Patent Publication Number: US-7725270-B2

Title: Industrial flow meter having an accessible digital interface

Description:
CROSS-REFERENCE TO RELATED PATENT APPLICATIONS 
     The present application claims the benefit of U.S. Provisional Patent Application No. 60/660,705 filed Mar. 10, 2005, which is incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     This invention relates generally to an apparatus for measuring a parameter of a process flow passing within a pipe, and more particularly to a flow measurement apparatus having an accessible memory interface for easily adding functionality to the apparatus, changing the functionality of the apparatus and performing a variety of diagnostic, meter configuration upgrades and data accumulation tasks. 
     BACKGROUND 
     A fluid flow process (flow process) includes any process that involves the flow of fluid through pipes, ducts, or other conduits, as well as through fluid control devices such as pumps, valves, orifices, heat exchangers, and the like. Flow processes are found in many different industries such as the oil and gas industry, refining, food and beverage industry, chemical and petrochemical industry, pulp and paper industry, power generation, pharmaceutical industry, and water and wastewater treatment industry. The fluid within the flow process may be a single phase fluid (e.g., gas, liquid or liquid/liquid mixture) and/or a multi-phase mixture (e.g. paper and pulp slurries or other solid/liquid mixtures). The multi-phase mixture may be a two-phase liquid/gas mixture, a solid/gas mixture or a solid/liquid mixture, gas entrained liquid or a three-phase mixture. 
     Various sensing technologies exist for measuring various physical parameters of fluids in an industrial flow process. Such physical parameters may include, for example, volumetric flow rate, composition, gas volume fraction, consistency, density, and mass flow rate. 
     One such sensing technology is described in commonly-owned U.S. Pat. No. 6,609,069 to Gysling, entitled “Method and Apparatus for Determining the Flow Velocity Within a Pipe”, which is incorporated herein by reference. The &#39;069 patent describes a method and corresponding apparatus for measuring the flow velocity of a fluid in an elongated body (pipe) by sensing vortical disturbances convecting with the fluid. The method includes the steps of: providing an array of at least two sensors disposed at predetermined locations along the elongated body, each sensor for sampling the pressure of the fluid at the position of the sensor at a predetermined sampling rate; accumulating the sampled data from each sensor at each of a number of instants of time spanning a predetermined sampling duration; and constructing from the accumulated sampled data at least a portion of a so called k-ω plot, where the k-ω plot is indicative of a dispersion relation for the propagation of acoustic pressures emanating from the vortical disturbances. The method also includes the steps of: identifying a convective ridge in the k-ω plot; determining the orientation of the convective ridge in the k-ω plot; and determining the flow velocity based on a predetermined correlation of the flow velocity with the slope of the convective ridge of the k-ω plot. 
     Another such sensing technology is described in commonly-owned U.S. Pat. Nos. 6,354,147 and 6,732,575 to Gysling et al, both of which are incorporated by reference herein in their entirety. The &#39;147 and &#39;575 patents describe a spatial array of acoustic pressure sensors placed at predetermined axial locations along a pipe. The pressure sensors provide acoustic pressure signals to signal processing logic which determines the speed of sound of the fluid (or mixture) in the pipe using any of a number of acoustic spatial array signal processing techniques with the direction of propagation of the acoustic signals along the longitudinal axis of the pipe. The speed of sound is provided to logic, which calculates the percent composition of the mixture, e.g., water fraction, or any other parameter of the mixture, or fluid, that is related to the sound speed. The logic may also determine the Mach number of the fluid. Such sensing technologies are effective in determining various parameters of a fluid flow within a pipe. However, as with any computationally complex process, there remains a need to increase computational efficiency and accuracy. 
     Unfortunately however, in most industrial plants the infrastructure required to obtain this information from installed meters is limited. For example, most infrastructures typically only provide an analog interface of 4-20 mA. This is inadequate for carrying the desired information due to an insufficient amount of bandwidth in its standard analog mode. Moreover, even with superimposed digital communications this analog interface is unable to provide the bandwidth required to transfer a sufficient amount of information for desired purposes. 
     Thus, the ability to obtain/upload information from/to a meter, including software upgrades/changes, commonly measured parameters, meter health information and any additional information that may pertain to the quality of the commonly measured parameters and/or functionality of the meter would be helpful. This is desirable because any information regarding the fluid and health/performance of the meter may aid in diagnosing and optimizing the meter performance. As such, a collection of this information from monitoring stations disposed in multiple locations around an industrial plant promises the potential for developing a better understanding and thus a more efficient control process. Additionally, this collection of information could better provide the ability to troubleshoot existing conditions and/or predict potential future problems. Moreover, the ability to reconfigure existing meters would allow meters to be tailored for a specific task as desired without the need to change the entire meter. 
     SUMMARY OF THE INVENTION 
     An apparatus for measuring a parameter of a fluid flowing within a pipe is provided, wherein the apparatus includes a sensing device having a sensor for sensing a characteristic of the fluid flow, wherein the sensing device generates sensor data responsive to the characteristic. A processing device is also included wherein the processing device is communicated with the sensing device, wherein the processing device receives and processes the sensor data to generate meter data indicative of the fluid. Additionally, at least one digital interface is provided, wherein at least one digital interface is communicated with the processing device and wherein the at least one digital interface is configured to associate with a portable external digital storage device for transferring information between the apparatus and the external digital storage device. 
     A processing unit for an apparatus having a sensor for measuring a parameter of a fluid flowing within a pipe is provided, wherein the processing unit includes a processing device communicated with the sensor, wherein the processing device receives and processes sensor data from the sensor to generate meter data and at least one digital interface communicated with the processing device, the at least one digital interface configured for interfacing with a portable external digital storage device for transferring information between the processing unit and the external digital storage device. 
     A method for implementing a processing unit for an apparatus having a sensor for measuring a parameter of a fluid flowing within a pipe is provided, wherein the processing unit includes a processing device and at least one digital interface, wherein The processing device is communicated with the sensor to receive and process sensor data from the sensor to generate meter data and wherein the at least one digital interface is communicated with the processing device and configured for interfacing with an external digital storage device for transferring information between the processing unit and said external digital storage device. The method includes associating the external digital storage device with the processing unit and transferring The information between the external digital device and the processing unit via the digital interface. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Referring now to the drawing wherein like items are numbered alike in the various Figures: 
         FIG. 1  is schematic diagram of an apparatus for determining at least one parameter associated with a fluid flowing in a pipe interfacing with an external digital storage device in accordance with various embodiments of the present invention; 
         FIG. 2  is a block diagram illustrating a method for implementing the apparatus of  FIG. 1 ; 
         FIG. 3  is a block diagram illustrating one flow for an automatic interface program for the apparatus of  FIG. 1 ; 
         FIG. 4  is a block diagram illustrating the advanced function menu flow for the automatic interface program of  FIG. 3 ; and 
         FIG. 5  is a block diagram illustrating the advanced function menu flow for the automatic interface program of  FIG. 3 . 
         FIG. 6  is a block diagram of a first embodiment of a flow logic used in the apparatus of the present invention; 
         FIG. 7  is a cross-sectional view of a pipe having coherent structures therein; 
         FIG. 8  a k-ω plot of data processed from an apparatus embodying the present invention that illustrates slope of the convective ridge, and a plot of the optimization function of the convective ridge; 
         FIG. 9  is a block diagram of a second embodiment of a flow logic used in the apparatus of the present invention; 
         FIG. 10  a k-ω plot of data processed from an apparatus embodying the present invention that illustrates slope of the acoustic ridges; 
         FIG. 11  is a plot of mixture sound speed as a function of gas volume fraction for a 5% consistency slurry over a range of process pressures; 
         FIG. 12  is a plot of sound speed as a function of frequency for air/particle mixtures with fixed particle size and varying air-to-particle mass ratio; 
         FIG. 13  is a plot of sound speed as a function of frequency for air/particle mixtures with fixed air-to-particle mass ration and fixed particle size; 
     
