Patent Abstract:
A system for real-time signal processing for vehicle monitoring, including a first device disposed in a tire of a vehicle and producing a signal that is a function of a tire contact time period, during which a point at the tire circumference stays in contact with the ground, and a second device operative to repetitively perform a first task of processing the signal to calculate the tire contact time period at a first predetermined rate, and to repetitively perform a second task of calculating a tire load based at least in part upon the calculated tire contact time period at a second predetermined rate, wherein said second predetermined rate is less than said first predetermined rate.

Full Description:
BACKGROUND OF THE INVENTION  
       [0001]     This invention relates in general to methods, systems, and apparatuses for processing signals for vehicle monitoring and specifically to methods, systems, and apparatuses for real-time processing of sensor signals for vehicle tire load monitoring.  
         [0002]     A typical automotive vehicle may include many monitoring and control systems, for example, a cruise assist system (cruise control), an Anti-Lock Braking System (ABS), an Anti-Theft Vehicle Protection System (AVP), a Global Positioning System (GPS), and a variety of lighting, safety, climate control, and audio systems, just to name a few. These systems include many different components; including, for example, sensors, processors, transmitters, receivers, memory devices, etc. There are many varieties of each component device, for example, the sensors in an automotive vehicle may include tachometers, accelerometers, thermostats, pressure gauges, photo-electric sensors, angle sensors, yaw-rate sensors, etc.  
         [0003]     One type of automotive vehicle system is a Tire Load Monitoring System (TLMS) disclosed in, for example, U.S. patent application Pub. No. US 2003/0058118 A1 published Mar. 27, 2003 in the name of Kitchener C. Wilson (herein after, “the Wilson application”), the disclosures of which are incorporated herein by reference. The Wilson application discloses an accelerometer-based TLMS that estimates tire load information based upon tire contact patch length. The tire contact patch length is calculated from the time period during which a point on the tire circumference stays in contact with the ground. In order to accomplish tire load monitoring in typical dynamic driving situations, the rate of data acquisition typically needs to be at least about 10 kHz to capture the signal from an accelerometer placed in the tire with sufficient resolution and accuracy in order to be useful in determining the tire load.  
         [0004]      FIG. 1  is a simplified block diagram of the known real-time tire monitoring system of the Wilson application, shown generally at  30 . The system  30  is incorporated in a vehicle  32  having a plurality of wheels  34  each carrying a tire  36  mounted on a rim  38 . The tires  36  are shown in their loaded condition, and accordingly each has a flattened deflection contact region  40  in contact with a load-bearing surface (ground), such as a road  42 .  
         [0005]     The tire monitoring system  30  generally includes a contact region detector  50  and an associated receiver-transmitter  52  within each tire  36 ; a tire identifying plaque  54  attached to the sidewall of each tire; and a receiver  56 , data processor  58 , a distributed control subsystem  60 , a data storage unit  62 , an operator display  64 , a remote receiver-transmitter  66  and a data bus  68  within the vehicle  32 . The monitoring system  30  further includes, remote from the vehicle, a remote monitor receiver-transmitter  70  for communicating information to and from the vehicle  32 ; a console  72  through which a technician interacts with the vehicle  32 ; a magnetic wand  74  to identify the physical locations of the tires; and a tire identifying plaque scanner  76  to read the parameter information on the tire identifying plaque  54 .  
         [0006]     Generally, the contact region detector  50  functions to detect tire load-induced deflections, to time the load-induced tire deflection duration and periodicity, and to reduce signal noise. The receiver-transmitter  52  serves to receive the timing information from the contact detector  50 , measure tire pressure and temperature, and transmit these data to the vehicle receiver  56 . The tire identifying plaque  54  on each tire  36  carries machine-readable data relating to parameter values specific to the tire model. The in-vehicle receiver  56  is adapted to receive data transmissions from all tires  36 . The data processor  58  determines tire deformation, tire load, tire molar (air) content, vehicle mass, and the distribution of vehicle mass. The distributed control system  60  includes adaptive vehicle subsystems such as brakes  60   a,  steering  60   b,  suspension  60   c,  engine  60   d,  transmission  60   e,  and so forth, that respond in predetermined fashions to the load, the vehicle mass and the distribution of the vehicle mass. The data storage unit  62  stores the values of parameters and of interim calculations while the operator display  64  provides status information and warnings. The remote receiver-transmitter  66  sends information to the remote monitor receiver-transmitter  70 . The data bus  68  interconnects the system components.  
