CN111671315A - Method for detecting humidity control abnormity of cooking equipment - Google Patents
Method for detecting humidity control abnormity of cooking equipment Download PDFInfo
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- CN111671315A CN111671315A CN202010382792.9A CN202010382792A CN111671315A CN 111671315 A CN111671315 A CN 111671315A CN 202010382792 A CN202010382792 A CN 202010382792A CN 111671315 A CN111671315 A CN 111671315A
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- 238000010411 cooking Methods 0.000 title claims abstract description 172
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000002159 abnormal effect Effects 0.000 claims description 30
- 230000005856 abnormality Effects 0.000 claims description 11
- 238000010025 steaming Methods 0.000 abstract description 11
- 238000001514 detection method Methods 0.000 description 10
- 230000006872 improvement Effects 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 230000009246 food effect Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 235000021471 food effect Nutrition 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- 239000000126 substance Substances 0.000 description 1
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47J—KITCHEN EQUIPMENT; COFFEE MILLS; SPICE MILLS; APPARATUS FOR MAKING BEVERAGES
- A47J36/00—Parts, details or accessories of cooking-vessels
- A47J36/32—Time-controlled igniting mechanisms or alarm devices
Abstract
The invention provides a method for detecting humidity control abnormity of cooking equipment, which comprises the following steps: detecting the food cooked this time; forming a last-time humidity control cooking model by utilizing humidity control data of the same food cooked by the cooking equipment last time; predicting the current food cooking humidity data according to the current environment temperature and humidity parameters by using the previous humidity control cooking model to form a current humidity control prediction model; when the cooking equipment cooks the food, acquiring real-time humidity control operation data; comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model; and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference value, entering a humidity control abnormity error reporting program. Whether the humidity control of the electric steaming oven normally operates is effectively judged.
Description
Technical Field
The invention relates to the technical field of kitchen appliances, in particular to a method for detecting humidity control abnormity of cooking equipment.
Background
In the high-end electric steaming oven of the existing kitchen electric product, a humidity sensor is arranged in a cooking inner cavity, and humidity data in the inner cavity are collected, so that the humidity of the steaming oven is automatically adjusted. Because humidity transducer sets up and exposes for a long time in the humiture culinary art environment of difference, the greasy dirt that the process of steaming easily appears the comdenstion water too much or toasts the process piles up and cause to detect badly at humidity transducer detection mouth, thereby can't realize accurate humidity control or obtain the user and set for realizing the culinary art food effect, seriously influence user experience, and current electric steaming oven is at the in-process of culinary art food, whether the user can't judge the humidity control of electric steaming oven and normally operates, whether break down, and then can't guarantee the culinary art effect of food.
Disclosure of Invention
The invention aims to solve one of the problems in the prior art to a certain extent, and therefore the invention aims to provide a method for detecting the humidity control abnormity of cooking equipment, which can effectively judge whether the humidity control of an electric steaming oven normally operates.
The above purpose is realized by the following technical scheme:
a method for detecting humidity control abnormality of a cooking device comprises the following steps:
detecting the food cooked this time;
forming a last-time humidity control cooking model by utilizing humidity control data of the same food cooked by the cooking equipment last time;
predicting the current food cooking humidity data according to the current environment temperature and humidity parameters by using the previous humidity control cooking model to form a current humidity control prediction model;
when the cooking equipment cooks the food, acquiring real-time humidity control operation data;
comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model;
and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference value, entering a humidity control abnormity error reporting program.
As a further improvement of the present invention, the step of forming the previous humidity control cooking model by using the humidity control data of the same food cooked by the cooking device last time specifically comprises: judging whether the cooking equipment fails in the cooking period of cooking the same food last time; if the cooking device does not have a fault during the cooking period of the same food cooked last time, detecting whether the temperature of an inner cavity of the cooking device reaches a constant value during the cooking period of the same food cooked last time by the cooking device; if the temperature of the inner cavity of the cooking equipment reaches constant during the cooking period when the cooking equipment cooks the same food last time, collecting humidity control data of the same food cooked last time by the cooking equipment within a fixed cooking time; and fitting humidity control data of the same food cooked by the cooking equipment at the last time within the fixed cooking time length to form a last-time humidity control cooking model.
