Patent Abstract:
Apparatus and methodologies are provided to selectively activate a liquid usage option in a washing apparatus based on the color of the liquid. Light from different light sources is passed through a liquid to be tested and the intensity of the light passing through the liquid is measured. The measurement is adjust based on a measurement of the turbidity of the liquid and the measurement compared to a reference value derived from measurements of a clear liquid. A decision is made based on the adjust measured color of the liquid regarding retention of the liquid for further use in the washing apparatus. The liquid tested may correspond to grey water from a previous wash cycle.

Full Description:
FIELD OF THE INVENTION 
     The present subject matter relates to color sensing in appliances. More particularly, the present subject matter relates to color sensing of previously used or “grey water” in appliances. 
     BACKGROUND OF THE INVENTION 
     In a typical laundry cycle the user will fill the tub with a laundry load and the machine will wash and rinse the load several times. A typical cycle may have  1  or more separate rinses and spinouts in which you would expect the wastewater to get progressively cleaner with each rinse. 
     In water reuse the concept is to save the water from any portion of the wash cycle, including but not limited to the last rinse, as this water would be the cleanest of any of the otherwise waste water, and then use it as either wash or rinse water in the next clothing load. 
     It is therefore very important to detect multiple characteristics of this grey water such as microbial content, color and turbidity, bleach content, etc. 
     In view of these known concerns it would be advantageous to provide a apparatus and methodology to accurately determine the color and turbidity of the grey water to prevent damaging clothing unintentionally should the wastewater be reused. 
     BRIEF DESCRIPTION OF THE INVENTION 
     Aspects and advantages of the invention will be set forth in part in the following description, or may be obvious from the description, or may be learned through practice of the invention. 
     The present subject matter relates to methodologies provided for selecting usage options for a liquid in a washing appliance. The method provides a plurality of different light sources and directs light from the light sources through a liquid to be tested. The light intensity received from each of the sources is measured after passing through the liquid. The turbidity within the liquid is also measured and the values of the measure light intensities are adjusted based on the measured turbidity. A selection from a plurality of water usage options is made based on the adjusted values. 
     In certain embodiments red, green, and blue light sources are provided and measurements are made by a light sensor paired with each of the light sources. In other embodiments a single light sensor is used and in particular embodiments an adjustment is made to the measured light values based on the angle of incidence of the light from the plurality of sensors onto the single sensor. 
     In other embodiments, the method provides for measuring turbidity using infrared light by directing light from the infrared light sources through a liquid to be tested and measuring the infrared light intensity received after passing through the liquid. Selected embodiments provided for establishing a reference value for light levels based on the measuring light intensity received after passing through a clear liquid. In certain embodiments, the method determines whether to dump the liquid or to keep and possibly treat it for later use. 
     In particular embodiments, the method establishes a plurality of light quantization levels so that measuring the light intensity received from each of the sources after passing through the liquid corresponds to assigning a measurement value corresponding one of the quantization levels. In particular such embodiments, the method established five quantization levels. 
     The present subject matter also relates to apparatus for selecting usage options for a liquid in a washing appliance. The apparatus includes a chamber for holding a liquid to be tested. There are also provided a plurality of different light sources configured to shine light through the liquid toward at least one light sensor. A turbidity sensor is provided to measure turbidity within the liquid and a controller is provided to receive signals from the at least one light sensor and the turbidity sensor and to adjust the values of the signals from the light sensor based on the measured turbidity. The controller will then activate a usage option based on the adjusted values. 
     In particular embodiments, the apparatus includes a source of clear liquid and a grey water storage tank. In such embodiments, the controller is further configured to establish color reference levels based on measured light levels through the clear liquid and to measure light levels after passing through grey water from said grey water storage tank. The controller then selectively operates either a valve or a pump to selectively dump, treat, or keep the grey water for later use. 
     These and other features, aspects and advantages of the present invention will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       A full and enabling disclosure of the present invention, including the best mode thereof, directed to one of ordinary skill in the art, is set forth in the specification, which makes reference to the appended figures, in which: 
         FIG. 1  is a cubical representation of a Red-Green-Blue (RGB) color space; 
         FIG. 2  is a Cartesian coordinate representation of the RGB color space of  FIG. 1 ; 
         FIG. 3  is a schematic diagram of a first embodiment of an RGB detector circuit in accordance with present technology; 
         FIG. 4  is a schematic diagram of a second embodiment of an RGB detector circuit in accordance with present technology; 
         FIG. 5  is a schematic diagram of a turbidity detector; 
         FIG. 6  is a graphical representation of the output voltage of a turbidity sensor vs. Nephelometric Turbidity Unit (NTU) for ten representative turbidity sensors; 
         FIG. 7  is a graphical representation of percent differences vs. turbidity measurements for the sensors of  FIG. 6 ; 
         FIG. 8  is a schematic representation of a water color detection circuit in accordance with present technology; 
         FIG. 9  is a color cube representation of an RGB color approximation space in accordance with present technology; 
         FIG. 10  is a color matrix lookup table of representative RGB percentiles for each of the colors represented in  FIG. 9 ; 
         FIG. 11  is a flow chart of a method in accordance with present technology; and 
         FIG. 12  is a representation of a washing appliance in which the present subject matter may be employed. 
     
