SE517992C2 - Method for cleaning laundry / dishwashing in a washing / dishwasher and device for carrying out the method - Google Patents

Abstract

The present invention relates to a method and a device for cleaning of washing/dishing material in a number of steps in a washing machine/dishwasher, into which the material is placed in a cleaning space that may be closed. Water is supplied in one or more cycles to the cleaning space with or without chemical detergents, the material is cleaned during a certain time and at a certain temperature during one or more cycles in a cleaning process. The water with cleaning remains is discharged in one or more cycles form the cleaning space where supply of water, the cleaning process and discharge of water is controlled in dependence of, for instance, detection of the presence of cleaning remains and detergent in the water. The water is detected electrochemically by sensor instruments (1) using voltammetry by means of application of a varying electric potential over at least two electrodes (3, 4), which are in contact with the water in order to form an electric circuit (7). The present electric current's magnitude in the electric circuit is measured. The current's magnitude as a response to supplied potential using multivariate data analysis (MVDA) is analysed to acquire information in dependence of the contents of the water. Then a comparison with reference data is carried out for determining the contents of the water during the cleaning process and by means of control instruments (30) the cleaning process based on the determined contents of the water with respect to predetermined parameters, at least processing time and processing temperature.

Description

DESCRIPTION OF THE DRAWINGS The invention will be described in more detail below with an exemplary embodiment with reference to the accompanying drawings, in which fi g. 1 schematically shows the method and the device according to the invention, fi g. 2-4 show examples of recognition patterns used to control the cleaning process, and fi g. 5 and 6 show examples of selected cleaning processes in a machine as a result of detected water content.

PREFERRED EMBODIMENT The invention is based in part on the application of a principally prior art technique in a new context, namely the use of an "electronic tongue" for controlling machines for special household washing / dishes.The principle of the electronic tongue used for this application is based on electrochemical This measuring technique uses electrodes that serve as working electrodes and are preferably made of platinum, rhodium or stainless steel, which "together with a counter electrode are in contact with an electrically conductive liquid, in the current application that is supplied in a washing / dishwasher the water. By water is meant here the liquid that is fed into the machine and used during the washing dish process and is discharged from the machine. This water is thus not chemically pure water, but in the various stages contains various soluble or insoluble substances such as minerals and other contaminants, chemical detergents / detergents and / or contaminants from the laundry / dishes.

The measurement technique voltammetry is based on a varying potential being applied to the electrodes, whereby switching takes place between the working electrodes and the current response is measured in the formed, closed circuit. The current response, including transients, is detected and evaluated at different potentials and for each connected working electrode, whereby a recognition pattern arises which provides information about the content or character of the liquid. The voltammetric measurement as such is not the subject of the present invention, but is described in detail in the published international patent application with publication number WO 99/13325 to which reference is hereby made and is hereby incorporated by reference into this application.

By utilizing the recognition pattern that arises during the voltammetric measurement, information can be created that is representative of the composition of the water both before a cleaning process and during and after the process. This information is used according to the invention for controlling the cleaning process, whereby parts of the process or the entire process can be controlled in terms of various parameters. Examples of parameters are times and temperatures for different cycles, dosage of detergent, amount of water, choice of type and number of cycles, such as prewash / wash, main wash / wash, rinse and (when washing) spin.

With the system diagram according to fl g. 1, the method and device according to the invention for cleaning laundry / dishes in a washing machine / dishwasher are damaged. With a dotted block, the electrochemical sensor unit 1 using voltammetry is damaged. For this purpose, a washing / dishwasher is provided with an electrode unit 2 with one or more working electrodes 3, 4, which consist of a stable metal, such as platinum, rhodium or stainless steel, encapsulated in an electrically insulating material, advantageously so that an end surface is in contact with the wash / dish water. In the case of two or fl your working electrodes 3, 4, different metals are selected for each electrode, which gives different electrochemical processes and thus supplementary information about the content of the water. At a suitable distance in the vicinity of the working electrodes, a counter electrode 5 of, for example, stainless steel is arranged. The electrode unit 2 and the counter electrode 5 are arranged in a suitable manner in the washing / dishwasher, either directly in the cleaning space of the machine or in a special container which is in communication with the space, for example space for a circulation pump. Optionally, additional electrode sets may be provided, for example a set at the water inlet and the outlet to selectively detect inlet water, process water and outlet water. The electrochemical sensor unit 1 10 15 20 25 30 annu o 517 992 4 includes a control unit 6 which is arranged to apply a varying potential, see e.g. curve E (t), over a working electrode 3, 4 at a time and the counter electrode 5 according to a certain pattern. The potential can vary continuously, e.g. linear, or be pulsed. At least two different types of pulse voltammetry can be used in this context, which provide different current responses. These are commonly referred to as LAPV (high amplitude pulse voltammetry) and SAPV (low amplitude pulse voltammetry). Furthermore, the electrodes and the control unit 6 are so connected that a closed electric circuit 7 is formed, through which an electric current flows, see e.g. curve E (t), in response to the applied potential. The control unit 6 includes a potentiostat which ensures that the predetermined potential is maintained at a certain moment and which measures the response current generated.

