CN116796208A - Electric kettle overheat protection method and device based on historical data - Google Patents
Electric kettle overheat protection method and device based on historical data Download PDFInfo
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Abstract
The invention discloses an electric kettle overheat protection method and device based on historical data, wherein the method comprises the following steps: acquiring working parameter data and overheat record data of a target electric kettle in a historical time period; determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the working parameter data and the overheating record data; acquiring real-time working data of the target electric kettle, and judging whether the target electric kettle is about to overheat according to the combination of the plurality of overheating rules and the real-time working data; if yes, starting overheat protection operation on the target electric kettle. Therefore, the invention can predict and judge whether the electric kettle is about to overheat by combining the historical working parameters and overheat records of the electric kettle through a rule analysis algorithm, thereby realizing more intelligent overheat protection of the electric kettle, improving the timeliness and the effect of overheat protection and reducing the probability of accidents.
Description
Technical Field
The invention relates to the technical field of intelligent home, in particular to an electric kettle overheat protection method and device based on historical data.
Background
With the maturity of smart home technology, more and more home devices begin to adopt more intelligent control schemes, wherein, some intelligent control technologies are also introduced into electric kettle devices to improve the intelligent degree, for example, the electric kettle can realize remote start and pause or realize sending and displaying of some information.
However, when the prior art is faced with the overheat protection problem of the electric kettle, the overheat protection is often realized by adopting a circuit scheme, and the overheat protection of the circuit scheme is not considered, so that the power supply can be cut off mechanically only when the electric kettle is overloaded, and the overheat time can not be judged in time in advance, so that the overheat protection effect is poor and the intelligent degree is not high. It can be seen that the prior art has defects and needs to be solved.
Disclosure of Invention
The invention aims to solve the technical problem of providing an electric kettle overheat protection method and device based on historical data, which can realize more intelligent overheat protection of the electric kettle, improve timeliness and effect of overheat protection and reduce probability of accidents.
In order to solve the technical problems, the first aspect of the invention discloses an electric kettle overheat protection method based on historical data, which comprises the following steps:
Acquiring working parameter data and overheat record data of a target electric kettle in a historical time period;
determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the working parameter data and the overheating record data;
acquiring real-time working data of the target electric kettle, and judging whether the target electric kettle is about to overheat according to the combination of the plurality of overheating rules and the real-time working data;
if yes, starting overheat protection operation on the target electric kettle.
As an optional implementation manner, in the first aspect of the present invention, the determining, based on a rule analysis algorithm, a plurality of overheating rule combinations of the target electric kettle according to the operating parameter data and the overheating record data includes:
based on a clustering grouping algorithm, the working parameter data are grouped for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes;
and determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time.
As an optional implementation manner, in the first aspect of the present invention, the operation parameter data includes operation data of a plurality of different historical time points with a plurality of different data types; the clustering grouping algorithm is based on, the working parameter data are grouped for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes, and the clustering algorithm comprises the following steps:
Grouping all the working data based on the data types to obtain a plurality of first data groups; all the working data in each first data group belong to the same data type;
grouping all the working data based on a preset data sequence association rule to obtain a plurality of second data groups; the historical time points corresponding to any two of the second data sets are strong association relations defined by the data sequential association rules between the working data of adjacent time points;
based on the data change rate parameters of each working data at the specific historical time point and based on a parameter similarity screening algorithm, grouping all the working data to obtain a plurality of third data sets; the parameter similarity between the data change rate parameters of any two working data in each third data set is smaller than a preset similarity threshold.
As an optional implementation manner, in the first aspect of the present invention, the overheating rule combination includes a data value, a data interval or a data relation of at least one data type; the determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time comprises the following steps:
Acquiring an overheat time point corresponding to each overheat record data;
determining working data in a plurality of data groups corresponding to each overheating time point in any grouping mode to obtain a plurality of data sets;
and determining a data value, a data interval or a data relation corresponding to each data set to obtain a plurality of overheating rule combinations of the target electric kettle.
In an optional implementation manner, in a first aspect of the present invention, the determining working data in a plurality of data groups corresponding to each overheating time point in any grouping manner, to obtain a plurality of data sets includes:
determining working data in all the first data sets corresponding to each overheating time point to obtain a plurality of first overheating data sets;
determining working data in all the second data sets corresponding to each overheating time point and front and back adjacent time points to obtain a plurality of second overheating data sets;
and determining the data change rate of the working data in all the third data sets corresponding to each overheating time point to obtain a plurality of third overheating data sets.
In an optional implementation manner, in a first aspect of the present invention, the determining a data value, a data interval, or a data relation corresponding to each data set, to obtain a plurality of overheating rule combinations of the target electric kettle includes:
Fitting to obtain polynomial data relation models corresponding to all data in each first overheat data set through a fitting algorithm to obtain a plurality of first type overheat rule combinations of the target electric kettle;
fitting to obtain binomial data relationship models corresponding to adjacent data at all time points in each second overheat data set through a fitting algorithm, and obtaining a plurality of second type overheat rule combinations of the target electric kettle;
and fitting to obtain data types and polynomial data relational models corresponding to all the data change rates in each third overheat data set through a fitting algorithm, and obtaining a plurality of third type overheat rule combinations of the target electric kettles.