    
    
     Repeat use of reference characters throughout the present specification and appended drawings is intended to represent same or analogous features or elements of the invention. 
     DETAILED DESCRIPTION OF THE INVENTION 
     Reference now will be made in detail to embodiments of the invention, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation of the invention, not limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present invention covers such modifications and variations as come within the scope of the appended claims and their equivalents. 
     As noted in the Summary section, the present subject matter is directed toward color sensing of previously used or “grey water” in appliances such as the washing appliance illustrated in  FIG. 12 . 
     Referring now to  FIGS. 1 and 2 , the visible spectrum is the portion of the electromagnetic spectrum that is visible to the human eye. Electromagnetic radiation in this range of wavelengths is called visible light or simply light. A typical human eye will respond to wavelengths from about 390 to 750 nm. Typically the eye is most sensitive to light at about 555 nm, generally corresponding to the green region of the optical spectrum. The spectrum does not, however, contain all the colors that the human eyes and brain can distinguish. Unsaturated colors such as pink, or purple variations such as magenta, are absent, for example, because they can only be made by a mix of multiple wavelengths. 
     The RGB color space is the best-known and most widely used color model. In RGB each color is represented by three values red (R), green (G) and blue (B), positioned along the axes of the Cartesian coordinate system as illustrated in  FIG. 2 . The values of RGB are assumed to be in the range of [0,1] or in some cases in the range of [0-255]. In this way black may be represented as (0, 0, 0), and white as (1, 1, 1) or, in alternate scales, as (255, 255, 255). These black and the white colors are represented in  FIG. 1  by two of the opposite corner  102 ,  104  of cube  100  that can be defined by the R, G, B axes of the Cartesian coordinate systems illustrated in  FIG. 2 . Other corners of cube  100  represent the red ( 106 ), green ( 108 ), blue ( 110 ), cyan ( 112 ), magenta ( 114 ) and yellow ( 116 ) colors. Grayscale colors may be represented with identical R, G, B components. 
     With reference to  FIG. 3 , there is illustrated a schematic diagram of a first embodiment of an RGB detector circuit  300  in accordance with present technology. The hardware used to detect color in accordance with present technology consist of an array of photo-emitters  302 ,  304 ,  306  on one side of a chamber  310  and an array of photo-detectors  312 ,  314 ,  316  on the opposite side. In one embodiment, RED, GREEN, and BLUE Light Emitting Diodes (LEDs) may be used as the photo-emitters  302 ,  304 ,  306  and photo-diodes as the photo-detectors  312 ,  314 ,  316 . The selection of these colors is made as the present technology uses calculations based on the RGB Color Space. 
     LEDs  302 ,  304 ,  306  are controlled by a controller that can alter their brightness, duty cycle, and timing. The photo-diode signal is boosted through an op-amp network  324 ,  322 ,  326  and the resulting signals are fed into controller  330  for processing. 
     The medium, whether it be “clear reference fluid” or “filter medium” will act as a lens, allowing certain light frequencies to pass while blocking others. The medium would act as a “spatial filter” in this example. Theoretically the “clear” condition will allow all frequencies to pass unimpeded. In practice there will typically be some impedance, which will be accounted and corrected for in software for any condition. 
     In the instance of a clear condition when one of the colored LEDs  302 ,  304 ,  306  is turned on at a certain intensity, the output on the detector side will be at 100% for that color. When in a filter condition the output will be reduced based on the type, that is, color of the medium. In a further alternative configuration, it is possible to use actual colored LEDs as the detector and not emitter because they will work similarly and are more sensitive at the color they would normally emit. 
     An example of this is when in CLEAR condition, when LEDs  302 ,  304 ,  306  are turned on individually the OUTPUT=100% for each color. In an exemplary circuit, the 100% output level may correspond to about 4 Volts DC. When a colored lens such as a dyed water enters the chamber  310  the medium characteristics change. In an instance where the medium is slightly red colored it would be expected that the RED output should remain around 100% while the BLUE and GREEN outputs will drop to, for example, around 80%. The values of each color intensity/output drop permits approximation of the true color of the liquid. 