    
    
     DETAILED DESCRIPTION 
     As described in U.S. Pat. No. 6,354,147, filed on Jun. 25, 1999, U.S. Pat. No. 6,691,584, filed on Jul. 2, 1999, U.S. Pat. No. 6,587,798, filed on Nov. 28, 2001, U.S. Pat. No. 6,609,069, filed on Dec. 4, 2000, U.S. patent application Ser. No. 10/349,716, filed on Jan. 23, 2003, and U.S. patent application Ser. No. 10/376,427, filed on Feb. 26, 2003, which are all incorporated herein by reference, unsteady pressures along a pipe, as may be caused by one or both of acoustic waves propagating through the fluid within the pipe and/or pressure disturbances that convect with the fluid flowing in the pipe (e.g., turbulent eddies and vortical disturbances), contain useful information regarding parameters of the fluid and the flow process. 
     Referring to  FIG. 1 , an apparatus  100  for measuring at least one parameter associated with a fluid  102  flowing within a pipe  104  is shown. The parameter of the fluid may include, for example, at least one of: velocity of the fluid  102 , speed of sound in the fluid  102 , density of the fluid  102 , volumetric flow rate of the fluid  102 , mass flow rate of the fluid  102 , composition of the fluid  102 , entrained air in the fluid  102 , consistency of the fluid  102 , and size of particles in the fluid  102 . The fluid  102  may be a single or multiphase fluid  102  flowing through a duct, conduit or other form of pipe  104 . 
     The apparatus  100  includes a spatial array  106  of at least two pressure sensors  108  disposed at different axial locations x 1  . . . x N  along the pipe  104 . Each of the pressure sensors  108  provides a pressure signal P(t) indicative of unsteady pressure within the pipe  104  at a corresponding axial location x 1  . . . x N  of the pipe  104 . A signal processor  110  receives the pressure signals P 1 (t) . . . P N (t) from the pressure sensors  108  in the array  106 , determines the parameter of the fluid  102  using pressure signals from selected ones of the pressure sensors  108 , and outputs the parameter as a signal  112 . The signal processor  110  applies array-processing techniques to the pressure signals P 1 (t) . . . P N (t) to determine the velocity, speed of sound of the fluid  102 , and/or other parameters of the fluid  102 . More specifically, the signal processor  110  constructs from the signals at least a portion of a k-ω plot. The signal processor  110  then identifies a ridge in the k-ω plot. The slope of the ridge is assumed to be the fluid  102  velocity or sound velocity or correlated to the fluid  102  velocity or sound velocity in a known way. Thus, using the slope of the ridge, the parameters of the fluid  102  can be determined, as will be described in greater detail hereinafter. 
     While the apparatus  100  is shown as including four pressure sensors  108 , it is contemplated that the array  106  of pressure sensors  108  includes two or more pressure sensors  108 , each providing a pressure signal P(t) indicative of unsteady pressure within the pipe  104  at a corresponding axial location X of the pipe  104 . For example, the apparatus may include 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 pressure sensors  108 . Generally, the accuracy of the measurement improves as the number of sensors  108  in the array  106  increases. The degree of accuracy provided by the greater number of sensors  108  is offset by the increase in complexity and time for computing the desired output parameter of the flow. Therefore, the number of sensors  108  used is dependent at least on the degree of accuracy desired and the desire update rate of the output parameter provided by the apparatus  100 . 
     The signals P 1 (t) . . . P N (t) provided by the pressure sensors  108  in the array  106  are processed by the signal processor  110 , which may be part of a larger processing unit  114 . For example, the signal processor  110  may be a microprocessor and the processing unit  114  may be a personal computer or other general purpose computer. It is contemplated that the signal processor  110  may be any one or more analog or digital signal processing devices for executing programmed instructions, such as one or more microprocessors or application specific integrated circuits (ASICS), and may include memory for storing programmed instructions, set points, parameters, and for buffering or otherwise storing data. 
     To determine the one or more parameters  112  of the flow process, the signal processor  110  applies the data from the selected pressure sensors  108  to flow logic  116  executed by signal processor  110 . The flow logic  116  is described in further detail hereinafter. 
     The signal processor  110  may output the one or more parameters  112  to a display  118  or another input/output ( 110 ) device  120 . The I/O device  120  also accepts user input parameters as may be necessary for the flow logic  116 . The I/O device  120  includes an analog interface  122 , such as a 4-20 mA interface, and at least one digital interface  124 , wherein the digital interface  124  maybe a commonly known digital interface type configured to support a variety of external digital storage devices  164 , such as a Universal Serial Bus (USB) Flash Drive, a Compact Flash card, a Smart Media card, a Secure Digital card and/or a Multimedia card. The I/O device  120  allows a user to store sensor/meter values, interrogate sensor/apparatus parameters and/or setup the apparatus  100  for process optimization. Additionally, the I/O device  120  allows for the ability to change functionality of the apparatus  100 , add functionality to the apparatus  100 , customize functionality of the apparatus  100  as well as just update the software version to fix address any software problems. Additionally, as discussed in more detail hereinafter, the digital interface  124  allows for a simple, easily accessible data port which permits for the easy and efficient upload/download of data/scripts between an external digital storage device  164  (such as a USB memory stick) and the apparatus  100  to perform a variety of diagnostic, upgrade and data accumulation tasks that are not possible with prior art configurations. 
     This capability advantageously allows for a user (such as a customer, trained distributor and field technician) to easily access/reconfigure an apparatus  100  located in a remote location, save data over a period of time and download information periodically without having to carry and set up bulky, fragile, costly and sophisticated computer equipment. Moreover, the information may be downloaded/uploaded from/to the external digital storage device via an internet connection to allow for an easy interface capability with the manufacturer and/or a maintenance team. The I/O device  120 , display  118 , and signal processor  110  unit may be mounted in a common housing, which may be attached to the array  106  by a flexible cable, wireless connection, or the like. The flexible cable may also be used to provide operating power from the processing unit  114  to the array  106  if necessary. 
