduit. Preferably, the drive signal applies a forcing function to the conduit at one of a symmetric location and an asymmetric location of the conduit. Preferably, the asymmetric location of the conduit is a location of an antinode of the first vibration mode and the symmetric location of the conduit is a location of a node of the second vibration mode. Preferably, vibrating, with the drive signal, the sensor assembly in the first vibration mode and the second vibration mode comprises providing the drive signal to a single transducer disposed on the conduit. Preferably, determining the at least one meter verification parameter based on the first vibration mode and the second vibration mode comprises determining a first mode meter verification parameter value and a second mode meter verification parameter value. Preferably, determining a first mode meter verification parameter value and a second mode meter verification parameter value comprises determining a first mode meter stiffness value based on a fit to a first vibration mode frequency response function and a second mode meter stiffness value based on a fit to a second vibration mode frequency response function. Preferably, determining the first mode stiffness value comprises determining a first mode fit value and a second mode fit value at zero hertz, the first mode fit value being the fit to the first vibration mode frequency response function and the second mode fit value being the fit to the second vibration mode frequency response function. Preferably, determining the at least one meter verification parameter based on the first vibration mode and the second vibration mode comprises determining a first mode stiffness value and determining a second mode stiffness value. Preferably, the method further comprising determining a location of a condition in a conduit of the sensor assembly based on at least one of the first mode stiffness value and the second mode stiffness value. Preferably, the at least one meter verification parameter comprises a parameter relationship of a stiffness and / or damping. According to an aspect, a vibratory meter configured to determine a process- related parameter based on two or more vibration modes comprises a sensor assembly comprising a conduit and a driver disposed on the conduit and a meter electronics communicatively coupled to the sensor assembly, the meter electronics being configured to perform a method according to the foregoing. BRIEF DESCRIPTION OF THE DRAWINGS The same reference number represents the same element on all drawings. It should be understood that the drawings are not necessarily to scale. FIG.1 shows a vibratory meter 5 for determining a process related parameter based on two or more vibration modes. FIG.2 shows a block diagram of the vibratory meter 5, including a block diagram representation of the meter electronics 20. FIG.3 shows the meter electronics 20 for determining a process related parameter based on two or more vibration modes. FIGS.4A and 4B show wireline diagrams of conduits to illustrate vibration modes of the conduits, such as the conduits 130, 130’ described above. FIGS.5A-5C and FIGS. 6A-6C respectively show perspective and lateral views of a sensor assembly 510 of a vibratory meter having the vibratory modes described above with reference to FIGS. 4A and 4B. FIG.7 shows a three degree of freedom graph 700 for determining a process related parameter from two or more vibration modes. FIG.8 shows a graph 800 illustrating adding two signals having different frequencies. FIG.9 shows a vibratory meter 905 configured to have a driven twist mode for determining a process related parameter based on two or more vibration modes. FIG. 10 shows a switching circuit 1000 for driving a twist mode in a sensor assembly. FIG.11 shows a multi-sensor assembly system 1100. FIG.12 shows an aggregate frequency response function (“FRF”) graph 1200 illustrating FRFs corresponding to the nominal and twist configurations of the meter electronics 920. FIG. 13 shows a graph 1300 illustrating sensor signals plotted in a time domain when an asymmetrical forcing function is applied to a conduit. FIG.14 shows a drive signal frequency spectrum graph 1400. FIG.15 shows frequency response function 1500 for determining a process related parameter from two or more vibration modes. FIG. 16 shows a block diagram of a vibratory meter 1605 including meter verification using two or more fundamental frequencies. FIGS. 17 and 18 show pressure versus frequency ratio graphs 1700, 1800 for determining a process related parameter based on two or more vibration modes. FIG. 19 shows a sectioned perspective view of a temperature differential model of a sensor assembly 1910 for a vibratory meter. FIG. 20 shows a thermal operating graph 1900 illustrating possible operating ranges of the sensor assembly 1910. FIG. 21 shows a pressure-temperature versus frequency ratio graph 2100 for determining a process related parameter based on two or more vibration modes. FIG. 22 shows a multi-parameter time domain relational graph 2200. FIG. 23 shows a multi-parameter time domain relational graph 2300. FIG. 24 shows a pressure calculation graph 2400 for determining a process related parameter based on two or more vibration modes. FIG. 25 shows a frequency ratio-density graph 2500 for determining a process related parameter from two or more vibration modes. FIG. 26 shows a quadratic term graph 2600 for determining process related parameters based on two or more vibration modes. FIG.27 shows a method 2700 for determining process related parameters based on two or more vibration modes. FIG.28 shows a method 2800 for determining a process related parameter based on two or more vibration modes. FIG.29 shows a method 2900 for determining a process related parameter based on two or more vibration modes. DETAILED DESCRIPTION FIGS.1 – 29 and the following description depict specific examples to teach those skilled in the art how to make and use the best mode of embodiments of determining a process related parameter based on two or more vibration modes. For the purpose of teaching inventive principles, some conventional aspects have been simplified or omitted. Those skilled in the art will appreciate variations from these examples that fall within the scope of the present description. Those skilled in the art will appreciate that the features described below can be combined in various ways to form multiple variations of determining the process related parameter based on the two or more vibration modes. As a result, the embodiments described below are not limited to the specific examples described below, but only by the claims and their equivalents. FIG. 1 shows a vibratory meter 5 for determining a process related parameter based on two or more vibration modes. As shown in FIG.1, the vibratory meter 5 comprises a sensor assembly 10 and meter electronics 20. The sensor assembly 10 responds to mass flow rate and density of a process material. The meter electronics 20 is connected to the sensor assembly 10 via leads 100 to provide density, mass flow rate, and temperature information over port 26, as well as other information. The sensor assembly 10 includes a pair of manifolds 150 and 150', flanges 103 and 103' having flange necks 110 and 110', a pair of parallel conduits 130 and 130', driver 180, resistive temperature detector (RTD) 190, and a pair of pick-off sensors 170l and 170r. Conduits 130 and 130' have two essentially straight inlet legs 131, 131' and outlet legs 134, 134', which converge towards each other at conduit mounting blocks 120 and 120'. The conduits 130, 130' bend at two symmetrical locations along their length and are essentially parallel throughout their length. Brace bars 140 and 140' serve to define the axis W and W' about which each conduit 130, 130’ oscillates. The legs 131, 131' and 134, 134' of the conduits 130, 130' are fixedly attached to conduit mounting blocks 120 and 120' and these blocks, in turn, are fixedly attached to manifolds 150 and 150'. This provides a continuous closed material path through sensor assembly 10. When flanges 103 and 103', having holes 102 and 102' are connected, via inlet end 104 and outlet end 104' into a process line (not shown) which carries the process material that is being measured, material enters inlet end 104 of the meter through an orifice 101 in the flange 103 and is conducted through the manifold 150 to the conduit mounting block 120 having a surface 121. Within the manifold 150 the material is divided and routed through the conduits 130, 130'. Upon exiting the conduits 130, 130', the process material is recombined in a single stream within the block 120’ having a surface 121’ and the manifold 150' and is thereafter routed to outlet end 104' connected by the flange 103' having holes 102' to the process line (not shown). The conduits 130, 130' are selected and appropriately mounted to the conduit mounting blocks 120, 120' so as to have substantially the same mass distribution, moments of inertia and Young's modulus about bending axes W--W and W'--W', respectively. These bending axes go through the brace bars 140, 140'. Inasmuch as the Young's modulus of the conduits change with temperature, and this change affects the calculation of flow and density, RTD 190 is mounted to conduit 130' to continuously measure the temperature of the conduit 130’. The temperature of the conduit 130’ and hence the voltage appearing across the RTD 190 for a given current passing therethrough is governed by the temperature of the material passing through the conduit 130’. The temperature dependent voltage appearing across the RTD 190 is used in a well-known method by the meter electronics 20 to compensate for the change in elastic modulus of the conduits 130, 130' due to any changes in conduit temperature. The RTD 190 is connected to the meter electronics 20 by lead 195. Both of the conduits 130, 130' are driven by driver 180 in opposite directions about their respective bending axes W and W' and at what is termed the first out-of- phase bending mode of the flow meter. This driver 180 may comprise any one of many well-known arrangements, such as a magnet mounted to the conduit 130' and an opposing coil mounted to the conduit 130 and through which an alternating current is passed for vibrating both conduits 130, 130’. A suitable drive signal 185 is applied by the meter electronics 20, via a lead, to the driver 180. The meter electronics 20 receives the RTD temperature signal on lead 195, and sensor signals 165 appearing on leads 100 carrying left and right sensor signals 165l, 165r, respectively. The meter electronics 20 produces the drive signal 185 appearing on the lead to driver 180 and vibrate conduits 130, 130'. The meter electronics 20 processes the left and right sensor signals 165l, 165r and the RTD signal 190 to compute the mass flow rate and the density of the material passing through sensor assembly 10. This information, along with other information, is applied by meter electronics 20 over path 26 as a signal. A more detailed discussion of the meter electronics 20 follows. FIG. 2 shows a block diagram of the vibratory meter 5, including a block diagram representation of the meter electronics 20. As shown in FIG.2, the meter electronics 20 is communicatively coupled to the sensor assembly 10. As described in the foregoing with reference to FIG.1, the sensor assembly 10 includes the left and right pick-off sensors 170l, 170r, driver 180, and temperature sensor 190, which are communicatively coupled to the meter electronics 20 via the set of leads 100 through a communications channel 112. The meter electronics 20 provides a drive signal 185 via the leads 100. More specifically, the meter electronics 20 provides a drive signal 185 to the driver 180 in the sensor assembly 10. In addition, sensor signals 165 comprising the left sensor signal 165l and the right sensor signal 165r are provided by the sensor assembly 10. More specifically, in the embodiment shown, the sensor signals 165 are provided by the left and right pick-off sensor 170l, 170r in the sensor assembly 10. As can be appreciated, the sensor signals 165 are respectively provided to the meter electronics 20 through the communications channel 112. The meter electronics 20 includes a processor 210 communicatively coupled to one or more signal processors 220 and one or more memories 230. The processor 210 is also communicatively coupled to a user interface 30. The processor 210 is communicatively coupled with the host via a communication port over the port 26 and receives electrical power via an electrical power port 250. The processor 210 may be a microprocessor although any suitable processor may be employed. For example, the processor 210 may be comprised of sub-processors, such as a multi-core processor, serial communication ports, peripheral interfaces (e.g., serial peripheral interface), on- chip memory, I / O ports, and / or the like. In these and other embodiments, the processor 210 is configured to perform operations on received and processed signals, such as digitized signals. The processor 210 may receive digitized sensor signals from the one or more signal processors 220. The processor 210 is also configured to provide information, such as a phase difference, a property of a fluid in the sensor assembly 10, or the like. The processor 210 may provide the information to the host through the communication port. The processor 210 may also be configured to communicate with the one or more memories 230 to receive and / or store information in the one or more memories 230. For example, the processor 210 may receive calibration factors and / or sensor assembly zeros (e.g., phase difference when there is zero flow) from the one or more memories 230. Each of the calibration factors and / or sensor assembly zeros may respectively be associated with the flow meter 5 and / or the sensor assembly 10. The processor 210 may use the calibration factors to process digitized sensor signals received from the one or more signal processors 220. The one or more signal processors 220 is shown as being comprised of an encoder / decoder (CODEC) 222 and an analog-to-digital converter (ADC) 226. The one or more signal processors 220 may condition analog signals, digitize the conditioned analog signals, and / or provide the digitized signals. The CODEC 222 is configured to receive the sensor signals 165 from the left and right pick-off sensors 170l, 170r. The CODEC 222 is also configured to provide the drive signal 185 to the driver 180. In alternative embodiments, more or fewer signal processors may be employed. As shown, the sensor signals 165 are provided to the CODEC 222 via a signal conditioner 240. The drive signal 185 is provided to the driver 180 via the signal conditioner 240. Although the signal conditioner 240 is shown as a single block, the signal conditioner 240 may be comprised of signal conditioning components, such as two or more op-amps, filters, such as low pass filters, voltage-to-current amplifiers, or the like. For example, the sensor signals 165 may be amplified by a first amplifier and the drive signal 185 may be amplified by the voltage-to-current amplifier. The amplification can ensure that the magnitude of the sensor signals 165 is approximate the full-scale range of the CODEC 222. The portion of the CODEC 222 and signal conditioner 240 that generates the drive signal 185 may be referred to as a signal generator. The portion of the CODEC 222 and signal conditioner 240 that receives and processes the sensor signals 165 may be referred to as a sensor signal processor. It should be appreciated that the portions of the signal generator and the sensor signal processor that work together to generate the drive signal at a resonance frequency of the sensor assembly 10 may be referred to as a drive circuit. It should also be appreciated that the drive circuit can include additional components, such as switches, additional signal processors, and / or the like. In the embodiment shown, the one or more memories 230 is comprised of a read- only memory (ROM) 232, random access memory (RAM) 234, and a ferroelectric random-access memory (FRAM) 236. However, in alternative embodiments, the one or more memories 230 may be comprised of more or fewer memories. Additionally, or alternatively, the one or more memories 230 may be comprised of different types of memory (e.g., volatile, non-volatile, etc.). For example, a different type of non-volatile memory, such as, for example, erasable programmable read only memory (EPROM), or the like, may be employed instead of the FRAM 236. The one or more memories 230 may be a storage configured to store process data, such as drive or sensor signals, mass flow rate or density measurements, etc. Amass flow rate measurement ($% ) can be generated according to the equation:$% = ^^^[∆( ^ ∆(^] [1]The ∆t term comprises an operationally-derived (i.e., measured) time delay value comprising the time delay existing between the pickoff sensor signals, such as where the time delay is due to Coriolis effects related to mass flow rate through the vibratory flowmeter 5. The measured ∆t term ultimately determines the mass flow rate of the flow material as it flows through the vibratory flowmeter 5. The ∆t0term comprises a time delay / phase difference at zero flow calibration constant. The ∆t0 term is typically determined at the factory and programmed into the vibratory flowmeter 5. The time delay / phase difference at zero flow ∆t0term will not change, even where flow conditions are changing. A mass flow rate of flow material flowing through the flow meter is determined by multiplying a measured time delay (or phase difference / frequency) by the flow calibration factor FCF. The flow calibration factor FCF is proportional to a physical stiffness of the flow meter. As to density, a resonance frequency at which each conduit 130, 130’ will vibrate may be a function of the square root of a spring constant of the conduit 130, 130’ divided by the total mass of the conduit 130, 130’ having a material. The total mass of the conduit 130, 130’ having the material may be a mass of the conduit 130, 130’ plus a mass of a material inside the conduit 130, 130’. The mass of the material in the conduit 130, 130’ is directly proportional to the density of the material. Therefore, the density of this material may be proportional to the square of a period at which the conduit 130, 130’ containing the material oscillates multiplied by the spring constant of the conduit 130, 130’. Hence, by determining the period at which the conduit 130, 130’ oscillates and by appropriately scaling the result, an accurate measure of the density of the material contained by the conduit 130, 130’ can be obtained. The meter electronics 20 can determine the period or resonance frequency using the sensor signals 165 and / or the drive signal 185. The density value can be obtained by using calibration constants. Calibration to determine the FCF for determining the mass flow rate and density calibration constants can use fluids of known density. For example, two fluids with different densities may be used, such as water and air. Density can be calculated using a density equation that include the density calibration constants, such as Equation [2]: *= +0 ^ +1. ^ +2.