Patent Abstract:
A method for producing measurements of specific key characteristic parameters of small particles suspended within a scattering medium includes the step of directing a beam of light into the scattering medium, then detecting the Doppler-shifted components of light scattered by the movement of the suspended particles and unscattered light from the source and generating a first signal representative of the power spectral density of the Doppler-shifted components and unscattered light. The first signal is next applied to a plurality of bandpass filters to generate a plurality of second signals, the magnitude of which are representative of the power spectral density integrated over the bandpass. The first signal is also applied to a low pass filter that generates a third signal, used in deriving the concentration of the particles in the scattering medium. Each second signal is then normalized by dividing each second signal by the third signal, thereby developing a plurality of individual ratiometric signals whose magnitude is representative of a measurement of a specific key characteristic parameter of the particles in the scattering medium.

Full Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates generally to the field of measuring the size distribution of particles and more specifically to a method and system for measuring specific parameters of small particle characteristics. 
     2. Discussion of the Related Art 
     A number of methods exist for determining the size distribution of particulate material for particles in the approximate size range of 0.1 to 100.0 microns in diameter. One such method known and used effectively for determining the size of small particles is by sensing and measuring their Brownian motion. Brownian motion is caused by random collisions between the particles and thermally excited molecules of the dispersing media. The velocity and direction of the motion is random, however, the velocity distribution of many particles averaged over a period of time will approach a known functional form. Since small particles are known to move faster than larger particles, the particle size can be determined by measuring the size-dependent velocity distribution. For example, fiber optic Doppler anemometers such as those disclosed in U.S. Pat. No. 4,637,716 to Auweter et al, patented Jan. 20, 1987, and U.S. Pat. No. 4,818, 071 to Dyott, patented Apr. 4, 1989, are capable of measuring the size of very small particles down to a diameter of approximately 0.005 microns. However, such fiber optic Doppler anemometers have been useful for measuring particle size accurately only when all particles are of a uniform size. 
     One method presently known for measuring the particle size and distribution of very small particles of multiple sizes is disclosed by U.S. Pat. No. 5,094,532 to Trainer et al, patented Mar. 10, 1992. This patent discloses a fiber optic Doppler anemometer and method that directs a beam of light into a scattering medium which contains moving particles. The frequency of the scattered light is compared to non-scattered light emitted from the scattering medium and results in the generation of a first signal having a magnitude which is indicative of the difference in frequency between the scattered light and the non-scattered light. A second signal is generated having a magnitude which varies with frequency on a linear scale. The frequency scale of the second signal is then translated into a logarithmic scale and deconvolved to determine the size and distribution of moving particles within the scattering medium. The translation and deconvolving requires translation of analog signals to digital signals and subsequent processing by a central processor and a vector signal processor using fast fourier transfer techniques (FFT). In order to solve for an entire known particle size distribution of over 80 particle diameters the method just described must sample over 80 frequencies. Even though this method provides an accurate measurement of particle size and distribution, it does require a long time period to process all of the sample frequencies and, therefore, is best suited for use in a laboratory with samples that have been extracted from a process and prepared for analysis. Additionally, the central computer and vector processor required in his method add to its complexity and expense. 
     The measurement of particle size distribution finds use in the process industries in the manufacture of pharmaceuticals, chemicals, abrasives, ceramics, pigments and the like where the particle size affects the quality of the manufactured product. There is an advantage in the ability to measure particle size in-situ and on-line during the manufacturing process in order to more effectively and quickly respond to any changes in the process that may affect the quality of the finished product and to apply these measurements to a process control system that controls the manufacturing process. 
     BRIEF SUMMARY OF THE INVENTION 
     In accordance to the present invention, there is provided a method for producing measurements of specific key characteristic parameters of small particles suspended within a scattering medium which includes the step of directing a beam of light into the scattering medium, thereby detecting the Doppler-shifted components of light scattered by the movement of the suspended particles and the unscattered source light and generating a first signal representative of the power spectral density of the Doppler-shifted components and unscattered source light. The first signal is applied to a plurality of bandpass filters. Each bandpass filter generates a second signal, the magnitude of which is representative of the power spectral density integrated over the bandpass for a specific key characteristics parameter. The first signal is further applied to a low pass filter that generates a third signal, the magnitude of which represents a measurement of the concentration of the particles in the scattering medium. Each second signal is normalized by dividing each second signal by the third signal, thereby developing a plurality of individual ratiometric signals whose magnitudes are representative of a measurement of specific key characteristic parameters of the particles in the scattering medium. 
     It is, therefore, an object of the present invention to provide a method and system for effectively and accurately measuring the spectral power of scattered light in a few specific frequency ranges to provide measurement of selected particle size parameters. 
     It is also an object of the present invention to provide a method and system that is able to measure particle size parameters on-line, for use by a process control system. 
    
