EP1773172B1 - Procede d'etalonnage de capteurs - Google Patents

Procede d'etalonnage de capteurs Download PDF

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Publication number
EP1773172B1
EP1773172B1 EP05776127.2A EP05776127A EP1773172B1 EP 1773172 B1 EP1773172 B1 EP 1773172B1 EP 05776127 A EP05776127 A EP 05776127A EP 1773172 B1 EP1773172 B1 EP 1773172B1
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value
measured
values
reference value
measured values
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EP05776127.2A
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German (de)
English (en)
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EP1773172A1 (fr
Inventor
Georg Curtius
Michael Fauth
Reinhard Hering
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BSH Hausgeraete GmbH
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BSH Hausgeraete GmbH
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    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L15/00—Washing or rinsing machines for crockery or tableware
    • A47L15/42—Details
    • A47L15/4297—Arrangements for detecting or measuring the condition of the washing water, e.g. turbidity
    • D—TEXTILES; PAPER
    • D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
    • D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
    • D06F34/00—Details of control systems for washing machines, washer-dryers or laundry dryers
    • D06F34/14—Arrangements for detecting or measuring specific parameters
    • D06F34/22—Condition of the washing liquid, e.g. turbidity
    • D—TEXTILES; PAPER
    • D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
    • D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
    • D06F2103/00—Parameters monitored or detected for the control of domestic laundry washing machines, washer-dryers or laundry dryers
    • D06F2103/20—Washing liquid condition, e.g. turbidity
    • D—TEXTILES; PAPER
    • D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
    • D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
    • D06F2105/00—Systems or parameters controlled or affected by the control systems of washing machines, washer-dryers or laundry dryers
    • D06F2105/52—Changing sequence of operational steps; Carrying out additional operational steps; Modifying operational steps, e.g. by extending duration of steps