     There are several ways of implementing this principle concept including using only one photo-detector and compensating for the angle of each LED in relation to the photo-detector.  FIG. 4  illustrates such an alternate embodiment of an RGB detector circuit  400  in accordance with present technology. As may easily be seen from a comparison of  FIGS. 3 and 4 , the embodiment illustrated in  FIG. 4  is identical to that of  FIG. 3  except that the  FIG. 4  embodiment uses only a single photo-detector  414  to measure the outputs of the photo-emitters  402 ,  404 ,  406 . In this instance, controller  430  may be configured to operate LEDs  402 ,  404 ,  406  sequentially and to compensate for the angles of incidence of light represented by arrows  432 ,  434 ,  436  onto the single photo-detector  414 . Single op-amp circuit  424  then amplifies the received light signal from photo-detector  414  and passes the amplified signal on to controller  430 . 
     Within the context of the embodiments of both  FIGS. 3 and 4 , those of ordinary skill in the art should appreciate that the transmitters can be any combination of colored LEDs and the receivers can be multiple different components such as photo-diodes, photo-transistors, IC detectors, LEDs in reverse, etc. 
     With reference now to  FIGS. 5 ,  6 , and  7 , aspects of the present subject matter relating to turbidity detection will now be described.  FIG. 5  illustrates a schematic diagram of hardware corresponding to a turbidity detector  500  in accordance with present technology. The turbidity hardware  500  used is similar to turbidity sensors used in dishwasher and laundry systems currently and in principle is the same as described above but it utilizes infrared light from, for example, an infrared producing LED  502  so it is unaffected by the visible color spectrum. It is also put in line with the chamber  510  and its measurements not only give a reading of turbidity but also provides a measurement that is utilized in the to compensate the color calculations which will be discussed further below. 
     Turbidity within the context of laundry water reuse systems is most likely caused by, but not limited to, lint and fabric fibers in the water. The output of the turbidity sensor  504  will be a DC voltage and, in an exemplary configuration may range from 0 V to about 4 VDC. In this exemplary configuration, 4VDC output from sensor  504  would correspond to a clear condition while 0VDC would correspond to a maximum turbid condition. In certain embodiments of the present subject matter, a temperature sensor  506  may be provided as a part of turbidity sensor  500  to provide temperature feedback that can be used to calibrate the system under different temperature conditions. 
     Referring now to  FIGS. 6 and 7 , charts  600  and  700  illustrate the relationships between turbidity and sensor output.  FIG. 6  graphically illustrates a chart  600  of representative output voltages for an exemplary group of ten turbidity sensors. Graph  600  is presented in terms of turbidity sensor output voltage vs. Nephelometric Turbidity Units (NTU).  FIG. 7  illustrates a chart  700  of representative percent differences vs. turbidity measurements given in Nephelometric Turbidity Units (NTU) for the sensors represented in  FIG. 6 . 
     Referring now to  FIG. 8 , there is illustrated a schematic representation of a water color detection circuit  800  in accordance with present technology. The hardware of the system may be completely integrated and includes a controller system  810 , a sample chamber  820 , light emitters  832 ,  834 ,  836 , one or more light detectors  842 ,  844 ,  846 , a turbidity sensor  850 , a tap water source  862 , a grey water storage tank  864  and associated plumbing, valves, and pumps (not separately numbered). Controller system  810  may include a storage device corresponding to a memory  812 . Memory  812  may also be provided as a separate entity within the overall system. 
     Those of ordinary skill in the art will appreciated that while the system may be configured as a completely integrated package, other options are possible. Such options may include, for example without limitation, the use of a personal type computer or other software and/or hardware driven computational device operating as controller system  810 . The controller system  810  may also be constructed using application specific integrated circuit (ASIC) device. 
     In whatever manner the hardware portion of the system is implemented, the overall system, never-the-less, relies on a controller system in order to drive components, receive and analyze feedback, and then take actions based on the feedback analyzed. Implementation of such systems given the present level of disclosure herein is deemed to be well within the capabilities of those of ordinary skill in the art and thus will not be further described. 
     Referring now to  FIGS. 9 and 10 , there is illustrated in  FIG. 9  a color cube representation  900  of an RGB color approximation space in accordance with present technology and in  FIG. 10  a chart  1000  of representative RGB percentiles for each of the colors represented in  FIG. 9 . In general the control associated with color sensing takes a light intensity measurement of a known medium, for example, clear tap water, and compares it to the light intensity of a filter medium, for example, discolored water, for Red, Green, and Blue light. The filter mediums output may be less for at least some of the colors than the clear tap water. By comparing these two results a percentage may be calculated which indicates the amount of light intensity of each color being filtered by the filter medium. Using these percentages and applying to the RGB color scheme an approximation of the filter color can be achieved. 