         [0007]     The known approach taken to the detection of the deflection region of a loaded tire is to sense the acceleration of the rotating tire by means of an accelerometer mounted on the tire, preferably within the tire and more preferably on the inner tread lining of the tire. As the tire rotates and the accelerometer is off the flat deflection region, a high centripetal acceleration is sensed. Conversely, when the accelerometer is on the flat deflection region and not rotating, a low acceleration is sensed. The deflection points are determined at the points where the acceleration transitions between the high and low values.  
       SUMMARY OF THE INVENTION  
       [0008]     This invention relates to methods, systems, and apparatuses for real-time vehicle monitoring signal processing. In one embodiment, a method includes separating processing tasks into a fast task portion and a slow task portion. The fast task portion and slow task portion are performed at different rates. Optionally, the fast task portion and the slow task portion may be coordinated with the transmission of coordination flags. Further, information relating to the tasks may also be transmitted in relation to the flags. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0009]      FIG. 1  is a simplified block diagram of a known real-time tire monitoring system.  
         [0010]      FIG. 2  is a flowchart of a process for real-time tire load monitoring.  
         [0011]      FIG. 3  is a simplified block diagram of a real-time tire monitoring system in accordance with the present invention.  
         [0012]      FIG. 4  is a flowchart of a fast task portion of a process for real-time tire load monitoring in accordance with the present invention.  
         [0013]      FIG. 5  is a flowchart of a slow task portion of a process for real-time tire load monitoring in accordance with the present invention.  
         [0014]      FIG. 6  is a schematic of a Serial Processing Scheme in accordance with the present invention.  
         [0015]      FIG. 7  is a schematic of a Parallel Processing Scheme in accordance with the present invention.  
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0016]      FIG. 2  is a flowchart of a process for real-time tire load monitoring  210 , which, for example, may be used in the system  30  of the Wilson application. The process  210  begins in functional block  215  where a set of default internal variables are loaded into a real-time tire monitoring system, for example the system  30  of  FIG. 1 . The set of variables preferably includes a signal filter frequency value and an expected edge threshold value.  
         [0017]     The process  210  proceeds to functional block  220  where the system  30  acquires data from a contact patch sensor, such as the contact patch region detector  50 . Preferably, the data is acquired by receiving a data signal from a transmitter associated with an accelerometer based contact patch sensor, such as the receiver-transmitter  52 .  
         [0018]     The process  210  then proceeds to functional block  225  where the system  30  filters the data signal. The system  30  sets a frequency range for allowable data signal in order to reduce false data signals. Preferably, the system  30  sets the frequency range as a function of the signal filter frequency value.  
         [0019]     In decision block  230 , the system  30  detects for a rising pulse edge in the allowable data signal. If the rising pulse edge is not detected then the process  210  returns to functional block  220  and proceeds as before. If the rising pulse edge is detected then the process  210  proceeds to functional block  235  where the system  30  measures the duration of a pulse in the allowable data signal to generate a pulse duration value.  
         [0020]     In decision block  240 , the system  30  analyzes the pulse duration value for validity. If the pulse duration value is not valid then the process  210  returns to functional block  220  and proceeds as before. If the pulse duration value is valid then the process  210  proceeds to functional block  245  where the system  30  calculates a tire load value, as least partially based upon the pulse duration value.  
         [0021]     The process  210  proceeds to functional block  250  where the tire load value calculated is used to update a tire load value stored in the system  30 .  
         [0022]     The process  210  then proceeds to functional block  255  where the system  30  calculates an updated signal filter frequency value.  
         [0023]     The process  210  then proceeds to functional block  260  where the system  30  calculates an updated expected edge threshold value.  
         [0024]     The process then proceeds to functional block  265  where the updated internal variables are loaded in place of the internal variables previously used in the calculations in the system  30 .  
         [0025]     The process  210  then returns to functional block  220 , continues through as before, and runs until stopped by some outside interrupt, such as the system  30  being turned off or as will be described below.  
         [0026]     The Process  210  for real-time tire load monitoring consists of a signal processing portion, as generally indicated by a dashed line  270 , and a values calculation portion, as generally indicated by a dashed line  275 . The process  210  continually proceeds though the signal processing and then the value calculations, both portions occurring once per a single processing period.  
         [0027]     In order to accomplish tire load monitoring in dynamic driving situations, the signal processing portion needs to run at about 10 kHz (kilohertz) or faster; thus, typically the process  210  is running at least at about 10 kHz or faster.  