Definitions

  • the invention relates to a method for calibrating sensors, in particular turbidity sensors in household appliances and an associated household appliance for carrying out the method.
  • the cleaning program In household appliances, eg. As dishwashers or washing machines, turbidity sensors for determining the degree of contamination of the cleaning liquid, eg. As washing liquor or rinse liquor used. With the aid of the values of the degree of soiling determined by the turbidity sensor, further control of the cleaning program of the household appliance takes place.
  • the cleaning program In a dishwasher, for example, the cleaning program consists of the partial program steps "pre-rinsing", “cleaning”, “intermediate rinsing", “rinsing” and “drying". Within the sub-program step “intermediate rinsing" often several intermediate rinsing steps are performed.
  • the controller of the dishwasher By using the values of the degree of contamination determined by the turbidity sensor, it is possible to stop the execution of further intermediate rinsing steps by the controller of the dishwasher when it falls below a certain value of the degree of soiling. Thus, a considerable water and energy savings can be achieved with the same cleaning results.
  • the rinsing liquor from the "pre-rinse" can be used for the sub-program step "cleaning".
  • Turbidity is generally measured by passing light through the cleaning fluid.
  • other physical measuring methods eg. B. conceivable with sound.
  • the transmitting device is, for example, a lamp or a light emitting diode and the receiving device z. B. to a phototransistor.
  • the transceivers are subject to wear and aging changes. In addition, some significant deposits on the optical devices can occur. Temporary contamination at the transceivers can lead to significant errors in the measurements to lead. Over time, this leads to successively increasing errors in the measurements of the turbidity of the cleaning fluid. This leads to errors in the control of the household appliance.
  • From the EP 0 862 892 B1 is a household appliance with a measuring device for determining the degree of contamination of a cleaning liquid known.
  • a comparison measurement with the measuring device in a cleaning program in which the measuring device is used to determine the degree of contamination of the cleaning liquid, previous cleaning program performed, preferably in a program part with unpolluted rinsing liquid, eg. B. rinsing is performed.
  • the measured value for the adjustment of the measuring device in the following cleaning program can be stored in a non-volatile memory.
  • the disadvantage here is that with a small or hidden intermediate rinses not inconsiderable impurities in the rinsing liquor may also be contained during rinsing, so that the measurement results can be falsified.
  • only one adjustment measurement is carried out, so that in the case of randomly occurring heavy soiling, eg. B. at the transmitting device by punctual deposits, measured values for the adjustment of the measuring device with significant errors are the result.
  • a method for adjusting a turbidity sensor is known.
  • multiple calibration value measurements are performed at different times and stored in a first memory map, with calibration value measurements taken in multiple wash programs.
  • the calibration measured value with the lowest degree of contamination is determined by selection for each wash program and written in a second memory table.
  • the average value is calculated, which forms the reference value for the measurement with the turbidity sensor.
  • Object of the present invention is therefore to provide a method and an associated household appliance for performing the method, which allows a simple way under all operating conditions of a household appliance, especially for temporary contaminants, a reliable calibration of sensors, eg. B. turbidity sensors to allow.
  • the selection of the at least one measured value by methods of statistics or probability calculation is carried out in each case from a series of measured values which were measured at the same time points within a rinsing program sequence.
  • measured values are selected which were measured at the same times within a rinsing program sequence, so that they are similar to one another and suitable for further selection procedures or calculations.
  • the interval of the probable limits of the possible reference value is set smaller, so that at least one measured value lies outside and this selects at least one measured value. This is always at least a measured value is selected.
  • the method can thereby be adapted to changing conditions.
  • predetermined empirical values are preferably additionally used from the factory to determine the probable limits of the possible reference value, which empirical values are automatically adapted in the course of the process to changing conditions.
  • the determination of the at least one possible reference value for the calibration of the sensor from the remaining, non-selected measured values is carried out by averaging.
  • the possible reference values for the series of measured values for the measured values can be determined in a simple manner at any one time, and possibly existing incorrect measurements have only a small influence due to the averaging.
  • the determination of the at least one possible reference value for the calibration of the sensor from the remaining, non-selected measured values is carried out by selecting a measured value by means of statistical or probability calculation methods.
  • the measured value with the highest probability density is selected within the non-selected measured values. This makes it possible to rule out possible errors compared to averaging, which is based on measured values that may be subject to errors.
  • the most optimal ie generally the reference value with the smallest degree of contamination, is selected as the reference value for the calibration of the sensor.
  • a turbidity sensor 6 is shown. It has a transmitting device 1 as a lamp, which preferably emits visible light.
  • the transmitting device 1 can also electromagnetic waves from other arbitrary frequency ranges, eg. As infrared light, emit.
  • a receiving device 2 as a photocell, the light incident on it is converted into electricity.
  • a control and evaluation unit 4 supplies the transmitting device 1 with power and evaluates the power supplied by the receiving device 2.
  • the transmitting device 1 and the receiving device 2 are connected via electrical lines 5 to the control and evaluation unit 4.
