Abstract:
An object, such as a pistachio nut, is sorted based on a given trait. The sorting process commences by bouncing the object off a body so that the object emits a sound. The sound emitted by the object is converted to an electrical signal which is analyzed to determine electrical characteristics that indicate the trait of the object. For example, the electrical signal can be integrated and a signal gradient produced to discriminate among signals from different classes of objects.

Description:
BACKGROUND OF THE INVENTION  
         [0001]    The present invention relates to equipment for automatically sorting objects, such as pistachio nuts; and more particularly to such equipment which sorts the objects based on sound.  
           [0002]    Pistachio nuts are graded and sorted based on whether or not the shell has split open. A typical harvest of pistachio nuts comprises 17% with a closed shell, 5% with a thinly split shell, and 78% with a fully open shell. Nuts with closed shells have low consumer acceptance because they are difficult to open and may contain immature kernels. Thus closed shell pistachio nuts are less valuable than those with open shells.  
           [0003]    The pistachio industry currently utilizes a variety of methods and equipment to sort lesser quality nuts from the high grade product. A common mechanical device has a rotating drum with pins projecting inward from the interior surface. As the pistachio nuts tumble in the drum, those with open shells become lodged on the pins and carried upward. At the top of the drum a brush removes the open nuts from the pins and those nuts fall onto a collector. The pins can not impale the pistachio nuts with closed shells and these nuts pass through the drum into another collector.  
           [0004]    Furthermore, approximately five to ten percent of open shell pistachio nuts are incorrectly classified by the mechanical sorters as having a closed shell. Such incorrect classification costs the U.S. pistachio industry several millions of dollars a year.  
           [0005]    Machine vision systems also have been proposed for sorting pistachio nuts. However, these systems are relatively expensive and have a classification accuracy similar to that of mechanical sorting machines. Thus vision systems may not be economically justified.  
           [0006]    Therefore, there remains a need to increase the accuracy of the sorting process for closed shell pistachio nuts.  
         SUMMARY OF THE INVENTION  
         [0007]    The present novel object sorting method commences by creating an impact between the object and a body, such as by bouncing the object off the body. Preferably the body has a sufficiently large mass that it does not emit sound due to the impact. However, the object does emit a sound upon impact and a transducer produces an electrical signal representing that sound.  
           [0008]    The electrical signal is analyzed to determine a characteristic of the electrical signal which indicates a trait of the object on which sorting is to be based. For example, this method has application in sorting pistachio nuts based on whether their shells are open or closed. In response to the results of the analysis the object is directed along a selected a path.  
           [0009]    Analysis of the electrical signal preferably involves integrating a magnitude of the electrical signal, deriving a gradient for a portion of the electrical signal, or both of those arithmetic operations. In the preferred processing technique, the electrical signal is digitized into a plurality of signal samples. Then the absolute value of selected signal samples, acquired during a predefined interval after the impact, are integrated to produce an integration value. In addition, that signal samples which have a magnitude in a first predetermined range of values and a gradient in a second predetermined range of values are counted to produce a first count value. A second count value may be produced by counting the signal samples which have a magnitude in a third predetermined range of values and a gradient in a fourth predetermined range of values. The integration value and the first and second count values then are utilized to classify the object and the classification determines along which path to direct the object. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0010]    [0010]FIG. 1 is a diagram of an apparatus for sorting pistachio nuts; and  
         [0011]    [0011]FIG. 2 graphically illustrates waveforms of the sound emitted from pistachio nuts with open and closed shells bouncing off an impact plate of the apparatus; and  
         [0012]    [0012]FIGS. 3A and 3B are a flowchart depicting operation of the present sorting apparatus.  
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0013]    Although the present invention will be described in terms of apparatus for sorting pistachio nuts, the inventive concept can be applied to sorting other types of agricultural products.  
