Abstract:
A method and system for providing a linear signal from a flow transducer. A non-linear raw signal can be obtained from a mass flow transducer. An approximated error comprising a discrete sinusoidal function incremented by a variable and selectable omega value can then be subtracted from the non-linear raw signal, in order to provide a subtracted result and reduce an error range thereof. The linear signal can then be obtained from the subtracted result in order to linearize a raw output from the flow transducer. A user is thus permitted to tune a frequency increment associated with the variable and selectable omega value in order to reduce the error range thereof. Linearized airflow and liquid flow sensor outputs can thus be generated by allowing a user the freedom to tune the frequency increment depending upon the user&#39;s flow range for reducing errors.

Description:
TECHNICAL FIELD 
   Embodiments are generally related to flow sensors. Embodiments are also related to mass airflow transducers and liquid flow transducers. Embodiments are additionally related to techniques and devices for providing a linear signal from mass airflow transducers and/or liquid flow transducers. 
   BACKGROUND OF THE INVENTION 
   Mass Flow transducers are used in a variety of industries to quantify the flow rate of a substance. Various types of mass flow transducers are known. For example, mass airflow transducers and liquid flow transducers are utilized in many commercial, consumer and medical applications. The medical industry, for example, uses mass flow transducers to monitor and control the breathing of a patient. One common technique for sensing mass flow involves utilizing multiple resistive temperature detectors on each side of a heating element parallel to the direction of flow. As a mass such as a fluid or gas flows across the resistors, resistors that are located upstream from the heating element are cooled, and resistors located downstream from the heating element are heated. When a voltage is applied across these resistors, an electrical signal is generated. The signal generated using multiple resistive temperature detectors are highly non-linear and not ideal for use in most “high accuracy” control systems. 
   Two types of methods are currently utilized to approximate a non-linear mass flow signal into a linear output: piece-wise linear functions or polynomial approximation. In piece-wise linear functions, the linear signal is approximated by many linear equations distributed throughout the range of the signal. In polynomial approximation, a polynomial expression is used to describe the signal. Another method has been implemented for linearizing a mass flow signal by subtracting discrete sinusoidal functions incremented by omega, a frequency increment, that describe the original error (or non-linearity) of the signal. 
   A need exists for improved accuracy in the generation of linear signal with less coefficients and mathematical steps as a part of mass flow transducer. It is believed that a solution to this problem involves the implementation of an improved method and system for linearizing the raw output of a mass airflow and/or liquid flow transducer as described in greater detail herein. 
   BRIEF SUMMARY 
   The following summary is provided to facilitate an understanding of some of the innovative features unique to the embodiments disclosed and is not intended to be a full description. A full appreciation of the various aspects of the embodiments can be gained by taking the entire specification, claims, drawings, and abstract as a whole. 
   It is, therefore, one aspect of the present invention to provide for an improved flow sensor method and system. 
   It is another aspect of the present invention to provide for a method and system for generating a linear signal from a mass airflow transducer and/or a liquid flow transducer. 
   It is another aspect of the present invention to provide a method and system for linearizing a raw output signal from a mass flow transducer. 
   It is a further aspect of the present invention to provide for a method and system for providing a linear signal from a mass air flow and liquid flow transducer. 
   The aforementioned aspects and other objectives and advantages can now be achieved as described herein. A method and system for providing a linear signal from a flow transducer is disclosed. A non-linear raw signal can be obtained from a mass flow transducer. An approximated error comprising a discrete sinusoidal function incremented by a variable and selectable omega value can then be subtracted from the non-linear raw signal, in order to provide a subtracted result and reduce an error range thereof. The linear signal can then be obtained from the subtracted result in order to linearize a raw output from the flow transducer. A user is thus permitted to tune a frequency increment associated with the variable and selectable omega value in order to reduce the error range thereof. Linearized airflow and liquid flow sensor outputs can thus be generated by allowing a user the freedom to tune the frequency increment depending upon the user&#39;s flow range for reducing errors. 
   In general, a system for providing a linear signal from a flow transducer can be implemented, which includes a data-processing apparatus, a module executed by the data-processing apparatus, the module and the data-processing apparatus being operable in combination with one another to obtain a non-linear raw signal from a flow transducer; approximate a non-linear error from the non-linear raw signal; subtract from the non-linear raw signal, an approximated error comprising a discrete sinusoidal function incremented by a variable and selectable value, in order to provide a subtracted result and reduce an error range thereof; and obtain a linear signal from the subtracted result in order to linearize a raw output from the flow transducer. 