^; Equation [2]where:*is a density, which may not be corrected for other process related parameterslike temperature;.is a tube time-period or periodic time of a conduit in, for example, micro-seconds (01); and+0, +1, +2 are calibration constants.As explained above, the conduits 130, 130’ can vibrate in two or more modes. Parameters of two or more vibration modes, which may be referred to as mode parameters or vibration mode parameters, can be analyzed to detect, determine, analyze, and / or the like process related parameters. The process related parameters may include fluid parameters, sensor assembly parameters, meter electronics parameters, environmental parameters, etc. That is, process related parameters may be any parameter that influences and / or indicates something that is related to a process of which the vibratory meter is a component. By way of illustration, process related parameters may include a pressure or temperature of a fluid contained by the conduits 130, 130’, air or other fluid surrounding the conduits 130, 130’s, temperature of the manifolds 150, 150’, orientation of the sensor assembly 10, a case surrounding the conduits 130, 130’, etc. Such detection, determination, analysis, and / or the like can be performed by the meter electronics 20. Meter electronics FIG. 3 shows the meter electronics 20 for determining a process related parameter based on two or more vibration modes. As shown in FIG.3, the meter electronics 20 includes an interface 301 and a processing system 302. The meter electronics 20 receives a vibrational response, such as from the sensor assembly 10, for example. The meter electronics 20 processes the vibrational response in order to obtain flow characteristics of the flow material flowing through the sensor assembly 10. The interface 301 may receive the sensor signals 165 from one of the pick-off sensors 170l, 170r shown in FIGS.1 and 2. The interface 301 can perform any necessary or desired signal conditioning, such as any manner of formatting, amplification, buffering, etc. Alternatively, some or all of the signal conditioning can be performed in the processing system 302. In addition, the interface 301 can enable communications between the meter electronics 20 and external devices. The interface 301 can be capable of any manner of electronic, optical, or wireless communication. The interface 301 can provide information based on the vibrational response. The interface 301 may be coupled with a digitizer, such as the CODEC 222 shown in FIG. 2, wherein the sensor signal comprises an analog sensor signal. The digitizer samples and digitizes an analog sensor signal and produces a digitized sensor signal. The processing system 302 conducts operations of the meter electronics 20 and processes flow measurements from the sensor assembly 10. The processing system 302 executes one or more processing routines and thereby processes the flow measurements in order to produce one or more flow characteristics. The processing system 302 is communicatively coupled to the interface 301 and is configured to receive the information from the interface 301. The processing system 302 can comprise a general-purpose computer, a micro- processing system, a logic circuit, or some other general purpose or customized processing device. Additionally, or alternatively, the processing system 302 can be distributed among multiple processing devices. The processing system 302 can also include any manner of integral or independent electronic storage medium, such as the storage system 304. The storage system 304 can store flow meter parameters and data, software routines, constant values, and variable values. In one embodiment, the storage system 304 includes routines that are executed by the processing system 302, which will be discussed in more detail in the following. As shown in FIG.3, the storage system 304 includes an operational routine 310, a calibration routine 320, calibration information 330, correction routines 340, meter verification routines 350, multiplexing routines 360, and multi-phase routines 370, although more, fewer, and / or alternative routines may be stored and / or employed. The storage system 304 can also store statistical values, such as a standard deviation, confidence intervals, or the like. The operational routine 310 can determine a mass flow rate and / or a density value according to the above equations [1] and [2], although any suitable equation, relationships, etc., can be employed. The operational routine 310 can also determine various other fluid parameters, such as viscosity, fluid velocity, velocity of sound, fluid phase ratios, such as gas-mass ratios, void fractions, etc., and / or the like. The operational routine 310 can determine the fluid parameter values based on one or more vibration modes. For example, a mass flow rate may be determined based on a first bend mode, such as an out of phase bend mode. Additionally, or alternatively, and as will be described in more detail below, the operational routine 310 can determine other process related parameter values based on two or more vibration modes. The calibration routine 320 can determine various calibration factors, which may be calibration coefficients, constants, etc. The calibration routine 320 can determine, forexample, flow calibration factor FCF value(s), density calibration constants +0, +1, +2used to determine a density value, a temperature value based on the RTD signal 190, and / or the like. Other calibration factors, additional or alternative to those discussed herein, can be employed. The calibration constants can relate a sensed physical phenomenon to a measured value of the sensed phenomenon or other phenomenon. Calibration factors, as well as any other calibration related information can be stored in the calibration information 330. The correction routines 340 may compensate a measurement, such as a mass flow rate measurement, for an orientation of a vibratory meter. For example, the correction routines 340 may use various process related parameter values to compensate another process related parameter value. By way of illustration, a temperature of the process fluid can be used to correct a measured mass flow rate of a material flowing through a vibratory meter, such as the vibratory meter 5 described above. The meter verification routines 350 can verify that a sensor assembly, such as the sensor assembly 10 described above, does not have erosion, corrosion, deposits, and / or the like that can affect a measurement of fluid parameter. The multiplexing routines 360 can provide a drive signal to one or more transducers that are coupled to a conduit, such as the transducers described in the foregoing. For example, the multiplexing routines 360 can provide a drive signal that is at a first frequency corresponding to a first fundamental frequency and a second frequency corresponding to a second fundamental frequency. The first and second frequency may be provided in time division multiplex or frequency division multiplexed form. That is, the first and second frequency can be provided sequentially or simultaneously. The multi-phase routines 370 can determine if a fluid is in multi-phase condition, perform corrections of measured values using adjustments and / or the like based on the two or more vibration modes. For example, a totalization may be avoided by detecting a false flow condition in a sensor assembly. Additionally, or alternatively, the multi-phase routine 370 can adjust a mass flow rate of a flow based on a ratio of phases in a multi- phase fluid flow. As will be explained in more detail in the following, one or more of the above- described routines can operate a vibratory meter in two or more vibration modes of a sensor assembly. For example, a process related parameter may be determined, a meter verification may be performed, a mass flow rate may be compensated for multiphase effects, etc. Vibration modes FIGS. 4A and 4B show wireline diagrams of conduits to illustrate vibration modes of the conduits, such as the conduits 130, 130’ described above. As shown in FIGS.4A and 4B, the conduits are depicted by wirelines 410. The wirelines 410 have a U-shape to reflect U-shaped conduits, which may be comprised of a left conduit and a right conduit. As shown in FIGS.4A and 4B, the wirelines 410 include a left at-rest wireline 412a and a right at-rest wireline 412b. Also shown in FIGS. 4A and 4B are bend axes W—W, W’—W’, which is collocated with a vibration node of the wirelines 410. In FIG.4A, the wirelines 410 also include a left first order bend mode wireline 414a and a right first order bend mode wireline 414b. Also shown are a left second order bend mode wireline 416a and a right second order bend mode wireline 416b. In FIG. 4B, the wirelines 410 include a left first order twist mode 418a and a right first order twist mode 418b. The left and right first order bend mode wirelines 414a, 414b are shown by arrows to be 180 degrees out of phase. That is, they move in an opposing manner. This may be beneficial in various ways, such as reducing a vibration of a vibratory meter due to an unbalanced displacement of the conduits. The left and right first order bend mode wirelines 414a, 414b are also shown as having a single node, which is collocated with the bend axes W—W, W’—W’. The left and right second order bend mode wirelines 416a, 416b are also shown by arrows to be 180 degrees out of phase with each other. However, the left and right second order bend mode wirelines 416a, 416b have two vibration nodes, hence the term “second order.” A natural frequency of the left and right second order bend mode wirelines 416a, 416b may be higher than a natural frequency of the left and right first order bend mode wirelines 414a, 414b. The left first order twist mode 418a and the right first order twist mode 418b are shown as having asymmetric displacement relative to the left and right at-rest wirelines 412a, 412b along their respective lengths. Arrows illustrate that the left and right first order twist modes 418a, 418b are out of phase with each other. The vibration modes illustrated by the wirelines 410 are shown as being separate but may be superimposed onto the conduits modeled by the wirelines 410. That is, the conduits modeled by the wirelines 410 may have multiple vibration modes. For example, a left conduit of the conduits may have a first order bend mode, a second order bend mode, and a twist mode. Accordingly, the conduits may have a first order out of phase bend mode, a second order out of phase bend mode, and a first order twist mode. The conduits may have additional modes, such as higher order bend modes (e.g., third, fourth, fifth, etc.), in-phase bend modes, and higher order twist modes (e.g., second, third, fourth, etc.). As the foregoing illustrates, a vibration mode may have a shape, amplitude, and natural frequency. The shape of the vibration modes can be detected by comparing the sensor signals, such as the sensor signals 165, to each other. A phase difference between a sensor signal provided by the left pick-off sensor 170l and a sensor signal provided by the right pick-off sensor signal 170r may indicate a twist mode excitation caused by Coriolis forces due to flow through the vibratory meter as the tubes vibrate in a bending or other mode, and may be proportional to the phase difference between the conduits 130, 130’. The amplitude of the vibration modes may be proportional to an amplitude of the sensor signals 165. The frequencies of the vibration modes may be determined from the sensor signals 165 and / or the drive signal 185. More specifically, due to each vibration mode having a natural mode frequency, the sensor signals 165 may have components that correspond to the vibration modes of the conduits 130, 130’. Accordingly, filtering may be used to isolate the components to determine a frequency of each component. The frequency of each component corresponds to the frequency of a vibration mode. The frequencies of the vibration modes may be referred to individually as a mode frequency. That is, the mode frequency is a natural or fundamental frequency of a vibration mode, each of which corresponds to a component in the sensor signals 165 and / or the drive signal 185. The vibration modes may have relationships. For example, a relationship between two vibration modes, herein referred to as a mode relationship, may be based on the phase, amplitude, and frequency of the two vibration modes. In one example, a mode relationship may be a difference in a frequency of the left and right second order bend mode wirelines 416a, 416b and a frequency of the left and right first order bend mode wirelines 414a, 414b. The mode relationship may be quantified as mode difference. For example, the mode relationship may be a difference between a time- period of the left and right second order bend mode wirelines 416a, 416b relative to a time-period of the left and right first order bend mode wirelines 414a, 414b. A mode relationship may also be something other than a difference, such as relative values like ratios, percentages, etc. By way of illustration, a mode relationship may be a frequency ratio, difference, etc. Accordingly, a mode relationship can be indicated by a term that reflects the vibration mode and the vibration mode parameter. For example, a time-period of a vibration may be indicated as ("2where “MO” is a variable to denote the mode (m) and the order (O). The modes can be denoted by β and ζ respectively as bend and twist mode. The order may be denoted by 1, 2, 3. So a first order bend mode and a first order twist mode can be respectively denoted as β1 and ζ1. A first order bend mode and a second order bend mode may be denoted as β1 and β2. Accordingly, a difference of timeperiods between the first and second order bend modes may be defined as (3^ ^ (3^.This can be shortened to 5(3^3^. Similarly, frequencies of the first and order bend modes may by be denoted by ^3^, ^3^ where a difference between the frequenciesis indicated by ^3^ ^ ^3^, which can be shortened to 5^3^3^. Similarly, a frequencyratio between a first and second bend mode may be denoted by ^3^⁄ ^3^ , which, in thisexample, is greater than 1 because the second bend mode has a fundamental frequency greater than a fundamental frequency of the first bend mode. As will be explained in more detail in the following, a calibration may be performed such that conduit stress inducing parameters, such as material pressure, temperature gradient, etc., can be determined from the vibration mode parameters. Accordingly, the nomenclature where the first order bend mode and a first order twist mode are respectively denoted as β1 and ζ1 can be used for conduit stress inducing parameters, such as, for example, pressure or temperature. For example, a pressure determined using the first order bend mode and the second order bend mode may be defined by ^3^3^. A conduit stress inducing parameter gradient may be denoted by the symbol ∇. Accordingly, a pressure gradient determined based on the first and second bend modes can be denoted by ∇^3^3^. Similarly, a pressure determined based on, forexample, a frequency ratio of the first and second bend mode may be denoted by^^^3^⁄ ^3^ ^, where the second bend mode frequency is a numerator of the frequencyratio. Generally, stress in a conduit is due to a gradient of a stress inducing parameter. For example, a pressure gradient between the material pressure and the ambient pressure induces a stress in the conduit. Similarly, a temperature gradient along a conduit induces a stress in the conduit. However, it may be a reasonable assumption that, for example, a stress in a conduit is correlated with a material pressure due to the ambient pressure being a relatively small and / or consistent value. Accordingly, it should be appreciated that an absolute or relative conduit stress inducing parameter may be employed. For example, a material pressure may be used rather than a pressure gradient between the material pressure and ambient pressure, although the pressure gradient induces the stress. Stresses in conduits FIGS. 5A-5C and FIGS.6A-6C respectively show perspective and lateral views of a sensor assembly 510 of a vibratory meter having the vibratory modes described above with reference to FIGS. 4A and 4B. As shown in FIG. 5A-5C and FIGS. 6A-6C, the sensor assembly 510 has a U-shaped configuration consistent with the U-shape of the wirelines 410 of FIGS.4A and 4B. As shown in FIGS.5A-5C and FIGS.6A-6C, the sensor assembly 510 is comprised of conduits 513, 513’ that are mechanically fixed to mounting blocks 512, 512’. As with the vibratory meter 5 of FIG.1, brace bars 514 and 514' serve to define the axis W and W' about which each conduit 513, 513’ oscillates. As shown in FIGS. 5A and 6A, the sensor assembly 510 is in a first out of phase bend mode. As shown in FIGS. 5B and 6B, the sensor assembly 510 is in a first twist mode. As shown in FIGS. 5C and 6C, the sensor assembly 510 is in a second out of phase bend mode. It should be appreciated that the amount of displacement in the vibration modes are exaggerated such that the conduits 513513’ appear merged together or overlapping where the conduits 513, 513’ are displaced towards each other. As can be appreciated from FIGS. 5A-6C, a stress in the conduits 513, 513’ can affect parameters of the vibration modes. For example, a pressure gradient that increases a stiffness of the conduits 513, 513’ can increase a fundamental frequency of each vibration mode. However, the effect of the stress on a fundamental frequency of a given vibration mode may be more than the effect of the stress on a fundamental frequency of a different vibration mode. Accordingly, for example, a frequency ratio of fundamental frequencies of two different vibration modes may correspond to the stress. Similar effects can be observed with tube time periods of each vibration mode, etc. As is explained in more detail in the following, various vibration modes can be induced, and each vibration mode’s parameters can be detected and measured. Vibration model of a conduit FIG. 7 shows a three degree of freedom graph 700 for determining a process related parameter from two or more vibration modes. As shown in FIG.7, the three degree of freedom graph 700 is comprised of a mode shape graph 702 and a three degree of freedom model 704. The mode shape graph 702 is comprised of a conduit location axis 712 and a displacement axis 722, both of which may be in units of length. The conduit location axis 712 indicates a position along a conduit where the ends of the conduit location axis 712 are defined by brace bars, such as the brace bars 514, 514’ shown in FIGS. 5A-6C. The mode shape graph 702 includes mode plots 732 comprised of a first bend mode plot 732a, a twist mode plot 732b, and a second bend mode plot 732c. The three degree of freedom model 704 is shown as being comprised of sensor masses, shown as comprising a left pickoff mass LPO, a driver mass DR, a right pickoff mass RPO, springs 744, and dampers 724. It should be appreciated that the markers of the three modes correspond to the masses of the left and right pickoff sensors LPO, RPO and the driver DR. As discussed above, node locations of a given vibration mode are locations of zero displacement (indicated by a dashed line located at “0” on the displacement axis 722) of a conduit vibrating in the vibration mode, which may be an excited vibration mode. It should be appreciated