         [0014]    With initial reference to FIG. 1, the sorting apparatus  10  has hopper  12  into which the pistachio nuts  14  are received for processing. The nuts drop through the hopper  12  onto a tray  16  of a vibrating feeder  18 . As the tray  16  vibrates, the nuts pass through an outlet in the tray and fall one at a time onto a chute  20 , thus creating a linear stream of nuts.  
         [0015]    The chute  20  is a “V” trough of polished stainless steel that angles downward toward an impact plate  22  of polished stainless steel. For example, the chute is one meter long and is inclined at an angle θ of sixty degrees with respect to horizontal. As each nut  14  slides down the chute  20 , its longitudinal axis is oriented parallel to the direction of the travel. In the preferred embodiment of the sorting apparatus  10 , the impact plate  22  is 50.8 mm wide by 50.8 mm thick. The relatively large thickness of the impact plate  22  minimizes vibration of the block upon being impacted by the stream of pistachio nuts. As a consequence, the sound generated by the impact originates primarily from the nut.  
         [0016]    A highly directional “shotgun” microphone  24  is aimed at the location on the impact plate  22  which will be struck by the falling pistachio nuts. For example, the microphone  24  is a model ME67 with a K6 powering module sold by Sennheiser Electronics Corporation of Old Lyme, Conn. 06371 U.S.A. The highly directional nature of this microphone and careful aiming minimizes mixing ambient noise with the sound from the bouncing nuts.  
         [0017]    The electrical signal produced by the microphone  24  is applied to an analog input of a digital signal processor (DSP)  26  contained on a card inserted in a personal computer  28 . For example, the digital signal processor  26  is a model 310 manufactured by Dalanco Spry of Rochester, N.Y. 14620, U.S.A. An analog-to-digital converter in the digital signal processor  26  converts the microphone signal to digital samples with 14 bit resolution at a rate of 250 KHz. thereby acquiring a data sample of the microphone signal once every four microseconds. As will be described, the digital signal processor analyzes the audio signal emitted by each bouncing nut to determined whether its shell is open or closed.  
         [0018]    The digital signal processor  26  has an analog output that is connected to a driver circuit  30  for an electrically operated solenoid valve  32 . The solenoid valve  32  is connected to a supply line  34  from a source of compressed air (not shown). When the valve  32  is opened, in response to the output signal from the digital signal processor  26 , compressed air is expelled through a nozzle  36  across the path of the pistachio nuts that have bounced off the impact plate  22 . The stream of compressed air from the nozzle  36  blows selected pistachio nuts  40  in a different direction from the normally bouncing nuts  42 .  
         [0019]    [0019]FIG. 2 depicts electrical signals from the microphone  24 . The solid waveform  44  represents the sound emitted from a nut with an open shell, while the dotted waveform  46  corresponds to the sound from a nut with a closed shell. The waveform  44  for an open shell nut begins oscillating with a relatively moderate amplitude and keeps this moderate amplitude for most of the 1400 microsecond interval during which 350 data samples are acquired by the digital signal processor  26 . In contrast, the signal waveform  46  for the closed shell nut begins with oscillations of a relatively high amplitude during the first 300 microseconds after impact and diminishes significantly thereafter. These diverse audio signals enable the present sorting system to differentiate between pistachio nuts with closed and open shells.  
         [0020]    The signal features used for classification are extracted concurrently with the data acquisition. These features can be extracted from either the absolute value of the signal level (signal magnitude), the absolute value of the signal gradient, or both. The signal gradient is computed from:  
           G   X   =|I   (X−GAP)   −I   (X+GAP) | 
         [0021]    where G X  is the signal gradient value at data sample X; I X  is the signal level for data sample X; and GAP is the interval between data samples. Signal gradients are computed using GAPs of two, three, and four data samples.  
         [0022]    For separating closed-shell from open-shell pistachio nuts, a three-variable linear discriminate function was found to provide the lowest validation set classification error rate in real-time. The function used the following feature parameters:  
         [0023]    1. Integration of the absolute value of signal magnitude for 0.11 milliseconds (ms) after impact.  