     By way of example, the use of the digital interface  124  to allow for easy and unfettered access to the apparatus  100  is discussed further below. Referring to  FIG. 1  and  FIG. 2 , the apparatus  100  is shown interfacing with an external digital storage device  164  (in this case, a USB memory stick) and a method  200  for accessing the apparatus  100  using the USB memory stick  164  is provided. The method  200  includes generating sensor data and meter information using the apparatus  100 , as shown in operational block  202 . This may be accomplished by generating the sensor data and communicating the sensor data to the processing unit  114 , which receives the sensor data and generates meter information. The USB memory stick  164  may then be associated with the digital interface  124 , as shown in operational block  204 , by inserting the USB memory stick  124  into the digital interface  124  of the I/O device  120 . Sensor data and/or meter information may then be transferred between the USB memory stick  164  and the apparatus  100 , as shown in operational block  206 . It should be appreciated that the meter information may include raw sensor data directly from each of the sensors  108 , raw sensor data directly from a selected sensor  108 , processed data, programs/scripts for upload/download to the apparatus  100 , configuration data for the apparatus  100  and/or functional/troubleshooting data for the apparatus (i.e. parametric data, diagnostic data, functional scripts and meter control information). 
     At least one of the apparatus  100  and the USB memory stick  164  may be configured such that the transfer of information between the apparatus  100  and the USB memory stick  164  may occur either automatically upon insertion of the USB memory stick  164  into the digital interface  124  of the I/O device  120  or via a command from the user which causes the apparatus  100  to display a functional menu to the user via the display device  118 . This is particularly advantageous in that this enables a user to upload software to the apparatus to add functionality, limit functionality and/or change functionality of the apparatus altogether. Additionally, this enables a user to completely change and/or modify apparatus software or add software to correct bugs within the existing software. Typically, there may be two download/upload situations that occur with the USB memory stick  164 . The first situation involves an upload/download script that is automatically activated upon insertion of the USB memory stick  164  into the digital interface  124 . Referring to  FIG. 3 , a block diagram  300  illustrating this situation is shown. Upon insertion of the USB memory stick  164  into the digital interface  124 , as shown in block  302 , an automatic script is initiated to begin the upload/download process between the USB memory stick  164  and the apparatus  100 , as shown in block  304 . As shown in block  306 , the user is prompted via the display device  118  to either begin the upload/download process by pressing an ‘enter’ key on the display device  118  or cancel the upload/download process by pressing a ‘cancel’ key on the display device  118 , as shown in blocks  308  and  310 , respectively. 
     The second situation involves the situation where the upload/download process is not automatically initiated upon insertion of the USB memory stick  164  into the digital interface  118  but requires input from the user. Referring to  FIG. 4 , a block diagram  400  illustrating this situation is shown. Upon insertion of the USB memory stick  164  into the digital interface  124 , as shown in block  402 , a function menu is displayed to the user via the display device  118 , as shown in block  404 . This function menu displays several options to the user and prompts the user to select one of the options, as shown in block  406 , wherein the options include saving a system snapshot, loading meter configurations, accessing an advanced function menu and canceling the current action. If the user selects the option of saving a system snapshot, as shown in block  408 , then the user will be prompted to begin the action as shown in block  416 . Upon the user selecting the prompt, data responsive to the state of the apparatus  100  for a predetermined period of time will be downloaded and saved to the USB memory stick  164 . This data includes raw data directly from the sensor for a predetermined amount of time (i.e. last 5 minutes), system information data (i.e. version of meter firmware and/or software), system configuration data (i.e. initialization file) and meter data for a predetermined amount of time (i.e. last 24 hours). It should be appreciated that meter data includes the sensor data that has been processed by the processing device  110 , such as fluid Speed of Sound data, velocity data (i.e. convective velocity of the pressure fields created by the fluid flow), Volumetric Flow rate data, Fluid Flow rate data and Gas Volume Fraction data. 
     If the user selects the option of loading meter configurations, as shown in block  410 , then the user will be prompted to begin loading new meter configuration data, such as a new initialization file and/or a software upgrade, from the USB memory stick  164  to the apparatus  100 , as shown in block  416 . Upon the user selecting the prompt, the new meter configuration data will be uploaded and saved to the apparatus  100 . If the user selects the cancel option, as shown in block  412 , then the display device  118  of the apparatus  100  returns to its normal state and the user has to reinsert the USB memory stick  164  to reactivate the function menu. However, referring to  FIG. 5 , if the user selects the option of accessing the advanced function menu, as shown in block  414 , then the user is prompted to select between several advanced menu options, as shown in block  418 , wherein the options include accessing the system configuration, saving raw sensor data, saving data history, managing files on the apparatus  100 , and setting the date and time of the apparatus  100 . 
     If the user selects the option of accessing the system configuration of the apparatus  100 , as shown in block  420 , the user will be prompted to select between several options, as shown in block  430 . The first option includes loading a new configuration file from the USB memory stick  164  into the apparatus  100 . In this case, if several configuration files are available, then a list of the available configuration files will be displayed to the user for selection. The second option includes saving the current configuration file to the USB memory stick  164  and the third option includes renaming and saving the current configuration file to a different location. It should be appreciated that the name of the configuration file may include meter identification information appended by file type information. For example, a system configuration file from meter number  1  may be saved as “0001_Config.” As such, information (data/software) for multiple meters may be uploaded/downloaded and uniquely identified for a specific meter and/or a specific type of meter. 