As an optional implementation manner, in the first aspect of the present invention, the operation parameter data or the real-time operation data includes at least two of ambient temperature sensing data, ambient humidity sensing data, current continuous operation time data and heating power data; and/or the number of the groups of groups,
judging whether the target electric kettle is about to overheat according to the plurality of overheat rule combinations and the real-time working data, wherein the method comprises the following steps:
Judging whether the real-time working data accords with the overheat rule combination or not;
if the real-time working data is judged to be not in accordance with any overheating rule combination, judging that the target electric kettle is not about to overheat;
if the real-time working data accords with any one of the overheating rule combinations, screening all the overheating rule combinations which accord with the overheating rule combinations;
judging whether all the conforming overheating rule combinations comprise at least two types of overheating rule combinations, if so, judging that the target electric kettle is about to overheat, and if not, judging that the target electric kettle is not about to overheat;
and/or the number of the groups of groups,
the starting overheat protection operation for the target electric kettle comprises the following steps:
sending a breaking command of a heating line to the target electric kettle; and/or the number of the groups of groups,
and sending a power reduction command to the target electric kettle.
The invention discloses an electric kettle overheat protection device based on historical data, which comprises:
the acquisition module is used for acquiring working parameter data and overheat record data of the target electric kettle in a historical time period;
the determining module is used for determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the working parameter data and the overheating record data;
The judging module is used for acquiring real-time working data of the target electric kettle and judging whether the target electric kettle is about to overheat according to the combination of the plurality of overheating rules and the real-time working data;
and the operation module is used for starting overheat protection operation on the target electric kettle when the judging result of the judging module is yes.
As an optional implementation manner, in the second aspect of the present invention, the determining module determines, based on a rule analysis algorithm, a specific manner of combining a plurality of overheating rules of the target electric kettle according to the operating parameter data and the overheating record data, where the specific manner includes:
based on a clustering grouping algorithm, the working parameter data are grouped for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes;
and determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time.
As an alternative embodiment, in the second aspect of the present invention, the operating parameter data includes operating data at a plurality of different historical time points with a plurality of different data types; the determining module groups the working parameter data for a plurality of times based on a clustering grouping algorithm to obtain a plurality of data groups in different grouping modes corresponding to the working parameter data, and the determining module comprises the following specific modes:
Grouping all the working data based on the data types to obtain a plurality of first data groups; all the working data in each first data group belong to the same data type;
grouping all the working data based on a preset data sequence association rule to obtain a plurality of second data groups; the historical time points corresponding to any two of the second data sets are strong association relations defined by the data sequential association rules between the working data of adjacent time points;
based on the data change rate parameters of each working data at the specific historical time point and based on a parameter similarity screening algorithm, grouping all the working data to obtain a plurality of third data sets; the parameter similarity between the data change rate parameters of any two working data in each third data set is smaller than a preset similarity threshold.
In a second aspect of the present invention, as an alternative implementation manner, the overheating rule combination includes a data value, a data interval or a data relation of at least one data type; the determining module determines a specific mode of combining a plurality of overheating rules of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time, and the specific mode comprises the following steps:
Acquiring an overheat time point corresponding to each overheat record data;
determining working data in a plurality of data groups corresponding to each overheating time point in any grouping mode to obtain a plurality of data sets;
and determining a data value, a data interval or a data relation corresponding to each data set to obtain a plurality of overheating rule combinations of the target electric kettle.
In a second aspect of the present invention, the determining module determines working data in a plurality of data groups corresponding to each overheating time point in any grouping manner, to obtain a specific manner of a plurality of data sets, where the specific manner includes:
determining working data in all the first data sets corresponding to each overheating time point to obtain a plurality of first overheating data sets;
determining working data in all the second data sets corresponding to each overheating time point and front and back adjacent time points to obtain a plurality of second overheating data sets;
and determining the data change rate of the working data in all the third data sets corresponding to each overheating time point to obtain a plurality of third overheating data sets.
In a second aspect of the present invention, the determining module determines a data value, a data interval or a data relation corresponding to each data set, to obtain a specific manner of combining multiple overheating rules of the target electric kettle, where the specific manner includes:
fitting to obtain polynomial data relation models corresponding to all data in each first overheat data set through a fitting algorithm to obtain a plurality of first type overheat rule combinations of the target electric kettle;
fitting to obtain binomial data relationship models corresponding to adjacent data at all time points in each second overheat data set through a fitting algorithm, and obtaining a plurality of second type overheat rule combinations of the target electric kettle;
and fitting to obtain data types and polynomial data relational models corresponding to all the data change rates in each third overheat data set through a fitting algorithm, and obtaining a plurality of third type overheat rule combinations of the target electric kettles.
