Patent Abstract:
Methods and systems for predicting fuel sensor performance during motion are disclosed. In one embodiment, a method includes receiving tank geometry information, receiving sensor configuration information, and receiving tank motion information. The method then computes a fuel (surface) plane-to-sensor intersection for at least one tank position based on the tank motion information, and also computes a wetted volume at every fuel (surface) plane-to-sensor intersection for each sensor location based on the sensor configuration information. Finally, the method computes a fuel quantity at every fuel (surface) plane-to-sensor intersection based on a sum of the wetted volumes.

Full Description:
FIELD OF THE INVENTION 
   The present disclosure relates to measurement systems, and more specifically, to methods and systems for predicting the accuracy of information supplied by sensors within fuel or other liquid tanks experiencing motion with six degrees of freedom. 
   BACKGROUND OF THE INVENTION 
   Fuel sensors may be placed within the fuel tanks of aircraft in order to approximate the amount of fuel remaining in the tanks. During flight, the aircraft, along with the fuel tanks and the fuel within the tanks, may experience motion throughout six degrees of freedom (including pitch, roll, and yaw). For some types of aircraft, including high performance fighter aircraft, the fuel within the tanks may be subject to very high velocities and very large gravitational forces, thus causing the fuel within the tanks to shift substantially within the tanks. The placement of the sensors within the fuel tanks may therefore be critical to the accuracy of the fuel measurements, particularly during such extreme flight conditions. 
   Conventional methods of determining the placement of the sensors within the fuel tanks depend upon trial-and-error techniques. For example, a designer may make a “best guess” placement of the sensors within the fuel tanks. This initial design is then built and tested in a test fixture that simulates actual flight conditions and measures the performance. If this initial design does not provide the required degree of accuracy, the locations of the sensors may be adjusted, and the testing process repeated, until a satisfactory result is obtained. 
   Although desirable results have been achieved using such conventional methods, the trial-and-error method of determining the locations of the fuel sensors may be expensive, particularly for designs that require a relatively large number of iterations to achieve acceptable sensor locations. The repeated design, fabrication, and testing of fuel tank designs may involve considerable labor costs and may take a substantial amount of time to complete as well. Novel methods for predicting the accuracy of information supplied by sensors within fuel tanks that may reduce or eliminate the expense of the conventional trial-and-error methods would therefore be useful. 
   SUMMARY OF THE INVENTION 
   The present invention relates to methods and systems for predicting the accuracy of the information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom. Apparatus and methods in accordance with the present invention may advantageously allow a designer to rapidly perform computational simulations for a variety of system configurations, sensor configurations, etc. that predict the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom. Thus, improved system designs may be achieved at lower cost in comparison with state-of-the-art trial-and-error methods. 
   In one embodiment, a method of determining a volume of liquid within a tank during motion includes receiving tank geometry information, receiving sensor configuration information, and receiving tank motion information. The method then computes a fuel (surface) plane-to-sensor intersection for at least one tank position based on the tank motion information, and also computes a wetted volume at every fuel (surface) plane-to-sensor intersection for each sensor location based on the sensor configuration information. Finally, the method computes a fuel quantity at every fuel (surface) plane-to-sensor intersection based on the sum of the wetted volumes. In further embodiments, the method may also include determining a computational error, and comparing that error with at least one previously computed error to determine an optimized sensor configuration. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The preferred and alternative embodiments of the present invention are described in detail below with reference to the following drawings. 
       FIGS. 1A through 1D  show a flow chart of a method of predicting the accuracy of information supplied by sensors within fuel tanks during motion in accordance with an embodiment of the invention; 
       FIG. 2  is a representative system for predicting the accuracy of information supplied by sensors within fuel tanks during motion in accordance with another embodiment of the present invention; and 
       FIG. 3  is a side elevational view of a fuel tank having a plurality of sensors. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   The present invention relates to methods and systems for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom. Many specific details of certain embodiments of the invention are set forth in the following description and in  FIGS. 1–2  to provide a thorough understanding of such embodiments. One skilled in the art, however, will understand that the present invention may have additional embodiments, or that the present invention may be practiced without several of the details described in the following description. 
