CN114689207A - Heating device, abnormality detection method and apparatus for heating device, electronic device, and storage medium - Google Patents
Heating device, abnormality detection method and apparatus for heating device, electronic device, and storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K3/00—Thermometers giving results other than momentary value of temperature
- G01K3/08—Thermometers giving results other than momentary value of temperature giving differences of values; giving differentiated values
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/12—Timing analysis or timing optimisation
Abstract
The invention relates to the technical field of heating equipment, and provides heating equipment, an abnormality detection method and device thereof, electronic equipment and a storage medium. The temperature abnormality detection method of a heating apparatus includes: acquiring an actual temperature value of heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a corresponding historical actual temperature value within a set time length before the current moment; obtaining a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value; and judging that the temperature of the heating equipment is abnormal based on the condition that the relation between the current actual temperature value and the current theoretical temperature value meets a set relation. The method can detect the temperature abnormity of the heating equipment, control the heating equipment to carry out related safe operation based on the detection result, or remind the heating equipment to carry out related safe operation, ensure the use safety and avoid danger.
Description
Technical Field
The present invention relates to the field of heating device technologies, and in particular, to a heating device, an abnormality detection method and apparatus thereof, an electronic device, and a storage medium.
Background
The detection of temperature abnormality of the heating apparatus is of safety in use, and therefore is of great importance for the detection of temperature abnormality of the heating apparatus. Taking the warmer as an example, as the service life of the warmer increases, the warmer may age; in addition, improper operation of the warmer may cause the warmer to malfunction. The above factors may cause the heater to generate abnormal temperature and fire. Or, the heater may not be heated normally due to abnormal temperature of the heater, and the user may get a cold due to freezing.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a temperature anomaly detection method of heating equipment, which is used for ensuring the use safety and the normal work of the heating equipment.
The invention also provides a temperature anomaly detection device of the heating equipment.
The invention also provides heating equipment.
The invention also provides a server.
The invention further provides the electronic equipment.
The invention also proposes a non-transitory computer-readable storage medium.
A method of detecting a temperature abnormality of a heating apparatus according to an embodiment of a first aspect of the present invention includes:
acquiring an actual temperature value of heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a corresponding historical actual temperature value within a set time length before the current moment;
obtaining a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value;
and judging that the temperature of the heating equipment is abnormal based on the condition that the relation between the current actual temperature value and the current theoretical temperature value meets a set relation.
According to the temperature anomaly detection method provided by the embodiment of the invention, the temperature anomaly of the heating equipment can be detected, and then the heating equipment can be controlled to carry out related safe operation based on the detection result, or the related safe operation is reminded to carry out, so that the use safety of the heating equipment is ensured, and the occurrence of danger is avoided. Particularly, when a fire disaster occurs in the heating equipment, a fire disaster early warning mechanism can be established based on the temperature abnormity detection method of the heating equipment provided by the embodiment of the invention, so that the use safety of the heating equipment is improved.
According to an embodiment of the present invention, in the step of obtaining the actual temperature value of the heating device, the current actual temperature value and the historical actual temperature value are sorted in chronological order.
According to an embodiment of the present invention, the step of obtaining the theoretical temperature value based on the actual temperature value includes:
establishing a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value;
and acquiring the current theoretical temperature value based on the linear regression model.
According to an embodiment of the present invention, the step of establishing a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value includes:
based on a linear regression equation: t is a unit ofi＝k*ti+ b calculation of the least squares solution k of k and b0And b0(ii) a Wherein, i is 1,2,3, …, n, which refers to the serial number of the actual temperature value, and the serial number of the current actual temperature value is n; t isiThe ith actual temperature value of the heating equipment is obtained; k and b are constants in the linear regression equation; t is tiA timestamp corresponding to the ith actual temperature value of the heating equipment;
the step of obtaining the current theoretical temperature value based on the linear regression model includes:
based on formula k0*tn+b0And acquiring the current theoretical temperature value.
According to an embodiment of the present invention, the step of determining that the temperature of the heating apparatus is abnormal based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying a set relationship includes:
acquiring a residual error sequence of the theoretical temperature value and the actual temperature value corresponding to the theoretical temperature value, wherein the theoretical temperature value comprises a historical theoretical temperature value corresponding to the historical actual temperature value; carrying out standardization processing on the residual error sequence; judging that the temperature of the heating equipment is abnormally increased if the current residual standardized value obtained based on the standardization processing is larger than a first set parameter, or judging that the temperature of the heating equipment is abnormally decreased if the current residual standardized value obtained based on the standardization processing is smaller than a second set parameter;
and/or the presence of a gas in the atmosphere,
and judging that the temperature of the heating equipment is abnormally increased based on the fact that the current actual temperature value is greater than the upper quantile of the actual temperature value in the set time length, or judging that the temperature of the heating equipment is abnormally decreased based on the fact that the current actual temperature value is less than the lower quantile of the actual temperature value in the set time length.