     In accordance with present disclosure, a few assumptions may be made. The first is that RGB [0,0,0] equates to completely BLACK while RGB[1,1,1] is CLEAR, that is, not white. Secondly, all points where R=G=B, such as RGB[0.5,0.5,0.5] are considered to be grayscale shades which grow darker as you approach RGB[1,1,1]. 
     As previously noted, in some color scales, the scale for colors ranges form 0-255. Because the present technology is configured for local, as opposed to online, calculations, a lookup table may be created in software and stored in a memory which contains “all colors.” In reality, not all colors are seen continuously but rather are seen in discrete levels. For example, if colors are quantize in levels from 0 to 255 there would be produced a color cube of length, width, and height 255 which would consist of 255 3 =16581375 individual cubes of discrete color. This number is quite large so that in practice to conserve memory space and complexity while still meeting system performance requirements the quantization level can be brought down to below 255 or higher if precise resolution is required at the cost of memory. 
     Referring to  FIG. 9 , there is illustrated a cube  900  with quantization levels 0-4. These five levels may be considered to be equivalent to 0%, 25%, 50%, 75%, and 100% color intensity output such that there are 5 3 =125 discrete colors that can be referenced. Cube  900  and associated color matrix lookup table  1000  may be implemented in software as appropriate for a particular implementation of the present technology. It should be appreciated that while this particular embodiment provides for a reduced quantization level of 125 discrete colors for the color cube, other scales and quantization levels can be provided to meet resolution demand of any particular system. The more levels provided, the more colors that can be approximated. With reference to  FIG. 10 , it will be appreciated that color matrix lookup table  1000 , in order to avoid unnecessary clutter, does not list all 125 different combinations of colors, but the percentage of RGB colors for all 125 should, never-the-less, be quite evident to those of ordinary skill in the art based on the illustrated progression. 
     This reduced quantization level scheme will work for all transparent liquids with some level of coloring. However, laundry system, as described herein, will often encounter turbid conditions which can result in unreliable color approximations. In accordance with present technology, in order to compensate for such turbid conditions a turbidity measurement may be taken and then mathematically apply the results to accurately sense the true color and turbidity. 
     Referring to  FIG. 11  there is illustrated a flow chart  100  of a method in accordance with present technology. In accordance with present technology, it has been appreciated that turbidity in the system will cause inaccurate color approximations. While the system will accurately detect the color of a liquid that is not turbid using color sensing methodologies alone, turbidity compensation is needed for most cases where the liquid will be at least somewhat turbid. 
     Turbidity is the measure of how cloudy, or how much material, is in a liquid. So in the instance of a laundry environment, lint, soils, detergents, etc could all add to system turbidity. Because the present technology uses photo-optics to emit and receive light to provide intensity measurements, system turbidity could introduce errors in intensity measurements and hence calculations and color approximations, since the turbid material may block some elements of the light. 
     The color sensing methodology of the present technology relies on the color of the medium alone to block elements and frequencies of light between the photo-emitters and photo-detectors. Given that a turbid condition would also block these frequencies, regardless of color, the system should be configured to compensate for the turbid condition. In accordance with present technology, this may be accomplished through the use of a turbidly sensor  500  as previously discussed with reference to  FIG. 5 . In a manner and similar to the way color intensity is measured in the visible spectrum turbidity content may be measured by examining the infrared spectrum intensity that can pass through a medium. The infrared light will be impeded only by turbidity and not the color of the liquid. 
     In this manner the system is made aware of how turbid the liquid is and can calculate a percentage decrease in the output due to the turbidity. Because the turbidity will effect all visible colors equally, the amount of intensity that is lost due to turbidity needs to be added back to the color-detectors. In accordance with present technology, a percentage of output lost due to turbidity to all color intensity measurements will be restored to obtain a true and accurate approximation of color. This turbidity correction may be made using the equation:
 
