Doing the Wash: Cycle Two

1984 ◽  
Vol 43 (1) ◽  
pp. 49
Author(s):  
Thomas A. Burns
Keyword(s):  
Wash Cycle

Washing Machine Health Diagnostics Through Information Synthesis

2001 ◽  
Author(s):  
J. Brown ◽  
M. A. Franchek
Keyword(s):  
Lumped Parameter Model ◽  
Washing Machine ◽  
Wash Cycle ◽  
Information Synthesis ◽  
Pulse Input ◽  
Lumped Parameter ◽  
Design Values ◽  
Simulation Results ◽  
Machine Health ◽  
Measured Displacement

Abstract Presented in this paper is a model-based method for assessing suspension and motor health of washing machines. The diagnosis of the suspension and motor health is achieved by processing the measured dynamics of the washtub. In particular, an online adapted lumped parameter model of the washtub is used to estimate key suspension and motor parameters. These parameters are identified from the measured displacement of the washtub due to a motor pulse input prior to the beginning of the wash cycle. Comparing the estimated values to design values assesses both suspension and motor health. Included are simulation results to validate the parameter estimation process.

Development of a sound quality index for the wash cycle process of front-loading washing machines considering the impacts of individual noise sources

2015 ◽  
Vol 87 ◽  
pp. 183-189 ◽  
Author(s):  
Un-Chang Jeong ◽  
Jin-Su Kim ◽  
Jae-Eun Jeong ◽  
In-Hyung Yang ◽  
Jae-Eung Oh
Keyword(s):  
Quality Index ◽  
Sound Quality ◽  
Noise Sources ◽  
Wash Cycle ◽  
Washing Machines

scholarly journals A fully automated liquid–liquid extraction system utilizing interface detection

2000 ◽  
Vol 22 (6) ◽  
pp. 187-194 ◽  
Author(s):  
Eugene Maslana ◽  
Robert Schmitt ◽  
Jeffrey Pan
Keyword(s):  
High Speed ◽  
Methylene Chloride ◽  
Phase Interface ◽  
Liquid Extraction ◽  
Automated System ◽  
Extraction System ◽  
Wash Cycle ◽  
Large Sets ◽  
Liquid Liquid Extraction

The development of the Abbott Liquid-Liquid Extraction Station was a result of the need for an automated system to perform aqueous extraction on large sets of newly synthesized organic compounds used for drug discovery. The system utilizes a cylindrical laboratory robot to shuttle sample vials between two loading racks, two identical extraction stations, and a centrifuge. Extraction is performed by detecting the phase interface (by difference in refractive index) of the moving column of fluid drawn from the bottom of each vial containing a biphasic mixture. The integration of interface detection with fluid extraction maximizes sample throughput. Abbott-developed electronics process the detector signals. Sample mixing is performed by high-speed solvent injection. Centrifuging of the samples reduces interface emulsions. Operating software permits the user to program wash protocols with any one of six solvents per wash cycle with as many cycle repeats as necessary. Station capacity is eighty, 15 ml vials. This system has proven successful with a broad spectrum of both ethyl acetate and methylene chloride based chemistries. The development and characterization of this automated extraction system will be presented.

Long wash cycle duration as a potential for saving energy in laundry washing

2016 ◽  
Vol 10 (4) ◽  
pp. 823-838 ◽  
Author(s):  
Farnaz Alborzi ◽  
Angelika Schmitz ◽  
Rainer Stamminger
Keyword(s):  
Cycle Duration ◽  
Saving Energy ◽  
Wash Cycle ◽  
Laundry Washing

Introduction to Fuzzy Logic and Fuzzy Linear Programming

2011 ◽  
pp. 539-553 ◽  
Author(s):  
Pandian Vasant ◽  
Hrishikesh S. Kale
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Linear Programming ◽  
Approximate Reasoning ◽  
University Of California ◽  
Wash Cycle ◽  
Black And White ◽  
Asset Values ◽  
Vague Data ◽  
The University ◽  
Load Size

Fuzzy logic (FL) is a mathematical technique for dealing with imprecise data and problems that have many solutions rather than one. Although it is implemented in digital computers which ultimately make only yesno decisions, FL works with ranges of values, solving problems in a way that more resembles human logic. FL is a multi-valued (as opposed to binary) logic developed to deal with imprecise or vague data. Classical logic holds that everything can be expressed in binary terms: 0 and 1, black and white, yes or no; in terms of Boolean algebra, everything is in one set or another but not in both. FL allows for partial membership in asset values between 0 and 1, shades of gray, and introduces the concept of the “fuzzy set.” When the approximate reasoning of FL (Zadeh, 1965) is used with an expert system, logical inferences can be drawn from imprecise relationships. FL theory was developed by Lofti A. Zadeh at the University of California in the mid 1960s. However, it was not applied commercially until 1987 when the Matsushita Industrial Electric Co. used it to automatically optimize the wash cycle of a washing machine by sensing the load size, fabric mix, and quantity of detergent and has applications in the control of passenger elevators, household applications, and so forth.

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