Furthermore, the control unit 6 ensures that switching takes place between the working electrodes 3, 4 in combination with variation of the potential, whereby the current response, including its transients, provides information about the electrochemical process in the cleaning water. The technique described in the above-mentioned international patent application can be used for the current electrochemical sensor 1, but the technique can also be modified to adapt to the current application.

The measurement of the current at different potentials and changes in potential at certain determined moments of time and with the use of a certain working electrode at different moments during the cleaning process results in a quantity of data, which must be reduced and sorted to be evaluated and used to control the cleaning process. For this purpose, an analysis step 8 is included, which receives the large amount of data from the sensor unit 1. The function of the analysis step is based on a basically known analysis method, called multivariate data analysis MVDA. MVDA has two main purposes, one is to achieve structure and correlation of data, the other is to provide calibration models that can predict groupings of data. MVDA can use different methods to process data from the sensor unit. A multivariate data analysis method that can be used in the present invention is Principal Component Analysis (PCA). With PCA, an overview is created of the very large amount of data received from the sensor unit 1, in this case the voltammogram. Information on the following can be obtained: o Important less important variables o Correlation between variables o Systematic variation separated from noise o Deviating objects o Groups of objects PCA is a mathematical transformation used to explain the variance in a matrix (called the X-matrix) with the number N objects (ie measurements) and the number of K variables (ie output signals from the sensor unit 1). This creates a four-dimensional space of K dimensions, containing N points.

Using PCA, a vector is calculated, which describes the largest variances, ie, the direction that describes the largest difference between the observations. This is the first main component PC1. The second main component PC2 is perpendicular to PC1. PC2 describes as much as possible of the remaining information. This continues until all information has been reported.

The dimensions K are thus reduced to a smaller number of dimensions, which are defined by the main components. Not only have the dimensions been reduced, but in addition the latent structure of raw data, such as chemical or physical changes, can be visualized. The main components define a plane that maximizes the variation in raw data, with data projected on this plane. This creates a result image, so-called score-plot. 10 15 20 25 30 517 992. 6 Another MVDA method consists of "Partial Least Square" PLC, which is also called "Projection to Latent Structures". PLCs require not only process or sensor data in an X matrix, but also data for a Y matrix, which may, for example, be results, known concentrations or biological activity. A model is created to: o Find a relationship between X and Y o Predict new Y o Create a model for one or fl your y-variables A PLC is created by performing a PCA on the X-matrix and the Y-matrix, after which a linear regression is performed for each PC between the results for the X and Y matrices. The algorithms try to maximize covariances between X and Y.

The aim is to obtain a regression model between the X and Y matrices that can be used to predict, for example, unknown substances. PLS can handle "missing data", ie incomplete matrices, similar to / PCA.

An additional, alternative MVDA method, which can be used in the present invention, is Artiiçiella Neurala Nät ANN (Arti fi clal Neural Networks).

With the help of ANN, a model can be created that can assume almost any mathematical transformation. In addition, ANN is tolerant of noise and errors.

The disadvantages are that the network requires ät er measurements and longer learning time compared to PLC. ANN cannot handle many variables, as the number of observations required will increase rapidly. After learning and optimization, the model can: o Classify complicated (even non-linear) patterns o Predict new objects 10 15 20 25 30 517 992 7 ANN is designed to mimic the way in which the human brain works. In the brain, the function is based on signal transmissions between the neurons in a complex network. The neurons are connected via synapses.

In MVDA stage 8 (which is a microcomputer), the neurons have been replaced by nodes. A node receives information from many other nodes, performs a simple calculation of the information and forwards it to the other nodes.

The strength of the information is determined by the coupling constant of the node, which is multiplied by the strength of the single. Such a network has an ability for learning and memory storage.

ANN is a layer structure, there is an input layer, hidden (hidden) layer and an output layer. The hidden layer (s) and the output layer are the ones that are active and process information. The number of nodes in each layer and the number hidden on the problem.

The properties and knowledge of the network are determined by the characteristics of the individual node (weighting factor) and the mutual arrangement of the nodes (topology). Layers are determined by the user and depend on There are many available learning algorithms that are useful for learning the web. During learning, output values from ANN are compared with fair value, whereby the coupling constant is adjusted to give minimal differences by minimizing the sum of the squared error "square" error.