     If the user selects the option of saving raw sensor data from the apparatus  100 , as shown in block  422 , the user will be prompted to select the period of duration of sensor data desired, as shown in block  432 . For example, the user may select to save raw sensor data for the previous 1 minute, 5 minutes, 10 minutes, 30 minutes, 60 minutes, 120 minutes and 240 minutes. Additionally, the user may also select an option to save data in a continuous fashion by saving raw sensor data until the memory of the USB memory stick  164  is full. It should be appreciated that if the user fails to select a displayed duration length, then a predetermined default duration length may be used for obtaining the raw sensor data. If the user selects the option to save the data history, as shown in block  424 , the user will be prompted to select the decimation (i.e. sample rate) of the data being saved and the length or period of time of the data sample being saved, as shown in block  434 . Additionally, the user will be prompted as to whether the data should be saved as compressed data or text data and whether the data history should be erased entirely from the apparatus  100 . Upon selecting the decimation of the data being saved, the user will be given a plurality of sampling rate options, such as a sample rate of 2 (i.e. for every two measurements taken, one measurement is saved), 10, 100, 500 and ALL (i.e. every measurement is saved). Moreover, upon selecting the length of time over which the sample should be obtained, the user will be given a plurality of length options, such as for the previous 1 day (i.e. save the data obtained over a period of 24 hours), 5 days, 30 days, 100 days and 500 days. If the user fails to select a displayed decimation rate and/or a period of time over which the data sample should be taken, then predetermined default rates may be used. 
     If the user selects the option of managing files on the apparatus  100 , as shown in block  426 , the user will be prompted to select between the options of deleting a file, erasing all files on the apparatus  100  and obtaining disk information, as shown in block  436 . If the user elects to delete a particular file, a list of files on the apparatus  100  will be displayed to the user and the user may select one or more files for deletion. If the user elects to obtain and save disk information, the information pertaining to the disk will be saved and may include total disk size, used disk space, free disk space, files located on the disk, date/time of creation of any files located on the disk, date/time of modification of any files located on the disk and date/time the user selected to save the disk information. If the user selects the option of setting the date and/or time on the apparatus  100 , as shown in block  428 , the user will be prompted to enter the desired date and/or time changes to the apparatus  100 , as shown in block  438 . 
     It should be appreciated that the ability to easily access and change/modify the apparatus  100  with the use of a USB memory stick  164  provides for a more robust apparatus  100  by allowing the apparatus  100  to be modified with upgraded meter software for enhanced performance and to change and/or include added functionality (i.e. a flow meter and a GVF meter combination). 
     Flow Logic 
     Velocity Processing 
     Referring to  FIG. 6 , an example of flow logic  116  is shown. As previously described, the array  106  of at least two sensors  108  located at two locations x 1 , x 2  axially along the pipe  104  sense respective stochastic signals propagating between the sensors  108  within the pipe  104  at their respective locations. Each sensor  108  provides a signal indicating an unsteady pressure at the location of each sensor  108 , at each instant in a series of sampling instants. One will appreciate that the array  106  may include more than two sensors  108  distributed at locations x 1  . . . x N . The pressure generated by the convective pressure disturbances (e.g., eddies  140 , see  FIG. 7 ) may be measured through strained-based sensors  108  and/or pressure sensors  108 . The sensors  108  provide analog pressure time-varying signals P 1 (t),P 2 (t),P 3 (t) . . . P N (t) to the signal processor  110 , which in turn applies selected ones of these signals P 1 (t),P 2 (t),P 3 (t), . . . P N (t) to the flow logic  116 . 
     The flow logic  116  processes the selected signals P 1 (t),P 2 (t),P 3 (t), . . . P N (t) to first provide output signals (parameters)  126  indicative of the pressure disturbances that convect with the fluid (process flow)  102 , and subsequently, provide output signals (parameters)  126  in response to pressure disturbances generated by convective waves propagating through the fluid  102 , such as velocity, Mach number and volumetric flow rate of the process flow  102 . 
     The signal processor  110  includes data acquisition unit  128  (e.g., A/D converter) that converts the analog signals P 1 (t) . . . P N( t) to respective digital signals and provides the digital signals P 1 (t) . . . P N (t) to FFT logic  130 . The FFT logic  130  calculates the Fourier transform of the digitized time-based input signals P 1 (t) . . . P N (t) and provides complex frequency domain (or frequency based) signals P 1 (ω),P 2 (ω),P 3 (ω), . . . P N (ω) indicative of the frequency content of the input signals. Instead of FFT&#39;s, any other technique for obtaining the frequency domain characteristics of the signals P 1 (t)-P N (t), may be used. For example, the cross-spectral density and the power spectral density may be used to form a frequency domain transfer functions (or frequency response or ratios) discussed hereinafter. 
     One technique of determining the convection velocity of the turbulent eddies  140  within the process flow  102  is by characterizing a convective ridge of the resulting unsteady pressures using an array of sensors  108  or other beam forming techniques, similar to that described in U.S. Pat. No. 6,691,584, filed on Jul. 2, 1999 and U.S. Pat. No. 6,609,069, filed on Dec. 4, 2000, which are incorporated herein by reference. 
     A data accumulator  132  accumulates the frequency signals P 1 (ω)-P N (ω) over a sampling interval, and provides the data to an array processor  134 , which performs a spatial-temporal (two-dimensional) transform of the sensor data, from the xt domain to the k-ω domain, and then calculates the power in the k-ω plane, as represented by a k-ω plot. 
     The array processor  134  uses standard so-called beam forming, array processing, or adaptive array-processing algorithms, i.e. algorithms for processing the sensor signals using various delays and weighting to create suitable phase relationships between the signals provided by the different sensors, thereby creating phased antenna array functionality. In other words, the beam forming or array processing algorithms transform the time domain signals from the sensor array  106  into their spatial and temporal frequency components, i.e. into a set of wave numbers given by k=2π/λ where λ is the wavelength of a spectral component, and corresponding angular frequencies given by ω=2πν. 
     The prior art teaches many algorithms of use in spatially and temporally decomposing a signal from a phased array of sensors  108 , and the present invention is not restricted to any particular algorithm. One particularly adaptive array processing algorithm is the Capon method/algorithm. While the Capon method is described as one method, the present invention contemplates the use of other adaptive array processing algorithms, such as MUSIC algorithm. The present invention recognizes that such techniques can be used to determine flow rate, i.e. that the signals caused by a stochastic parameter convecting with a flow are time stationary and have a coherence length long enough that it is practical to locate sensor units apart from each other and yet still be within the coherence length. 
     Convective characteristics or parameters have a dispersion relationship that can be approximated by the straight-line equation,
 