   In general, embodiments of the present invention may allow a designer to rapidly perform computational simulations to predict the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of motion. Accordingly, the designer may quickly and efficiently perform optimization studies of various sensor configurations until a satisfactory or optimal configuration is determined. Embodiments of the present invention may advantageously reduce or eliminate the relatively higher costs associated with trial-and-error experimental studies, and may provide improved system designs at lower cost in comparison with conventional state-of-the-art trial-and-error methods. 
     FIGS. 1A through 1D  show a flow chart of a method  100  of predicting the accuracy of information supplied by sensors  304 ,  306 ,  308  within a fuel tanks  300  ( FIG. 3 ) experiencing motion in accordance with an embodiment of the invention. In this embodiment, the method  100  is initiated at block  102  by launching a web-based browser application. At a block  104 , one or more height-to-volume files are input into the analysis program, along with one or more files defining the geometric definition of the fuel tank  300  and a sensor configuration for analysis. The System and Sensor configuration files and height-to-volume files are saved to the user&#39;s account. A user may then select applicable height-to-volume files, system files, and sensor configuration files to run an analysis at block  106 . The analysis is then initiated at block  108 . The system configuration selected by the user is read into the analysis program at block  110 , and the sensor configuration is read into the analysis program at block  112 . The tank height-to-volume information is read in at block  114 . As noted in block  114  of  FIG. 1A , the height-to-volume information varies with attitude because, generally speaking, a fuel tank may be geometrically non-linear resulting in different fuel plane height for every attitude of the same fuel quantity. Height-to-volume information may be obtained from a Computer Aided Design (CAD) model by placing the tank solid at a given attitude, and then slicing through the solid from top to bottom in incremental steps. Each slice is the volume of the solid at that height. If necessary, a conversion of the coordinates of the height-to-volume information must be performed at block  116  to agree with the coordinate system specified in the system configuration. 
   With reference to  FIG. 1B , the method  100  continues by initiating an iteration loop, starting at the initial attitude at block  118  and continuing until all attitudes have been completed. The next step in the iteration loop, at block  120 , mathematically transforms the coordinates of the sensor configuration based on new pitch and roll attitude geometry. A validation of the transformation is also performed at block  120 . The method  100  further includes assigning height-to-volume array values to the new attitude at block  122 . Next, at block  124 , the height-to-volume information of the new attitude is expanded (via interpolation) to achieve sensor readings at one or more desired fuel (surface) plane-to-sensor intersections. A wetted volume on each transformed sensor (e.g. wetted volumes  316 ,  318 ,  320  corresponding to sensors  304 ,  306 ,  308  in  FIG. 3 ) is determined at every fuel (surface) plane-to-sensor intersection (e.g. fuel plane  302  intersects sensors  304 ,  306 ,  308  at fuel plane-to-sensor intersections  310 ,  312 ,  314  in  FIG. 3 ) at block  126 . The quantity of fuel is calculated at block  128  for every fuel (surface) plane-to-sensor intersection  310 ,  312 ,  314  based on the sum of the wetted sensor volumes  316 ,  318 ,  320  plus or minus any gain. 
   As further shown in  FIG. 1B , error is calculated to determine whether an optimum reduction of the error was achieved, at block  130 . In one embodiment, the error is calculated by determining the sensor value (based on wetted area) at each level and comparing it to the actual (known) value the tank holds at that level. Any difference is error. 
   The optimization of the error is best explained by first describing how the sensor converts wetted area to quantity in at least one embodiment of the present invention. In one embodiment, a sensor consists of two or three concentric metal tubes. The sensors are electrically energized by a low voltage source (signal amplifier). As fuel covers the sensor, electrical current supplied by the amplifier is transferred from the inner to outer tube. The more that covers the sensor the greater the current transfer rate. This transfer rate is measured in capacitance (pF). The outer tube returns the capacitance value back to the signal amplifier which converts the value to quantity. 
   Optimization may then be conducted by changing the gap between the inner and outer tube to change the rate of capacitance or current transfer. This gap can be changed physically (e.g. inner tube is physically shaped) or electronically (e.g. inner tube diameter is constant). By determining the error (+/−) and applying a gain (loss) to the sensor, the gap can be electronically adjusted to increase or decrease its reading to minimize error. Optimization is adjusted throughout the entire sensor length to prevent an “overshoot” or illogical value (e.g. the sensor cannot read 10 gallons at 5 inches covered and 9.97 gallons at 5.03 inches covered). 