As an alternative embodiment, in the second aspect of the present invention, the operation parameter data or the real-time operation data includes at least two of ambient temperature sensing data, ambient humidity sensing data, current continued operation time data, and heating power data; and/or the number of the groups of groups,
The judging module judges whether the target electric kettle is about to overheat or not according to the plurality of overheat rule combinations and the real-time working data, and comprises the following steps:
judging whether the real-time working data accords with the overheat rule combination or not;
if the real-time working data is judged to be not in accordance with any overheating rule combination, judging that the target electric kettle is not about to overheat;
if the real-time working data accords with any one of the overheating rule combinations, screening all the overheating rule combinations which accord with the overheating rule combinations;
judging whether all the conforming overheating rule combinations comprise at least two types of overheating rule combinations, if so, judging that the target electric kettle is about to overheat, and if not, judging that the target electric kettle is not about to overheat;
and/or the number of the groups of groups,
the specific mode of starting overheat protection operation of the target electric kettle by the operation module comprises the following steps:
sending a breaking command of a heating line to the target electric kettle; and/or the number of the groups of groups,
and sending a power reduction command to the target electric kettle.
The third aspect of the invention discloses another electric kettle overheat protection device based on historical data, which comprises:
A memory storing executable program code;
a processor coupled to the memory;
the processor calls the executable program codes stored in the memory to execute part or all of the steps in the electric kettle overheat protection method based on the historical data disclosed in the first aspect of the invention.
A fourth aspect of the present invention discloses a computer storage medium storing computer instructions for executing part or all of the steps of the method for protecting an electric kettle against overheating based on historical data disclosed in the first aspect of the present invention when the computer instructions are called.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, whether the electric kettle is about to overheat can be predicted and judged through a rule analysis algorithm by combining the historical working parameters and overheat records of the electric kettle, so that the electric kettle can be more intelligently overheat-protected, the timeliness and the effect of overheat protection are improved, and the probability of accidents is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an electric kettle overheat protection method based on historical data, which is disclosed in the embodiment of the invention;
fig. 2 is a schematic structural diagram of an overheat protection device for an electric kettle based on historical data according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another electric kettle overheat protection device based on historical data according to the embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses an electric kettle overheat protection method and device based on historical data, which can predict and judge whether the electric kettle is about to overheat by combining historical working parameters and overheat records of the electric kettle through a rule analysis algorithm, so that the electric kettle can be more intelligently overheat-protected, the timeliness and the effect of overheat protection are improved, and the probability of accidents is reduced. The following will describe in detail.
Referring to fig. 1, fig. 1 is a schematic flow chart of an overheat protection method for an electric kettle based on historical data according to an embodiment of the present invention. The method described in fig. 1 may be applied to a corresponding data processing device, a data processing terminal, and a data processing server, where the server may be a local server or a cloud server, and the embodiment of the present invention is not limited to the method shown in fig. 1, and the method for protecting overheat of an electric kettle based on historical data may include the following operations:
101. And acquiring working parameter data and overheat record data of the target electric kettle in a historical time period.
Optionally, the operating parameter data includes operating data at a plurality of different historical points in time having a plurality of different data types. Optionally, the operating parameter data includes at least two of ambient temperature sensing data, ambient humidity sensing data, current sustained operating time data, and heating power data.
Alternatively, the overheat record data may comprise overheat records of the target electric kettle at historical time periods or historical time points, which may comprise line overheat automatic record data, user report data or record data detected by a specific sensor.
102. And determining a plurality of overheating rule combinations of the target electric kettle based on the rule analysis algorithm according to the working parameter data and the overheating record data.
103. And acquiring real-time working data of the target electric kettle, and judging whether the target electric kettle is about to overheat according to the combination of a plurality of overheating rules and the real-time working data.
Optionally, the real-time operation data includes at least two of ambient temperature sensing data, ambient humidity sensing data, current sustained operation time data, and heating power data.
104. If yes, starting overheat protection operation on the target electric kettle.
Therefore, the method described by implementing the embodiment of the invention can be used for predicting and judging whether the electric kettle is about to overheat by combining the historical working parameters and overheat records of the electric kettle through a rule analysis algorithm, so that the electric kettle can be more intelligently overheat-protected, the timeliness and the effect of overheat protection are improved, and the probability of accidents is reduced.
As an alternative embodiment, in the step, according to the working parameter data and the overheat record data, a plurality of overheat rule combinations of the target electric kettle are determined based on a rule analysis algorithm, including:
based on a clustering grouping algorithm, grouping the working parameter data for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes;
and determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time.
Through the embodiment, the working parameter data can be grouped for multiple times to obtain multiple data groups in different grouping modes, and then the combination of overheat rules is analyzed according to the corresponding relation of overheat record data, so that the characteristic that the rule combination obtained by analysis can better and more accurately represent the working data of the electric kettle when the electric kettle is overheated can be ensured, the electric kettle can be more intelligently overheat protected, and the timeliness and the effect of overheat protection are improved.
As an optional embodiment, in the step, based on a clustering grouping algorithm, the working parameter data is grouped multiple times to obtain multiple data groups corresponding to the working parameter data in different grouping modes, where the method includes:
grouping all working data based on the data type to obtain a plurality of first data groups; all working data in each first data group belong to the same data type;
grouping all working data based on a preset data sequence association rule to obtain a plurality of second data groups; the historical time points corresponding to any two of the second data sets are strong association relations defined by data sequential association rules between the working data of adjacent time points;
based on the data change rate parameters at specific historical time points corresponding to each working data, grouping all the working data based on a parameter similarity screening algorithm to obtain a plurality of third data sets; the parameter similarity between the data change rate parameters of any two working data in each third data set is smaller than a preset similarity threshold.