   The variable and selectable value generally comprises an omega variable. The data-processing apparatus and the module are also operable in combination with one another to permit a user to tune a frequency increment associated with the variable and selectable value in order to reduce the error range thereof. The data-processing apparatus can be provided as an Application Specific Integrated Circuit (ASIC) that is associated with the mass flow transducer and/or in the context of a computer, including components such as a memory, processor, etc. The data-processing apparatus or ASIC can be configured to include a memory for storing a plurality of memory storing coefficients, an amplifier, and an approximation mechanism for performing an approximation calculation, wherein the approximation receives the plurality of memory storing coefficients from the memory and an output signal from the amplifier and wherein the approximation mechanism approximates the non-linear error from the non-linear raw signal. Such an ASIC can also be configured to include a circuit for generating the discrete sine function, wherein the circuit provides the discrete sine function to the approximation mechanism, and a subtractor that receives an output signal from the amplifier and an output signal from the approximation mechanism, wherein the subtractor subtracts the approximated error from the non-linear signal to produce the subtracted result. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The accompanying figures, in which like reference numerals refer to identical or functionally-similar elements throughout the separate views and which are incorporated in and form a part of the specification, further illustrate the embodiments and, together with the detailed description, serve to explain the embodiments disclosed herein. 
       FIG. 1  illustrates a schematic diagram of a Temperature Sensing Wheatstone bridge circuit that can be adapted for use with a mass airflow transducer and/or a liquid flow transducer, in accordance with a preferred embodiment; 
       FIG. 2  illustrates a schematic diagram of a process for linearizing a non-linear, raw, mass flow signal, in accordance with a preferred embodiment; 
       FIG. 3  illustrates a graph depicting the voltage signal verses airflow of the non-compensated and compensated (desired) signals, in accordance with a preferred embodiment; 
       FIG. 4  illustrates a block diagram showing a process of linearizing a non-linear signal using an ASIC, in accordance with a preferred embodiment; 
       FIG. 5  illustrates a high level flow chart of operations depicting a linearization method for a mass flow transducers, in accordance with a preferred embodiment; 
       FIG. 6  illustrates a graph depicting a percentage error verses normalized flow for the linearized output of a mass flow transducer, in accordance with a preferred embodiment; 
       FIGS. 7(   a ) and  7 ( b ) illustrate an example equation, which can be implemented in accordance with a preferred embodiment; 
       FIG. 8  illustrates a graph depicting a percentage error verses normalized flow for the linearized output of a mass airflow sensor or liquid flow sensor, in accordance with a preferred embodiment; and 
       FIG. 9  illustrates a graph depicting a percentage error verses normalized flow for the linearized output of a mass airflow sensor or liquid flow sensor, in accordance with a preferred embodiment. 
   

   DETAILED DESCRIPTION 
   The particular values and configurations discussed in these non-limiting examples can be varied and are cited merely to illustrate at least one embodiment and are not intended to limit the scope thereof. 
     FIG. 1  illustrates a schematic diagram of bridge circuit  100  or system that can be adapted for use with a mass airflow transducer and/or a liquid flow transducer, and implemented in accordance with a preferred embodiment. The system of circuit  100  generally includes a group of resistors  104 ,  106 ,  108 ,  110 , which are connected to an excitation voltage  120  and an amplifier  115 . The resistors  104 ,  106 ,  108 ,  110  are arranged as a Wheatstone bridge circuit and are connected to the amplifier  115  at nodes V 1  and V 2 . The circuit  100  can be implemented in the context of an ASIC (Application Specific Integrated Circuit). 
   As mass flows across the group of resistors  104 ,  106 ,  108 ,  110 , the resistors  106  and  110  upstream from a resistor  109  (i.e., a heater) are cooled and the resistors  104  and  108  downstream from the heater or resistor  109  are heated. Note that the resistor  109  is connected to an excitation voltage  130 . An electrical signal can be generated when the excitation voltage  120  is applied across the group of resistors  104 ,  106 ,  108 ,  110 . A temperature difference is produced by the fluid stream passing over the heater  109  and then over the resistors  104  and  108 . This temperature difference, unbalances the bridge causing a voltage difference that is amplified using the amplifier  115  and then calibrated to the mass flow rate. The signal obtained from the amplifier  115  generally constitutes a non-linear raw signal with respect to fluid flow. 