  • the control and evaluation unit 4 can also be part of the control of a dishwasher according to the invention, ie it is no separate control and evaluation unit 4 for the turbidity sensor 6 is necessary. Due to the change in the incident on the receiving unit 2 light at preferably constant power supply for the transmitting device 1, the degree of contamination of the wash liquor 3 is determined. The lower the power supplied by the receiving device 2, the greater the degree of contamination.
  • the turbidity sensor 6 can in the dishwasher according to the invention z. B. be installed in the washing or in a line for rinsing. With the help of this value of the degree of contamination, the control of the dishwasher according to the invention controls the further program sequence. For example, falls below a certain degree of contamination, the implementation of further intermediate rinsing steps canceled or it takes place between pre-rinsing and cleaning no change in the rinse.
  • Fig. 2 is a conventional Spülprogrammablauf s a dishwasher shown. On the abscissa axis the time is applied and on the ordinate axis the amount of rinsing liquor in the dishwasher.
  • the wash program sequence consists of the program steps "Pre-wash”, “Clean”, “Intermediate wash”, “Rinse” and "Dry”.
  • a rinsing program sequence s only one measured value, preferably in the subprogram step "rinsing", can be measured, or also a plurality of reference values within the rinsing program, whereby also within a subprogram step, eg. B. "rinse", several readings, eg. B. m 3 1 , m 4 1 , for the calibration of the turbidity sensor 6 can be measured.
  • the method can also be refined to the effect that a separate series of measurements is stored for each different rinse program with at least one measurement.
  • the number of measurement series does not correspond to the number of measurement times t a , but totals the sum of the individual measurement times t a for each individual wash program.
  • Fig. 3 an inventive flowchart for the determination of the reference value m a s is shown.
  • the top section shows the measured values m a s .
  • B the measured values m a s only from Spülprogrammab threadn s determined that have a low load, if z. B corresponding load sensors are present.
  • a selection is carried out at least by preferably statistical methods a measured value m a s , which is no longer taken into account in the further steps.
  • An example of such a statistical method will be described below.
  • other methods come into consideration, eg. B. with methods of probability.
  • the mean value of the remaining measured values m a s of a column is formed, d, h. m a s ⁇ determined as a possible reference measured value. From these mean readings m a s ⁇ becomes the optimal mean reading in the following operator m a s ⁇ which is generally the mean reading m a s ⁇ with the smallest degree of contamination, ie the largest mean value m a s ⁇ is.
  • This optimal mean reading m a s ⁇ is the reference value for the turbidity measurement in the preferably subsequent rinse program.
  • other criteria such. For example, only possible reference values from a specific column, these criteria can also be set ex works and / or automatically adjusted.
  • Fig. 4 in this operation unit also from the selected measured values m a s by selection method, eg. B. with methods of statistics, error theory or the probability calculation, a single measured value m * a s from one column of measured values m a s for each t a , ie column, are selected. From these measured values m * a s as possible reference values, the optimal measured value m * a s is selected in the following operator, which is generally the measured value m * a s with the smallest degree of contamination, ie the largest measured value m * a s . This optimum measured value m * a s is the reference value for the turbidity measurement in the preferably subsequent rinsing program.
  • ⁇ a 2 m 1 1 - d a 2 + m 1 2 - d a 2 + ... + m 1 s - d a 2 s
  • measured values m a s lie outside this probable limit. Are measured values m a s outside, they will be selected. If there is an excessive number of measured values m a s in relation to the number of measured values m a s , only those measured values m a s which are outside the probable limit by a specific value can be excluded. If there are no measurement values m a s outside the border probable, metrics are m a s exclude that lie at a certain value within the likely limitations. For this purpose, empirically determined values can also be specified ex works, which are preferably arithmetically adjusted in the course of the process to changing conditions.
  • This method is carried out for all rows of the measured values m a s at the respective times t a .
  • the probability density for the arithmetic mean of the measured value m a s is greatest, regardless of how the Gaussian law of errors is designed.
  • the arithmetic mean is determined d '.
  • the distance of the individual measured values m a s from this arithmetic mean d ' a with d' 1 , d ' 2 , ... d' a is to be determined, ie the magnitude
  • the smallest value is selected with an algorithm.
  • the measured value m a s associated with this smallest value is used as a possible reference value for the calibration of the turbidity sensor.
  • the measured values m a s can also be selected before the selection in the uppermost operating unit of the at least one measured value m a s .
  • existing uppermost operation unit is thus not used.
  • the most optimal reference value is selected, which is generally the reference value with the smallest degree of contamination. This is done by means of a corresponding algorithm for determining the largest value.
  • the probability density can be determined for each measured value m a s according to the laws of the probability calculation, and the measured value which has the greatest probability density can be selected as the reference value.
  • the intermediate or final values determined in this method are preferably temporarily stored in non-volatile memories. The control is carried out with a corresponding computer system.
  • the present method according to the invention for calibrating sensors in household appliances makes it possible, by selecting individual measured values by statistical methods, to minimize errors resulting from the use of measured values with large deviations, for B. by temporary impurities, within a series of measurements to determine the reference value result. Individual measured values with large deviations are selected in particular using statistical methods.
  • the selection of a single measured value as a reference value permits the error, which is determined by measured values with, in particular, strong deviations, caused by incorrect measurements, for example, as compared to an averaging. B. in the case of short-term deposits on the receiving or transmitting devices, arises to prevent.