Alternatively, the data-sequence association rule may be set by the operator empirically or experimentally in advance, and is used to characterize the association relationship between the data value changes of different parameter data at the previous and subsequent time points, for example, the increase in heating power and the increase in temperature are necessarily strongly correlated, or the increase in the usage period and the decrease in heating power (due to the loss of the component) are necessarily strongly correlated.
Alternatively, the parameter similarity may be a vector distance, such as an L1 distance or an L2 distance, or may be a difference value or a ratio of the difference value to the total value, and other measurement manners that may be used to represent the proximity between the parameters are considered to be included in the scope of the present invention.
Through the embodiment, the working parameter data can be grouped for multiple times based on the data type, the data sequential association rule and the data change rate parameter corresponding to each working data, so that multiple data sets in different grouping modes can be obtained, the characteristic that the rule combination obtained by subsequent analysis can better and more accurately represent the working data of the electric kettle when the electric kettle is overheated can be ensured, the electric kettle can be more intelligently overheated protected, and the timeliness and the effect of the overheat protection are improved.
As an alternative embodiment, the overheat rule combination may include a data value, a data interval or a data relation of at least one data type, and specifically, in the above step, according to a corresponding relationship between overheat record data and a data set in time, determining, based on a rule analysis algorithm, a plurality of overheat rule combinations of the target electric kettle includes:
Acquiring an overheat time point corresponding to each overheat record data;
determining working data in a plurality of data groups corresponding to each overheat time point in any grouping mode to obtain a plurality of data sets;
and determining a data value, a data interval or a data relation corresponding to each data set to obtain a plurality of overheating rule combinations of the target electric kettle.
Through the embodiment, a plurality of overheating rule combinations of the target electric kettle can be obtained through analysis according to the data values, the data intervals or the data relation formulas of the corresponding data sets in the plurality of data sets in different grouping modes, so that the characteristics of working data of the electric kettle when the electric kettle is overheated can be better and more accurately represented by the rule combinations obtained through subsequent analysis, the electric kettle can be more intelligently subjected to overheating protection, and the timeliness and the effect of the overheating protection are improved.
As an optional embodiment, in the step, determining working data in a plurality of data groups corresponding to each overheating time point in any grouping manner, to obtain a plurality of data sets includes:
determining working data in all the first data sets corresponding to each overheating time point to obtain a plurality of first overheating data sets;
Determining working data in all second data sets corresponding to each overheating time point and front and back adjacent time points to obtain a plurality of second overheating data sets;
and determining the data change rate of the working data in all the third data sets corresponding to each overheating time point, and obtaining a plurality of third overheating data sets.
Through the embodiment, the mode of obtaining the data set can be determined according to different grouping modes, so that the obtained data set is more reasonable, the characteristic that the rule combination obtained by subsequent analysis can more reasonably and accurately represent the working data of the electric kettle when the electric kettle is overheated can be guaranteed, the electric kettle can be more intelligently overheat protected, and the timeliness and the effect of overheat protection are improved.
As an optional embodiment, in the step, determining a data value, a data interval or a data relation corresponding to each data set to obtain a plurality of overheating rule combinations of the target electric kettle includes:
fitting to obtain polynomial data relational models corresponding to all data in each first overheat data set through a fitting algorithm to obtain a plurality of first type overheat rule combinations of the target electric kettle;
Fitting to obtain binomial data relationship models corresponding to adjacent data at all time points in each second overheat data set through a fitting algorithm, so as to obtain a plurality of second type overheat rule combinations of the target electric kettle;
and fitting to obtain data types and polynomial data relational models corresponding to all data change rates in each third overheat data set through a fitting algorithm, and obtaining a plurality of third type overheat rule combinations of the target electric kettle.
Alternatively, the above fitting algorithm may implement the fitting of the model by a dynamic programming algorithm or other relational fitting algorithm, so as to perform fitting calculation on the data to obtain a corresponding relational model, and the operation may be implemented by some existing data analysis software or programming language.
Through the embodiment, the data set obtained by determining according to different grouping modes can be realized, and the calculation mode of fitting to obtain the rule combination is determined, so that the obtained overheat rule combination is more reasonable, the characteristic of working data when the electric kettle is overheated can be represented more reasonably and accurately by the rule combination obtained by analysis, the overheat protection of the electric kettle is realized more intelligently, and the timeliness and the effect of the overheat protection are improved.
As an optional embodiment, in the step, according to the combination of the plurality of overheating rules and the real-time working data, determining whether the target electric kettle is about to overheat includes:
judging whether the real-time working data accords with the overheat rule combination or not;
if the real-time working data is judged to be not in accordance with any overheat rule combination, judging that the target electric kettle is not about to overheat;
if the real-time working data accords with any overheating rule combination, screening out all the overheating rule combinations which accord with the overheating rule combinations;
judging whether all the conforming overheat rule combinations comprise at least two types of overheat rule combinations, if yes, judging that the target electric kettle is about to overheat, and if not, judging that the target electric kettle is not about to overheat.