         [0024]    2. The number of data samples taken between 0.6 and 1.4 milliseconds after impact which have a magnitude below 45.8 millivolts (mv) and a gradient (2-point GAP) below 45.8 millivolts.  
         [0025]    3. The number of data sample taken between 0.6 and 1.4 milliseconds after impact which have a magnitude below 57.2 millivolts and a gradient (3-point GAP) below 30.5 millivolts.  
         [0026]    Although the use of all three parameters is preferred to fully classify nuts as closed or open, it should be understood that an alternative sorting apparatus could utilize only one of these parameters or any two of them. Furthermore, the signal levels used may vary depending upon the object being sorted and the configuration of the system hardware, such as the chute  20 , impact plate  22  or the microphone  24 . For example, changing the length and angle of the chute can affect the intensity of the sound emitted by the pistachio nut upon impact. The specific signal intensities specified in these feature parameters were selected to distinguish between the two waveforms shown in FIG. 2 and those signal intensity values will change when other objects being sorted produce different waveforms.  
         [0027]    The classification function is implemented by programming the digital signal processor  26  to evaluate the microphone signal for 1.4 milliseconds which is the time required to obtain 350 digital data samples for each nut. The evaluation program is depicted by the flowchart which begins on FIG. 3A. At the commencement of data acquisition for a new nut the variables are initialized at step  100  after which the digital signal processor waits at step  102  for another data sample to be acquired. Each data sample is stored in the digital signal processor  26  at step  104 .  
         [0028]    At step  106  a determination is made whether the magnitude of the new data sample exceeds 85.0 millivolts which indicates that a nut has bounced off the impact plate  22  in FIG. 1. This signal threshold prevents ambient background noise from triggering the signal processing. This and other signal magnitudes specified herein may vary depending upon the particular environment and components of a particular sorting apparatus. Once a data sample produced by a nut bounce has been found, the program execution advances to step  108  where the processor waits for another data sample. That sample is stored into a pipeline memory within the digital signal processor  26  at step  110 .  
         [0029]    The signal gradient and intensity of each data sample of the microphone signal are utilized to derive the three feature parameters that quantify the signal characteristics of the impacting pistachio nut.  
         [0030]    The first parameter of the microphone signal quantifies the overall signal amplitude during the initial 0.08 milliseconds after impact, which corresponds to 28 data samples acquired after the microphone signal exceeded 85 millivolts. Specifically at step  112 , the absolute value of each data sample is computed and added to a running sum of all previous data samples for this particular nut. Next at step  114 , a determination is made whether 28 data samples have been summed which is achieved by a count of the total number of data samples acquired since initialization. The program keeps looping through steps  108 - 114  until 28 data sample have been acquired. Thereafter, the program execution advances to step  116  where the running sum computed in step  112  is stored in memory as a variable denoted SUM.  
         [0031]    Next, the process enters a loop which acquires data for another 0.488 milliseconds, or until a total of 150 data samples have been acquired. Specifically at step  118 , the program waits for the next data sample from the analog-to-digital converter in the digital signal processor  26  and stores the new sample in the pipeline memory at step  120 . A determination is made at step  122  when a total of 150 samples have been acquired, at which time the program advances to step  124 .  
         [0032]    At this juncture, the two additional parameters (COUNT1 and COUNT2) related to signal amplitude are derived by counting the number of data samples that have both an intensity and a gradient within specified value ranges. The parameter COUNT1 tabulates data samples with an absolute signal gradient value less than or equal to 45.78 millivolts and an absolute signal intensity less than or equal to 45.78 millivolts. This characterizes a relatively small signal amplitude in this region of the signal, which is characteristic of closed shell pistachio nuts. This parameter calculation commences at step  124  by computing the signal gradient value which is the difference between the values of the second and sixth most recently acquired data samples in the memory pipeline. Then at step  126 , this signal gradient value is tested to see if it falls within the specified range, i.e. is less than or equal to  45 . 78  millivolts. If that is not the case, the most recent data sample does not satisfy the criteria for the COUNT1 parameter and the program jumps to step  132  without incrementing that parameter count. Otherwise the program execution advances to step  128  where the absolute signal intensity value for the most recent data sample is tested to see if it falls within the specified range, i.e. is less than 45.78 millivolts. If that is true, the variable for parameter COUNT1 is incremented at step  130 .  