that the nodes of the vibration modes are symmetrically located on a conduit. That is, first bend mode plot 732a, twist mode plot 732b, and second bend mode plot 732c include end nodes that are equidistant from a center location of a conduit. The location of the end nodes may be determined by a brace bar or other suitable structure that can function as an anchor 764. The twist mode plot 732b shows a center node that is coincident with the driver mass DR. As can be appreciated, the center node is equidistant between the end nodes defined by the anchors 764 and is therefore symmetrically located. The second bend mode plot 732c illustrates an approximate location of nodes where the second bend mode plot 732c is at zero displacement, which are also symmetrically located on the conduit. Non-nodal locations of a given vibration mode can be determined where the first bend mode plot 732a, twist mode plot 732b, and second bend mode plot 732c are non-zero. The locations relative to the conduit location axis 712 of maximal displacement of the first bend mode plot 732a, twist mode plot 732b, and second bend mode plot 732c may be referred to as antinodes. The three degree of freedom model 704 is a simplified model of a conduit of a sensor assembly developed to illustrate the use of two or more vibration modes. The three degree of freedom model 704 representation lumps the mass, stiffness and damping of a conduit into a system that may be simple to analyze. The three lumped masses LPO, RPO, DR represent the pickoffs and driver of a conduit. Values for mass, stiffness and damping were chosen so that the modal frequencies are like those of an actual sensor assembly. Accordingly, FIG.7 depicts the three degree of freedom model 704 and its mode shapes in the mode shape graph 702. Mode 1 represents the first bending mode, the traditional mode which is driven. Mode 2 represents the first twist mode. Mode 3 is a higher mode which can be driven by the same driver that drives Mode 1. Mode 3 and Mode 1 can also be driven simultaneously as the following discussion illustrates. FIG. 8 shows a graph 800 illustrating adding two signals having different frequencies. As shown in FIG.8, the graph 800 includes a time-axis 810 and a magnitude axis 820, which may be in any suitable units. The graph 800 also includes three signals 830. The three signals 830 are comprised of a first signal 830a, a second signal 830b, and a third signal 830c. The first and second signals 830a, 830b are shown as being sinusoidal signals respectively having a first and second frequency f1, f2. The first signal 830a may be a first mode signal or, with more particularity, a mode signal associated with a first vibration mode. The second signal 830b may similarly be a second mode signal associated with a second vibration mode. For example, the first mode may be a first bend mode and the second mode may be a second bend mode. The third signal 830c is shown as being comprised of a summation of the first and second signal 830a, 830b. For example, a mixer may be employed to receive an input and mix the first and second signal 830a, 830b to obtain the third signal 830c. Accordingly, the third signal is not a simple sinusoidal signal but instead is a signal having two sinusoidal components at the first and second frequency f1, f2. It should be appreciated that the three signals 830 may drive signals that are provided to a sensor assembly. For example, a drive circuit in the meter electronics 20 described above may be configured to generate the first and second signals 830a, 830b and mix the first and second signals 830a, 830b to obtain the third signal 830c. The third signal 830c may be provided to a sensor assembly, such as the sensor assembly 10 described above with reference to FIGS. 1 and 2. It should be appreciated that the first signal 830a and the second signal 830b may be generated based on a feedback from the sensor assembly. That is, a feedback loop may receive and process signals corresponding to two or more vibration modes. Accordingly, the first and second signal 830a, 830b may be provided to the sensor assembly simultaneously to drive the first and second out of phase bend modes shown in, for example, FIGS.5A, 6A and 5C, 6C. However, it should be appreciated that non-simultaneous signals may be provided. Additionally, or alternatively, a drive signal that drives a twist mode may be provided, as the following discussion explains. Twist mode circuit FIG. 9 shows a vibratory meter 905 configured to have a driven twist mode for determining a process related parameter based on two or more vibration modes. As shown in FIG.9, the vibratory meter 905 is comprised of the sensor assembly 10 described with reference to FIGS.1 and 2. That is, the sensor assembly 10 includes the driver 180 that is located equidistant between the left and right pickoff sensors 170r, 170l. The sensor assembly 10 is communicatively coupled with the meter electronics 920. As will be explained in more detail in the following, the meter electronics 920 is configured to provide a drive signal that drives a twist mode in the sensor assembly 10, rather than the first and / or second out of phase bend mode that may be provided by the meter electronics 20 described with reference to FIGS.1 and 2. The meter electronics 920 shown in FIG. 9 includes all the components described with reference to FIG.2. However, the meter electronics 920 shown in FIG.9 also includes a signal switch 902 that connects the drive signal output of the signal conditioner 240 with the left pickoff sensor 170l and the driver 180 with the left pickoff sensor input of the signal conditioner 240. This connection may be referred to as a “twist mode” configuration and is shown in FIG.9. As can be appreciated, in the “twist mode” configuration, the meter electronics 920 provides a drive signal to the left pickoff sensor 170l and the driver 180 provides a pickoff sensor signal to the meter electronics 920. The pickoff sensor signal provided by the driver 180 to the meter electronics 920 is proportional to a displacement parameter of the conduit at the location of the driver 180. It should be appreciated that the drive signal provided to the left pickoff sensor 170l may be a sinusoidal signal having a frequency that is a fundamental frequency of the twist mode. As can be appreciated, the signal switch 902 is part of the meter electronics 920. However, other switches do not need to be part of the meter electronics 920, as the following explains. FIG. 10 shows a switching circuit 1000 for driving a twist mode in a sensor assembly. As shown in FIG. 10, the switching circuit 1000 is comprised of first connector 1001 coupled with a second connector 1003. The first and second connector 1001, 1003 are shown as being disposed electrically and mechanically between a sensor assembly and a meter electronics. Relay switches 1002 are disposed between the first and second connector 1001, 1003. Accordingly, that is, in contrast to the switch 902 of meter electronics 920 described with reference to FIG. 9, the switching circuit 1000 is not part of the meter electronics. As can be appreciated, the switching circuit 1000 can therefore be coupled to an existing meter electronics without requiring a new meter electronics, such as the meter electronics 920 described with reference to FIG. 9. As shown in FIG. 10, the switching circuit 1000 is comprised of meter electronics side circuits and sensor assembly side circuits where a given circuit loop (including the meter electronics and sensor assembly not shown), such as a left pickoff circuit loop and a driver circuit loop, includes the relay switches 1002. If a circuit loop does not include the relay switches 1002, then the terms “meter electronics side” and “sensor assembly side” are not used for circuit loops that do not include a relay switch. An ‘X’ in a circuit label indicates that a circuit is on the meter electronics side of the relay switches 1002. Accordingly, the switching circuit 1000 is shown as including a meter electronics side left pickoff circuit XLPO + / - and a meter electronics side driver circuit XDRIVE + / -. Also shown is a right pickoff circuit loop RPO+ / - and a resistive temperature circuit loop(s) RTD-HI / LO / SENSE, which do not include relays. It should be appreciated that alternative switching circuits may include relays in the right pickoff circuit loop RPO+ / -, additional or alternative to the left pickoff circuit loop shown in FIG.10. The relay switches 1002 are shown as being comprised of a first and second relay switch 1002a and 1002b, although more or fewer and / or alternative relay switches may be employed. As shown in FIG.10, the relay switches 1002 temporarily swap the meter electronics side left pickoff circuit XLPO + / - with the meter electronics side driver circuit XDRIVE + / - by intercepting the 9-wire connection between the meter electronics and sensor assembly. This allows a drive signal from the meter electronics side driver circuit XDRIVE + / - to apply a forcing function via the sensor side left pickoff circuit LPO+ / - to the sensor assembly or, more specifically, a conduit or conduits, at the LPO location rather than solely at the driver location. Due to the LPO not being at a node of the twist mode, the twist mode may therefore be excited. With more particularity, a drive or first bend mode on the sensor assembly 510 is illustrated in FIGS.5A and 6A by the symmetrically placed driver 518 in the center of the conduits 513, 513’. However, providing the drive signal to the driver 518 is not able to excite the twist mode shown in FIGS. 5B and 6B. This is because the driver 518 is located at a node of the twist mode at which the conduits 130, 130’ do not have motion. The left and right pickoffs 170l, 170r, however, may, for example, be located near the location of maximum motion of the conduits 130, 130’ in the twist mode, making it an ideal place to excite the twist mode. As shown in FIG. 10, swapping of the meter electronics side left pickoff (LPO) circuit XLPO + / - with the meter electronics side driver circuit XDRIVE + / - is achieved with the relay switch 1002 controlled through the discrete outputs (DO) of the meter electronics indicated by CHA+ / -. However, using the DO is not necessary to control relays as other signals may be employed in other relays. Referring to FIG.10, when the DO is off, the sensor assembly 510 is the drive mode shown in FIGS. 5A and 6A, but when the relay switches 1002 are activated, the drive signal from the meter electronics is routed to the left pickoff 170l on the sensor assembly 510 and the sensor signal from the driver 180 is routed to meter electronics via the meter electronics side left pickoff circuit XLPO + / -. It should be appreciated that the twist mode is excited and measured by changing the drive target for the drive signal and digital signal processing (DSP) filter parameters to the range expected for a given sensor assembly and pickoff sensors, such as the left and / or right pickoff sensors 517l, 517r, are measured. Accordingly, the frequency can be measured quickly, and the vibratory meter can be switched back to normal operation with minimal interruption. It should also be appreciated that the relay switches 1002 do not induce a zero to the vibratory meter and do not impact performance during first bend mode operation shown in FIGS. 5A and 6A. When the drive signal is provided to the left pickoff sensor, the single drive signal is provided to an asymmetrical location of the conduit. That is, the forcing function of the drive signal is provided at a location that is not at a center location of the conduit. Similarly, the sensor signals obtained from the driver and the right pickoff sensor are obtained from asymmetrical locations in that they are not equidistant from the center location of the conduit or respectively proximate end nodes. It also should be appreciated that being able to measure the instantaneous twist mode frequency allows for insights into countless characteristics of the process parameters including pressure, speed of sound, viscosity, etc. This may be especially useful because it does not require any alterations to current sensor assembly or meter electronics design, and it can be added to vibratory meters already in use. In addition, the foregoing explains that the two or more vibration modes may be simultaneously or alternately driven. For example, a meter electronics may drive the sensor assembly in a first bend mode for a time span, predetermined, conditional, or the like, and then switch to a second bend mode for a second time span. As can be appreciated, this ability to switch between various vibration modes can be beneficial in other ways, as the following discussion explains. Sensor crosstalk FIG. 11 shows a multi-sensor assembly system 1100. As shown in FIG.11, the multi-sensor assembly system 1100 is comprised of a first and second vibratory meter 1105a, 1105b. The first and second vibratory meter 1105a, 1105b are respectively shown as being comprised of a sensor assembly 1110a, 1110b communicatively coupled with a meter electronics 1120a, 1120b. It should be appreciated that the two sensor assemblies 1110a, 1110b may respectively be referred to as a first sensor assembly and a second sensor assembly. Similarly, the two meter electronics 1120a, 1120b may respectively be referred to as a first meter electronics and a second meter electronics. Alternatively, the two meter electronics 1120a, 1120b may be a single meter electronics that provides and / or receives sensor and / or drive signals to and / or from the two sensor assemblies 1110a, 1110b. Also shown in FIG. 11, is a processor 1121 illustrated as a dashed box, which may or may not be distinct from the two meter electronics 1120a, 1120b. For example, the processor 1121 may be a real and / or virtual processor, whether a single, multiple, distributed, and / or the like instance, that utilizes resources, such as memory, processing, signal processing, and / or the like, of the meter electronics 1120a, 1120b. When the first sensor assembly 1110a vibrates in a vibration mode, such as a first vibration mode, the vibration mode may inadvertently couple to the second sensor assembly. That is, the first sensor assembly 1110a can induce a particular vibration mode in the second sensor assembly. Similarly, the second sensor assembly 1110b can induce a particular vibration mode in the first sensor assembly. When the two sensor assemblies 1110a, 1110b are being driven in at or about the same frequencies, crosstalk or, with more particularity, vibration mode crosstalk can occur. The vibration mode crosstalk can occur between any two sensor assemblies that are mechanically coupled together, directly or via intervening structures, such as piping. For example, although the first and second sensor assembly 1110a, 1110b are shown as fluidly connected in series, alternative multi-sensor assembly systems may employ parallel and / or series arrangements of their sensor assemblies. The vibration mode crosstalk can cause performance issues, such as inaccurate measurement values, or other undesirable results. As can be appreciated, preventing two vibratory meters from operating at the same frequency can prevent such undesirable results. Accordingly, the processor 1121 may be configured to coordinate between the two vibratory meters. As discussed above, multiple vibration modes may be driven in a sensor assembly, such as the sensor assemblies 10, 510 described with reference to FIGS. 1 and 2, and FIGS.5A through 6C. For example, the first and second bend mode may be induced by the meter electronics 20, 920 described with reference to FIGS.1, 2, and 9. The first twist mode can be induced by the meter electronics 920 described with reference to FIG.9. With more particularity, a “nominal configuration” can be employed to drive the first and second out of phase bend mode and a “twist configuration” can be used to drive the twist mode. The following illustrates the effect of the twist configuration on the FRFs of the sensor assembly. Frequency response functions FIG. 12 shows an aggregate frequency response function (“FRF”) graph 1200 illustrating FRFs corresponding to the nominal and twist configurations of the meter electronics 920. As shown in FIG.12, the aggregate FRF graph 1200 includes FRF plots 1230. The FRF plots 1230 include a first FRF plot 1230a, a second FRF plot 1230b, a third FRF plot 1230c, and a fourth FRF plot 1230d. Each of the first through fourth FRF plots 1230a-1230d correspond to a configuration of the meter electronics 920 and a transducer pair used for an FRF ratio. As shown in FIG.12, the FRF ratio is a “Velocity / excitation force” ratio. A legend 1240 illustrates the various configuration and FRF ratios of the FRF plots 1230. As shown in FIG. 12, the configurations of the meter electronics 920 may be “nominal” and “twist.” The “nominal” configuration refers to the drive signal being provided to the driver 180 of the sensor assembly 10. The “twist” configuration refers to the drive signal being provided to the LPO sensor 170l. The FRF ratios illustrate which transducer receives the driver signal and which is used for the “velocity” value in an FRF ratio. As shown in FIG.12, the FRF ratios include “LPO / DRV”, “RPO / DRV”, “DRV / LPO”, and “RPO / LPO.” The “LPO / DRV” label indicates that the “velocity” is determined from the LPO sensor 170l and the drive signal is provided to the driver 180. This is consistent with the “nominal configuration” of the meter electronics 920, which provides a drive signal to the driver 180. As can be appreciated, in the “nominal configuration,” the meter electronics 920 may determine the “velocity” of the FRF ratio based on either the LPO or RPO signal. Accordingly, the legend 1240 also includes a “Nominal – RPO / DRV” line. As can be appreciated, the first FRF plot 1230a corresponds to the nominal configuration with an LPO / DRV FRF ratio and the second FRF plot 1230b corresponds to the nominal configuration with an RPO / DRV FRF ratio. Accordingly, the first and second FRF plots 1230a, 1230b correspond to the nominal configuration where the numerator of the FRF ratio is based on the LPO signal or the RPO signal. The third FRF plot 1230c corresponds to the meter electronics 920 being in a twist configuration, where the drive signal is provided to the LPO sensor 170l, and the driver 180 provides a sensor signal that is used to determine the “velocity” of the FRF ratio. The fourth FRF plot 1230d also corresponds to the twist configuration of the meter electronics 920, but the velocity of the FRF ratio is determined based on the RPO signal provided by the RPO sensor 170r. As can be appreciated, the LPO sensor 170l is not shown as providing a sensor signal when the meter electronics 920 is in the twist configuration, which may be due to the LPO sensor 170l being switched to the drive signal. The FRF plots 1230 shows that a transducer not positioned at a node of a given normal mode can measure and / or excite the given normal mode. So, in a sensor assembly having a centrally located driver with two symmetrically offset pickoff sensors, the centrally located driver is at a node of the first order twist mode. Hence, a mostly flat response with a very narrow response at about 520 Hz is observed when the driver DRV is a numerator or denominator of the FRF