Through the embodiment, the situation that the single type of overheat rule combination possibly has overfitting or error can be detected according to the specific test process, so that under the condition that the data volume is large enough, the situation that the working data of the electric kettle is about to overheat is judged when the working data accords with the combination of at least two types of overheat rules is ensured, so that the electric kettle is more intelligently overheat-protected, the timeliness and the effect of overheat protection are improved, and the error is reduced.
As an alternative embodiment, in the above steps, starting the overheat protection operation on the target electric kettle includes:
sending a breaking command of the heating circuit to a target electric kettle; and/or the number of the groups of groups,
sending a power down command to the target electric kettle.
Alternatively, the selection of different operations may be determined based on the number or the ratio of all the combinations of the compliance with the overheating laws screened in the previous embodiment, which may be determined empirically or experimentally by an operator, for example, when the number or the ratio of all the combinations of the compliance with the overheating laws exceeds a certain level, the operation of sending the open command of the heating line to the target electric kettle may be considered to achieve more aggressive overheating protection, or else the operation of sending the power reduction command to the target electric kettle may be considered to achieve more gentle overheating protection.
Through the embodiment, the overheat protection operation can be started on the target electric kettle, so that the electric kettle is more intelligently overheat protected, the timeliness and the effect of overheat protection are improved, and errors are reduced.
Referring to fig. 2, fig. 2 is a schematic structural diagram of an overheat protection device for an electric kettle based on historical data according to an embodiment of the present invention. The apparatus described in fig. 2 may be applied to a corresponding data processing device, a data processing terminal, and a data processing server, where the server may be a local server or a cloud server, and embodiments of the present invention are not limited. As shown in fig. 2, the apparatus may include:
The acquisition module 201 is configured to acquire operating parameter data and overheat record data of the target electric kettle in a historical period.
Optionally, the operating parameter data includes operating data at a plurality of different historical points in time having a plurality of different data types. Optionally, the operating parameter data includes at least two of ambient temperature sensing data, ambient humidity sensing data, current sustained operating time data, and heating power data.
Alternatively, the overheat record data may comprise overheat records of the target electric kettle at historical time periods or historical time points, which may comprise line overheat automatic record data, user report data or record data detected by a specific sensor.
The determining module 202 is configured to determine a plurality of overheating rule combinations of the target electric kettle based on the rule analysis algorithm according to the working parameter data and the overheating record data.
And the judging module 203 is configured to obtain real-time working data of the target electric kettle, and judge whether the target electric kettle is about to overheat according to the combination of the plurality of overheating rules and the real-time working data.
Optionally, the real-time operation data includes at least two of ambient temperature sensing data, ambient humidity sensing data, current sustained operation time data, and heating power data.
And an operation module 204, configured to start overheat protection operation for the target electric kettle when the determination result of the determination module 203 is yes.
Therefore, the device described by implementing the embodiment of the invention can predict and judge whether the electric kettle is about to overheat by combining the historical working parameters and overheat records of the electric kettle through a rule analysis algorithm, so that the electric kettle can be more intelligently overheat-protected, the timeliness and the effect of overheat protection are improved, and the probability of accidents is reduced.
As an alternative embodiment, the determining module 202 determines, based on the rule analysis algorithm, a specific manner of combining a plurality of overheating rules of the target electric kettle according to the operating parameter data and the overheating record data, including:
based on a clustering grouping algorithm, grouping the working parameter data for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes;
and determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time.
Through the embodiment, the working parameter data can be grouped for multiple times to obtain multiple data groups in different grouping modes, and then the combination of overheat rules is analyzed according to the corresponding relation of overheat record data, so that the characteristic that the rule combination obtained by analysis can better and more accurately represent the working data of the electric kettle when the electric kettle is overheated can be ensured, the electric kettle can be more intelligently overheat protected, and the timeliness and the effect of overheat protection are improved.
As an optional embodiment, the determining module 202 groups the working parameter data multiple times based on a clustering grouping algorithm to obtain specific modes of multiple data sets in different grouping modes corresponding to the working parameter data, where the specific modes include:
grouping all working data based on the data type to obtain a plurality of first data groups; all working data in each first data group belong to the same data type;
grouping all working data based on a preset data sequence association rule to obtain a plurality of second data groups; the historical time points corresponding to any two of the second data sets are strong association relations defined by data sequential association rules between the working data of adjacent time points;
based on the data change rate parameters at specific historical time points corresponding to each working data, grouping all the working data based on a parameter similarity screening algorithm to obtain a plurality of third data sets; the parameter similarity between the data change rate parameters of any two working data in each third data set is smaller than a preset similarity threshold.
Alternatively, the data-sequence association rule may be set by the operator empirically or experimentally in advance, and is used to characterize the association relationship between the data value changes of different parameter data at the previous and subsequent time points, for example, the increase in heating power and the increase in temperature are necessarily strongly correlated, or the increase in the usage period and the decrease in heating power (due to the loss of the component) are necessarily strongly correlated.