    
     BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
     Other objects, features, and advantages of the present invention will be apparent from the following description of a preferred embodiment thereof, taken in conjunction with the sheets of drawings, in which: 
     FIG. 1 is a block diagram of a measurement instrument used with the present invention; and 
     FIG. 2 is a block diagram of a system used to practice the measuring of specific parameters of small particle characteristics in accordance to the present invention. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     It should be understood that the system and method for measuring specific characteristics of small particles of the present invention is applicable to both angular light scattering instruments and devices of the type referred to in U.S. Pat. Nos. 5 3,873,206, 4,134,679 and 5,416,580 and also to dynamic light scattering instruments of the type illustrated in U.S. Pat. Nos. 4,637,716, 4,818,071 and 5,094,526 and to any scattering instruments which detect Brownian motion. 
     Referring to FIG. 1, a dynamic scattering instrument  10  is shown that is used for practicing the method of the present invention. The instrument  10  is preferably an optical Doppler velocimeter and includes a laser diode light source  12 , which transmits a beam of light into an optical coupler  14 . Light from the coupler  14  is transmitted along an optical cable  16 , the end of which is submerged into a sample cell  18  holding the particulate matter  20  suspended in a scattering medium, such as water. The particular scattering medium may be selected from a wide range of media as long as it is inert with respect to the particulate matter suspended therein. Even though optical cable  16  is shown immersed into a sampling cell  18  that is isolated from a manufacturing process, it will be well understood by those skilled in the art that the sampling cell  18  could be part of an apparatus which extracts and prepares representative samples of the manufactured product withdrawn from a conduit transporting the product from one stage of the manufacturing process to another. The prepared sample can be automatically delivered to the sampling cell  18  or delivered to the sampling cell  18  on a demand basis. 
     The size distribution of the particulate matter  20  is determined by measuring the Brownian motion. Median velocities for typical particles between 0.0005 and 2.0 microns in diameter is on the order of 6000 to 15 microns per second. Such velocities change direction and amplitude continuously, resulting in very small cumulative motion. Light scattering has proven to be the best method to measure such small motions. Light scattered from each particle is Doppler shifted by the particle motion. These Doppler frequency shifts, ranging from a few Hz to several kHz, are proportional to the instantaneous particle velocity. Using frequency beating techniques it is known that one can measure such small frequency shifts which are twelve orders of magnitude smaller than the optical frequency itself. 
     Light emitted from the immersed end of optical cable  16  is scattered back by the particles  20  into the optical cable  16 . In addition, due to the refractive index difference between the glass in the fiber core and the scattering medium, a small portion of the light, emitted from the fiber, is also Fresnel reflected back into the optical cable  16 . The Fresnel reflected signal has the optical frequency of the laser diode source  12  and is compared to the frequency of the scattered light from the particles  20 . This comparison is made possible since the scattered light is Doppler frequency shifted form the source frequency by the Brownian motion of the particles  20 . The scattered and non-scattered (Fresnel reflected) signals are transmitted back through the optical cable  16  and the coupler  14  to photodiode detector  22 . In essence the detector mixes the scattered and unscattered light components to produce a stochastic signal indicative of the Doppler spectral broadening of the light scattered by the moving particles. The detector  22  is arranged to sense the fluctuations of light scattered from the particles  20  that are in Brownian motion. The power spectral density of the detector current is high at low frequencies and falls off at higher frequencies. In presently known methods the detector current is filtered, amplified, converted into a digital signal by analog-to-digital conversion means for FFT analysis and power spectrum determination by a local computer or other signal processing device. In order to solve for the entire particle size distribution of the sample (number, volume and area distribution) of 80 particle diameters, the power spectrum must be sampled at 80 frequencies. However, on-line applications that monitor and sense the quality of product production based on particle size distribution usually require less than three characteristics of particle distribution to be measured. 
     For purposes of this embodiment, these characteristics are defined as mean size (mean particle radius), standard deviation and particle concentration. Therefore, only three frequency regions need to be measured to solve for the three identified characteristics. 