COLOR(adjusted)=%COLOR/%TURBIDITY
 
     For example if %TURBIDITY=80% and %RED=50% the adjusted color approximation for RED due to error caused by turbidity would be:
 
Red(adjusted)=%RED/%TURBIDITY
 
Red(adjusted)=50/80=62.5%
 
     This difference of 12.5% between the observed RED intensity and the adjusted RED intensity is caused by the amount of turbidity in the water and if not corrected would cause a great deal of error in the color approximation. 
     Consider another example where the measured color percent output intensities are RGB [0.329, 0.706, 0.176] or in the rounded 255 scale, RGB [84, 180, 45]. Without turbidity compensation, the color sensing methodology would approximate the color incorrectly. In accordance with present technology, however, when examining the contribution of turbidity it may be found that the percent turbidity is measured at 75%. This means that there is a 25% decline in the entire scale of light intensity output for all colors of 25%. Compensation for this decline should be made as follows:
         %TURBIDITY=75%   %RED=32.9%   %GREEN=70.6%   %BLUE=17.6%   Red(adjusted)=%RED/%TURBIDITY   Red(adjusted)=32.9/75=43.4%   GREEN(adjusted)=%GREEN/%TURBIDITY   GREEN(adjusted)=70.6/75=94.1%   BLUE(adjusted)=%BLUE/%TURBIDITY   BLUE(adjusted)=17.6/75=23.5%       

     With turbidity compensation in accordance with present technology, the color sensing parameters become RGB [0.434, 0.941, 0.235] or in the rounded 255 scale RGB [112, 240, 60]. Through the implementation of the present technology, an accurate means of measuring color and turbidity is obtained such that the washer control system can take proper actions with respect to decisions including such as whether to save and/or treat the rinse water for further use or to dump the water. 
     An embodiment of the present invention can also be embodied in the form of computer program code, for example, whether stored in a storage medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits. The technical effect of the executable code is to facilitate prediction and optimization of modeled devices and systems. 
     This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they include structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.

Technology Classification (CPC): 3