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  • Engineering & Computer Science (AREA)
  • Textile Engineering (AREA)
  • Washing And Drying Of Tableware (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Control Of Washing Machine And Dryer (AREA)

Claims (10)

  1. Procédé d'étalonnage d'un capteur, en particulier d'un capteur de turbidité (6) dans un appareil ménager, p. ex. un lave-vaisselle ou un lave-linge, à l'aide de valeurs de référence ( m a s ‾ ,
    Figure imgb0050
     m*a s), comprenant les étapes suivantes :
    - détermination d'au moins deux valeurs de mesure (ma s) pendant le déroulement (s) d'au moins un programme de nettoyage,
    - sélection d'au moins une valeur de mesure (ma s) par des méthodes de la statistique ou du calcul des probabilités, valeur qui n'est plus prise en compte dans l'étape suivante et
    - détermination d'au moins une valeur de référence possible ( m a s ‾ ,
    Figure imgb0051
     m*a s) pour l'étalonnage du capteur, à partir des valeurs de mesure (ma s) non sélectionnées, et
    - sélection d'une valeur de référence optimale ( m a s ‾ ,
    Figure imgb0052
     m*a s) à partir de la au moins une valeur de référence possible ( m a s ‾ ,
    Figure imgb0053
     m*a s), si plus de deux valeurs de référence possibles ( m a s ‾ ,
    Figure imgb0054
     m*a s) ont été déterminées.
  2. Procédé selon la revendication 1, caractérisé en ce que la sélection de la au moins une valeur de mesure (ma s) qui n'est plus prise en compte dans l'étape suivante, par des méthodes de la statistique ou du calcul des probabilités, est effectuée à chaque fois à partir d'une série de valeurs de mesure (ma s) ayant été mesurées aux mêmes moments (ta) pendant le déroulement (s) d'un programme de lavage.
  3. Procédé selon la revendication 1 ou 2, caractérisé en ce que, afin de sélectionner au moins une valeur de mesure (ma s), les étapes suivantes sont effectuées :
    - détermination de la moyenne arithmétique (d1 à da) pour les valeurs de mesure (ma s pour a=1, 2, ..., a), selon la formule d a = m a 1 + m a 2 + m a 3 + m a 4 + ⋯ + m a s s ,
    Figure imgb0055
    - détermination de l'erreur quadratique moyenne (σa 2 pour σ1 2 à σa 2) avec da de la première étape, selon la formule σ a 2 = m 1 1 − d a 2 + m 1 2 − d a 2 + ⋯ + m 1 s − d a 2 s
    Figure imgb0056
    - détermination des limites probables de la valeur de référence possible (m*a s, m a s ‾
    Figure imgb0057
     pour m*1 s, m 1 s ‾
    Figure imgb0058
     à m*a s, m a s ‾ ) ,
    Figure imgb0059
    ) celles-ci étant situées au sein de d a ± 0 , 6746 s
    Figure imgb0060
     et
    - sélection des valeurs de mesure (ma s) situées en dehors de ces limites.
  4. Procédé selon la revendication 3, caractérisé en ce que, si aucune valeur de mesure (ma s) n'est située en dehors des limites probables de la valeur de référence possible (m*a s, m a s ‾
    Figure imgb0061
    ), l'intervalle des limites probables de la valeur de référence possible (m*a s, m a s ‾
    Figure imgb0062
    ) est choisi plus petit, de sorte qu'au moins une valeur de mesure (ma s) est située en dehors de ces limites et que cette au moins une valeur de mesure (ma s) est sélectionnée.
  5. Procédé selon la revendication 4 ou 5, caractérisé en ce que, afin de déterminer les limites probables de la valeur de référence possible (m*a s, m a s ‾
    Figure imgb0063
    ), on utilise à titre complémentaire des valeurs empiriques de préférence prédéfinies en usine, lesquelles sont automatiquement adaptées au cours du procédé en fonction de l'évolution des conditions.
  6. Procédé selon la revendication 1 ou 2, caractérisé en ce que la détermination de la au moins une valeur de référence possible m a s ‾
    Figure imgb0064
     pour l'étalonnage du capteur, à partir des valeurs de mesure (ma s) non sélectionnées restantes, est effectuée par formation d'une valeur moyenne.
  7. Procédé selon la revendication 1 ou 2, caractérisé en ce que la détermination de la au moins une valeur de référence possible (m*a s) pour l'étalonnage du capteur, à partir des valeurs de mesure (ma s) non sélectionnées restantes, est effectuée par sélection d'une valeur de mesure (ma s) au moyen de méthodes de la statistique ou du calcul des probabilités.
  8. Procédé selon la revendication 7, caractérisé en ce que l'on sélectionne la valeur de mesure (ma s) ayant la densité de probabilité la plus élevée au sein des valeurs de mesure (ma s) non sélectionnées.
  9. Procédé selon la revendication 7 ou 8, caractérisé en ce que l'on sélectionne comme valeur de référence possible (m*a s) la valeur de mesure (ma s) la plus proche de la moyenne arithmétique des valeurs de mesure (ma s) non sélectionnées, par les étapes suivantes :
    - détermination des moyennes arithmétiques (d'a pour a= 1, 2, a) des valeurs de mesure (ma s) non sélectionnées,
    - détermination du montant de | d'a - ma s |, sachant que l'on sélectionne la valeur de mesure (ma s) où le montant de | d'a - ma s | est le plus petit.
  10. Procédé selon l'une des revendications précédentes, caractérisé en ce que l'on sélectionne parmi les valeurs de référence possibles ( m a s ‾ ,
    Figure imgb0065
     m*a s) la valeur optimale, soit en général la valeur de référence ( m a s ‾ ,
    Figure imgb0066
     m*a s) présentant le degré de salissure le plus faible, comme valeur de référence ( ( m a s ‾ ,
    Figure imgb0067
     m*a s) pour l'étalonnage du capteur.
EP05776127.2A 2004-07-23 2005-07-22 Procede d'etalonnage de capteurs Expired - Lifetime EP1773172B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102004035848A DE102004035848A1 (de) 2004-07-23 2004-07-23 Verfahren zum Kalibrieren von Sensoren
PCT/EP2005/053589 WO2006010744A1 (fr) 2004-07-23 2005-07-22 Procede d'etalonnage de capteurs