     The present invention accomplishes the measurement of these above-identified characteristics by passing the spectral density of the detector current through three electrical bandpass filters and producing inversion functions of the characteristics being measured. The derived signals so produced can than be directly input into the process control computer of a process control system. FIG. 2, shows a system  25  in accordance to the present invention. The system  25  includes a first bandpass filter  30  (BP 1 ), a second bandpass filter  40  (BP 2 ) and a low pass filter  50  (LP). The photocurrent of the detector  22  is applied to each of the filters  30 ,  40  and  50  and the outputs of each filter  30 ,  40  and  50  applied to an associated root mean square circuit RMS 1   31 , RMS 2   41  and RMS 3   51 , respectively. The outputs of the root mean square circuits  31 ,  41  and  51  are functions of mean particle radius (P 1 ), standard deviation (P 2 ) and particle concentration (P 3 ), respectively. The two bandpass measurements P 1 , P 2 , however, are not independent unless they are normalized by the power of the LP bandpass to account for the particle concentration of the sample. This is accomplished by analog divide circuits  32  (DIV 1 ) and  42  (DIV 2 ). The ratios R 1  (P 1 /P 3 ) and R 2  (P 2 /P 3 ) are provided by the circuits  32  and  42 , respectively, and applied to the transformation circuit  60  (T). The circuit  60  receives the normalized ratios R 1  and R 2  and the analog representation P 3  of particle concentration. The normalized values for R 1  and R 2  are inverted by solving a set of simultaneous equations for the mean particle radius and standard deviation. The output of the transformation circuit is three signals representing the measured particle characteristics {overscore (a)}, σ and C, where {overscore (a)} is the mean particle radius, σ is the standard deviation and C is the particle concentration. These three analog power signals can be input into a process control computer for analysis. 
     In order to better understand the way in which the present invention functions, it may be helpful to understand the mathematical relationships involved in deriving the output signals. As explained earlier, the signal received from the light detector  22  of the dynamic scattering instrument  10  contains the Doppler-shifted components of the stochastic Brownian motion process. The power spectral density of the light detector  22  current can be expressed by the integral equation:          S        (   w   )       =     K        ∫       N        (   a   )            a     1   +       (     wa   B     )     2                 a                                  
     where 
     S(w)=power spectral density 
     K=instrumental constant 
     w=angular frequency 
     a=particle radius 
     B=constant which is a function of scattering angle, temperature and viscosity 
     N(a)=number of particles per unit size interval 
     To determine the power passed by the analog electronic filters BP 1 , BP 2  of bandpass (ΔW), the power spectral density is integrated over the bandpass and over the total range of particle radii to give the power (P) for each bandpass. This is a function of the particle size distribution and the bandpass.          P        (     Δ                 W     )       =     K        ∫       N        (   a   )              ∫     Δ                 W              a     1   +       (     wa   B     )     2                            w             a                                      
     The bandpass integral (f) is defined as:          f        (     a   ,     Δ                 W       )       =       ∫     Δ                 W              a     1   +       (     wa   B     )     2                            w                                
     When the number of particles per unit size (N(a)) is parameterized, the parameters can be solved for by measuring an equal number of independent bandpass filters. For example, assume that the particle size distribution is Gaussian, with the parameters of mean particle radius, {overscore (a)}, and radius standard deviation σ. Then each bandpass power measurement (P 1 , P 2  of the arrangement above) is a known function of only {overscore (a)} and σ as shown by equations below:          N        (   a   )       =       N   _                     (       a   _     ,   σ   ,   a     )                 P        (       a   _     ,   σ   ,     Δ                 W       )       =     K        ∫         N   _          (       a   _     ,   σ   ,   a     )            f        (     a   ,     Δ                 W       )               a                                  
     where 
     {overscore (N)} ({overscore (a)}, σ, a)=Gaussian particle radius distribution (number per unit radius) 
     {overscore (a)}=mean particle radius 
     σ=standard deviation 
     Using the equations just defined, the mean particle radius is a function of RMS 1  and the standard deviation is a function of RMS 2 . 
     As can be seen in FIG. 2, the detector current is also applied to the low pass filter  50  and a RMS circuit  51 , to output signal P 3  representing the particle concentration of the sample. The two bandpass measurements P 1  and P 2 , however, cannot be considered independent unless they are normalized by power P 3  from the low bandpass, LP  50 , to account for the third unknown, particle concentration. This is accomplished by passing signals P 1 , P 2  and P 3  to division circuits DIV 1   32  and DIV 2   42 , where the following normalized values R 1  and R 2  are derived by the following equations: 
     