     FIG. 2  illustrates a schematic diagram of a system  200  of linearizing the non-linear raw signal obtained from the amplifier  115 , in accordance with a preferred embodiment. Note that in  FIGS. 1-2 , identical or similar parts or elements are generally indicated by identical reference numerals. For example, resistors  104 ,  106 ,  108 ,  110  depicted in  FIG. 1 , generally represent the group of resistors  207  depicted in  FIG. 2 . The amplifier  115  and heater  109  of the bridge circuit  100  are also depicted in  FIG. 2  and can be adapted for use with a mass flow transducer  202 , which is electrically connected to an ASIC  201 . The ASIC  201  generally includes an amplifier  115 , which provides an electrical signal to an approximation mechanism  225 . ASIC  201  also includes a memory  240 , which can store coefficients describing an error realized during calibration. Memory  240  and amplifier  115  are electrically connected to an approximation mechanism  225 . 
   The output signal from the circuit  100  can be provided to the amplifier  115  and is subject to amplification by amplifier  115 . The output signals from a memory storing coefficients describing an error realized during calibration are stored in memory  240 . The data stored in memory  240  and an amplified non-linear signal from amplifier  115  can be provided as input signals to approximation mechanism  225 . Such an approximation method approximates an error from the original non-linear raw signal utilizing a circuit  220  for generating a discrete sine function. A subtractor  230  can then be utilized to subtract the approximated error from the original non-linear raw signal, in order to obtain a linear signal  235 . Thus, the embodiments described herein can be implemented using ASIC  201  (Application Specific Integrated Circuit) mated with a raw mass flow transducer  202 . 
     FIG. 3  illustrates a graph  300  depicting the variation of voltage verses fluid flow for a non-linear, non-compensated, signal  305  and a linear desired signal  235  in accordance with a preferred embodiment. As indicated in graph  300 , a non-linear raw signal  305  obtained from a mass flow transducer  202  is converted into a linear signal  235  as a result of the operations depicted in  FIG. 2  and in association with the circuit  100  depicted in  FIG. 1 . The method for linearizing the signal will be contained in the ASIC  201 . 
     FIG. 4  illustrates a block diagram  400  showing a process of linearizing a non-linear signal using an ASIC  201 , in accordance with a preferred embodiment. Note that in  FIGS. 1-3 , identical or similar parts or elements are generally indicated by identical reference numerals. The  FIG. 4  illustrates a group of resistors  207 , an excitation voltage  120 , a functionality  348  for changing mass flow, an amplifier  115 , a non linear signal  350 , an ASIC  201 , a circuit  220  for generating discrete sine functions, a subtractor  230 , an approximation mechanism  225  and a linear signal  235  as depicted previously with respect to in  FIG. 2  and  FIG. 3 . Note that the functionality  348  for changing mass flow is utilized for creating the non-linear signal. 
     FIG. 5  illustrates a high level flow chart of operations depicting a linearization method  500  for a mass flow transducer  202 , in accordance with a preferred embodiment. As indicated at block  505 , a linear signal can be obtained from the mass flow transducer  202  depicted in  FIG. 2 . Thereafter, as described at block  510 , a non-linear error obtained from the raw output signal generated by circuit  100  depicted in  FIG. 1  can be approximated using a discrete sine function generated by the circuit  220  depicted in  FIG. 2 . Thereafter, as depicted at block  520 , a linear signal can be obtained by subtracting (e.g., using the subtractor  230  depicted in  FIG. 2 ) the approximated error from the original raw signal as depicted previously at block  515 . 
     FIG. 6  illustrates a graph  600  depicting a percentage error verses normalized flow for the linearized output of a mass flow sensor, in accordance with a preferred embodiment. As indicated in graph  600 , an optimized 7 th  order polynomial approximation  610  and a 10 segment piece-wise linear approximation  605  can be compared with the Error Plot of subtracting 7 optimized sinusoidal curves  615  used to approximate the original error from the raw signal. Note that instead of approximating the mass flow signal, however, one can approximate the ERROR from the original raw signal using discrete sine functions and subtract the ERROR from the original raw signal to linearize it. This method allows for improved accuracy in the linear signal with less coefficients and mathematical steps. This method for linearizing the raw output of a mass flow transducer is superior to present Industry methods due to the reduction of Error (increase in accuracy) for less coefficients (less mathematical calculations providing a decrease in overall sensor response time) used to describe the signal. Such a method is based on the ability to manipulate the frequency increment of the Sinusoidal Expressions describing the Original Sensor&#39;s Error. 