As a further improvement of the present invention, when the cooking device cooks the current food, the step of acquiring the real-time humidity control operation data specifically comprises: detecting whether the temperature of an inner cavity of the cooking equipment reaches a constant value or not in real time; and if the temperature of the inner cavity of the cooking equipment reaches a constant value, acquiring real-time humidity control operation data within a fixed cooking time.
As a further improvement of the present invention, the step of obtaining real-time humidity control operation data within a fixed cooking time period further comprises the steps of: judging whether the real-time humidity control operation data within the fixed cooking time length has an abnormal value or not; and if the real-time humidity control operation data in the fixed cooking time length has no abnormal value, comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model.
As a further improvement of the present invention, the step of determining whether the real-time humidity control operation data within the fixed cooking time period has an abnormal value is specifically: if the real-time humidity control operation data in the fixed cooking time length has an abnormal value, the real-time humidity control operation data in the fixed cooking time length is obtained again; and if the real-time humidity control operation data in the fixed cooking time length has no abnormal value, comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model.
As a further development of the invention, the fixed cooking time period is less than 60 s.
As a further improvement of the invention, the step of comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model specifically comprises the following steps: if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is smaller than the preset difference value, maintaining the current control parameter to continue cooking until the cooking is finished; and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference value, entering a humidity control abnormity error reporting program.
As a further improvement of the present invention, the method for calculating the difference between the average value of the real-time humidity control operation data and the average value of the humidity control data of the current humidity control prediction model specifically comprises the following steps: if the average value of the real-time humidity control operation data is larger than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the real-time humidity control operation data-the average value of the humidity control data of the current humidity control prediction model; and if the average value of the real-time humidity control operation data is smaller than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the humidity control data of the current humidity control prediction model-the average value of the real-time humidity control operation data.
As a further development of the invention, the predetermined difference is 5% to 15%.
Compared with the prior art, the invention at least comprises the following beneficial effects:
1. the invention provides a method for detecting the humidity control abnormity of cooking equipment, which can effectively judge whether the humidity control of an electric steaming oven normally operates.
Drawings
Fig. 1 is a flowchart of a method for detecting an abnormality in humidity control of a cooking apparatus according to the present invention.
Detailed Description
The present invention is illustrated by the following examples, but the present invention is not limited to these examples. Modifications to the embodiments of the invention or equivalent substitutions of parts of technical features without departing from the spirit of the invention are intended to be covered by the scope of the claims of the invention.
Referring to fig. 1, a method for detecting humidity control abnormality of a cooking apparatus includes the steps of:
detecting the food cooked this time S1; the method comprises the steps of detecting information such as the type, weight, maturity degree and the like of the food cooked at this time.
Forming a last-time humidity control cooking model S2 by using humidity control data of the same food cooked by the cooking equipment last time; the same food includes the same kind, the same weight, the same degree of maturity, etc. as the last cooked food, i.e. the respective detected parameters of the food are the same.
Predicting the current food cooking humidity data according to the current environment temperature and humidity parameters by using the previous humidity control cooking model to form a current humidity control prediction model S3; the environment temperature and humidity parameters influence the temperature and humidity of food cooking, so that the temperature and humidity data of the current food cooking are predicted in combination with the environment temperature and humidity, the humidity control prediction model is more accurate, and the requirements are met more.
When the cooking equipment cooks the food, acquiring real-time humidity control operation data S4; the same control parameters of the same food as the food cooked last time are input on a control interface of the cooking equipment, and a humidity detection device is arranged in the cooking equipment, so that real-time humidity control operation data can be obtained.
Comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model S5;
if the difference between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference, the humidity control abnormity error reporting program S6 is entered. The humidity control abnormity error reporting program can be used for giving an abnormity alarm sound to remind a user of the abnormity of the humidity control of the cooking equipment, and/or controlling the closing of the cooking equipment to prevent the cooked food from being continuously cooked under the abnormal humidity, and/or other error reporting programs.
The current electric steaming oven is at the in-process of culinary art food, and whether normal operating, whether break down of humidity control that the user can't judge electric steaming oven, and then can't guarantee the culinary art effect of food. The invention provides a method for detecting the abnormal humidity control of cooking equipment, which can effectively judge whether the humidity control of an electric steaming oven normally operates or not and ensure that the cooking equipment can realize the food cooking effect according to the requirements set by a user.
The step of forming the previous humidity control cooking model S2 by using the humidity control data of the same food cooked by the cooking apparatus last time is specifically as follows: judging whether the cooking equipment fails in the cooking period of cooking the same food last time; if the cooking equipment fails in the cooking period of cooking the same food last time, judging whether the cooking equipment fails in the cooking period of cooking the same food last time; if the cooking device does not have a fault during the cooking period of the same food cooked last time, detecting whether the temperature of an inner cavity of the cooking device reaches a constant value during the cooking period of the same food cooked last time by the cooking device; if the temperature of the inner cavity of the cooking equipment reaches constant during the cooking period when the cooking equipment cooks the same food last time, collecting humidity control data of the same food cooked last time by the cooking equipment within a fixed cooking time; and fitting humidity control data of the same food cooked by the cooking equipment at the last time within the fixed cooking time length to form a last-time humidity control cooking model. The temperature rise process exists when cooking equipment cooks food, the temperature is kept invariable after rising to the set temperature, the inner chamber humidity change of the cooking equipment is great in the temperature rise process, if the humidity data is detected at the moment, the fluctuation of the detected humidity data is great, the detection result is unreliable, and when the temperature rises to the set temperature and is kept invariable, the humidity change is small, so that the humidity control data of the same food cooked by the cooking equipment last time in the fixed cooking time length is collected when the inner chamber temperature of the cooking equipment reaches invariable, and the data are more reliable. The fixed cooking time period is less than 60s, and in the present embodiment, the fixed cooking time period is 40 s. Namely, the humidity control data in 40s is collected, and the collection of the humidity control data is carried out in the 40s, so that the detection period of the humidity detection device is prevented from being too long, and the energy is saved. The fixed cooking time corresponds to one working cycle of the single steam generating device, and the working cycle of the steam generating device comprises the water injection working time, the heating working time and the dry burning working time of the steam generating device.
When the cooking equipment cooks the food, the step of acquiring the real-time humidity control operation data S4 specifically comprises the following steps: detecting whether the temperature of an inner cavity of the cooking equipment reaches a constant value or not in real time; if the temperature of the inner cavity of the cooking equipment does not reach the constant temperature, continuously detecting that the temperature of the inner cavity of the cooking equipment reaches the constant temperature; and if the temperature of the inner cavity of the cooking equipment reaches a constant value, acquiring real-time humidity control operation data within a fixed cooking time.
The step of obtaining real-time humidity control operation data within a fixed cooking time period further comprises the following steps: judging whether the real-time humidity control operation data within the fixed cooking time length has an abnormal value or not; if the real-time humidity control operation data within the fixed cooking time length has no abnormal value, comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model; and if the real-time humidity control operation data in the fixed cooking time length has an abnormal value, re-acquiring the real-time humidity control operation data in the fixed cooking time length. If 10 pieces of real-time humidity control operation data are acquired, and one or two pieces of real-time humidity control operation data are detected to have larger difference with other data, judging that the real-time humidity control operation data have abnormal values; however, if 10 pieces of real-time humidity control operation data are acquired, it is detected that the difference between three pieces of real-time humidity control operation data and other data is large, and the three pieces of real-time humidity control operation data are not determined as abnormal values, that is, in the present embodiment, the number of the abnormal values cannot exceed 20 percent of the number of the real-time humidity control operation data, and the abnormal values can be adjusted according to the needs of the actual application environment. If the number of the abnormal values exceeds 20 percent of the number of the real-time humidity control operation data, the abnormal values are not used as the abnormal values for judgment, then the average value of the real-time humidity control operation data is compared with the average value of the humidity control data of the current humidity control prediction model, and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control data of the current humidity control prediction model is larger than a preset difference value, a humidity control abnormal error reporting program is started.