       
           Pi=P ({overscore (a)},σ,Δ W   i ) 
       
     
     where 
     i=1,2,3 
     then, 
     
       
           R   1 = P   1 / P   3   
       
     
     
       
           R   2 = P   2 / P   3   
       
     
     The normalized values R 1  and R 2  are then inverted by solving the following simultaneous equations for mean particle radius {overscore (a)}, and radius standard deviation a. This is accomplished by the transformation circuit 60 producing the inversion functions T a  and T σ.   
     
       
           {overscore (a)}=T   a ( R   1 , R   2 ) 
       
     
     
       
         σ= T   σ ( R   1 , R   2 ) 
       
     
     The method just explained effectively reduces the number of measurements that are made by a particle measurement system and effectively provides for a direct analog transmission of the results to a remotely-located process control computer. This allows for the direct connection of the measured parameters to a remote process control computer, via a standard 4-20 mA current loop, thereby eliminating the need for local analog-to-digital converters, FFT hardware and any local computer or signal processors. Using the method of the present invention a single multi-wire cable would provide power to drive the laser diode and detector of the measurement instrument  10  and return the analog power signals to a process control computer from the analog circuits of the arrangement  25  of the present invention. 
     In its broadest aspect the present invention teaches a method and system that uses multiple analog signal measurements (in this case spectral bandpass power) to transform analog signal measurements into multiple parameters by a single transformation circuit or network, T. In the present embodiment, the three bandpass power measurements (BP 1 , BP 2 , and LP) and the ratiometric signals derived by the DIV 1  and DIV 2  functions are combined by a single transformation circuit ( 60 ) shown in the present invention as being local to the system  25 . However, signals P 1 , P 2 , and P 3  could be transmitted as analog signals to a remotely located process control computer to be transformed into parameters via digital computation, by the process control computer. In such a remote configuration, only a limited number of analog signals can be effectively sent from the measurement instrument to the process control computer over a long distance. The unknown parameters will usually not have a one-to-one correspondence with the analog signals (in this case the power measurements). Each derived parameter of small particle characteristic will usually depend on all of the analog signals and so a set of simultaneous (linear or non-linear) equations would be required to be used to solve for the specific parameters measured. For example LP ( 50 ) alone will not provide the particle concentration C without using the signals from BP 1  ( 30 ) and BP 2  ( 40 ). However, all three power measurements are proportional to concentration for a fixed particle size distribution. 
     It will be understood by those skilled in the art that the method just explained is just one of many versions for measuring a particular set of particle characteristics. Any set of other particle parameters can be chosen by the proper definition of N(a), which then would produce the appropriate transformation algorithm T. The number of bandpass filters must be greater than or equal to the number of particle parameters. For example, if the particle size distribution is constant, particle concentration can be measured with one bandpass filter in the high frequency range. 
     Parameters such as 10%, 50% and 90% of the cumulative volume distribution could be solved with three bandpass filters by assuming a form for N(a). The form for this function is determined from the nominal process being measured so that accurate parameter deviations are generated. This is due because at or near the nominal process control point, the transformation equations of the T circuit  60  will be linear. Since in an automatic process control system, the control parameter only needs to correlate to product quality in order to define a set point, a simple linear T circuit network may be sufficient. In order to improve noise immunity and linearity, the T equations of the T circuits  60  could be replaced with neural networks or other expert systems. 
     Finally, it will be apparent to those skilled in the art, that the method and system of the present invention can also be effectively applied to apparatus that use only the scattered light components, or a so called “self-beating” measurement system, for determining particle size distribution. 
     The present invention has been described with particular reference to the preferred embodiments thereof. It will be obvious that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Technology Classification (CPC): 6