   If the optimum reduction in error was not achieved (block  132 ), then the method  100  includes a gain adjustment (plus or minus) on one or more of the sensors to reduce the error at block  134 . The method  100  then returns to block  126  to repeat the actions set forth in blocks  126  through  130 . If, however, the optimum reduction in error is achieved (block  136 ), then the method  100  determines whether all attitudes of interest have been computed at block  138 . If all attitudes of interest have not been computed (block  140 ), then the next attitude is set, and the method  100  returns to block  120  and repeats the actions set forth in blocks  120  through block  140 . 
   If all the attitudes of interest have been computed (block  142 ), then a determination is made regarding whether the fuel gauging system is non-linear at block  144 , as shown in  FIG. 1C . This determination may depend, for example, on the fact that sensors may be procured as non-linear or linear. If the result of this determination is negative, meaning a linear fuel gauging system (block  146 ), then the method  100  proceeds to output the computational results for import to an on-board computer at block  148 . Furthermore, a secondary formatting of these results may also be prepared for graphical display at block  148 . 
   With continued reference to  FIG. 1C , if the fuel gauging system is determined to be non-linear (block  150 ), then the method  100  provides the option to optimize for one attitude or all attitudes of interest at block  152 . If the user desires to optimize for only one attitude (block  154 ), then the method  100  begins iterating through all attitudes at block  156  in order to determine the errors based on the one selected attitude. It will be appreciated that optimization for only one attitude for a non-linear system permits the user to test a fixed value sensor—one that is optimized for only one attitude—against all other attitudes to get the resulting errors. Errors may be severe in this case, but it permits the user to determine if the errors are tolerable. At block  158 , the method  100  begins iterating through each fuel (surface) plane-to-sensor intersection (e.g. fuel plane-to-sensor intersections  310 ,  312 ,  314  in  FIG. 3 ). Gain values of a preferred optimized attitude are assigned to the remaining attitudes at block  160 . The method  100  then calculates quantities of fuel based on the sum of all wetted sensor volumes (e.g. wetted volumes  316 ,  318 ,  320  corresponding to sensors  304 ,  306 ,  308  in  FIG. 3 ) plus the optimized gain at block  162 . An error is then calculated at block  164 , and the method  100  proceeds to block  148  and outputs the computational results for import to an on-board computer (and also the secondary formatting for graphical display) at block  148 . 
   If it is determined at block  152  that the results are to be optimized for all attitudes (block  166 ), then the method  100  begins iterating through all attitudes at block  168 , as shown in  FIG. 1D . Similarly, the method  100  begins iterating through each fuel (surface) plane-to-sensor intersection at block  170 . At block  172 , a gain is assigned and fuel quantities are recalculated. The method  100  then determines whether all attitudes of interest have been completed at block  174 . If not (block  176 ), then the method  100  increments to the next attitude at block  178 , and the method  100  returns to the block  170  to repeat the actions set forth in blocks  170  through  174 . 
   After all attitudes have been completed (block  180 ), the method  100  then calculates the error for all attitudes using a common gain, and determines whether an optimum reduction in error has been achieved, at block  182 . If an optimum reduction in error has not been achieved (block  184 ), then a common gain is adjusted (plus or minus) for every intersection at block  186 . The method  100  then returns to block  168  and repeats the actions set forth in blocks  168  through  182 . If, however, at block  182  it was determined that an optimum reduction in error had been achieved (block  188 ), then the method  100  proceeds to a block  190  and prepares the computational results for import to an on-board computer, and also for secondary formatting of the results for graphical display. 
   A variety of systems may be conceived that may incorporate methods for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom. For example,  FIG. 2  is a representative system  200  for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom in accordance with another embodiment of the present invention. Unless otherwise specified below, the components of the system  200  are of generally-known construction, and will not be described in detail. For the sake of brevity, only significant details and aspects of the system  200  will be described. 
   As shown in  FIG. 2 , in this embodiment, the system  200  includes a computer  202  having a Central Processing Unit (CPU)  204  and a memory component  206 . The memory component  206  may include one or more memory modules, such as Random Access Memory (RAM) modules, Read Only Memory (ROM) modules, Dynamic Random Access Memory (DRAM) modules, and any other suitable memory modules. The computer  202  also includes Input/Output (I/O) components  208  that may include a variety of known I/O devices, including but not limited to, network connections, video and graphics cards, disk drives or other computer-readable media drives, displays, or any other suitable I/O modules. A data bus  210  operatively couples the CPU  204 , memory component  206 , and the I/O component  208 . 