Alternatively, the parameter similarity may be a vector distance, such as an L1 distance or an L2 distance, or may be a difference value or a ratio of the difference value to the total value, and other measurement manners that may be used to represent the proximity between the parameters are considered to be included in the scope of the present invention.
Through the embodiment, the working parameter data can be grouped for multiple times based on the data type, the data sequential association rule and the data change rate parameter corresponding to each working data, so that multiple data sets in different grouping modes can be obtained, the characteristic that the rule combination obtained by subsequent analysis can better and more accurately represent the working data of the electric kettle when the electric kettle is overheated can be ensured, the electric kettle can be more intelligently overheated protected, and the timeliness and the effect of the overheat protection are improved.
As an alternative embodiment, the overheating rule combination includes a data value, a data interval or a data relation of at least one data type, specifically, the determining module 202 determines, based on a rule analysis algorithm, a specific manner of combining a plurality of overheating rules of the target electric kettle according to a corresponding relationship between the overheating record data and the data set in time, including:
Acquiring an overheat time point corresponding to each overheat record data;
determining working data in a plurality of data groups corresponding to each overheat time point in any grouping mode to obtain a plurality of data sets;
and determining a data value, a data interval or a data relation corresponding to each data set to obtain a plurality of overheating rule combinations of the target electric kettle.
Through the embodiment, a plurality of overheating rule combinations of the target electric kettle can be obtained through analysis according to the data values, the data intervals or the data relation formulas of the corresponding data sets in the plurality of data sets in different grouping modes, so that the characteristics of working data of the electric kettle when the electric kettle is overheated can be better and more accurately represented by the rule combinations obtained through subsequent analysis, the electric kettle can be more intelligently subjected to overheating protection, and the timeliness and the effect of the overheating protection are improved.
As an optional embodiment, the determining module 202 determines working data in a plurality of data groups corresponding to each overheating time point in any grouping manner, to obtain a specific manner of a plurality of data sets, which includes:
determining working data in all the first data sets corresponding to each overheating time point to obtain a plurality of first overheating data sets;
Determining working data in all second data sets corresponding to each overheating time point and front and back adjacent time points to obtain a plurality of second overheating data sets;
and determining the data change rate of the working data in all the third data sets corresponding to each overheating time point, and obtaining a plurality of third overheating data sets.
Through the embodiment, the mode of obtaining the data set can be determined according to different grouping modes, so that the obtained data set is more reasonable, the characteristic that the rule combination obtained by subsequent analysis can more reasonably and accurately represent the working data of the electric kettle when the electric kettle is overheated can be guaranteed, the electric kettle can be more intelligently overheat protected, and the timeliness and the effect of overheat protection are improved.
As an optional embodiment, the determining module 202 determines a data value, a data interval or a data relation corresponding to each data set, to obtain a specific manner of combining multiple overheating rules of the target electric kettle, including:
fitting to obtain polynomial data relational models corresponding to all data in each first overheat data set through a fitting algorithm to obtain a plurality of first type overheat rule combinations of the target electric kettle;
Fitting to obtain binomial data relationship models corresponding to adjacent data at all time points in each second overheat data set through a fitting algorithm, so as to obtain a plurality of second type overheat rule combinations of the target electric kettle;
and fitting to obtain data types and polynomial data relational models corresponding to all data change rates in each third overheat data set through a fitting algorithm, and obtaining a plurality of third type overheat rule combinations of the target electric kettle.
Alternatively, the above fitting algorithm may implement the fitting of the model by a dynamic programming algorithm or other relational fitting algorithm, so as to perform fitting calculation on the data to obtain a corresponding relational model, and the operation may be implemented by some existing data analysis software or programming language.
Through the embodiment, the data set obtained by determining according to different grouping modes can be realized, and the calculation mode of fitting to obtain the rule combination is determined, so that the obtained overheat rule combination is more reasonable, the characteristic of working data when the electric kettle is overheated can be represented more reasonably and accurately by the rule combination obtained by analysis, the overheat protection of the electric kettle is realized more intelligently, and the timeliness and the effect of the overheat protection are improved.
As an alternative embodiment, the determining module 203 determines, according to a combination of a plurality of overheating rules and real-time working data, a specific manner of determining whether the target electric kettle is about to overheat, including:
judging whether the real-time working data accords with the overheat rule combination or not;
if the real-time working data is judged to be not in accordance with any overheat rule combination, judging that the target electric kettle is not about to overheat;
if the real-time working data accords with any overheating rule combination, screening out all the overheating rule combinations which accord with the overheating rule combinations;
judging whether all the conforming overheat rule combinations comprise at least two types of overheat rule combinations, if yes, judging that the target electric kettle is about to overheat, and if not, judging that the target electric kettle is not about to overheat.
Through the embodiment, the situation that the single type of overheat rule combination possibly has overfitting or error can be detected according to the specific test process, so that under the condition that the data volume is large enough, the situation that the working data of the electric kettle is about to overheat is judged when the working data accords with the combination of at least two types of overheat rules is ensured, so that the electric kettle is more intelligently overheat-protected, the timeliness and the effect of overheat protection are improved, and the error is reduced.