Preferably, if the real-time humidity control operation data within the fixed cooking time period has an abnormal value, the real-time humidity control operation data within the fixed cooking time period is corrected, and the real-time humidity control operation data within the fixed cooking time period is obtained again after the correction. During the use process of the cooking equipment, detection errors may happen to the humidity detection device or other parts of the cooking equipment, or the fan encounters the influence of external impurities and obstacles, so that the rotating speed of the fan is unstable; or the working efficiency of the evaporator is unstable due to the influence of foreign matters. Errors of other parts of the humidity detection device or the cooking equipment are transient, a large amount of manpower and material resources do not need to be consumed to repair or pause the cooking of food, accidental errors have small influence on the cooking of the food and can be ignored, and real-time humidity control operation data in a fixed cooking time length can be obtained again after the food is recovered to be normal. The working state of the fan or the evaporator is unstable due to the influence of external substances, correction is needed, namely, simple barrier removal is carried out manually, and real-time humidity control operation data within a fixed cooking time length are obtained again after correction. The normal operation of the cooking equipment can be recovered only by simply correcting the conditions such as unstable working state caused by the influence of foreign objects on the parts of the cooking equipment, such as clearing obstacles, and the equipment does not need to be restarted to adjust cooking parameters so as to cook food again. The judgment of the abnormal value effectively avoids the humidity detection device from entering a humidity abnormal error reporting program due to accidental detection errors, and effectively saves resources. However, if the number of the abnormal values exceeds the preset ratio, the abnormal values are not judged as the abnormal values, and the next step is needed to enter the humidity control abnormal error reporting program.
The step of comparing the average value of the real-time humidity control operation data with the average value of the humidity control prediction model humidity control data is specifically as follows: if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is smaller than the preset difference value, maintaining the current control parameter to continue cooking until the cooking is finished; and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference value, entering a humidity control abnormity error reporting program. The preset difference is 5% -15%. In this embodiment, the preset difference is 10%.
The method for calculating the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control data of the current humidity control prediction model specifically comprises the following steps: if the average value of the real-time humidity control operation data is larger than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the real-time humidity control operation data-the average value of the humidity control data of the current humidity control prediction model; and if the average value of the real-time humidity control operation data is smaller than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the humidity control data of the current humidity control prediction model-the average value of the real-time humidity control operation data.
If the average value of the real-time humidity control operation data is 70%, the average value of the current humidity control prediction model humidity control data is 75%, and the average value of the current humidity control prediction model humidity control data is larger than the average value of the real-time humidity control operation data, the difference is the average value of the current humidity control prediction model humidity control data-the average value of the real-time humidity control operation data, namely the difference is 75% -70% -5%, and 5% is smaller than the preset difference of 10%, the current control parameter is maintained to continue cooking until cooking is finished.
If the average value of the real-time humidity control operation data is 80%, the average value of the humidity control data of the current humidity control prediction model is 65%, and the average value of the real-time humidity control operation data is larger than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the real-time humidity control operation data-the average value of the humidity control data of the current humidity control prediction model, namely the difference value is 80% -65%, namely 15%, and 15% is larger than the preset difference value of 10%, then entering a humidity control abnormity error reporting program.
The cooking device mentioned in the embodiment includes, but is not limited to, a steam oven, an electric oven, an oven, and a steam box.
The above preferred embodiments should be considered as examples of the embodiments of the present application, and technical deductions, substitutions, improvements and the like similar to, similar to or based on the embodiments of the present application should be considered as the protection scope of the present patent.