ratio. Conversely, when the left pickoff LPO provides the forcing function and the right pickoff RPO measures the velocity, the twist mode is evident at the same frequency. The FRF plots 1230 also show that the magnitudes of the first order bend mode are essentially the same at the right pickoff sensor RPO for either the “nominal” or “twist” configuration of the drive circuit. Accordingly, the same calibration factors can be used to determine density when the drive signal is provided to the left pickoff sensor LPO or the driver DRV. Additionally, the “switching” between the left pickoff sensor LPO and the driver DRV only affects the ability of the drive circuit to drive the twist mode. That is, the first order bend mode may have a temporally constant amplitude if the drive signal is at a fundamental frequency of the first order bend mode even if the drive signal is provided to the LPO sensor. Therefore, the drive circuit may be unaffected in that the RPO sensor may measure an amplitude of the bend modes and / or the twist modes. As can also be appreciated from the FRF plots 1230, damping is present at the twist mode frequency, which can determine how quickly an excited vibration mode will settle out after excitation is stopped. Accordingly, an amplitude of a twist mode driven by the “twist” configuration could settle relatively quickly after switching back to the “nominal” configuration. It should also be appreciated that all of the normal modes can be excited when the drive circuit is in the “twist” configuration, such as that shown in FIG.9. That is, as a frequency of the drive signal provided to the LPO sensor 170l is swept from 0 Hz to 2000 Hz, the first and second bend modes as well as the first and second twist modes are excited. This is due to the LPO and RPO sensors 170l, 170r not being at nodes of the bend or twist modes. In addition, although the LPO sensor 170l is not at a central location of the conduits 130, 130’ and therefore a forcing function is applied at an asymmetrical location relative to the central node of the first twist mode, the central node of the first twist mode is at the central location corresponding to the driver 180, as the following discussion demonstrates. FIG. 13 shows a graph 1300 illustrating sensor signals plotted in a time domain when an asymmetrical forcing function is applied to a conduit. As shown in FIG. 13, the graph 1300 includes a time axis 1310 and a magnitude axis 1320 respectively in units of milli-seconds (ms) and volts (V), although any suitable units may be employed. Also shown are sensor signal plots 1330 comprising an RPO pickoff sensor signal plot 1330a and a driver sensor signal plot 1330b. The term “driver sensor signal plot” refers to a driver connected to a meter electronics in a “twist mode” configuration so as to provide a sensor signal to the meter electronics, such as the “twist mode” configuration described above with reference to FIG.9. A magnitude of the sensor signal plots 1330 indicates an amount of physical displacement of the conduit at the location of the RPO sensor and the driver. As can be appreciated, the RPO pickoff sensor signal plot 1330a indicates a displacement of the conduit at the RPO sensor location. The magnitude of the RPO pickoff sensor signal plot 1330a ranges from about 1.5 to -1.75 volts. However, the magnitude of the driver sensor signal plot 1330b ranges from 0 to about 0.2 volts. That is, the magnitude of the driver sensor signal 1330b indicates that there is about or effectively zero displacement of the conduit at the driver location of the conduit. Accordingly, it should be appreciated that although the forcing function is applied to the conduit at an asymmetrical location, the first twist mode is not distorted by, for example, a near static displacement. The twist mode can be used to predict a calibration factor or constant, such as the FCF described above with reference to Equation [1]. With more particularity, the FCF may be correlated with a stiffness of a conduit. A magnitude of the phase difference between the periodic amplitudes of the two pickoffs is related to the twist motion of the tubes induced by a Coriolis force that is generated by the motion of the material through the oscillating conduits in a vibratory meter. The extent of the twist motion, in turn, will be dictated by the stiffness of the tube geometry to this induced twisting motion. Hence, the FCF will be related to the stiffness of the conduit geometry to the first twist mode motion. As discussed above, the FCF relates the mass flow through the Coriolis meters to the magnitude of the phase difference between the periodic amplitudes at the two pickoffs. Determining the FCF can require a significant amount of time. In addition, some vibratory meters must meet stringent flow rate accuracy. Accordingly, being able to predict which vibratory meter, manufactured but not yet calibrated, may meet the stringent requirement can ensure that calibration time is not consumed on a vibratory meter that will not meet the requirement. In addition, determining an FCF without requiring the calibration could reduce manufacturing costs by a significant amount. By driving a first twist mode as described above, or by other techniques, an additional measurement of this twist mode frequency at the diagnostic stand to better predict FCF for a vibratory meter may be obtained. This additional measurement at a diagnostic stand may be relatively easy to implement and may not significantly increase testing time. The elimination of FCF calibration for most units during the calibration stage will reduce the time for calibration significantly, without significantly adding additional measurement time at the diagnostic stand. This is above and beyond any possible savings that may be attained by using the additional twist mode frequency measurement to sort and bin the meters appropriately to increase their probability of passing different (as per the customer order) mass flow error specifications. It should be appreciated that the foregoing discussion of multiple modes in a vibratory meter may depend somewhat on a conduit that has no deposits, erosion, corrosion, and / or the like. In addition, it should also be appreciated that the different vibration modes can be used for meter verification at about their respective frequency ranges, as the following discussion illustrates. Meter verification Meter verification is a process that can verify whether or not vibration parameters of a sensor assembly have been affected by changes affecting the sensor assembly. Exemplary changes that affect a sensor assembly include erosion, corrosion, deposits, etc. Performing meter verification in two or more modes can provide additional diagnostic information about a vibratory meter. This information can be used on its own in the manner currently used in traditional meter verification. It could also be used in conjunction with the meter verification information about the traditional drive mode. The description below shows how meter verification can be used in two vibration modes to identify and track the characteristic stiffness, damping, or other parameters determined from each driven vibration mode. FIG. 14 shows a drive signal frequency spectrum graph 1400. As shown in FIG. 14, the drive signal frequency spectrum graph 1400 includes a frequency axis 1410 in units of hertz (Hz) and a drive signal amplitude axis 1420 that is unitless, but may be in units of volts, current, velocity (correlated), etc. The frequency axis 1410 ranges from zero to 800 hertz although any suitable range can be employed. The drive signal frequency spectrum graph 1400 includes a first drive signal plot 1430a and a second drive signal plot 1430b. As can be appreciated, the first and second drive signal plots 1430a, 1430b are in the frequency domain. As can also be appreciated, the first and second drive signal plots 1430a, 1430b are comprised of sinusoidal or tone components. With more particularity, the first and second drive signal plots 1430a, 1430b include a resonant frequency drive component and four offset test tones. The resonant frequency drive component may be generated based on a feedback loop that uses a fundamental frequency of a corresponding vibration mode. For example, the first and second drive signal plots 1430a, 1430b may respectively include a resonant frequency drive component that is based on a sensor signal that includes a fundamental frequency of a first vibration mode and second vibration mode. Accordingly, the first and second drive signal plots 1430a, 1430b may respectively correspond to a first vibration mode and a second vibration mode. As discussed above, a first vibration mode may be a first bend mode and a second vibration mode may be a second bend mode. FIG. 15 shows frequency response function 1500 for determining a process related parameter from two or more vibration modes. As shown in FIG.15, the frequency response function 1500 is comprised of a first frequency response graph 1500a and a second frequency response graph 1500b. The first and second frequency response graphs 1500a, 1500b are respectively comprised of frequency axes 1510a, 1510b and magnitude axes 1520a, 1520b. The frequency axes 1510a, 1510b range from zero to 1000 hertz (Hz), although any suitable range and units may be employed. The magnitude axes 1520a, 1520b are response-to-forcing function ratios (X / F) and are not shown with units but may be in any suitable unit. The magnitude axes 1520a, 1520b range from 10-9to 10-4, although any suitable range or ranges may be employed. The first and second frequency response graphs 1500a, 1500b also include a frequency response function plot 1530. As can be appreciated, the frequency response function plot 1530 include a first, second, and third fundamental frequency peak 1530a, 1530b, 1530c indicated as “Mode 1”, “Mode 2”, and “Mode 3.” That is, each of the first, second, and third fundamental frequency peak 1530a, 1530b, 1530c respectively correspond to a first, second, and third vibration mode. The first vibration mode may be a first bend mode, the second vibration mode may be a first twist mode, and the third vibration mode may be a second bend mode, although more or fewer and alternative vibration modes and fundamental frequency peaks may be employed. The frequency response function plot 1530 may be obtained by sweeping a frequency of a model of a conduit, such as the three degree of freedom model 704 described with reference to FIG.7. That is, the three degree of freedom model 704 described with reference to FIG.7 can be characterized by its frequency response function (FRF). As shown in FIG.15, the frequency response function plot 1530 provides an FRF of each pickoff LPO, RPO shown in FIG. 7 to harmonic driver excitation from 0 Hz (DC or static) to 1,000 Hz. With more specificity, the frequency response function plot 1530 includes an LPO / Driver FRF plot labeled as “LPO” and the RPO / Driver FRF labeled as “RPO”, which are superimposed. The frequency response function plot 1530 also includes a first mode peak 1530a, a second mode peak 1530b, and a third mode peak 1530c, which respectively correspond to modal or fundamental frequencies of the first through third vibration modes. The frequency response function plot 1530 is shown in both the first and second frequency response graphs 1500a, 1500b. It should be appreciated that a perfectly built and balanced vibratory meter should not have a pickoff response of Mode 2 from driver excitation and thus would not show up on this figure. An imbalance was provided to a model to visualize Mode 2 on the frequency response function plot 1530. Also shown respectively in the first and second frequency response graphs 1500a, 1500b is a first and second single mode-single degree of freedom fits 1540a, 1540b. The first and second single mode-single degree of freedom fits 1540a, 1540b are fitted to the frequency response function plot 1530 according to their respective vibration modes indicated by “Mode 1” and “Mode 3.” The first and second single mode-single degree of freedom fits 1540a, 1540b are shown as superimposed with the frequency response function plot 1530. The first and second single mode-single degree of freedom fits 1540a, 1540b are fitted to the frequency response function plot 1530 and represent a meter verification for the given mode whose parameters are being estimated. The first and second single mode-single degree of freedom fits 1540a, 1540b shows a meter verification fit for the first vibration mode indicated by “Mode 1” and the second single mode-single degree of freedom fit 1540b shows a meter verification fit for the third vibration mode indicated by “Mode 3.” Meter verification may track a change in static stiffness, or other structural characteristics, of a conduit, such as the conduit 130, 130’ described above, in the first bend mode, which may be referred to as a drive mode. As shown in FIG.15, the first bend mode is the first vibration mode indicated by “Mode 1.” The stiffness value may be derived from the value of the single mode single degree of freedom fit of the drive mode where the first single mode single degree of freedom fit 1540a crosses the magnitude axis 1520a at 0 Hz, which are indicated by stars. As can be appreciated, the first and second single mode-single degree of freedom fits 1540a, 1540b for first vibration mode “Mode 1” and the third vibration mode “Mode 3” are different values. These values can and will change if the structure itself changes in a way that affects stiffness or other meter parameter values. As can be appreciated, a meter electronics may provide one or more drive signals according to the first and second drive signal plots 1430a, 1430b to a sensor assembly to obtain the first and / or second single mode single degree of freedom fits 1540a, 1540b, or the like, to determine the stiffness or other sensor assembly properties for detecting if a change has occurred. It should be appreciated from the discussion of FIG.15 that obtaining a fit at or about the fundamental frequency of each mode may not require sweeping an entire frequency range encompassing the fundamental frequencies. For example, as can be appreciated from comparing FIGS.14 and 15, a sectioned or piece wise fit may be obtained with four FRF magnitudes at or about the fundamental frequencies. The following describes meter electronics that can obtain the described and other single mode fits. FIG. 16 shows a block diagram of a vibratory meter 1605 including meter verification using two or more fundamental frequencies. As shown in FIG.16, the vibratory meter 1605 includes a meter electronics 1620 communicatively (e.g., electrically) coupled to a sensor 1610. The sensor assembly 1610 is comprised of two conduits 1613 although only one conduit is shown for clarity. The sensor assembly 1610 also includes an LPO sensor 1617l and an RPO sensor 1617r that are fixed to the two conduits 1613 to measure a relative displacement related parameter between the two conduits 1613. A centrally located driver 1618 is also shown fixed to the two conduits 1613. The LPO sensor 1617l, RPO sensor 1617r, and / or driver 1618 may be configured to receive a drive signal from and / or provide a sensor signal to the meter electronics 1620. The meter electronics 1620 includes a signal circuit 1621 configured to receive sensor signals, such as two sensor signals, from the sensor assembly 1610. The signal circuit 1621 is also configured to provide a drive signal to the sensor assembly 1610. The signal circuit 1621 may include switches, signal conditioning, signal processing, amplifiers, and / or the like that may be employed for signals provided to or from the sensor assembly 1610. For example, the signal circuit 1621 may include a switch that switches a drive signal from the driver 1618 to the LPO sensor 1617l and then provides a sensor signal from the driver 1618 to, for example, filters in the signal circuit 1621 for filtering. The meter electronics 1620 also includes a drive circuit 1622 that provides a drive signal to the sensor assembly 1610. The sensor assembly 1610 is communicatively coupled with and provides sensor signals to the meter electronics 1620. A demodulation filter 1624 receives the sensor signals from the sensor assembly 1610 and passes signals that are within a demodulation window or windows of the demodulation filter 1624. The signals passed by the demodulation filter 1624 are provided to an FRF estimation unit 1625. Notch filters 1626 also receives the sensor signal, which passes a resonant component to the drive circuit 1622 and a flow and density measurement module 1627, which can determine a fluid property value of a fluid. The sensor assembly 1610 receives the multi-tone drive signal from the meter electronics 1620 and provides the sensor signals to the meter electronics 1620 to characterize the sensor assembly 1610. The multi-tone drive signal is therefore an input to a frequency response of the sensor assembly 1610 and the sensor signal is an output of the frequency response of the sensor assembly 1610. By comparing the input and the output, the frequency response of the sensor assembly 1610 may be characterized. Further, an analytical solution may be formulated by, for example, fitting a curve to the characterization of the sensor assembly 1610. As the foregoing discussion illustrates, a vibration mode relationship (e.g., a ratio between fundamental frequencies and / or time-periods of two or more vibration modes, difference, etc.) between the two SDOF fits can provide more diagnostic information about the vibratory meter, in particular the sensor assembly, and how it may have changed. Because different modes have different vibration shapes, and therefore more or less bending action in different locations along the flow tube, meter verification in different modes may be more or less sensitive to erosion or other issues in different locations. For example, the first bend mode may have a significant amount of strain near the brace bar, therefore meter verification should be especially sensitive to erosion proximate the brace bar, while the first bend mode has no strain at the driver location and therefore may not pick up on changes that occurred there. Running meter verification in multiple modes may provide sensitivity to effects like erosion, corrosion, deposition, and / or the like, in various locations of the flow tube where the given mode has mode strain. As can be appreciated from the above discussion referring to, for example, FIG. 12, the vibratory meter may be operated in more than two modes. By way of illustration, the vibratory meter may be operated in a first bend mode, a first twist mode, and a second bend mode. In this example, the three modes could be excited by the meter electronics capable of applying a forcing function at a fundamental frequency of each of the three modes at a non-nodal location on the conduit, such as an asymmetric location of the conduit where the nodes are symmetrically located on the conduit. The meter electronics 920, 1020 described above are able to provide drive signals at the fundamental frequencies and non-nodal locations of the first and second bend mode and the first twist mode, as is explained above. Additionally, or alternatively, the forcing function could be applied to a non- nodal location of an excited mode that is also a nodal