 k=ω/u,  
 
     where u is the convection velocity (flow velocity). A plot of k-ω pairs obtained from a spectral analysis of sensor samples associated with convective parameters portrayed so that the energy of the disturbance spectrally corresponding to pairings that might be described as a substantially straight ridge, a ridge that in turbulent boundary layer theory is called a convective ridge. What is being sensed are not discrete events of turbulent eddies  140 , but rather a continuum of possibly overlapping events forming a temporally stationary, essentially white process over the frequency range of interest. In other words, the convective eddies  140  is distributed over a range of length scales and hence temporal frequencies. 
     To calculate the power in the k-ω plane, as represented by a k-ω plot (see  FIG. 8 ) of either the signals, the array processor  134  determines the wavelength and so the (spatial) wavenumber k, and also the (temporal) frequency and so the angular frequency ω, of various of the spectral components of the stochastic parameter. There are numerous algorithms available in the public domain to perform the spatial/temporal decomposition of arrays of sensors  108 . 
     The present invention may use temporal and spatial filtering to precondition the signals to effectively filter out the common mode characteristics Pcommon mode and other long wavelength (compared to the sensor spacing) characteristics in the pipe  104  by differencing adjacent sensors  108  and retaining a substantial portion of the stochastic parameter associated with the flow field and any other short wavelength (compared to the sensor spacing) low frequency stochastic parameters. 
     In the case of suitable turbulent eddies  140  (see  FIG. 7 ) being present, the power in the k-ω plane shown in a k-ω plot of  FIG. 8  shows a convective ridge  144 . The convective ridge  144  represents the concentration of a stochastic parameter that convects with the flow and is a mathematical manifestation of the relationship between the spatial variations and temporal variations described above. Such a plot will indicate a tendency for k-ω pairs to appear more or less along a line  144  with some slope, the slope indicating the flow velocity. 
     Once the power in the k-ω plane is determined, a convective ridge identifier  136  uses one or another feature extraction method to determine the location and orientation (slope) of any convective ridge  144  present in the k-ω plane. In one embodiment, the convective ridge identifier  136  accumulates energy (power) of k-ω pairs in the k-ω plot along different rays emanating from the origin, each different ray being associated with a different trial velocity (in that the slope of a ray is assumed to be the fluid  102  velocity or correlated to the fluid  102  velocity in a known way). The convective ridge identifier  136  may accumulate energy for each array by summing the energy of k-ω pairs along the ray. Alternatively, other methods of accumulating energy along the ray (e.g., averaging) may be used. In any case, accumulated energy is determined for a range of trial velocities between a predetermined minimum velocity and a predetermined maximum velocity. The convective ridge  144  has an orientation that is the slope of the ray having the largest accumulated energy. The convective ridge identifier  136  provides information about the different trial velocities, information referred to generally as convective ridge information. 
     The analyzer  138  examines the convective ridge information including the convective ridge orientation (slope). Assuming the straight-line dispersion relation given by k=ω/u, the analyzer  138  determines the flow velocity, Mach number and/or volumetric flow, which are output as parameters  126 . The volumetric flow is determined by multiplying the cross-sectional area of the inside of the pipe  104  with the velocity of the process  102  flow. 
     Some or all of the functions within the flow logic  116  may be implemented in software (using a microprocessor or computer) and/or firmware, or may be implemented using analog and/or digital hardware, having sufficient memory, interfaces, and capacity to perform the functions described herein. 
     Speed of Sound (SOS) Processing 
     Referring to  FIG. 9 , another example of flow logic  116  is shown. While the examples of  FIG. 6  and  FIG. 9  are shown separately, it is contemplated that the flow logic  116  may perform all of the functions described with reference to  FIG. 6  and  FIG. 9 . As previously described, the array  106  of at least two sensors  108  located at two locations x1, x2 axially along the pipe  104  sense respective stochastic signals propagating between the sensors  108  within the pipe  104  at their respective locations. Each sensor  108  provides a signal indicating an unsteady pressure at the location of each sensor  108 , at each instant in a series of sampling instants. One will appreciate that the sensor array  106  may include more than two pressure sensors  108  distributed at locations x 1  . . . x N . The pressure generated by the acoustic pressure disturbances (e.g., acoustic waves  142 , see  FIG. 8 ) may be measured through strained-based sensors and/or pressure sensors. The sensors  108  provide analog pressure time-varying signals P 1 (t),P 2 (t),P 3 (t), . . . P N (t) to the flow logic  116 . The flow logic  116  processes the signals P 1 (t),P 2 (t),P 3 (t), . . . P N (t) from the sensors  108  to first provide output signals indicative of the speed of sound propagating through the fluid (process flow)  102 , and subsequently, provide output signals in response to pressure disturbances generated by acoustic waves propagating through the process flow  102 , such as velocity, Mach number and volumetric flow rate of the process flow  102 . 
     The signal processor  110  receives the pressure signals from the array  106  of sensors  108 . A data acquisition unit  146  digitizes selected ones of the pressure signals P 1 (t) . . . P N (t) associated with the acoustic waves  142  propagating through the pipe  104 . Similarly to the FFT logic  130  of  FIG. 6 , an FFT logic  148  calculates the Fourier transform of the selected digitized time-based input signals P 1 (t) . . . P N (t) and provides complex frequency domain (or frequency based) signals P 1 (ω),P 2 (ω),P 3 (ω), . . . P N (ω) indicative of the frequency content of the input signals. 
     A data accumulator  150  accumulates the frequency signals P 1 (ω) . . . P N (ω) over a sampling interval, and provides the data to an array processor  152 , which performs a spatial-temporal (two-dimensional) transform of the sensor data, from the xt domain to the k-ω domain, and then calculates the power in the k-ω plane, as represented by a k-ω plot. 
     To calculate the power in the k-ω plane, as represented by a k-ω plot (see  FIG. 10 ) of either the signals or the differenced signals, the array processor  152  determines the wavelength and so the (spatial) wavenumber k, and also the (temporal) frequency and so the angular frequency ω, of various of the spectral components of the stochastic parameter. There are numerous algorithms available in the public domain to perform the spatial/temporal decomposition of arrays of sensor units  108 . 
     In the case of suitable acoustic waves  142  being present in both axial directions, the power in the k-ω plane shown in a k-ω plot of  FIG. 10  so determined will exhibit a structure that is called an acoustic ridge  160 ,  162  in both the left and right planes of the plot, wherein one of the acoustic ridges  160  is indicative of the speed of sound traveling in one axial direction and the other acoustic ridge  162  being indicative of the speed of sound traveling in the other axial direction. The acoustic ridges  160 ,  162  represent the concentration of a stochastic parameter that propagates through the flow and is a mathematical manifestation of the relationship between the spatial variations and temporal variations described above. Such a plot will indicate a tendency for k-ω pairs to appear more or less along a line  160 ,  162  with some slope, the slope indicating the speed of sound. 
     The power in the k-ω plane so determined is then provided to an acoustic ridge identifier  154 , which uses one or another feature extraction method to determine the location and orientation (slope) of any acoustic ridge present in the left and/or right k-ω plane. The velocity may be determined by using the slope of one of the two acoustic ridges  160 ,  162  or averaging the slopes of the acoustic ridges  160 ,  162 . 
     Finally, information including the acoustic ridge orientation (slope) is used by an analyzer  156  to determine the flow parameters relating to a measured speed of sound, such as the consistency or composition of the flow, the density of the flow, the average size of particles in the flow, the air/mass ratio of the flow, gas volume fraction of the flow, the speed of sound propagating through the flow, and/or the percentage of entrained air within the flow. 
     Similar to the array processor  134  of  FIG. 6 , the array processor  152  uses standard so-called beam forming, array processing, or adaptive array-processing algorithms, i.e. algorithms for processing the sensor signals using various delays and weighting to create suitable phase relationships between the signals provided by the different sensors, thereby creating phased antenna array functionality. In other words, the beam forming or array processing algorithms transform the time domain signals from the sensor array  106  into their spatial and temporal frequency components, i.e. into a set of wave numbers given by k=2π/λ where λ is the wavelength of a spectral component, and corresponding angular frequencies given by ω=2πν. 
     One such technique of determining the speed of sound propagating through the process flow  102  is using array processing techniques to define an acoustic ridge  160 ,  162  in the k-ω plane as shown in  FIG. 10 . The slope of the acoustic ridge  160 ,  162  is indicative of the speed of sound propagating through the process flow  102 . The speed of sound (SOS) is determined by applying sonar arraying processing techniques to determine the speed at which the one dimensional acoustic waves propagate past the axial array of unsteady pressure measurements distributed along the pipe  104 . 
     The flow logic  116  of the present embodiment measures the speed of sound (SOS) of one-dimensional sound waves propagating through the process flow  102  to determine the gas volume fraction of the process flow  102 . It is known that sound propagates through various mediums at various speeds in such fields as SONAR and RADAR fields. The speed of sound propagating through the pipe  104  and process flow  102  may be determined using a number of known techniques, such as those set forth in U.S. patent application Ser. No. 09/344,094, filed Jun. 25, 1999, now U.S. Pat. No. 6,354,147; U.S. patent application Ser. No. 10/795,111, filed Mar. 4, 2004; U.S. patent application Ser. No. 09/997,221, filed Nov. 28, 2001, now U.S. Pat. No. 6,587,798; U.S. patent application Ser. No. 10/007,749, filed Nov. 7, 2001, and U.S. patent application Ser. No. 10/762,410, filed Jan. 21, 2004, each of which are incorporated herein by reference. 
     While the sonar-based flow meter using an array of sensors  106  to measure the speed of sound of an acoustic wave propagating through the mixture  102  is shown and described, one will appreciate that any means for measuring the speed of sound of the acoustic wave may used to determine the entrained gas volume fraction of the mixture/fluid  102  or other characteristics of the flow described hereinbefore. 
     The analyzer  156  of the flow logic  116  provides output parameters  158  indicative of characteristics of the process flow  102  that are related to the measured speed of sound (SOS) propagating through the process flow  102 . For example, to determine the gas volume fraction (or phase fraction), the analyzer  156  assumes a nearly isothermal condition for the process flow  102 . As such the gas volume fraction or the void fraction is related to the speed of sound by the following quadratic equation:
 