         [0028]      FIG. 3  is a simplified block diagram of a real-time tire monitoring system in accordance with the present invention, shown generally at  130 . The system  130  is entirely incorporated in a vehicle  132  having a plurality of wheels  134  each carrying a tire  136  mounted on a rim  138 . The tires  136  are shown in their loaded condition, and accordingly each has a flattened deflection contact region  140  in contact with a load-bearing surface (ground), such as a road  142 .  
         [0029]     The tire monitoring system  130  generally includes a contact region detector  150 , including, for example, an accelerometer, a microprocessor, and an associated receiver-transmitter  152  within each tire  136 . Preferably, the contact region detector  150  and the associated receiver-transmitter  152  are integrated and mounted on the tire  136 . However, the contact region detector  150  and the associated receiver-transmitter  152  may be separated, for example as the contact region detector  50  and the associated receiver-transmitter  52  are in the Wilson application. Further, the contact region detector  150  and the associated receiver-transmitter  152  may be connected by any suitable manner, such as electrical wiring, RF transmission, or optical interface. The system  130  further generally includes a vehicle receiver-transmitter  156 , a data processor  158 , a distributed control subsystem  160 , a data storage unit  162 , an operator display  164 , and a data bus  168  within the vehicle  132 .  
         [0030]     Generally, the contact region detector  150  functions to detect tire load-induced deflections, to time the load-induced tire deflection duration and periodicity, and to reduce signal noise. The associated receiver-transmitter  152  serves to receive and transmit information to and from the contact detector  150 , and the vehicle receiver-transmitter  156 . The associated receiver-transmitter  152  may also receive and transmit additional information, such as tire pressure and temperature, which may be received from a pressure sensor (not shown) and a temperature sensor (not shown), within each tire  136 . The in-vehicle vehicle receiver-transmitter  156  is adapted to receive and transmit data transmissions to and from all tires  136 . The data processor  158  determines tire deformation, and tire load. Additionally, the data processor may also determine the amount of air in the tire (i.e. the tire molar air content), vehicle mass, and the distribution of vehicle mass. The distributed control system  160  includes adaptive vehicle subsystems such as brakes  160   a,  steering  160   b,  suspension  160   c,  engine  160   d,  transmission  160   e,  and so forth, that may respond in predetermined fashions to the load, the vehicle mass and the distribution of the vehicle mass. The data storage unit  162 , preferably a RAM module, stores the values of parameters and of interim calculations while the operator display  164  provides status information and warnings. The data bus  168  interconnects the system components.  
         [0031]     The approach of the present invention taken to the detection of the deflection region of a loaded tire is to sense the acceleration of the rotating tire by means of the accelerometer of the detector  150  mounted on the tire  136 , preferably on the interior surface of the tire  136  and more preferably on the inner tread lining of the tire  136 . As the tire  136  rotates and the accelerometer is off the flat deflection region, a high centripetal acceleration is sensed. Conversely, when the accelerometer is on the flat deflection region and not rotating, a low acceleration is sensed. The deflection points are determined at the points where the acceleration transitions between the high and low values.  
         [0032]     In one embodiment of the present invention, a process for real-time tire load monitoring, which, for example, may be used in the system  130 , the signal processing and values calculation processes are broken down to two sub-task portions, i.e. a fast task portion  211 , as shown in  FIG. 4 , and a slow task portion  212 , as shown in  FIG. 5 .  
         [0033]      FIG. 4  is a flowchart of the fast task portion  211  of a process for real-time tire load monitoring in accordance with the present invention. Preferably, the fast task portion  211  is running at the same sample rate as data acquisition, typically about 10 kHz. However, the fast task portion  211  may be running at a rate faster or slower than the sample rate of data acquisition.  
         [0034]     Preferably the fast task portion  211  has access to a common data storage, such as the common data storage  162  of the system  130 , where the fast task portion  211  can, for example, access default internal variables and updated internal variables, and store values, for example, a pulse duration value. The fast task portion  211  may have direct access to the common data storage, such as through a wired or wireless interface, or the fast task portion  211  may have indirect access to the common data storage, such as through a command processor. For example, the data processor  158  of the system  130  may act as such a command processor.  
         [0035]     The fast task portion  211  begins in functional block  215  where a set of default internal variables is loaded into the real-time tire monitoring system  130 . The set of variables preferably includes a signal filter frequency value and an expected edge threshold value.  