Claims (9)
1. A method for detecting humidity control abnormality of a cooking apparatus, comprising the steps of:
detecting the food cooked this time;
forming a last-time humidity control cooking model by utilizing humidity control data of the same food cooked by the cooking equipment last time;
predicting the current food cooking humidity data according to the current environment temperature and humidity parameters by using the previous humidity control cooking model to form a current humidity control prediction model;
when the cooking equipment cooks the food, acquiring real-time humidity control operation data;
comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model;
and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference value, entering a humidity control abnormity error reporting program.
2. The method for detecting abnormality in humidity control of a cooking appliance according to claim 1, wherein the step of forming a previous humidity control cooking model using humidity control data of the same food as the previous cooking appliance is specifically as follows:
judging whether the cooking equipment fails in the cooking period of cooking the same food last time;
if the cooking device does not have a fault during the cooking period of the same food cooked last time, detecting whether the temperature of an inner cavity of the cooking device reaches a constant value during the cooking period of the same food cooked last time by the cooking device;
if the temperature of the inner cavity of the cooking equipment reaches constant during the cooking period when the cooking equipment cooks the same food last time, collecting humidity control data of the same food cooked last time by the cooking equipment within a fixed cooking time;
and fitting humidity control data of the same food cooked by the cooking equipment at the last time within the fixed cooking time length to form a last-time humidity control cooking model.
3. The method for detecting humidity control abnormality of cooking equipment according to claim 1, wherein the step of acquiring real-time humidity control operation data when the cooking equipment cooks the food is specifically as follows:
detecting whether the temperature of an inner cavity of the cooking equipment reaches a constant value or not in real time;
and if the temperature of the inner cavity of the cooking equipment reaches a constant value, acquiring real-time humidity control operation data within a fixed cooking time.
4. The method for detecting humidity control abnormality of cooking equipment according to claim 3, wherein the step of obtaining real-time humidity control operation data within a fixed cooking time period further comprises the steps of:
judging whether the real-time humidity control operation data within the fixed cooking time length has an abnormal value or not;
and if the real-time humidity control operation data in the fixed cooking time length has no abnormal value, comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model.
5. The method for detecting abnormality in humidity control of cooking equipment according to claim 4, wherein the step of determining whether the real-time humidity control operation data within the fixed cooking time period has an abnormal value is specifically:
if the real-time humidity control operation data in the fixed cooking time length has an abnormal value, the real-time humidity control operation data in the fixed cooking time length is obtained again;
and if the real-time humidity control operation data in the fixed cooking time length has no abnormal value, comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model.
6. The method of claim 3, 4 or 5, wherein the fixed cooking time period is less than 60 s.
7. The method for detecting humidity control abnormality of cooking equipment according to claim 1, wherein the step of comparing the average value of the real-time humidity control operation data with the average value of the humidity control data of the current humidity control prediction model specifically comprises:
if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is smaller than the preset difference value, maintaining the current control parameter to continue cooking until the cooking is finished;
and if the difference value between the average value of the real-time humidity control operation data and the average value of the humidity control prediction model humidity control data is larger than the preset difference value, entering a humidity control abnormity error reporting program.
8. The method for detecting abnormality in humidity control of cooking equipment according to claim 1, wherein the method for calculating the difference between the average value of the real-time humidity control operation data and the average value of the humidity control data of the current humidity control prediction model specifically comprises:
if the average value of the real-time humidity control operation data is larger than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the real-time humidity control operation data-the average value of the humidity control data of the current humidity control prediction model;
and if the average value of the real-time humidity control operation data is smaller than the average value of the humidity control data of the current humidity control prediction model, the difference value is the average value of the humidity control data of the current humidity control prediction model-the average value of the real-time humidity control operation data.
9. The method for detecting humidity control abnormality of cooking equipment according to claim 1 or 7, wherein the preset difference is 5% -15%.
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