location of a non-excited mode. For example, applying a forcing function at a center location of a conduit of a symmetrical sensor assembly, such as to the driver 180, 518 as the sensor assemblies 10, 510 described with reference to FIGS.1 and 5A-5C, at a fundamental frequency of the first order bend mode can excite the first bend mode, but will not excite the first twist mode. In this example, the first twist mode can be asynchronously excited by switching the drive signal having a sinusoidal frequency at a fundamental frequency of the first twist mode to an asymmetric location, such as to the LPO sensor 170l, 517l described above. Process related parameters in two or more modes Not only might it be useful to perform meter verification in two or more modes, but making process measurements in two or more modes may be useful for several reasons. Mass (and volume) flow, density, drive gain, pickoff amplitude, etc., can be measured in the second mode also. A vibratory meter can have better / worse accuracy depending on fluid properties and the given vibratory meter’s operating frequency. Making a flow measurement, for example, in two modes could indicate something about entrained gas, VOS, flow profile, etc. If the flow measurement is the same in both modes, the ratio of measured flow rates should be 1. An indication of “1” could mean high confidence in the given measurement. If the ratio goes up or down it may indicate the presence of any number of field effects like entrained gas, VOS, flow profile, etc. Depending on knowledge of the application, the vibratory meter could be configured to use the most accurate mode of vibration for a particular application. For example, entrained gas is known to cause greater errors at higher frequency, thus the lower mode could be used exclusively when entrained gas is detected, for example by a high drive gain reading. Other challenges include temperature gradients from, for example, sunlight on the case, compressible fluids, mode interaction, pipeline or installation stress, pipeline compression, etc. Other uses of making process measurements in two or more vibration modes may include detection of an entrained gas or wet gas state, detection or correction of velocity of sound errors in compressible fluids, detection of zero stability problems (stiffer, higher frequency modes have shown to have more stable zeroes in some situations), etc. Pressure As will be explained in more detail in the following, various process-related parameters may be correlated with a vibration mode parameter relationship. As discussed above, a vibration mode parameter relationship may be a ratio, difference, and / or the like between parameters of two different vibration modes. For example, a frequency ratio of a first and second vibration mode can be a vibration mode parameter relationship. A given vibration mode parameter relationship can be correlated with a process-related parameter, such as a pressure or temperature, or gradients or differences thereof. It should be appreciated that other process-related parameters may also be correlated with a vibration mode parameter relationship if, for example, the process- related parameter, or its gradient, or the like, induces a stress in a conduit of a vibratory meter, as the following explains by using pressure as an example. FIGS. 17 and 18 show pressure versus frequency ratio graphs 1700, 1800 for determining a process related parameter based on two or more vibration modes. As shown in FIGS.17 and 18, the pressure versus frequency ratio graphs 1700, 1800 included frequency ratio axes 1710, 1810 that are unitless. As shown in FIGS.17 and 18, the frequency ratio axes 1710, 1810 are values representing frequency ratio of a fundamental frequency of a first mode and a second mode. The pressure axes 1720, 1820 are pressure at which the frequency ratios are determined. The frequency values of the fundamental frequencies of the first and second mode may be determined from, for example, a drive signal after resonance is achieved (e.g., when drive gain is less than a threshold value that indicates resonance). As shown in FIGS. 17 and 18, the first mode is a first bend mode and the second mode is a second bend mode, although any suitable mode or orders of modes may be employed. For example, alternative frequency ratios may be employed. In FIG. 17, the calibration is performed with water and in FIG.18 the calibration is performed with nitrogen. That is, the calibration is performed with air / air equivalent or water contained by the conduit at various pressures to obtain a water pressure versus frequency ratio data plot 1730 and a nitrogen pressure versus frequency data plot 1830 respectively shown in FIGS.17 and 18. It should be understood that any suitable density points can be employed. For example, materials other than air, nitrogen, and water may be employed as calibration fluids. As can be appreciated, the water pressure versus frequency ratio data plot 1730 and the nitrogen pressure versus frequency data plot 1830 are substantially linear. That is, the pressure and the frequency ratio have a linear relationship. Accordingly, FIGS. 17 and 18 also respectively include a water pressure versus frequency ratio relationship plot 1740 and a nitrogen pressure versus frequency relationship plot 1840 which may be obtained by, for example, linear regression although any suitable method may be employed. As can be appreciated, an estimated pressure can be accurately determined from a ratio of two vibratory mode fundamental frequencies. That is, a pressure can be determined from the water pressure versus frequency ratio relationship plot 1740 or nitrogen pressure versus frequency relationship plot 1840. As can also be appreciated from the foregoing discussion, the water pressure versus frequency ratio relationship plot 1740 and the nitrogen pressure versus frequency relationship plot 1840 may be sufficiently accurate for only water or nitrogen. That is, the water pressure versus frequency ratio relationship plot 1740 and the nitrogen pressure versus frequency relationship plot 1840 may respectively only be used if the conduit contains either water or nitrogen. Additionally, process parameters other than pressure may affect a frequency ratio of a conduit. Temperature FIG. 19 shows a sectioned perspective view of a temperature differential model of a sensor assembly 1910 for a vibratory meter. As shown in FIG. 19, the sensor assembly 1910 includes a single conduit 1913 due to the sectioned perspective view but is a dual conduit design. Accordingly, the conduits of the sensor assembly 1910 will refer to conduits 1913 in plural although only a single conduit is shown. A driver 1918 and left and right pickoff sensors 1917l, 1917r are affixed to the conduits 1913. The sensor assembly 1910 also includes manifolds 1915, 1915’ affixed to the conduits 1913. Proximate but spaced apart from the manifolds 1915, 1915’, the conduits 1913 are affixed to each other with brace bars 1914, 1914’. The brace bars 1914, 1914’ define vibration nodes for all vibration modes of the conduits 1913. Flanges 1903, 1903’ are affixed to the manifolds 1915, 1915’. The sensor assembly 1910 also includes a case 1902 that surrounds and encapsulates the conduits 1913 and is mechanically affixed to the manifolds. FIG.19 shows a FEM where a set temperature is applied to the conduits 1913 (left side of FIG. 19) and the case 1902 (middle of FIG.19), and the resulting steady state thermal distribution on the entire FEM resulting from a given thermal gradient. Referring to FIG.19, the FEM is indicated by circular marks where the temperature is applied to the conduit 1913 and case 1902, and the resulting steady state thermal distribution on the entire FEM resulting from a given thermal gradient. During FEM, this thermal distribution was applied as a preload to the normal modes analysis. The following discusses parameters, results and assumptions of the analysis. FIG. 20 shows a thermal operating graph 2000 illustrating possible operating ranges of the sensor assembly 1910. As shown in FIG. 20, the thermal operating graph 2000 includes a process temperature axis 2010 and an ambient temperature axis 2020, both of which are shown in units of temperature. The scales of process temperature axis 2010 and an ambient temperature axis 2020 are in both Fahrenheit and Celsius where the temperature in Celsius is in parentheses. The process temperature axis 2010 ranges from -400 ºF to 400 ºF, although any suitable range may be employed. The ambient temperature axis 2020 axis ranges from -148 ºF to 140 ºF, although any suitable range may be employed. Also shown are labels “A”, “B”, and “C” for temperature regions. Region “A” is a high temperature region where the process temperatures may be considered “normal” for a given nominal ambient temperature application, region “B” may be considered for high process-low ambient temperature applications, and region “C” may be considered for cryogenic processes in nominal ambient temperatures. A temperature gradient in a sensor assembly may correspond to a temperature difference between an ambient temperature and a process temperature. Locations where corners of each region “A” through “C” intersect are indicated with numbers “1” through “4” in box labels. The points indicated as “1” and “2” may represent the most extreme temperature gradients of normal process temperatures in nominal ambient conditions. That is, points “1” and “2” represent the most extreme temperature differences a given sensor assembly may encounter. Point “1” may be a low process- high ambient temperature application coordinate 2030a and point “2” may be a low ambient-high process temperature application coordinate 2030b. As can be appreciated, it may be a reasonable assumption that points “1” and “2” may represent the most significant stress conditions for a sensor assembly. Simulations of these conditions were performed on the sensor assembly 1910 shown in FIG. 19. FIG. 21 shows a pressure-temperature versus frequency ratio graph 2100 for determining a process related parameter based on two or more vibration modes. The pressure-temperature versus frequency ratio graph 2100 can be obtained from FEM (see FIG.19) analysis results. As shown in FIG. 21, the pressure-temperature versus frequency ratio graph 2100 includes a frequency ratio axis 2110 and a pressure axis 2120. As shown, the frequency ratio axis 2110 is unitless and the pressure axis 2120 is in units of pounds-per-square inch (psi). The frequency ratio axis 2110 ranges from 5.2 to 5.45, although any suitable range may be employed. The pressure axis 2120 ranges from zero to 1600 psi although any suitable range may be employed. Also shown in FIG. 21 are pressure-temperature versus frequency ratio calibration plots 2130 comprised of a first set of pressure-temperature versus frequency ratio calibration plots 2130a and a second set of pressure-temperature versus frequency ratio calibration plots 2130b. The first and second set of pressure-temperature versus frequency ratio calibration plots 2130a, 2130b are respectively performed with air and water. The pressure calibration graph 2100 includes a legend to assist in interpreting the pressure- temperature versus frequency ratio calibration plots 2130. As indicated in the legend 2140, the first pressure-temperature versus frequency ratio calibration plots 2130a are obtained by using air as a material in the conduit, which, according to the legend 2140, are indicated by square shaped end points on the lines. The legend 2140 also indicates that the second pressure-temperature versus frequency ratio calibration plots 2130b are obtained by using water in the conduits 1913. The second pressure-temperature versus frequency ratio calibration plots 2130b are indicated by circle shaped endpoints on the lines. Labels in the legend 2140 also indicate what temperature a given plot or line was obtained at. With more specificity, the labels n100, p21, and p204 respectively indicate -100 ºC, 21 ºC, and 204 ºC, which are indicated in the parentheses of thermal operating graph 2000. Referring to FIG. 21, the points and lines appearing in the graph 2100 in the pressure-temperature versus frequency ratio calibration plots 2130 present the output of normal modes analyses conducted on a Finite Element Model (FEM) of the sensor assembly 1910 shown in FIG. 19. This FEM was subjected to various thermal scenarios defined by an operating environment described in FIG.20. The thermal analyses were conducted with ambient gage pressure (0 PSIG) and 1500 PSI gage inside the conduits 1913 as well as for internal fluid mass density of ambient air and water. Referring to FIG.20, the specific thermal environments whose analysis output is given in the graph are labeled “1” and “2” in the upper left figure. Specifically, at point “1”, the conduit 1813 temperature was -100 ºC and the ambient or case 1902 temperature was 60 ºC. At point “2”, the conduit 1913 temperature was 204 ºC and the ambient or case 1902 temperature was -40 ºC. These two points represent the greatest thermal gradients between the process or conduit 1913 and ambient or case 1902. As can be appreciated from FIGS.19-21, it is possible to observe a shift in the frequency ratio when high temperature gradients exist between the process fluid and the ambient temperature. For example, the sensor assembly 1910 might see a shift in frequency ratio (regardless of pressure) when process and ambient temperature conditions vary from point 1 through 4 of the thermal operating graph 2000 shown in FIG.20. It should be understood that FIG.21 represents a linear regression between two pressure points of zero and 1500 psig, although more and / or alternative pressure points may be employed. For example, one or more intermediate pressure values (e.g., 750, 250, etc., and / or the like) may be employed to identify any non-linearities. Additionally, or alternatively, extrapolation may be employed. For example, the pressure-temperature versus frequency ratio calibration plots 2130 may be extrapolated to higher and / or lower pressures than shown in FIG.21. As can also be appreciated, various process-related parameters can affect a stress in the conduits 1913 and therefore various process-related parameters can affect a vibration mode parameter relationship, such as a frequency ratio between a first and second bend mode. The following explains how, for example, pressure can be determined despite various other process-related parameters affecting the vibration mode parameter relationship. Quantitative effects Quantitative effects of various process parameters may be determined using analytical techniques on empirical data; for example, a multi-dimensional least-squares fit (which may be referred to as “multiple linear regression”) between several measured parameters from a vibratory meter, such as the vibratory meters described above to estimate the pressure in the flow path. Such a technique can generally be used to identify the sensitivity of a desired output to various inputs and the relative importance of each input. The method described below aims to include only inputs and effects that make sense from a physical standpoint, though the method can be applied broadly using effects that may not have physical meaning. Multiple linear regression can be expressed as:^ = ^^ ^ ^^^^ ^ ⋯ ^ ^^^^ ^ ⋯ ^ ^^^ ^^^^ ^ ^ #, for j = 1 to NVAR;Equation [3]where:^ is a response variable;^^ is a jth predictor variable;^^ is the average effect on ^ of an increase in ^^ predictor variable, holding allother predictors fixed; NVAR is the number of predictor variables; and#is an error term.In multiple linear regression, the error term is minimized. As used herein, the response variable ^ and the predictor variables ^^are process related variables. For example, the response variable ^ may be, for example, pressure P, and the predictor variables ^^may include a parameter relationship between two or more vibration modes, such as a frequency ratio FR, temperature T, density ρ, etc. It should be appreciated that the response variable ^ can be something other than pressure P, such as the temperature T. After the coefficients are determined, they can be plugged into Equation [3] to obtainEquation [4] without the error term:^ = ^^ ^ ^^^^ ^ … ^ ^^^^ ^ ⋯ ^ ^^^ ^^"^ ^, for j = 1 to NVAR. Equation [4]Assuming that the pressure can be described by a function of various parameters of a vibratory meter. For example, experimental observations have shown that Frequency Ratio (“FR”), or Tube Period Ratio (“TPR”), noting that frequency and tube period are inversed of one another and “tube” is synonymous with conduit, density ^,and temperature ^ in degrees Celsius correlate to the prediction of internal pressure P:^ = ^^^^, ^, ^^. Equation [5]The frequency ratio FR, density ^, ant temperature ^ are measured by the unit under test (“UUT”), and ^ is the estimated pressure inside the conduits. P is measured by a reference pressure transmitter at time of "calibration" or initial test, and then is predicted in situ once the function on the right side of the equation is determined. It should be appreciated that more, fewer, and / or other parameters than the three parameters being modeled be used for pressure prediction. Pickoff voltage, drive current, Flow Calibration Factor (“FCF”) for each driven mode, Density Calibration Factors (“DCF”) (Kl and K2) for each driven mode, etc., may also be valid inputs to a model for pressure prediction. Expanding the function that describes frequency ratio FR about a nominal operating point (which may be defined or set to zero) with sensitivities to deviations in the changes of the independent variables about the operating point include at least a quadratic term in the frequency ratio FR (e.g., where testing has shown this may be necessary), and consider an interaction between frequency ratio FR and frequency ratioFR, density ^, ant temperature ^. The interaction between density ^ and ant temperature^ will be omitted for this derivation, which may be unnecessary since density ^ mayalready be corrected for temperature ^.^ ≅ ^ ^ ^^^^^^ ^ ^^^^ ^ ^^^^ ^ ^^^ ^ ^^^^ ^ ^^^ ^ ^^^^^^^ ^ ^^^^^ ^^ ^ ^ ^ variables that are experimentally determined. The constant ^ is to be determined. Nominal values are denoted by subscript “0” and can be defined as needed. For the remainder of this derivation the nominal values are set to zero. Further, Equation [6] can be modified to include (or exclude) other combinations of independent variables that may (or may not) make sense and / or have significant sensitivities. Equation [6] can be solved by least-squares once it is properly arranged, and an adequate data set has been collected via testing, as is explained below with reference to FIG.24. Equation [6] can be rewritten using linear algebra to separate the measured values from the unknown sensitivities being identified. ^ì ^ üïï8^9 = [1 ^^ ^ ^ ^^^ ^ ∙ ^^. Equation [7] The measured values will become a large as test data is accumulated. Explicitly, the previous equation will become a data set that looks like:^ì ü^^^ ^ ï^^^ï. on the right: ^ D. With these sensitivities identified, they can be inserted back into Equation [7] for in situ pressure estimation. Accordingly, in a general form, a function relationship may be expressed as: ^= ^^^^, ^^, … ^^ , … , ^^^ ^^; for j=1 to NVAR; Equation