         [0036]     The fast task portion  211  proceeds to functional block  220  where the system  130  acquires data from the contact patch sensor  150 . Preferably, the data is acquired by receiving a data signal from the receiver-transmitter  152  associated with the accelerometer based contact patch sensor  150 .  
         [0037]     The fast task portion  211  then proceeds to functional block  225  where the system  130  filters the data signal. Preferably, the system  130  uses the signal filter frequency value to filter the data signal.  
         [0038]     In decision block  230 , the system  130  detects for a rising pulse edge in the data signal. If the rising pulse edge is not detected then the fast task portion  211  returns to functional block  220  and proceeds as before. If the rising pulse edge is detected then the fast task portion  211  proceeds to functional block  235  where the system  130  measures the duration of a pulse in the data signal to generate a pulse duration value.  
         [0039]     The fast task portion  211  proceeds to functional block  236  where the system  130  stores the pulse duration value, preferably in the common data storage  162 . It must be understood, however, that the fast task portion  211  may store the pulse duration value in any suitable module. For example, in an alternative embodiment of the invention, the fast task portion  211  stores the pulse duration value in a command processor. In one embodiment of the invention, the data processor  158  of the system  130  acts as such a command processor.  
         [0040]     The fast task portion  211  then proceeds to functional block  265  where updated internal variables are loaded in place of the internal variables currently being used in the system  130 , preferably retrieved from the common data storage  162 .  
         [0041]     The fast task portion  211  then returns to functional block  220  and continues through as before and runs until stopped by some outside interrupt, such as, the system  130  being turned off or as will be described below.  
         [0042]      FIG. 5  is a flowchart of the slow task portion  212  of a process for real-time tire load monitoring in accordance with the present invention. Preferably, the slow task portion  212  is running at a sample rate as slower than the rate of data acquisition, i.e. slower than the rate of the fast task portion  211 . Typically, the sample rate of the slow task portion  212  is greater than the duration of one wheel rotation. For example, at 80 mph (miles per hour) a typical vehicle wheel is rotating at about 15 Hz (hertz). The typical rate of data acquisition is about 10 kHz. As discussed above the fast task portion  211  would preferably be running at least at about the same rate as the rate of data acquisition, and thus the fast task portion typically would be running at about 10 kHz. Thus, in this example the slow task portion would be preferably running at a rate between about 15 Hz and about 10 kHz. Generally, the slow task portion  212  performs updated filter frequency calculation, updated expected edge threshold calculation, and tire load calculation, as will be described below.  
         [0043]     Preferably, the slow task portion  212  has access to the common data storage, such as the common data storage  162  of the system  130 , where the slow task portion  212  can, for example, access vehicle sensor data, such as wheel speed and tire inflation. The slow task portion  212  may have direct access to the common data storage, such as through a wired or wireless interface, or the slow task portion  212  may have indirect access to the common data storage, such as through a command processor. For example, the data processor  158  of the system  130  may act as such a command processor.  
         [0044]     Preferably, the slow task portion  212  will use instantaneous wheel speed information to calculate a contact patch length from a contact time period and in turn calculate tire load. Further, the slow task portion  212  will preferably use instantaneous wheel speed information to calculate an updated filter frequency, and an updated expected edge threshold in order to deal with dynamic driving situations when wheel speeds change significantly between two adjacent pulses in the acceleration signal.  
         [0045]     The slow task portion  212  begins in decision block  239  where a real-time tire monitoring system  130  queries for a new pulse duration value. If the new pulse duration value is available then the slow task portion  212  proceeds to decision block  240 .  
         [0046]     In decision block  240 , the system  130  analyzes the pulse duration value for validity. If the pulse duration value is not valid then the slow task portion  212  returns to decision block  239  and proceeds as before. If the pulse duration value is valid then the slow task portion  212  proceeds to functional block  245  where the system  130  calculates a tire load value, as least partially based upon the pulse duration value.  
         [0047]     The slow task portion  212  proceeds to functional block  250  where the tire load value calculated is used to update a tire load value stored in the system  130 . The slow task portion  212  then returns to decision block  239  and proceeds as before.  
         [0048]     If in decision block  239  the new pulse duration value is not available then the slow task portion  212  proceeds to functional block  255  where the system  130  calculates an updated signal filter frequency value. The slow task then proceeds to functional block  256  where the system  130  stores the updated signal filter frequency value.  