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EP1773172A1 EP1773172A1 (fr) 2007-04-18
EP1773172B1 true EP1773172B1 (fr) 2017-09-06

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US (1) US7558690B2 (fr)
EP (1) EP1773172B1 (fr)
KR (1) KR20070041496A (fr)
CN (1) CN1988838B (fr)
DE (1) DE102004035848A1 (fr)
WO (1) WO2006010744A1 (fr)

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CN104485923B (zh) * 2014-11-03 2017-09-15 佛山市顺德区美的洗涤电器制造有限公司 一种洗碗机及浊度传感器校准控制方法和装置
DE102016221446A1 (de) * 2016-11-02 2018-05-03 BSH Hausgeräte GmbH Kalibrieren eines Sauerstoffsensors eines Haushaltsgeräts
CN107478260A (zh) * 2017-07-19 2017-12-15 武汉华显光电技术有限公司 计算机可读存储介质、感测器及其自动校准方法
DE102017217585A1 (de) * 2017-10-04 2019-04-04 BSH Hausgeräte GmbH Verfahren zum Betreiben eines Haushaltsgeräts und Haushaltsgerät
CN107907468B (zh) * 2017-12-04 2020-11-06 广东美的制冷设备有限公司 传感器校准方法、传感器和空气处理设备
CN110879284B (zh) * 2019-12-02 2023-12-22 上海明胜品智人工智能科技有限公司 水质的检测方法及装置、存储介质和电子装置
US12011134B2 (en) 2020-01-14 2024-06-18 Midea Group Co., Ltd. Washing apparatus including cloud connected spectrometer
DE102020212542A1 (de) * 2020-10-05 2022-04-07 BSH Hausgeräte GmbH Wäschepflegegerät mit einer Steuerung
CN113598682B (zh) * 2021-07-19 2022-11-08 佛山市百斯特电器科技有限公司 一种浊度检测装置的校准方法、校准装置及洗涤设备
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US7558690B2 (en) 2009-07-07
KR20070041496A (ko) 2007-04-18
DE102004035848A1 (de) 2006-03-23
EP1773172A1 (fr) 2007-04-18
CN1988838A (zh) 2007-06-27
US20080040063A1 (en) 2008-02-14
WO2006010744A1 (fr) 2006-02-02
CN1988838B (zh) 2010-11-17

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