 Ax   2   +Bx+C= 0
 
     wherein x is the speed of sound, A=1+rg/rl*(K eff /P−1)−K eff /P, B=K eff /P−2+rg/rl; C=1−K eff /rl*a meas ^2; Rg=gas density, rl=liquid density, K eff =effective K (modulus of the liquid and pipewall), P=pressure, and a meas =measured speed of sound. 
     Effectively,
 
Gas Voulume Fraction (GVF)=(− B +sqrt( B^ 2−4 *A*C ))/(2 *A ).
 
     Alternatively, the sound speed of a mixture can be related to volumetric phase fraction (□ i ) of the components and the sound speed (a) and densities (ρ) of the component through the Wood equation. 
     
       
         
           
             
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           where 
         
       
       
         
           
             
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     One dimensional compression waves propagating within a process flow  102  contained within a pipe  104  exert an unsteady internal pressure loading on the pipe  104 . The degree to which the pipe  104  displaces as a result of the unsteady pressure loading influences the speed of propagation of the compression wave. The relationship among the infinite domain speed of sound and density of a mixture; the elastic modulus (E), thickness (t), and radius (R) of a vacuum-backed cylindrical conduit; and the effective propagation velocity (aeff) for one dimensional compression is given by the following expression: 
     
       
         
           
             
               
                 
                   
                     a 
                     eff 
                   
                   = 
                   
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                           1 
                           
                             a 
                             
                               mix 
                               ∞ 
                             
                             2 
                           
                         
                         + 
                         
                           
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                           ⁢ 
                           
                             
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     The mixing rule essentially states that the compressibility of a process flow (1/(ρa 2 )) is the volumetrically-weighted average of the compressibilities of the components. For a process flow  102  consisting of a gas/liquid mixture at pressure and temperatures typical of paper and pulp industry, the compressibility of gas phase is orders of magnitudes greater than that of the liquid. Thus, the compressibility of the gas phase and the density of the liquid phase primarily determine mixture sound speed, and as such, it is necessary to have a good estimate of process pressure to interpret mixture sound speed in terms of volumetric fraction of entrained gas. The effect of process pressure on the relationship between sound speed and entrained air volume fraction is shown in  FIG. 11 . 
     As described hereinbefore, the flow logic  116  of the present embodiment includes the ability to accurately determine the average particle size of a particle/air or droplet/air mixture within the pipe  104  and the air to particle ratio. Provided there is no appreciable slip between the air and the solid coal particle, the propagation of one dimensional sound wave through multiphase mixtures is influenced by the effective mass and the effective compressibility of the mixture. For an air transport system, the degree to which the no-slip assumption applies is a strong function of particle size and frequency. In the limit of small particles and low frequency, the no-slip assumption is valid. As the size of the particles increases and the frequency of the sound waves increase, the non-slip assumption becomes increasing less valid. For a given average particle size, the increase in slip with frequency causes dispersion, or, in other words, the sound speed of the mixture to change with frequency. With appropriate calibration the dispersive characteristic of a process flow  102  will provide a measurement of the average particle size, as well as, the air to particle ratio (particle/fluid ratio) of the process flow  102 . 
     In accordance with the present invention the dispersive nature of the system utilizes a first principles model of the interaction between the air and particles. This model is viewed as being representative of a class of models that seek to account for dispersive effects. Other models could be used to account for dispersive effects without altering the intent of this disclosure (for example, see the paper titled “Viscous Attenuation of Acoustic Waves in Suspensions” by R. L. Gibson, Jr. and M. N. Toksöz), which is incorporated herein by reference. The model allows for slip between the local velocity of the continuous fluid phase and that of the particles. 
     The following relation can be derived for the dispersive behavior of an idealized fluid particle mixture: 
     
       
         
           
             