   The system  200  embodiment shown in  FIG. 2  further includes a data storage component  212  operatively coupled to the computer  202 . In this embodiment, the data storage component  212  includes a plurality of input files  214  that may be selected by a user  230  to perform simulation studies, as described more fully above. The data storage component  212  is operatively coupled to the computer  202  via a first communication link  216 . In alternate embodiments, the data storage component  212  may be integral with the computer  202 , or may be remotely situated with respect to the computer  202 . In further embodiments, the input files  214  may be stored on the memory component  206  of the computer  202 , and the data storage component  212  may be eliminated. 
   As further shown in  FIG. 2 , the system  200  further includes a control component  220  having a monitor  222  and a command input device  224  (e.g. a keyboard, an audio-visual input device, etc.). A second communication link  218  operatively couples the control component  220  to the computer  202 . The system  200  also includes an auxiliary output device  226  coupled to the computer  202  by a third communication link  228 . The auxiliary output device  226  may include a printer, a writeable Compact Disk (CD) device, a magnetic storage device, a communication port, or any other desired output device. 
   In one aspect, a machine-readable medium may be used to store a set of machine-readable instructions (e.g. a computer program) into the computer  202 , wherein the machine-readable instructions embody a method for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom in accordance with the teachings of the present invention. The machine-readable medium may be any type of medium which can store data that is readable by the computer  202 , including but not limited to, for example, a floppy disk, CD ROM, optical storage disk, magnetic tape, flash memory card, digital video disk, RAM, ROM, or any other suitable storage medium. The machine-readable medium, or the instructions stored thereon, may be temporarily or permanently installed in any desired component of the system  200 , including, for example, the I/O component  208 , the memory component  206 , the data storage component  212 , and the auxiliary output device  226 . Alternately, the machine-readable instructions may be implemented directly into one or more components of the computer  202 , without the assistance of the machine-readable medium. 
   In operation, the computer  202  may be configured to perform one or more of the aspects of the methods for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom described above with reference to  FIGS. 1A through 1D . For example, an operator  230  may input a command through the command input device  224  to initiate the browser application, and to input one or more of the input files  214  described above. More specifically, the input files  214  may represent one or more of the system configuration files, the sensor configuration files, and the tank height-to-volume files, or any other inputs provided to and utilized by the method  100  described above and shown in  FIG. 1 . 
   For example, the input files  214  may be transmitted from the data storage component  212  to the computer  202 . The computer  202  may be configured to perform the above-described method for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom. In a preferred embodiment, a set of software instructions may be stored in the computer  202  (e.g. in the memory component  206 ) that causes the user inputs to be read into the memory component  206  and processed using the CPU  204  in accordance with the teachings herein, including one or more of the processes described above with respect to  FIGS. 1A through 1D . Alternately, one or more aspects of the various processes described above may be implemented in the computer  202  using any suitable programmable or semi-programmable hardware components (e.g. Erasable Programmable Read Only Memory [EPROM] components). 
   Results of the analysis in accordance with one the present invention may be transmitted via the data bus  210  to the I/O component  208 . The results may also be transmitted to the control component  220  and to the auxiliary output device  226  via the second and third communications links  218  and  228 . The operator  230  may view the results of the analysis method(s) on the control monitor  222 , and may take appropriate action, including revising analysis parameters and inputs, and continuing or repeating the one or more embodiments of analysis methods using different test data as desired. 
   Embodiments of methods and systems for predicting the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom may provide significant advantages over the current methods. For example, embodiments of the present invention may allow a designer to rapidly perform computational simulations for a variety of system configurations, sensor configurations, etc. to predict the accuracy of information supplied by sensors within fuel tanks experiencing motion with six degrees of freedom. Since the designer may quickly and efficiently perform iteration studies of various sensor configurations using methods and systems in accordance with the present invention, the relatively higher costs associated with trial-and-error experimental studies may be reduced or eliminated. Thus, improved system designs may be achieved at lower cost in comparison with current trial-and-error methods. 
   While preferred and alternate embodiments of the invention have been illustrated and described, as noted above, many changes can be made without departing from the spirit and scope of the invention. Accordingly, the scope of the invention is not limited by the disclosure of the preferred embodiment. Instead, the invention should be determined entirely by reference to the claims that follow.

Technology Classification (CPC): 6