[0010] where:^^ is a jthprocess related parameter; andNVAR is the number of other process related parameters. An example of this form is shown in Equation [5]. A typical "calibration" or characterization test involves connecting the Unit Under Test (UUT) to a pressure source with a given fluid. Frequency ratio FR, density ^ and temperature T are collected from the UUT, and a reference pressure is simultaneously measured. All the measurables are collected while changing pressure throughout a desired range (e.g., up to 100 bar). This may be repeated on fluid with different density as shown in FIGS.17 and 18, and possibly repeated while changing temperature as shown in FIG.20. The data sets can be combined and everything needed to solve for the sensitivities has been measured, as the following discussion illustrates. FIG. 22 shows a multi-parameter time domain relational graph 2200. As shown in FIG. 22, the multi-parameter time domain relational graph 2200 includes a pressure graph 2200a, a frequency ratio graph 2200b, a density graph 2200c, and a temperature graph 2200d. The pressure graph 2200a, frequency ratio graph 2200b, density graph 2200c, and temperature graph 2200d include a common time axis 2210, which is not shown in any particular unit but may be in any suitable unit, such as seconds, sample number, etc. The pressure graph 2200a, frequency ratio graph 2200b, density graph 2200c, and temperature graph 2200d are a test profile for characterizing a pressure estimation based on a mode parameter relationship. Here, the mode parameter relationship is a frequency ratio, shown in the frequency ratio graph 2200b. The pressure graph 2200a is a history of pressure measurements on a per sample basis. The frequency ratio graph 2200b, density graph 2200c, and temperature graph 2200d illustrate measured parameters of a vibratory meter, which is a UUT, which may indicate a response to the pressure in the vibratory meter. FIG. 23 shows a multi-parameter time domain relational graph 2300. As shown in FIG. 23, the multi-parameter time domain relational graph 2300 includes a pressure- pressure error graph 2300a and a density-temperature graph 2300b. The pressure- pressure error graph 2300a and the density-temperature graph 2300b includes common time axis 2310 which is shown as ranging from 0 to about 2700 seconds, although any suitable ranges and / or units may be employed. The pressure-pressure error graph 2300a is shown as including a pressure axis 2320p that ranges from 0 to 1500 pounds-per- square inch gauge (“psig”) and a pressure error axis 2320e ranging from -150 to 150 psig, although any suitable ranges and / or units may be employed. The pressure-pressure error graph 2300a is shown as including a reference pressure plot 2330p, a calculated pressure plot 2330c, and a pressure error plot 2330e. The density-temperature graph 2300b includes a density axis 2320d ranging from 0 to 1 kg / m3 and a temperature axis 2320t ranging from 14 to a little over 24 degrees Celsius, although any suitable ranges and / or units may be employed. FIG. 23 shows raw data from FIG.22 formatted differently and including a pressure error between the reference pressure measurement and the pressure estimation using the above characterization process. The reference pressure plot 2330p data is sampled at a subset of the full data set and is used to "train" the algorithm indicated by circle markers. The training set allows sensitivities to be identified and applied to the full data set for a representative look at the accuracy of the estimate once an equation is implemented. The estimate of the full data set is the calculated pressure plot 2330c. The error between the calculated pressure plot 2330c and the reference pressure plot 2330p is the pressure error plot 2330e. The density-temperature graph 2300b is provided for comparative purposes to illustrate effects of changing the pressure. For example, in density-temperature graph 2300b, increasing the pressure tended to increase a density and temperature of the nitrogen. As can be seen, the pressure error plot 2330e indicates that the error remains within a range of values despite the pressure and temperature varying. It should be appreciated that a given model based on the assumption that ^ =^^^^, ^, ^^ of Equation [5] reflect the most pertinent parameters may not use the sameterms. For example, one or more terms can be dropped. By way of illustration, three slightly different models are provided below for comparison to one another. The models are variations to the model discussed above to illustrate nonlinearity observed between Pressure P and frequency ratio ^^. For the below discussion, temperature has been omitted from the assumption of ^^^^, ^, ^^ serving the basis of the model for brevity.An overview of the three models is given below in Table 1. Table 1. Coefficients for models ^^^^ ^^ ^ ^^ ∙ ^M d l 1 Y Y Y Y Y The results of the models are discussed in the following. FIG. 24 shows a pressure calculation and error relative to a reference pressure graph 2400 for determining a process related parameter based on two or more vibration modes. As shown in FIG. 24, the pressure calculation and error relative to a reference pressure graph 2400 includes a reference pressure graph 2400a, a first pressure calculation error graph 2400b and a second pressure calculation error graph 2400c. The reference pressure graph 2400a is comprised of an elapsed time axis 2410a ranging from zero to 3000 seconds and a pressure axis 2420a ranging from 0 to 1500 psig, although any suitable ranges and / or units may be employed. The first and second pressure calculation error graphs 2400b, 2400c include a common reference pressure axis 2410b, 2410c ranging from -200 to 1600 psig and respective first and second pressure error axes 2420b, 2420c ranging from -100 to 100 psig, although any suitable ranges and / or units may be employed. The reference pressure graph 2400a is the same data as that shown and described with reference to FIGS. 23 and 24, although any suitable data may be employed. The data of the reference pressure graph 2400a is used for Model 1 through Model 3. The first and second pressure calculation error graphs 2400b, 2400c respectively represent pressure error that results for Model 1 and Model 2. That is, the first pressure calculation error graph 2400b are the results obtained from Model 1 and the second pressure calculation error graph 2400c are representative of the results obtained from Model 2. The results of Model 3 are not expressly depicted but are substantially the same as the results obtained from Model 2 with slightly different pressure error versus reference pressure. As can be appreciated from the foregoing discussion, Model 1 is the model whose "Pressure Error" is least nonlinear. It has a full quadratic characterization of pressure P versus frequency ratio FR. Models 2 and 3 leave one of the terms out of this relationship and their "Pressure Error" plots show more nonlinearity, suggesting the Models 2 and 3 are not capturing what Model 1 captures. It should be understood that the error values shown in first and second pressure calculation error graphs 2400b, 2400c may be improved with alternative coefficients, measurement and / or modeling techniques, and / or the like. Turning to the result of Model 1, the Model 1 coefficients are shown in the below Table 2. Table 2. Model 1 coefficients Model 1 coefficients The values shown in Table 2 may be viewed as “raw” coefficients that can be normalized or scaled when implemented. That is, the values shown in Table 2 numbers may not have a physical “feel” and their respective units may be needed to understand their meaning. A process may scale the model space (e.g., convert 0-MAX PSI to 0-1), such that the coefficients can be returned with more consistent values representative of the scaled range. Referring to Table 2, as can be appreciated, the values are large. It should be appreciated that a range of frequency ratios a vibratory meter operates over may be relatively small. Accordingly, a frequency ratio measurement may or may not be an accurate indicator of a particular pressure. As can be appreciated, obtaining a model may be resource intensive. That is, multiple measurements need to be made, as is shown in above Equation [8]. Additionally, FRF characteristics between production units of a given sensor assembly design can be consistent. That is, the FR ratios between production units of the given sensor assembly design can be about the same. Therefore, it may be a valid assumption that a model of a sensor assembly of a given sensor assembly design will be about the same between units of the given sensor assembly design. However, to meet performance specification, calibrations nevertheless need to be performed. The following explains how to obtain an accurate model of a specific sensor assembly using a model of a well- characterized sensor assembly having about the same FR characteristics. FIG. 25 shows a frequency ratio-density graph 2500 for determining a process related parameter from two or more vibration modes. As shown in FIG. 25, the frequency ratio-density graph 2500 includes a density axis 2510 ranging from 0.0 to 1.2 grams-per-cubic centimeter (g / cc) and a second bend mode-to-drive mode frequency ratio ranging from 6.05 to 6.13, although any suitable ranges and units may be employed. The frequency ratio-density graph 2500 also includes pressure variant frequency ratio-density plots 2530 obtained when pressure is at 1500 psi and 0 psi for ideal and measured conditions. In particular, the frequency ratio-density graph 2500 is comprised of an ideal pressure variant frequency ratio-density plots 2530a and a measured pressure variant frequency ratio-density plots 2530b. The pressure variant frequency ratio-density plots 2530 adapts a generalized curve fit relationship for a given Coriolis mass flow sensor and fits it to actual measurements on that specific sensor. It should be appreciated that mode relationships, such as the frequencies of the first and second out of phase bend modes (frequency ratio) shown in FIG.25, can be easily estimated and measured. However, variations between sensor assemblies due to manufacturing tolerances may make calibrating each vibratory meter necessary. Nevertheless, because the sensor assemblies show repeated trends when subjected to pressure, full characterization of the pressure versus frequency ratio may not be required. While these trends can be repeatable, the starting points are not close enough between individual sensors to apply the same model of a vibratory meter to each without calibration. This method may preferably use measurements at two set densities matching the same used in Coriolis density calibration: air (about .001 g / cc) and water (about 1 g / cc). Fitting may also require making those two density measurements at two pressures, such as the 0 psig and 1500 psig shown in FIG.25. It may be assumed and has been found that temperature may not be a significant contributor to this measurement. Nevertheless, it may be preferable that these measurements should be taken at a known and / or constant temperature. As shown in FIG. 25, in ideal situation illustrated by the ideal pressure variant frequency ratio-density plots 2530a, measurements would be taken at these or similar test points: 1.0.001 g / cc, 0 psig (air, low pressure) 2.0.001 g / cc, 1500 psig (air, high pressure) 3.1 g / cc, 0 psig (water, low pressure) 4.1 g / cc, 1500 psig (water, high pressure) As can be appreciated, in this ideal situation, the density value is the same when measured at 1500 psig and when measured at 0 psig. If nitrogen is used as an approximation of air, the base density at 1500 PSI and 20 degrees C is 0.119 g / cc, is far greater than the target of 0.001 g / cc. Therefore, it may be necessary to interpolate and extrapolate to convert the measured data to determine the density and frequency ratio coordinates at the ideal points listed above, which is illustrated by the pressure variant frequency ratio-density plots 2530. Through a combination of computational modeling and / or extensive lab testing, idealized models may be created for various vibratory meters. A model that relates process pressure with other process-related parameters is directly measured by the vibratory meter including frequency ratio and density. These models are morphed to fit the known points for each specific sensor with the relationships of the model being adjusted to fit between the measured points. For example, a model obtained according to Equations [5] through [9] included coefficients for process related parameter variables. These coefficients are essentially slopes for their corresponding process-related parameter variable. By way of illustration, the ^^coefficient is a pressure-density slope for the density variable ^. Accordingly, when all other terms in Equation [7] are held constant, the estimated pressure P varies linearly with respect to the density variable ^. Accordingly, the pressure-density slope of the model can be adjusted with a corresponding slope derived from a simplified calibration described with reference to FIG.25. For example, a pressure-density slope of the model, such as the ^^coefficient, can be adjusted based on a corresponding pressure-density slope derived from a simple calibration process. As can be appreciated, the exact value of the change to the coefficients will be based on all of the process related parameters of the simplified calibration. That is, pressure, density, and frequency ratio 3-tuples derived from FIG.24 can be used as inputs to Equation [7] to obtain adjusted coefficients. This allows for the model to be used with just a few test points rather than needing an extensive battery of lab testing. A particular form of the pressure calculation model may not be important as any model can be adjusted to fit the calibration points measured for each sensor. It should be appreciated that the ideal pressure variant frequency ratio-density plots 2530a may be viewed as normalized from a model. For example, the ideal pressure variant frequency ratio-density plots 2530a may be a model according to above Equation [7]. This is due to the model being obtained using density measurements while also varying a pressure of the fluid in a sensor assembly. It should also be appreciated that models other than linear equations can be used. Additionally, or alternatively, more or fewer and / or different coefficients and / or process-related parameters can be employed. FIG. 26 shows a quadratic term graph 2600 for determining process related parameters based on two or more vibration modes. As shown in FIG.26, the quadratic term graph 2600 includes a frequency ratio axis 2610 and a model calibrated pressure axis 2620 in units of pounds per square inch. The frequency ratio axis 2610 ranges from -2 to 12 and the model calibrated pressure axis 2620 ranges from -2 to 12 psig. The quadratic term graph 2600 includes a quadratic term plot 2630 that is an equation including the first three terms in the above Table 1. The quadratic term plot 2600 also includes a model constant marker 2640 at a frequency ratio FR and calculated pressure coordinate of zero and 733685.3412 psig. Also shown is a Coriolis calculated domain 2650 indicated by circle markers. The quadrative term plot 2600 shows Model 1 over a larger frequency ratio FR range