               
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     In the above relation, the fluid SOS, density (ρ) and viscosity (φ) are those of the pure phase fluid, v p  is the volume of individual particles and ρ p  is the volumetric phase fraction of the particles in the mixture. 
     Two parameters of particular interest in steam processes and air-conveyed particles processes are particle size and air-to-fuel mass ratio or steam quality. To this end, it is of interest to examine the dispersive characteristics of the mixture as a function of these two variables.  FIG. 12  and  FIG. 13  show the dispersive behavior in relations to the speed of sound for coal/air mixtures with parameters typical of those used in pulverized coal deliver systems. 
     In particular  FIG. 12  shows the predicted behavior for nominally 50 micrometer size coal in air for a range of air-to-fuel ratios. As shown, the effect of air-to-fuel ratio is well defined in the low frequency limit. However, the effect of the air-to-fuel ratio becomes indistinguishable at higher frequencies, approaching the sound speed of the pure air at high frequencies (above ˜100 Hz). 
     Similarly,  FIG. 13  shows the predicted behavior for a coal/air mixture with an air-to-fuel ratio of 1.8 with varying particle size. This figure illustrates that particle size has no influence on either the low frequency limit (quasi-steady) sound speed, or on the high frequency limit of the sound speed. However, particle size does have a pronounced effect in the transition region. 
       FIG. 12  and  FIG. 13  illustrate an aspect of the present invention. Namely, that the dispersive properties of dilute mixtures of particles suspended in a continuous liquid can be broadly classified into three frequency regimes: low frequency range, high frequency range and a transitional frequency range. Although the effect of particle size and air-to-fuel ratio are inter-related, the predominant effect of air-to-fuel ratio is to determine the low frequency limit of the sound speed to be measured and the predominate effect of particle size is to determine the frequency range of the transitional regions. As particle size increases, the frequency at which the dispersive properties appear decreases. For typical pulverized coal applications, this transitional region begins at fairly low frequencies, ˜2 Hz for 50 micrometer size particles. 
     Given the difficulties measuring sufficiently low frequencies to apply the quasi-steady model and recognizing that the high frequency sound speed contains no direct information on either particle size or air-to-fuel ratio, it becomes apparent that the dispersive characteristics of the coal/air mixture should be utilized to determine particle size and air-to-fuel ratio based on speed of sound measurements. 
     Some or all of the functions within the flow logic  116  may be implemented in software (using a microprocessor or computer) and/or firmware, or may be implemented using analog and/or digital hardware, having sufficient memory, interfaces, and capacity to perform the functions described herein. 
     While  FIG. 6  and  FIG. 9  depict two different embodiments of the flow logic  116  to measure various parameters of the flow process, the present invention contemplates that the functions of these two embodiments may be performed by a single flow logic  116 . 
     The pressure sensors  108  may include electrical strain gages, optical fibers and/or gratings, ported sensors, ultrasonic sensors, among others as described herein, and may be attached to the pipe by adhesive, glue, epoxy, tape or other suitable attachment means to ensure suitable contact between the sensor  108  and the pipe  104 . The sensors  108  may alternatively be removable or permanently attached via known mechanical techniques such as mechanical fastener, spring loaded, clamped, clam shell arrangement, strapping or other equivalents. Alternatively, strain gages, including optical fibers and/or gratings, may be embedded in a composite pipe  104 . If desired, for certain applications, gratings may be detached from (or strain or acoustically isolated from) the pipe  104  if desired. It is also within the scope of the present invention that any other strain sensing technique may be used to measure the variations in strain in the pipe  104 , such as highly sensitive piezoelectric, electronic or electric, strain gages attached to or embedded in the pipe  104 . 
     In various embodiments of the present invention, a piezo-electronic pressure transducer may be used as one or more of the pressure sensors and it may measure the unsteady (or dynamic or ac) pressure variations inside the pipe  104  by measuring the pressure levels inside the pipe  104 . In one embodiment of the present invention, the sensors  104  comprise pressure sensors  108  manufactured by PCB Piezotronics of Depew, N.Y. For example, in one pressure sensor  108  there are integrated circuit piezoelectric voltage mode-type sensors that feature built-in microelectronic amplifiers, and convert the high-impedance charge into a low-impedance voltage output. Specifically, a Model 106B manufactured by PCB Piezotronics is used which is a high sensitivity, acceleration compensated integrated circuit piezoelectric quartz pressure sensor suitable for measuring low pressure acoustic phenomena in hydraulic and pneumatic systems. It has the unique capability to measure small pressure changes of less than 0.001 psi under high static conditions. The 106B has a 300 mV/psi sensitivity and a resolution of 91 dB (0.0001 psi). 
     The pressure sensors  108  may incorporate a built-in MOSFET microelectronic amplifier to convert the high-impedance charge output into a low-impedance voltage signal. The sensors  108  may be powered from a constant-current source and can operate over long coaxial or ribbon cable without signal degradation. The low-impedance voltage signal is not affected by triboelectric cable noise or insulation resistance-degrading contaminants. Power to operate integrated circuit piezoelectric sensors generally takes the form of a low-cost, 24 to 27 VDC, 2 to 20 mA constant-current supply. 
     Most piezoelectric pressure sensors  108  are constructed with either compression mode quartz crystals preloaded in a rigid housing, or unconstrained tourmaline crystals. These designs give the sensors  108  microsecond response times and resonant frequencies in the hundreds of kHz, with minimal overshoot or ringing. Small diaphragm diameters ensure spatial resolution of narrow shock waves. 