As an alternative embodiment, the specific manner in which the operation module 204 initiates the overheat protection operation for the target electric kettle includes:
sending a breaking command of the heating circuit to a target electric kettle; and/or the number of the groups of groups,
sending a power down command to the target electric kettle.
Alternatively, the selection of different operations may be determined based on the number or the ratio of all the combinations of the compliance with the overheating laws screened in the previous embodiment, which may be determined empirically or experimentally by an operator, for example, when the number or the ratio of all the combinations of the compliance with the overheating laws exceeds a certain level, the operation of sending the open command of the heating line to the target electric kettle may be considered to achieve more aggressive overheating protection, or else the operation of sending the power reduction command to the target electric kettle may be considered to achieve more gentle overheating protection.
Through the embodiment, the overheat protection operation can be started on the target electric kettle, so that the electric kettle is more intelligently overheat protected, the timeliness and the effect of overheat protection are improved, and errors are reduced.
Referring to fig. 3, fig. 3 is a schematic structural diagram of another overheat protection device for an electric kettle based on historical data according to an embodiment of the present invention. As shown in fig. 3, the apparatus may include:
A memory 301 storing executable program code;
a processor 302 coupled with the memory 301;
the processor 302 invokes the executable program code stored in the memory 301 to perform some or all of the steps in the method for protecting the overheat of the electric kettle based on the history data according to the embodiment of the present invention.
In a fourth embodiment, the present invention discloses a computer storage medium, where computer instructions are stored, and when the computer instructions are called, the computer instructions are used to execute part or all of the steps in the method for protecting an electric kettle from overheating based on historical data disclosed in the first embodiment of the present invention.
The foregoing describes certain embodiments of the present disclosure, other embodiments being within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. Furthermore, the processes depicted in the accompanying drawings do not necessarily have to be in the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-transitory computer readable storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to portions of the description of method embodiments being relevant.
The apparatus, the device, the nonvolatile computer readable storage medium and the method provided in the embodiments of the present disclosure correspond to each other, and therefore, the apparatus, the device, and the nonvolatile computer storage medium also have similar advantageous technical effects as those of the corresponding method, and since the advantageous technical effects of the method have been described in detail above, the advantageous technical effects of the corresponding apparatus, device, and nonvolatile computer storage medium are not described herein again.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.
It will be appreciated by those skilled in the art that the present description may be provided as a method, system, or computer program product. Accordingly, the present specification embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description embodiments may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present description is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
Finally, it should be noted that: the embodiment of the invention discloses an electric kettle overheat protection method and device based on historical data, which are disclosed by the embodiment of the invention only for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (10)
1. An electric kettle overheat protection method based on historical data is characterized by comprising the following steps:
acquiring working parameter data and overheat record data of a target electric kettle in a historical time period;
determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the working parameter data and the overheating record data;
acquiring real-time working data of the target electric kettle, and judging whether the target electric kettle is about to overheat according to the combination of the plurality of overheating rules and the real-time working data;
If yes, starting overheat protection operation on the target electric kettle.
2. The method for overheat protection of an electric kettle based on historical data according to claim 1, wherein the determining a plurality of overheat rule combinations of the target electric kettle based on a rule analysis algorithm according to the operation parameter data and overheat record data comprises:
based on a clustering grouping algorithm, the working parameter data are grouped for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes;
and determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time.
3. The method for overheat protection of an electric kettle based on historical data according to claim 2, wherein the operating parameter data comprises operating data of a plurality of different historical time points having a plurality of different data types; the clustering grouping algorithm is based on, the working parameter data are grouped for a plurality of times to obtain a plurality of data groups corresponding to the working parameter data in different grouping modes, and the clustering algorithm comprises the following steps:
grouping all the working data based on the data types to obtain a plurality of first data groups; all the working data in each first data group belong to the same data type;
Grouping all the working data based on a preset data sequence association rule to obtain a plurality of second data groups; the historical time points corresponding to any two of the second data sets are strong association relations defined by the data sequential association rules between the working data of adjacent time points;
based on the data change rate parameters of each working data at the specific historical time point and based on a parameter similarity screening algorithm, grouping all the working data to obtain a plurality of third data sets; the parameter similarity between the data change rate parameters of any two working data in each third data set is smaller than a preset similarity threshold.
4. The method for overheat protection of an electric kettle based on historical data according to claim 3, wherein the overheat rule combination comprises a data value, a data interval or a data relation of at least one data type; the determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the corresponding relation between the overheating record data and the data set in time comprises the following steps:
Acquiring an overheat time point corresponding to each overheat record data;
determining working data in a plurality of data groups corresponding to each overheating time point in any grouping mode to obtain a plurality of data sets;
and determining a data value, a data interval or a data relation corresponding to each data set to obtain a plurality of overheating rule combinations of the target electric kettle.