         [0033]    Similarly, the value of parameter COUNT2 is computed by counting data samples with an absolute signal gradient value less than or equal to 30.51 millivolts and an absolute signal intensity less than or equal to 57.22 millivolts. This characterizes a small signal amplitude in this region of the signal, which is characteristic of closed shell pistachio nuts. A signal gradient value is computed at step  132  as the difference between the values of the first and seventh most recently acquired data samples in the memory pipeline. Next, at step  134  a determination is made whether the new signal gradient value is less than or equal to 30.51 millivolts. If so, a determination is made whether the signal intensity value for the present data sample is less than or equal to 57.22 millivolts. If that is the case, the parameter COUNT2 is incremented at step  138 . The parameter COUNT2 is not incremented when either condition specified at steps  134  and  136  is not satisfied.  
         [0034]    The evaluation of the microphone signal by the digital signal processor  26  loops through steps  118 - 138 , continuing to compute the two parameters COUNT1 and COUNT2, for 1.4 milliseconds during which interval  350  total data samples have been acquired for the current nut. When this occurs as determined at step  140 , the program advances to step  142  on FIG. 3B.  
         [0035]    At this point discriminate functions are solved to determine whether the present nut is open or closed. The discriminate functions D O  for open shell nuts and DC for closed shell nuts are:  
           D   O   =C   O1   −C   O2 (SUM)− C   O3 (COUNT1)+ C   O4 (COUNT2)  
           D   C   =C   C1   −C   C2 (SUM)− C   C3 (COUNT1)− C   C4 (COUNT2)  
         [0036]    where C XX  are constants having the following values: C O1 =44939, C O2 =430, C O3 =751, C O4 =211, C C1   =268020, C   C2 =1152, C C3 =205, and C C4 =1419. The precise discriminate functions and constants employed will vary depending upon the specific type of object being sorted and configuration of the sorting system.  
         [0037]    Then the program execution advances to step  144  where the values of the discriminate functions D O  and D C  are compared. The value of the open shell discriminate function D O  being less than the value of closed shell discriminate function D C  indicates a likelihood that the present nut belongs to the open shell class, in which event the program execution jumps to step  150 .  
         [0038]    When the closed shell discriminate function Dc has a lesser value than the open shell discriminate function D O , there is greater likelihood that this nut belongs to the closed shell class. In this event, the program proceeds to step  146  where the digital signal processor  26  produces an analog output signal that activates the solenoid valve  32 . Then at step  148 , a delay occurs to provide a ten millisecond blast of compressed air to blow the present nut along the path of nuts  40 . In the absence of a compressed air blast the nuts  42  that are open bounce along a different path. After that delay the analog output signal from the digital signal processor  26  terminates at step  150  and the solenoid valve  32  closes.  
         [0039]    When the solenoid valve  32  is open, the microphone signal rises to high levels due to the air blast and exceeds the signal levels expected from a nut. Therefore, the signal processing delays at step  152  for nine milliseconds to allow the microphone  24  settle down so that its output signal will not cause another execution cycle of the program. A four millisecond delay also occurs at step  154  when the solenoid valve  32  is not activated to ensure that an open nut  42  travels far enough away from the microphone  24  so that any sound continuing to be emitted also does not reactive program execution. After that delay, the program returns to step  100  to await another nut bouncing off the impact plate  22 .  
         [0040]    The foregoing description is directed to the preferred embodiment of the invention. Although some attention was given to various alternatives within the scope of the invention, skilled artisans will likely realize additional alternatives that are now apparent from the disclosure of those embodiments. Accordingly, the scope of the invention should be determined from the following claims and not limited by the above disclosure.