Examples of other MVDA methods that can be used in this context are: o Multiple Linear Regression MLR (Multiple Linear Regression) a simple linear method for prediction and calibration of Principal Component Regression PCR (Principal Component Regression) a linear method for prediction and calibration o Projection Pursuit Regression (PPR), a non-linear method of prediction and calibration After the above-described reduction and structuring of data from sensor unit 1 using the analysis step 8 MVDA, see fi g. 1, data can thus be obtained which indicate the content of the cleaning water, which is explained in more detail below. The content of the cleaning water is advantageously detected or measured at different stages of the cleaning process, either at different time intervals or continuously.

It is also conceivable for two or more sensor units to be placed in the machine to detect the cleaning water in parallel or in sequence.

An advantageous measurement or detection can be made of incoming water either in the form of a special sensor unit located at the inlet or measurement for a short time during filling, before the water has time to be affected by the cleaning goods. The measurement can be done before and after the addition of chemical cleaners. An important parameter in water quality is water hardness, which depends on the content of calcium and magnesium. This measurement can be used for monitoring softeners in, for example, a dishwasher, for example by controlling the addition of salt. However, there are other parameters in the water that are important for the overall water quality, such as copper and iron.

A second measuring step is measuring the water before starting the cleaning process. At this stage, according to the invention, it can be determined what kind and amount of dirt and contaminants are in the machine by letting the laundry or dishwashing liquid come into contact with the cleaning water, so that the contents can be mixed or dissolved in the water and detected by the sensor unit 1. of the measurements performed, is it possible to select a 10 15 20 25 30 517 992? 9 cleaning programs that are optimal for cleaning with as little water and energy as possible.

A third measuring step can be done during the cleaning process itself, whereby the process can be followed and controlled so that the process runs according to plan. If something unexpected occurs, such as the user opening the dishwasher door and inserting additional dirty dishes, the machine can react to this and adjust the process by changing certain parameters so that the method ensures that the desired dishwashing result is obtained, usually that the goods are clean.

A fourth measuring step can be done during the rinsing process, whereby it can be monitored that the effluent is sufficiently clean before the goods are ready. In addition to dirt and contaminants, it is essential to ensure that all detergent has been removed by rinsing.

Fig. 2 shows a concrete example of the above-described score plot obtained by measurements of different types of incoming water qualities and after multivariable data analysis MVDA of the PCA type. The scoreplot shows the results of olika your various measurements partly before the addition of chemical detergent and partly after the addition of chemical detergent. The result appears as a coordinate system where the measurement results are grouped in different positions in the coordinate system. Thus, in the present example, positions 9 and 10 represent distilled water before and after the addition of detergent, positions 11 and 12, soft seawater, positions 13, 14 relatively hard tap water, positions 15 and 16 hardened, hard tap water and positions 17 and 18 not hardened hard water, all in each group representing water before and after the addition of detergent. Through the positions of the different groups, a detection of the quality of the water can be obtained in this way, which is consistently given a new position after the addition of detergent. Because the results are recurring with limited deviations, the positions can be used to give control instructions to the machine depending on the water quality. Fig. 3 shows an example of a score plot or result image obtained after four typical case measurements in a washing machine at the beginning of the washing process, when the laundry has been soaked. Each point comes from a measurement, where the laundry in the machine was soiled with the current dirt. The score plot has also in this case been obtained after multivariate data analysis of the type main component analysis (PCA). Even after this analysis, it can be stated that dirt of different nature has obtained clearly separated positions in the score plot. Here, before each measurement, the laundry has been soiled with one variety at a time of the varieties used in the standard tests used, namely wine appearing at point or position 19, blood at position 20, oil at position 21 and chocolate at position 22. It may be added that the measurement in this case has been made after the addition of detergent and thus with one type of dirt at a time for each test run.

Fig. 4 shows a corresponding measurement in a dishwasher, but in this case before the addition of detergent. Here, too, a series of test runs were carried out, where in each run a single type of dirt was present. It could be stated that the different subject types had a relatively good spread over the scoré plot. Thus, margarine has obtained position 23, egg position 24, minced meat position 25, spinach position 26, tea position 27, milk position 28 and porridge position 29. It can be stated that eggs and minced meat are relatively close to each other, due to the fact that the minced meat contains eggs. Likewise, spinach and tea are relatively close to each other, which is due to similarity in character. It can also be stated that for this reason the substances that are close to each other in position thus need a similar cleaning process.

Regardless of how many types of dirt the laundry / dishes contain, each measurement after treatment in MVDA step 8 results in a single measuring point. The position of the measuring point is affected by the individual types of dirt and the extent of their occurrence and thus provides information about this.

The measuring points from the individual types of dirt and mixtures thereof will thus end up somewhere in the space described by the score plot. 10 15 20 25 30 517 992š 11 By teaching the machine control step 30, see fi g. 1, which area corresponds to which soil mixture (and which washing / washing program is necessary for each area), the score plots can be divided into many specified areas. Fig. 5 shows a schematic sketch of what such a division might look like in a two-dimensional score plot. The training step requires many measurements of many different soil mixtures. Each area 36 thus corresponds to a certain mixture of dirt.