to give context to the model and where the pressure estimate operates within the relatively wide range. FIG. 26 shows the quadratic terms characterizing the relationship between the frequency ratio FR and pressure. The quadratic term plot 2630 is given for context and shows Model 1 plotted over a wide frequency ratio range. The model constant indicated by the model constant marker 2640 signifies the "y-intercept" because the abscissa has a value of zero. The Coriolis calculated domain 2650 representing a Coriolis meter operating domain is also shown within the range. As can be appreciated, the Coriolis meter operating domain occupies a very small portion of the quadratic function. It should be appreciated that that care may need to be taken when employing this method since it will be highly sensitive to how well the model coefficients are characterized. Methods FIG. 27 shows a method 2700 for determining process related parameters based on two or more vibration modes. As shown in FIG.27, the method 2700, in step 2710, may vibrate, with a drive signal, a sensor assembly in a first vibration mode. In step 2720, the method 2700 can vibrate, with the drive signal, the sensor assembly in a second vibration mode. The method 2700 can estimate a process related parameter value based on the first vibration mode and the second vibration mode in step 2730. Estimating the process related parameter value based on the first vibration mode and the second vibration mode can comprise estimating the process related parameter based on a mode relationship between the first vibration mode and the second vibration mode. As is explained above, the mode relationship between the first vibration mode and the second vibration mode can comprise a relationship between parameters of the first vibration mode and the second vibration mode. For example, the mode relationship can comprise one of a ratio and a difference between the first vibration mode and the second vibration mode. The mode relationship between the first vibration mode and the second vibration mode may be comprised of a frequency, time-period, and / or an amplitude of the first and second vibration mode. Additionally, or alternatively, estimating the process related parameter may comprise estimating the process related parameter based on a relationship between the process related parameter and a plurality of other process related parameters. For example, a relationship between a pressure P as a dependent variable and a frequency ratio FR, density ρ, and temperature T as independent variables may be utilized. Accordingly, the relationship between a process related parameter and the plurality of other process related parameters can comprise a function between the process related parameter and the plurality of other process related parameters. By way of illustration, the function relationship may have the form of Equation [4]. The function relationship may be defined as in Equation [6]. Additionally, or alternatively, estimating the process related parameter value based on the first vibration mode and the second vibration mode may comprise calculating the process related parameter value based on a predetermined measured process related parameter value and the first vibration mode and the second vibration mode. For example, calculating the process related parameter value based on a predetermined measured process related parameter value and the first vibration mode and the second vibration mode comprises calculating the process related parameter value based on interpolations between the process related parameter values and vibration mode parameter values. For example, the calculations may be based on interpolations of data shown in FIG.17, 18, and / or 21. It should be appreciated that the process related parameter value estimated based on the first and second vibration mode may be any suitable process related parameter value. For example, the process related parameter value may comprise estimating a pressure value and / or a temperature value. FIG. 28 shows a method 2800 for determining a process related parameter based on two or more vibration modes. As shown in FIG.28, the method 2800, in step 2810, vibrates, with a drive signal, a sensor assembly of a vibratory meter in a first vibration mode. In step 2820, the method 2800 vibrates, with the drive signal, the sensor assembly of the vibratory meter in a second vibration mode. The method 2800, in step 2830, can determine a relationship between a process related parameter and the first vibration mode and the second vibration mode. Determining the relationship between the process related parameter and the first vibration mode and the second vibration mode can comprise minimizing an error # between a model of the relationship between the process related parameter and the first vibration mode and the second vibration mode and a plurality of data points determined based on the first vibration mode and the second vibration mode. Minimizing the error # between a model of the relationship between the process related parameter and the first vibration mode and the second vibration mode and a plurality of data points determined based on the first vibration mode and the second vibration mode comprises minimizing the error # in a multiple linear regression according to Equation [3]. It should be appreciated that each data point of the plurality of data points comprises an ordered sequence of the response variable ^ and the predictor variables ^^. For example, each data point may be an n-tuple of process related parameter values. Additionally, or alternatively, determining the relationship between a process related parameter and the first vibration mode and the second vibration mode can comprise obtaining a plurality of samples of the process related parameters, such as, for example, pressure P, frequency ratio FR, density ρ, and temperature T. The plurality of samples of the process related parameters can therefore, for example, comprise a plurality of samples of the pressure, frequency ratio, density, and temperature (P, FR, ρ, T) data points. That is, the plurality of data point is comprised of a sequence, such as a list, database, etc., of 4-tuples of (P, FR, ρ, T). The plurality of samples of the process related parameters can be obtained from one of an analysis of a finite element model or measurements of the sensor assembly. For example, as is explained above, measurements of the process-related parameters can be made to a real-world sensor assembly and collected and stored as data points to which a fit may be made. Additionally, or alternatively, a physical model, such as a finite element model may be employed in a finite element analysis that includes process related variables, such as, for example, pressure, temperature, fluid, etc., that can be adjusted and / or determined during a simulation. The process related parameter values can be collected as data points to which a model, such as a relationship, may be fit. FIG. 29 shows a method 2900 for determining a process related parameter based on two or more vibration modes. As shown in FIG.29, the method 2900, in step 2910, vibrates, with a drive signal, a sensor assembly of a vibratory meter in a first vibration mode. In step 2920, the method 2900 vibrates, with the drive signal, the sensor assembly of the vibratory meter in a second vibration mode. The method 2900, in step 2930, determines at least one meter verification parameter based on the first vibration mode and the second vibration mode. Determining the at least one meter verification parameter based on the first vibration mode and the second vibration mode can comprise determining a first mode meter verification parameter value and a second mode meter verification parameter value. Determining a first mode meter verification parameter value and a second mode meter verification parameter value may comprise determining a first mode meter stiffness value based on a fit to a first vibration mode frequency response function (FRF) and a second mode meter stiffness value based on a fit to a second vibration mode frequency response function (FRF), such as, for example, the first and second single mode-single degree of freedom fits 1540a, 1540b shown in FIG. 15. It should be appreciated that determining the first mode stiffness value can comprise determining a first mode fit value and a second mode fit value at zero hertz, the first mode fit value being the fit to the first vibration mode FRF and the second mode fit value being the fit to the second vibration mode FRF. Additionally, or alternatively, determining the at least one meter verification parameter based on the first vibration mode and the second vibration mode can comprise determining a first mode stiffness value and determining a second mode stiffness value. The method 2900 may further comprise determining a location of a condition in a conduit of the sensor assembly based on at least one of the first mode stiffness value and the second mode stiffness value. For example, as can be appreciated from the discussion referring to FIGS 14 through 16, a twist mode stiffness value determined based on single mode-single degree of freedom fit to the second mode “Mode 2” shown in FIG. 15 may be more sensitive to changes around the central location of a conduit than a first bend mode stiffness value determined based on first single mode-single degree of freedom fits 1540a shown in FIG. 15. Accordingly, the at least one meter verification parameter can comprise a parameter relationship of a stiffness and / or damping. For example, a ratio of a first bend mode stiffness and a first twist mode may be indicative of a change in a conduit of the sensor assembly proximate a central location of a conduit of the sensor assembly. It should be appreciated that, in the methods 2700, 2800, 2900 described above, nodes of the first vibration mode and nodes of the second vibration mode are located at symmetric positions of a conduit of the sensor assembly. Additionally, the sensor assembly further comprises a driver symmetrically disposed on a conduit of the sensor assembly. The driver being symmetrically disposed on the conduit of the sensor assembly may comprise the driver being disposed equidistance between brace bars coupled to the conduit. The brace bars may define end nodes of the nodes of the first vibration mode and the node of the second vibration mode. The driver being symmetrically disposed on the conduit may comprise the driver being disposed at a node of the nodes of the second vibration mode. The sensor assembly may further comprise a pickoff sensor disposed on the conduit of the sensor assembly, wherein the drive signal is provided to one of the driver and the pickoff sensor. Additionally, or alternatively, vibrating the sensor assembly in the first vibration mode may comprise providing the drive signal to the sensor assembly at a fundamental frequency of the first vibration mode and vibrating the sensor assembly in the second vibration mode may comprise providing the drive signal to the sensor assembly at a fundamental frequency of the second vibration mode. The first vibration mode can be a first bend mode and the second vibration mode can be a second bend mode or a first twist mode. The driver being symmetrically disposed on the conduit of the sensor assembly may comprise the driver being symmetrically disposed between two or more pickoff sensors disposed on the conduit of the sensor assembly. The driver being symmetrically disposed on the conduit of the sensor assembly may be comprised of a single driver affixed to the conduit at a center of a longitudinal length of the conduit. Additionally, or alternatively, the drive signal can apply a forcing function to the conduit at one of a symmetric location and an asymmetric location of the conduit. The asymmetric location of the conduit may be a location of an antinode of the first vibration mode and the symmetric location of the conduit may be a location of a node of the second vibration mode. Vibrating, with a drive signal, the sensor assembly in the first vibration mode and the second vibration mode may comprise providing the drive signal to a single transducer disposed on the conduit. It should also be appreciated that the methods 2700, 2800, 2900 can be performed using the vibratory meters 5, 905, 1105a, 1105b, 1605 described above, although any suitable vibratory meter may be employed. That is, a vibratory meter may be comprised of a sensor assembly comprising a conduit and a driver disposed on the conduit. A meter electronics may be communicatively coupled to the sensor assembly. The meter electronics may be configured to perform a method according to at least one of the methods 2700, 2800, 2900 described above. The foregoing describes vibratory meters 5, 905, 1105a, 1105b, 1605, a system 1100, and methods 2700, 2800, 2900 for determining a process related parameter based on two or more vibration modes. As explained above, the determining the process related parameter based on the two or more vibration modes may allow for avoiding complex electronics and / or sensor assembly configurations. By way of illustration, if a pressure is estimated, then a pressure sensor may not be required. Additionally, or alternatively, the process related parameter determined based on the two or more vibration modes can allow a comparison between the estimated value and an actual measured value for verification of the sensor assembly, a process related parameter sensor, and / or the like. It should also be appreciated that such estimated process related parameter values can be determined without utilizing a significant amount of calibration resources by using simplified and / or normalized models of a well-characterized model. The estimated process related parameter values can also be calibrated at a vibratory meter manufacturer without requiring additional calibrations and / or additional configurations at an installation site. For example, additional sensors may not need to be calibrated and configured with the vibratory meter to determine a pressure and / or temperature of a process fluid. The detailed descriptions of the above embodiments are not exhaustive descriptions of all embodiments contemplated by the inventors to be within the scope of the present description. Indeed, persons skilled in the art will recognize that certain elements of the above-described embodiments may variously be combined or eliminated to create further embodiments, and such further embodiments fall within the scope and teachings of the present description. It will also be apparent to those of ordinary skill in the art that the above-described embodiments may be combined in whole or in part to create additional embodiments within the scope and teachings of the present description. Thus, although specific embodiments are described herein for illustrative purposes, various equivalent modifications are possible within the scope of the present description, as those skilled in the relevant art will recognize. The teachings provided herein can be applied to other meter electronics, vibratory meters, and methods for determining a process related parameter based on two or more vibration signals and not just to the embodiments described above and shown in the accompanying figures. Accordingly, the scope of the embodiments described above should be determined from the following claims.