According to an embodiment of the present invention, in the step of obtaining the residual sequence of the theoretical temperature value and the actual temperature value corresponding to the theoretical temperature value, based on a formula: r ═ k0*ti+b0-Ti|i＝1,2,3,…,n}，
Obtaining a residual sequence between a theoretical temperature value and an actual temperature value, wherein r is the residual sequence obtained by arranging the residual values of the theoretical temperature value and the actual temperature value according to a sequence number, and the residual sequence r comprises ri，ri＝k0*ti+b0-TiWherein i is 1,2,3, …, n;
in the step of standardizing the residual sequence, the mean value mu and the standard deviation s of the residual sequence are obtained based on a formula
Normalizing the residual sequence, wherein,
is the ith residual normalized value, i ═ 1,2,3, … n;
in the step of determining that the temperature of the heating device is abnormally increased when the current residual error normalized value obtained based on the normalization processing is larger than a first set parameter
Based on
>A first setting parameter that determines an abnormal rise in temperature of the heating apparatus,
normalizing the current residual error;
in the step of determining that the current residual error normalized value obtained based on the normalization processing is smaller than a second set parameter and the temperature of the heating equipment is abnormally reduced, the method obtains
Based on
<And a second setting parameter for determining an abnormal decrease in the temperature of the heating apparatus.
According to an embodiment of the present invention, the step of determining that the temperature of the heating apparatus abnormally increases based on the upper quantile that the current actual temperature value is greater than the actual temperature value within the set time period, or determining that the temperature of the heating apparatus abnormally decreases based on the lower quantile that the current actual temperature value is less than the actual temperature value within the set time period includes:
obtaining a temperature sequence { (T) between the actual temperature value and a timestamp corresponding to the actual temperature valuei,ti)|i＝1,2,3,…,n}；
Obtaining an upper quantile alpha of the temperature sequenceεOr lower side indexingNumber alpha'εWherein epsilon is a set value;
based on the current actual temperature value Tn>αεDetermining that the temperature of the heating apparatus is abnormally increased, or based on the current actual temperature value Tn<α′εAnd judging that the temperature of the heating equipment is abnormally reduced.
According to an embodiment of the invention, the first setting parameter is based on the first setting parameter
Is determined, the second setting parameter is based on the upper quantile of the statistical distribution
Is determined.
According to an embodiment of the present invention, in the step of obtaining the actual temperature value of the heating device, the actual temperature value of the local heating device is obtained, or the actual temperature value reported by the heating device is obtained.
A temperature abnormality detection device of a heating apparatus according to an embodiment of a second aspect of the present invention includes:
the temperature acquisition module is used for acquiring an actual temperature value of the heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current time and a corresponding historical actual temperature value within a set time length before the current time;
the calculation module is used for acquiring a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value;
and the judging module is used for judging the temperature abnormality of the heating equipment based on the condition that the relationship between the current actual temperature value and the current theoretical temperature value meets a set relationship.
The technical effect of the temperature anomaly detection device of the heating equipment according to the embodiment of the invention corresponds to the effect of the temperature anomaly detection method of the heating equipment, and details are not repeated here.
According to the heating apparatus of the embodiment of the third aspect of the invention,
the method comprises the following steps:
a processor that implements the method for detecting a temperature abnormality of the heating apparatus when executing a computer program;
the temperature detector is used for acquiring the actual temperature value of the heating equipment and sending the actual temperature value to the processor;
the processor sends a control signal and/or an alarm signal of the heating device based on the temperature abnormity of the heating device.
According to the heating device of the embodiment of the invention, since the processor executes the temperature abnormality detection method of the heating device, the technical effect of the temperature abnormality detection device is achieved, and the details are not repeated here.
According to an embodiment of the present invention, the heating device is a heater, a water heater, a dryer, an induction cooker, an electric iron, an electric range, a microwave oven, an induction cooker, an electric oven, a rice cooker, an electric blanket, an electric quilt or an electric clothes.
An electronic device according to an embodiment of the fourth aspect of the invention comprises a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for detecting a temperature anomaly of a heating device as described above when executing the computer program.
The technical effect of the electronic device according to the embodiment of the present invention corresponds to the effect of the method for detecting temperature abnormality of the heating device, and details thereof are not repeated here.
A non-transitory computer-readable storage medium according to an embodiment of the fifth aspect of the present invention has stored thereon a computer program that, when executed by a processor, implements the steps of the temperature abnormality detection method of the heating apparatus as described above.
The technical effect of the non-transitory computer-readable storage medium according to the embodiment of the present invention corresponds to the effect of the above-mentioned method for detecting a temperature abnormality of a heating device, and is not described herein again.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flow chart of a method for detecting temperature abnormality of a heating apparatus according to an embodiment of the present invention;
fig. 2 is a block schematic diagram of a temperature abnormality detection device of a heating apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in further detail with reference to the drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Before the embodiments of the present invention are explained in detail, the entire application scenario is described. The temperature anomaly detection method of the heating equipment, the temperature anomaly detection device of the heating equipment, the electronic equipment and the readable storage medium can be applied to a cloud platform in the field of Internet of things, can also be applied to cloud platforms in other kinds of Internet fields, or can also be applied to third-party equipment, or can also be applied to the heating equipment. The third-party device may include a plurality of different types such as a mobile phone, a tablet computer, a notebook, a vehicle-mounted computer, and other smart home appliances.