5. The method for overheat protection of an electric kettle based on historical data according to claim 4, wherein determining the working data in the plurality of data groups corresponding to each overheat time point in any grouping manner, to obtain a plurality of data sets, comprises:
determining working data in all the first data sets corresponding to each overheating time point to obtain a plurality of first overheating data sets;
determining working data in all the second data sets corresponding to each overheating time point and front and back adjacent time points to obtain a plurality of second overheating data sets;
and determining the data change rate of the working data in all the third data sets corresponding to each overheating time point to obtain a plurality of third overheating data sets.
6. The method for protecting an electric kettle from overheat according to claim 5, wherein determining the data value, the data interval or the data relation corresponding to each data set to obtain a plurality of overheat rule combinations of the target electric kettle comprises:
fitting to obtain polynomial data relation models corresponding to all data in each first overheat data set through a fitting algorithm to obtain a plurality of first type overheat rule combinations of the target electric kettle;
fitting to obtain binomial data relationship models corresponding to adjacent data at all time points in each second overheat data set through a fitting algorithm, and obtaining a plurality of second type overheat rule combinations of the target electric kettle;
and fitting to obtain data types and polynomial data relational models corresponding to all the data change rates in each third overheat data set through a fitting algorithm, and obtaining a plurality of third type overheat rule combinations of the target electric kettles.
7. The method of claim 6, wherein the operating parameter data or the real-time operating data comprises at least two of ambient temperature sensing data, ambient humidity sensing data, current sustained operating time data, and heating power data; and/or the number of the groups of groups,
Judging whether the target electric kettle is about to overheat according to the plurality of overheat rule combinations and the real-time working data, wherein the method comprises the following steps:
judging whether the real-time working data accords with the overheat rule combination or not;
if the real-time working data is judged to be not in accordance with any overheating rule combination, judging that the target electric kettle is not about to overheat;
if the real-time working data accords with any one of the overheating rule combinations, screening all the overheating rule combinations which accord with the overheating rule combinations;
judging whether all the conforming overheating rule combinations comprise at least two types of overheating rule combinations, if so, judging that the target electric kettle is about to overheat, and if not, judging that the target electric kettle is not about to overheat;
and/or the number of the groups of groups,
the starting overheat protection operation for the target electric kettle comprises the following steps:
sending a breaking command of a heating line to the target electric kettle; and/or the number of the groups of groups,
and sending a power reduction command to the target electric kettle.
8. An electric kettle overheat protection device based on historical data, the device comprising:
the acquisition module is used for acquiring working parameter data and overheat record data of the target electric kettle in a historical time period;
The determining module is used for determining a plurality of overheating rule combinations of the target electric kettle based on a rule analysis algorithm according to the working parameter data and the overheating record data;
the judging module is used for acquiring real-time working data of the target electric kettle and judging whether the target electric kettle is about to overheat according to the combination of the plurality of overheating rules and the real-time working data;
and the operation module is used for starting overheat protection operation on the target electric kettle when the judging result of the judging module is yes.
9. An electric kettle overheat protection device based on historical data, the device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the historic data based electric kettle overheat protection method as claimed in any one of claims 1 to 7.
10. A computer storage medium storing computer instructions for performing the historic data based electric kettle overheat protection method according to any one of claims 1 to 7 when called.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05115368A (en) * | 1991-10-28 | 1993-05-14 | Matsushita Electric Ind Co Ltd | Electric kettle |
| CN109655678A (en) * | 2017-10-11 | 2019-04-19 | 湖南中车时代电动汽车股份有限公司 | A kind of heat dissipation performance appraisal procedure and system for electricity consumption device |
| WO2021042339A1 (en) * | 2019-09-05 | 2021-03-11 | 阿里巴巴集团控股有限公司 | Heat dissipation control and model training method, device and system, and storage medium |
| CN114353877A (en) * | 2022-01-10 | 2022-04-15 | 蔡晓东 | Electric power iron tower monitoring and protecting system and method based on meteorological data |
| US20220147852A1 (en) * | 2020-11-10 | 2022-05-12 | International Business Machines Corporation | Mitigating partiality in regression models |
| CN116611006A (en) * | 2023-05-22 | 2023-08-18 | 广州吉谷电器有限公司 | Fault identification method and device of electric kettle based on user feedback |
-
2023
- 2023-08-23 CN CN202311062251.8A patent/CN116796208B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05115368A (en) * | 1991-10-28 | 1993-05-14 | Matsushita Electric Ind Co Ltd | Electric kettle |
| CN109655678A (en) * | 2017-10-11 | 2019-04-19 | 湖南中车时代电动汽车股份有限公司 | A kind of heat dissipation performance appraisal procedure and system for electricity consumption device |
| WO2021042339A1 (en) * | 2019-09-05 | 2021-03-11 | 阿里巴巴集团控股有限公司 | Heat dissipation control and model training method, device and system, and storage medium |
| US20220147852A1 (en) * | 2020-11-10 | 2022-05-12 | International Business Machines Corporation | Mitigating partiality in regression models |
| CN114353877A (en) * | 2022-01-10 | 2022-04-15 | 蔡晓东 | Electric power iron tower monitoring and protecting system and method based on meteorological data |
| CN116611006A (en) * | 2023-05-22 | 2023-08-18 | 广州吉谷电器有限公司 | Fault identification method and device of electric kettle based on user feedback |
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