     The output characteristic of piezoelectric pressure sensor systems is that of an AC-coupled system, where repetitive signals decay until there is an equal area above and below the original base line. As magnitude levels of the monitored event fluctuate, the output remains stabilized around the base line with the positive and negative areas of the curve remaining equal. 
     Furthermore the present invention contemplates that each of the pressure sensors  108  may include a piezoelectric sensor that provides a piezoelectric material to measure the unsteady pressures of the fluid  102 . The piezoelectric material, such as the polymer, polarized fluoropolymer, PVDF, measures the strain induced within the process pipe  104  due to unsteady pressure variations within the fluid  102 . Strain within the pipe  104  is transduced to an output voltage or current by the attached piezoelectric sensors  108 . 
     The PVDF material forming each piezoelectric sensor  108  may be adhered to the outer surface of a steel strap that extends around and clamps onto the outer surface of the pipe  104 . The piezoelectric sensing element is typically conformal to allow complete or nearly complete circumferential measurement of induced strain. The sensors  108  can be formed from PVDF films, co-polymer films, or flexible PZT sensors, similar to that described in “Piezo Film Sensors technical Manual” provided by Measurement Specialties, Inc. of Fairfield, N.J., which is incorporated herein by reference. The advantages of this technique are the following: 
     1. Non-intrusive flow rate measurements; 
     2. Low cost; 
     3. Measurement technique requires no excitation source. Ambient flow noise is used as a source; 
     4. Flexible piezoelectric sensors can be mounted in a variety of configurations to enhance signal detection schemes. These configurations include a) co-located sensors, b) segmented sensors with opposing polarity configurations, c) wide sensors to enhance acoustic signal detection and minimize vortical noise detection, d) tailored sensor geometries to minimize sensitivity to pipe modes, e) differencing of sensors to eliminate acoustic noise from vortical signals; and 
     5. Higher Temperatures (140C) (co-polymers) 
     It should be appreciated that the use of a USB memory stick  164  with the digital interface  124  allows for the unique ability to easily access and change/modify the functionality of apparatus  100 . For example, because the apparatus may be dependent upon fluid flow characteristics, the apparatus may require customization to function as desired. The use of the USB memory stick  164 , allows the apparatus  100  to be customized easily. Additionally, the portability and ease of use of the USB memory stick  164  allows a user to walk between multiple apparatus  100  and download software and/or upload software as desired. This is because the USB memory stick  164  allows for the storage of data wherein the data may be uniquely identifiable by meter and/or date/time. As such, the use of the USB memory stick  164  provides for a more robust apparatus  100  by allowing the apparatus  100  to be modified with upgraded meter software for enhanced performance and to change and/or include added functionality (i.e. a flow meter and a GVF meter combination). 
     It should be further appreciated that the use of the digital interface  124  with the USB memory stick  164  advantageously allows for easy servicing and/or customizing of the apparatus as required. For example, service on the apparatus  100  may be performed using a variety of different tools depending upon the person (customer, trained distributor, field technician) performing the service. Typically, when there is a service requirement, the person performing the service needs to obtain basic information regarding the state of the apparatus  100  by querying the processing unit  114  via a front panel keypad on the display device  118 . Depending upon the information obtained and the level of service to be conducted, more detailed internal systemic parametric information from the processing unit  114  may be required. This may be obtained via the USB memory stick  164  and the data obtained may be uniquely identified by the meter and/or date/time and sent to an external facility (i.e. distributor and/or manufacturer) for further analysis. Using this data, it may then be determined if an issue exists and if so, whether the issue may be fixed remotely or whether a configuration file with appropriate parameter changes can be uploaded to the apparatus  100  via the USB memory stick  164  by the customer/distributor rep or whether a site visit by a trained distributor service technician or manufacturer field technician is required. Alternatively, the user may send the USB memory stick  164  containing the obtained data to the distributor and/or manufacturer for further analysis and diagnosis of the industrial meter offsite. In return, the distributor and/or manufacturer may send the user a USB memory stick  164  having any appropriate software fixes and/or meter settings stored thereon which the user may simply upload to the apparatus  100  to update and/or fix the apparatus  100 . 
     It should be understood that any of the features, characteristics, alternatives or modifications described regarding a particular embodiment herein may also be applied, used, or incorporated with any other embodiment described herein. 
     Although the invention has been described and illustrated with respect to exemplary embodiments thereof, the foregoing and various other additions and omissions may be made therein and thereto without departing from the spirit and scope of the present invention. 
     The present invention can be embodied in the form of computer-implemented processes and apparatuses for practicing those processes. The present invention can also be embodied in the form of computer program code containing instructions embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other computer-readable storage medium, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. The present invention can also be embodied in the form of computer program code, for example, whether stored in a storage medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits. 
     It should be understood that any of the features, characteristics, alternatives or modifications described regarding a particular embodiment herein may also be applied, used, or incorporated with any other embodiment described herein. 
     Although the invention has been described and illustrated with respect to exemplary embodiments thereof, the foregoing and various other additions and omissions may be made therein and thereto without departing from the spirit and scope of the present invention.