Claims

We claim:

1. A method of determining a process related parameter value from two or more vibration modes, the method comprising: vibrating, with a drive signal, a sensor assembly in a first vibration mode; vibrating, with the drive signal, the sensor assembly in a second vibration mode; and estimating a process related parameter value based on the first vibration mode and the second vibration mode.

2. The method of claim 1, wherein the first vibration mode and the second vibration mode are normal modes of the sensor assembly.

3. The method of claim 1, wherein the first vibration mode is a first bend mode and the second vibration mode is one of a second bend mode and a first twist mode.

4. The method of claim 1, wherein estimating the process related parameter value based on the first vibration mode and the second vibration mode comprises estimating the process related parameter based on a mode relationship between the first vibration mode and the second vibration mode.

5. The method of claim 4, wherein the mode relationship between the first vibration mode and the second vibration mode comprises a relationship between parameters of the first vibration mode and the second vibration mode.

6. The method of claim 4, wherein the mode relationship comprises one of a ratio and a difference between the first vibration mode and the second vibration mode.

7. The method of claim 4, wherein the mode relationship between the first vibration mode and the second vibration mode is comprised of a frequency, time-period, and / or an amplitude of the first and second vibration mode.

8. The method of claim 1, wherein estimating the process related parameter comprises estimating the process related parameter based on a relationship between the process related parameter and a plurality of other process related parameters.

9. The method of claim 8, wherein the relationship between a process related parameter and the plurality of other process related parameters comprises a function relationship between the process related parameter and the plurality of other process related parameters.

10. The method of claim 9, wherein the function relationship determines a pressure Paccording to:^ = ^^^^, ^, ^^;where:^ is an internal pressure or pressure inside a conduit of a sensor assembly;^^ is a frequency ratio between the first and second vibration modes;^is a density of a material contained by the conduit; and^ is a temperature of the conduit.

11. The method of claim 10, wherein the function relationship is defined as:^ ≅ ^ ^ ^ ^^^ ^ ^^ ^ ^ ^ ^^ ^ ^ ^ ^^ ^^^^ ^ ^ ^ ^^ ^ ^^ ^ ^ ^^ ^ ^^^ ^^ ^ ^^^ ^^is an estimated pressure;^^, ^, ^ are the independent variables, which herein are process-relatedvariables;^^^, ^^, ^^, ^^^^, ^^,^^, ^^,^^ are coefficients referred to sensitivities tochanges in the independent variables; and^^^, ^^, ^^are nominal values of the independent variables.

12. The method of claim 9, wherein the function relationship has the form of:^ = ^^^^, ^^, … ^^ , … , ^^^ ^^; for j=1 to NVAR;^^ is a jth process related parameter; andNVAR is the number of other process related parameters.

13. The method of claim 12, wherein the function relationship has the form of:^ = ^^ ^ ^^^^ ^ … ^ ^^^^ ^ ⋯ ^ ^^^ ^^"^ ^, for j = 1 to NVAR;where:^ is a response variable;^ is th^ a j predictor variable;^^ is the average effect on ^ of an increase in ^^ predictor variable, holding allother predictors fixed; and NVAR is the number of predictor variables.

14. The method of claim 1, wherein estimating the process related parameter value based on the first vibration mode and the second vibration mode comprises calculating the process related parameter value based on a predetermined measured process related parameter value and the first vibration mode and the second vibration mode.

15. The method of claim 14, wherein calculating the process related parameter value based on a predetermined measured process related parameter value and the first vibration mode and the second vibration mode comprises calculating the process related parameter value based on interpolations between the process related parameter values and vibration mode parameter values.

16. The method of claim 1, wherein estimating the process related parameter value comprises estimating one of a pressure value and a temperature value.

17. A vibratory meter (5, 905, 1105a, 1105b, 1605) configured to determine a process-related parameter based on two or more vibration modes, the vibratory meter (5, 905, 1105a, 1105b, 1605) comprising:a sensor assembly (10, 910, 1110a, 1110b, 1610) comprising a conduit (130, 130’) and a driver (180) disposed on the conduit; a meter electronics (20, 920, 1120a, 1120b, 1620) communicatively coupled to the sensor assembly (10, 910, 1110a, 1110b, 1610), the meter electronics (20, 920, 1120a, 1120b, 1620) being configured to perform a method according to one of the foregoing claims 1 through 16.

18. A method of determining a process related parameter from two or more vibration modes, the method comprising: vibrating, with a drive signal, a sensor assembly in a first vibration mode; vibrating, with the drive signal, the sensor assembly in a second vibration mode; and determining a relationship between a process related parameter and the first vibration mode and the second vibration mode.

19. The method of claim 18, wherein determining the relationship between the process related parameter and the first vibration mode and the second vibration mode comprises minimizing an error # between a model of the relationship between the process related parameter and the first vibration mode and the second vibration mode and a plurality of data points determined based on the first vibration mode and the second vibration mode.

20. The method of claim 19, wherein minimizing the error # between a model of the relationship between the process related parameter and the first vibration mode and the second vibration mode and a plurality of data points determined based on the first vibration mode and the second vibration mode comprises minimizing the error # in amultiple linear regression according to:^ = ^^ ^ ^^^^ ^ ⋯ ^ ^^^^ ^ ⋯ ^ ^^^ ^^^^ ^ ^ #, for j = 1 to NVAR;where:^ is a response variable;^th^ is a j predictor variable;^^is the average effect on ^ of an increase in ^^predictor variable, holding all other predictors fixed; NVAR is the number of predictor variables; and#is an error term.

21. The method of claim 20, wherein each data point of the plurality of data points comprises an ordered sequence of the response variable ^ and the predictor variables ^^.

22. The method of claim 18, wherein determining the relationship between a process related parameter and the first vibration mode and the second vibration mode comprises obtaining a plurality of samples of the process related parameters.

23. The method of claim 22, wherein the plurality of samples of the process related parameters comprises a plurality of samples of the pressure, frequency ratio, density, and temperature (P, FR, ρ, T) data points.

24. The method of claim 22, wherein the plurality of samples of the process related parameters is obtained from one of an analysis of a finite element model or measurements of the sensor assembly.

25. A vibratory meter (5, 905, 1105a, 1105b, 1605) configured to determine a process-related parameter based on two or more vibration modes, the vibratory meter (5, 905, 1105a, 1105b, 1605) comprising: a sensor assembly (10, 910, 1110a, 1110b, 1610) comprising a conduit (130, 130’) and a driver (180) disposed on the conduit; a meter electronics (20, 920, 1120a, 1120b, 1620) communicatively coupled to the sensor assembly (10, 910, 1110a, 1110b, 1610), the meter electronics (20, 920, 1120a, 1120b, 1620) being configured to perform a method according to one of the foregoing claims 18 through 24.

26. A method of determining a process-related parameter based on two or more vibration modes, the method comprising:vibrating, with a drive signal, a sensor assembly of a vibratory meter in a first vibration mode; and vibrating, with the drive signal, the sensor assembly of the vibratory meter in a second vibration mode; determining at least one meter verification parameter based on the first vibration mode and the second vibration mode.

27. The method of claim 26, wherein nodes of the first vibration mode and nodes of the second vibration mode are located at symmetric positions of a conduit of the sensor assembly.

28. The method of one of claim 26 or claim 27, wherein the sensor assembly further comprises a driver symmetrically disposed on a conduit of the sensor assembly.

29. The method of claim 28, wherein the driver being symmetrically disposed on the conduit of the sensor assembly comprises the driver being disposed equidistance between brace bars coupled to the conduit.

30. The method of claim 29, wherein the brace bars define end nodes of the nodes of the first vibration mode and the node of the second vibration mode.

31. The method of claim 28, wherein the driver being symmetrically disposed on the conduit comprises the driver being disposed at a node of the nodes of the second vibration mode.

32. The method of claim 28, wherein the sensor assembly further comprises a pickoff sensor disposed on the conduit of the sensor assembly, wherein the drive signal is provided to one of the driver and the pickoff sensor.

33. The method of claim 26, wherein: vibrating the sensor assembly in the first vibration mode comprises providing the drive signal to the sensor assembly at a fundamental frequency of the first vibration mode; and vibrating the sensor assembly in the second vibration mode comprises providing the drive signal to the sensor assembly at a fundamental frequency of the second vibration mode.

34. The method of claim 26, wherein the first vibration mode is a first bend mode and the second vibration mode is one of a second bend mode and a first twist mode.

35. The method of claim 28, wherein the driver being symmetrically disposed on the conduit of the sensor assembly comprises the driver being symmetrically disposed between two or more pickoff sensors disposed on the conduit of the sensor assembly.

36. The method of claim 28, wherein the driver symmetrically disposed on the conduit of the sensor assembly is comprised of a single driver affixed to the conduit at a center of a longitudinal length of the conduit.

37. The method of claim 26, wherein the drive signal applies a forcing function to the conduit at one of a symmetric location and an asymmetric location of the conduit.

38. The method of claim 37, wherein: the asymmetric location of the conduit is a location of an antinode of the first vibration mode; and the symmetric location of the conduit is a location of a node of the second vibration mode.

39. The method of claim 26, wherein vibrating, with the drive signal, the sensor assembly in the first vibration mode and the second vibration mode comprises providing the drive signal to a single transducer disposed on the conduit.

40. The method of claim 26, wherein determining the at least one meter verification parameter based on the first vibration mode and the second vibration mode comprises determining a first mode meter verification parameter value and a second mode meter verification parameter value.

41. The method of claim 40, wherein determining a first mode meter verification parameter value and a second mode meter verification parameter value comprises determining a first mode meter stiffness value based on a fit to a first vibration mode frequency response function (FRF) and a second mode meter stiffness value based on a fit to a second vibration mode frequency response function (FRF).

42. The method of claim 41, wherein determining the first mode stiffness value comprises determining a first mode fit value and a second mode fit value at zero hertz, the first mode fit value being the fit to the first vibration mode frequency response function (FRF) and the second mode fit value being the fit to the second vibration mode frequency response function (FRF).

43. The method of claim 26, wherein determining the at least one meter verification parameter based on the first vibration mode and the second vibration mode comprises determining a first mode stiffness value and determining a second mode stiffness value.

44. The method of claim 43, further comprising determining a location of a condition in a conduit of the sensor assembly based on at least one of the first mode stiffness value and the second mode stiffness value.

45. The method of claim 26, wherein the at least one meter verification parameter comprises a parameter relationship of a stiffness and / or damping.

46. A vibratory meter (5, 905, 1105a, 1105b, 1605) configured to determine a process-related parameter based on two or more vibration modes, the vibratory meter (5, 9051605) comprising:a sensor assembly (10, 910, 1110a, 1110b, 1610) comprising a conduit (130, 130’) and a driver (180) disposed on the conduit; a meter electronics (20, 920, 1120a, 1120b, 1620) communicatively coupled to the sensor assembly (10, 910, 1110a, 1110b, 1610), the meter electronics (20, 920, 1120a, 1120b, 1620) being configured to perform a method according to one of the foregoing claims 26 through 45.

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