         [0049]     The slow task portion  212  then proceeds to functional block  260  where the system  130  calculates an updated expected edge threshold value. The slow task then proceeds to functional block  261  where the system  130  stores the updated expected edge threshold value.  
         [0050]     The slow task portion  212  then returns to decision block  239  and continues through as before and runs until stopped by some outside interrupt, such as, the system  130  being turned off or as will be described below.  
         [0051]     In one embodiment of the present invention, a process for real-time tire load monitoring consists of the fast task portion  211 , as generally exemplified in  FIG. 4 , and the slow task portion  212 , as generally exemplified in  FIG. 5 . The fast task portion  211  preferably continually proceeds though signal processing and the slow task portion  212  preferably continually proceeds through value calculation, both portions cycle once per a respective processing period. Preferably, each respective period is less than the duration of one wheel rotation. However, the cycle of each portion is independent of the other, and may run asynchronously, i.e. without temporal concurrence, and/or asequentially, i.e. run without succeeding or following in order.  
         [0052]     Further, in one embodiment of the present invention execution of a fast task portion and a slow task portion of a process for real-time tire load monitoring is not scheduled in a conventional process time-sharing way, i.e. where a fast task portion takes priority over a slow task portion. Two exemplary schemes are described as follows.  
         [0053]     Referring again to the drawings,  FIG. 6  schematically illustrates a serial-processing scheme, indicated generally at  310 . The serial-processing scheme  310  includes a single microprocessing system  314 . The fast task portion  211  and the slow task portion  212  of a process for real-time tire load monitoring in accordance with a first embodiment of the present invention are programmed into the single microprocessing system  314 . The fast task portion  211  is communicatively connected to the slow task portion  212  by a first communications pathway  330 . The slow task portion  212  is communicatively connected to the fast task portion  212  by a second communications pathway  334 . The fast task portion  211  and the slow task portion  212  are executed during different portions of a processing cycle, as will be described below. The processing cycle corresponds to a sensor data signal period, preferably a signal period of a transmitter associated with an accelerometer based contact patch sensor, preferably, the contact region detector  150  of the tire monitoring system  130 .  
         [0054]     The fast task portion  211  is further communicatively connected to a task scheduler process  346  by a third communications pathway  350 . The task scheduler process  346  is communicatively connected to the fast task portion  211  by a fourth communications pathway  354 . The task scheduler process  346  is further communicatively connected to the slow task portion  212  by a fifth communications pathway  358 . The slow task portion  212  is communicatively connected to the task scheduler process  346  by a sixth communications pathway  362 .  
         [0055]     The single microprocessing system  314  is preferably placed with the accelerometer of the detector  150 , embedded inside the tire  136 . For example, the single microprocessing system  314  may be the microprocessor included in the detector  150 . However, it will be appreciated that the single microprocessing system  314  may be placed in any appropriate location within a vehicle. For example, the single microprocessing system  314  may be the data processor  158  included in the system  130 . In an alternate embodiment of the invention where the single microprocessing system  314  is the data processor  158 , the detector  150  does not include a microprocessor.  
         [0056]     For practical application, signal processing and value calculation processes are broken down into the two sub-tasks portion, the fast task portion  211 , and the slow task portion  212 . The fast task portion  211  performs loading of internal variables  366 , acquisition of an acceleration signal, filtering of the signal, detection of a rising pulse edge, measurement of a pulse duration, and transmission of a pulse duration value  370 . Preferably, the fast task portion  211  performs all functions at the same rate as the sample data acquisition rate, i.e. within the processing cycle corresponding to the sensor data signal period. The pulse duration value  370  is transmitted from the fast task portion  211  to the slow task portion  212  via the first communications pathway  330 , preferably through a common data storage module, such as a RAM module. A first coordination flag  374  is transmitted from the fast task portion  211  to the task scheduler process  346  via the third communications pathway  350  to indicate that the fast task portion  211  has fully performed one of its functions.  