     FIGS. 7(   a ) and  7 ( b ) illustrate an example equation  702  as indicated at block  700 , which can be implemented in accordance with a preferred embodiment.  FIGS. 7(   a ) and  7 ( b ) illustrate the same equation  702 . The illustration presented in  FIG. 7(   b ) is provided, however to demonstrate the fact that the Omega, w, the Frequency increment is preferably a variable inside the digital ASIC  100  that can be tuned for best results to describe the original error of the signal within the range required by a particular user. 
   In the cases where a customer desires to use an airflow (or liquid flow) sensor in a flow range smaller than the mechanical flow range of the sensor, the frequency increment can be “tuned” to the specific range that the user will use for the sensor. For example, a user may desire to utilize a +/−200 sccm (meaning 200 sccm, standard cubic centimeters per minute, in each direction) airflow sensor in a range of −200 sccm to 100 sccm. In this case, by providing the user with the freedom to change the frequency increment, the user can “tune” the sensor “digitally” to that specific range instead of using the +/−200 sccm range. For example, refer to the projected Error Plots  800  and  900  respectively depicted in  FIGS. 8 and 9  using SAME raw-transducer signal data with different frequency increments. 
     FIG. 8  illustrates a graph  800  depicting a percentage error verses normalized flow for the linearized output of a mass airflow sensor or liquid flow sensor, in accordance with a preferred embodiment.  FIG. 9  illustrates a graph  900  depicting a percentage error verses normalized flow for the linearized output of a mass airflow sensor or liquid flow sensor, in accordance with a preferred embodiment. Graph  800  is generally plotted in a range of −200 sccm to +200 sccm. Graph  900 , on the other hand, is generally plotted in a range of −200 sccm to +100 sccm.  FIG. 9  indicates that the Frequency increment can be “tuned” for the specific customer range within the full mechanical range. Thus, it can be appreciated that Omega, w, is not a constant as in the prior art, but is implemented as a tunable variable in order to digitally tweak the process depending on the mass air flow and/or liquid flow range. 
   Note that the embodiments disclosed herein can be implemented in the context of a host operating system and one or more module(s). In the computer programming arts, a software module can be typically implemented as a collection of routines and/or data structures that perform particular tasks or implement a particular abstract data type. Software modules generally comprise instruction media storable within a memory location of a data-processing apparatus and are typically composed of two parts. First, a software module may list the constants, data types, variables, routines and the like that can be accessed by other modules or routines. Second, a software module can be configured as an implementation, which can be private (i.e., accessible perhaps only to the module), and that contains the source code that actually implements the routines or subroutines upon which the module is based. The term module, as utilized herein can therefore refer to software modules or implementations thereof. Such modules or instruction media can be utilized separately or together to form a program product that can be implemented through signal-bearing media, including transmission media and recordable media. Such a module or modules can be utilized, for example, to carry out the methodology depicted in  FIG. 5 . 
   A data-processing apparatus can be provided via the ASIC  201  described herein to perform a particular task or series of tasks or via another data-processing apparatus, such as a computer. Alternatively, ASIC  201  may function in association with a computer to provide the functionalities described herein. Although such a data-processing apparatus can be implemented in the context of a fully functional data-processing apparatus, those skilled in the art will appreciate that the mechanisms of the present invention are capable of being distributed as a program product in a variety of forms, and that the present invention applies equally regardless of the particular type of signal-bearing media utilized to actually carry out the distribution. Examples of signal bearing media include, but are not limited to, recordable-type media such as floppy disks or CD ROMs and transmission-type media such as analogue or digital communications links. 
   Any type of computer-readable media that can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, digital versatile discs (DVDs), Bernoulli cartridges, random access memories (RAMs), and read only memories (ROMs) can be used in connection with the embodiments. 
   It will be appreciated that variations of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Also that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.