As measurements take place continuously, the measuring points will fl surface from area to area and the program thus adapts so that the process will follow an optimal path to the desired end result. This is illustrated in fi g. 6, where a dishwasher process is followed (from right to left) by rapid, continuous measurement.

F ig. 7 and 8 illustrate examples of changing the cleaning process based on a normal program. Fig. 7 shows an example of a normal dishwashing program illustrated by a dashed curve 32, where the temperature changes with time during the washing process are illustrated. For the sake of clarity, a case has been chosen here where the dirt consists only of margarine. In this case, a program is selected in the machine control step 30 which is illustrated by the curve 33.

The total change as a result of the measurement performed according to the invention is: Time: -20% Detergent: -20% Added energy: no change Water: -40% By measuring the water content by means of sensor unit 1, data analysis of the measurement information in analysis step 8 and selection in In the machine control step 30 of washing process, a temperature curve was obtained over time, which is shown by a solid curve 33 and thus deviates significantly from the normal program. 10 15 20 25 30 517 992 12 Correspondingly illustrated in fi g. 8 a simple situation in a washing machine to show the principle according to the invention. A normal program is shown with dashed line 34, the course of the washing process. When detecting only blood in the wash, the machine control step 30 selected the following change, which also resulted in one that involves relatively high temperatures below curve 35 along the solid line.

Time: -15% Detergent: -20% Added energy: -75% Water: no change Points 37 on the score plot in fi g. 6 thus represents the current status of the cleaning water at each measurement, whereby an indication of final wash / wash result 38 can be set in relation to the water quality (possibly after softening) in the process water or the outlet water. In some cases, it is desired to end the process, without achieving final purity in the goods, e.g. if you only want to rinse the dishes, or if for some reason you are content with less clean laundry. In this case, an end point 40 is selected, see fi g.6, ie the process is interrupted at a point which deviates from an end point, which normally corresponds to the final washing / washing result.

The invention is not limited to the examples described above and shown in the drawings, but can be varied within the scope of the following claims. continuously measure the result.in the control of the dosage can also include choices between different detergent / detergent types.It should be added, the machine control stage 30 is realized in the form of microcomputers that both the heavy control stage 6 and the analysis stage 8 and 517 992š * 13 (microchips) programmed with computer programs to perform the functions described above. For example, the tongue control 6 is designed as a microchip which also contains the above-mentioned potentiostat and an AID converter, while the analysis step 8 and the machine control step 30 are included in a second microchip.

Claims (2)

10 15 20 25 30 517 992 .u n n ø v o o; n n n u c ~ o ø nu 14 PATENT CLAIMS Method for cleaning laundry / dishes in a washing / dishwasher, in which the goods are placed in a lockable cleaning room, water is added in one or more cycles to the cleaning room with or without chemical cleaners, the goods are cleaned for a certain time and with a certain temperature in a or several cycles in a cleaning process (31), the water with cleaning residues is discharged in one or more cycles from the cleaning space, whereby the supply of water, the cleaning process and discharge of water are controlled depending on, among other things, and detection of the presence of cleaning residues detergent in the water, characterized by the steps: - electrochemical detection of the water by voltammetry by applying a varying electrical potential over at least two electrodes (3, 4, 5), which are in contact with the water to form a circuit and measuring the occurring electric current in the circuit (7 ), - analysis of the current in response to applied potential by means of mult variable data analysis (MVDA (8)) to obtain information depending on the content of the water, - comparison with reference data for determining the content of the water during the cleaning process (31), - control (30) of the cleaning process on the basis of the determined content of the water with respect to predetermined parameters, at least process time and process temperature. Device for cleaning laundry / dishes in a washing / dishwasher with a closable cleaning space in which the dishes are placed, water being added in one or more cycles to the cleaning room with or without chemical cleaners, the goods are cleaned for a certain time and with a certain temperature in one or two cycles in a cleaning process (31), the water with cleaning residues is discharged in one or more cycles from the cleaning space, the supply of water, the cleaning process and the discharge of water being controlled in 10 s171g92 v I - v ø ou, oo 1 o | u - a dependence on, inter alia, the detection of the presence of cleaning residues and detergents in the water, characterized by sensor means (1) for electrochemical detection of the water by voltammetry by applying a varying electrical potential across at least two electrodes (3, 4, 5), in contact with the water to form a circuit (7) and measuring the occurring electric current in the circuit, by means (8) for analyzing the current in response to applied potential by means of multivariate data analysis (MVDA) and means (30) for comparison with reference data for determining the content of the water during the cleaning process (31) and control (30) of the cleaning process on the basis of the determined content of the water with respect to predetermined parameters, at least process time and process temperature.