         [0057]     The task scheduler process  346  transmits a second coordination flag  378  to the slow task portion  212  via the fifth communication pathway  358  to enable the slow task portion  212  to execute. The slow task portion  212  calculates updated filter frequency value and expected edge threshold value, transmits the updated filter frequency value and expected edge threshold value as internal variables  366 , performs duration value validity analysis, and calculation of tire load. Preferably, the slow task portion  212  is running at a slower sample rate than the fast task portion  211 . Additionally, the slow task portion  212  has access to wheel speed sensor data and tire inflation sensor data. In order to deal with dynamic driving situations, such as when wheel speeds change significantly between two adjacent pulses in the acceleration signal, instantaneous wheel speed information is used to assist in calculating contact patch length, updated filter frequency value, and expected edge threshold value. The internal variables  366 , the updated filter frequency value, and the updated expected edge threshold value, are transmitted from the slow task portion  212  to the fast task portion  211  via the second communications pathway  334 . A third coordination flag  382  is transmitted from the slow task portion  212  to the task scheduler process  346  via the sixth communications pathway  362  to indicate that the slow task process  322  has fully performed one of its functions.  
         [0058]     The task scheduler process  346  transmits a fourth coordination flag  386  to the fast task portion  211  via the fourth communication pathway  354  to enable the fast task portion  211  to execute. The fast task portion  211  loads the internal variables  366 . The fast task portion  211  then performs acquisition of the acceleration signal, filtering of the signal, detection of the rising pulse edge, measurement of the pulse duration, and transmission of the pulse duration value  370  and the process continues through the cycle as before.  
         [0059]     Although the fast task portion  211  may be executed to perform different functions during the processing cycle, it is preferred that the slow task portion  212  is executed only once during the processing cycle. The invention contemplates loading the internal variables, i.e. updating the signal filter frequency value and expected edge threshold value, within the cycle in the acceleration signal. However, the fast task portion  211  would be executed as a time-sharing multi-rate task and the slow task portion  212  would be executed once within the cycle following the completion of detecting a rising pulse edge and the fast task portion  211  would be executed subsequently to finish.  
         [0060]      FIG. 7  illustrates a Parallel Processing Scheme indicated generally at  390 . The Parallel Processing Scheme  390  includes a dual microprocessing system  392 . The fast task portion  211  and the slow task portion  212  of a process for real-time tire load monitoring in accordance with a second embodiment of the present invention are executed in two separate microprocessors, a first microprocessor  394  and a second microprocessor  398 , respectively.  
         [0061]     In the dual microprocessing system  392 , the first microprocessor  394  containing the fast task portion  211  is preferably placed with the accelerometer of the detector  150 , embedded inside the tire  136 , and the second microprocessor  398  is preferably placed elsewhere in the vehicle  132 . For example, while the first microprocessor  394  may be the microprocessor included in the detector  150 , the second microprocessor  398  may be the data processor  158  included in the system  130 . However, it will be appreciated that the first microprocessor  394  and the second microprocessor  398  may be placed in any appropriate location within a vehicle.  
         [0062]     The fast task portion  211  performs loading of internal variables  366 , acquisition of an acceleration signal, filtering of the signal, detection of a rising pulse edge, measurement of a pulse duration, and transmission of a pulse duration value  370 .  
         [0063]     The pulse duration value  370  is transmitted from the fast task portion  211  to the slow task portion  212  via a first communications pathway  398 , through a common data storage module, such as a RAM module, preferably the data storage unit  162  of the system  130 .  
         [0064]     The slow task portion  212  calculates updated filter frequency value and expected edge threshold value, transmits the updated filter frequency value and expected edge threshold value as the internal variables  366 , performs duration value validity analysis, and calculation of tire load  
         [0065]     The internal variables  366 , i.e. the updated filter frequency value and expected edge threshold value, are transmitted from the slow task portion  212  to the fast task portion  211  via a second communications pathway  399 .  
         [0066]     Preferably, the fast task portion  211  loads the internal variables and then performs acquisition of the acceleration signal, filtering of the signal, detection of the rising pulse edge, measurement of the pulse duration, and transmission of the pulse duration value  370  and then continues through the cycle until stopped by some outside interrupt, such as the system being turned off or input of a stop command from elsewhere in the system  130 .  
         [0067]     Although, the Parallel Processing Scheme  390  has been described for use with one wheel, the invention contemplates a scheme where the first microprocessor  394 , embedded in one or more wheels, performs the fast task portion  211  for each the wheels in which the first microprocessor  394  is embedded, and where the second microprocessor  396  performs the slow task portion  212  for all of the wheels in which a first microprocessor  394  is embedded.  
         [0068]     In summary, the invention may include various aspects, which differ from the prior art and provide advantages over the prior art. While the principal and mode of operation of this invention have been explained and illustrated in its preferred embodiment, it must be understood that this invention may be practiced otherwise than as specifically explained and illustrated without departing from its spirit or scope.

Technology Classification (CPC): 1