Referring to fig. 1, a method for detecting temperature abnormality of a heating apparatus according to an embodiment of the first aspect of the present invention, referring to fig. 1, includes:
s1, acquiring the actual temperature value of the heating equipment, wherein the actual temperature value comprises the current actual temperature value corresponding to the current time and the corresponding historical actual temperature value within the set time length before the current time.
For example, the cloud platform is used to obtain an actual temperature value from the heating device. The current actual temperature value in the actual temperature values refers to temperature data of the heating device currently detected, or may also be understood as temperature data of the heating device finally measured in chronological order.
Assuming each process of temperature anomaly detection, the cloud platform acquires temperature data of the heating device for the past 1 hour, and the heating device uploads the temperature data every ten minutes. The cloud platform obtains the current actual temperature value and also obtains six historical actual temperature values uploaded by the heating device in the past hour. In this case, the set time period is 1 hour. Of course, the set time period may be determined based on different situations, for example, for a heating device with a large temperature fluctuation, the set time period may also take a longer value, for example, for a water heater, temperature data within the last 24 hours may be obtained; for equipment with small temperature fluctuation, the set time length can also be shorter, for example, for a warmer, temperature data within the past 12 hours can be acquired. Of course, this is only an example, and the set duration may be a value within any reasonable duration range, which may be less than half a day, or greater than one day, or may be a value between half a day and one day. In addition, the rule of reporting the actual temperature value by the heating device is not limited, and the actual temperature value may be reported every ten minutes, or may be reported according to other frequencies.
According to the embodiment of the invention, in general, the longer the set time is, or the higher the frequency of reporting the actual temperature value by the heating device is, the more accurate the theoretical temperature value finally obtained based on the actual temperature value may be. Of course, if the setting time is too long, the more actual temperature values need to be obtained, and further, the calculation efficiency of the theoretical temperature values may be affected.
In an embodiment, taking the example that the cloud platform acquires the actual temperature value reported by the heating device, the heating device may package and send the actual temperature value and the timestamp corresponding to the actual temperature value to the cloud platform, and then the actual temperature value and the timestamp have a one-to-one correspondence relationship. Of course, the timestamp does not have to be obtained from the heating device, and for example, after the cloud platform obtains the actual temperature value from the heating device, a mapping relationship between the actual temperature value and the timestamp may also be established on the cloud platform.
According to the embodiment of the present invention, the type of the heating device is not limited, and may be a heater, a water heater, a dryer, an induction cooker, an electric iron, an electric cooker, a microwave oven, an induction cooker, an electric oven, an electric rice cooker, an electric blanket, an electric quilt, an electric clothes, or the like.
Taking the heater as an example, the heater needs to be turned on for a long time in winter in northern areas, and is very important for detecting abnormal temperature of the heater. If the temperature data is found to be abnormal, a fire disaster is possibly caused, and the disaster situation can be found in time by the temperature abnormality detection method, so that the fire disaster is prevented from being aggravated, and the safety of a user is ensured.
In one embodiment, the heating device is turned on and off one operation at a time. And the cloud platform acquires the current actual temperature value and the historical actual temperature value within the set time length in the working process.
According to the embodiment of the invention, the current actual temperature value and the historical actual temperature value are sequenced in time sequence. On the basis, the subsequent steps carry out correlation processing based on the actual temperature values after sorting.
And S2, acquiring theoretical temperature values based on the actual temperature values, wherein the theoretical temperature values comprise current theoretical temperature values corresponding to the current actual temperature values.
On the basis of obtaining the plurality of actual temperature values, a current theoretical temperature value corresponding to the current actual data can be obtained based on analysis and processing of the plurality of actual temperature values. For example, theoretical current temperature data may be obtained by finite element analysis of a plurality of actual temperature values. Or, theoretical current temperature data can be obtained through finite element analysis of a plurality of actual temperature values by a simulation analysis method.
Wherein, for the heating equipment, within a set time length, the change of the temperature data of the heating equipment tends to show a specific rule. Based on this rule, the current theoretical temperature value can be calculated.
In one embodiment, step S2 includes:
s201, establishing a linear regression model between an actual temperature value and a timestamp corresponding to the actual temperature value;
s202, obtaining the current theoretical temperature value based on the linear regression model.
In step S201, the timestamp may be obtained when the actual temperature value is obtained, that is, the timestamp corresponding to the actual temperature value is obtained while the heating device is obtained in step S1, for example, the heating device may pack the actual temperature value and the timestamp together to form actual temperature data, and send the actual temperature data to the cloud.
For example, if the set time duration is 1 hour, then in this hour, assuming that the total number of actual temperature values including the current actual temperature value and the historical actual temperature value is n, the number of timestamps corresponding to the actual temperature values is also n. And establishing a linear regression model based on the two variables of the actual temperature value and the timestamp, and calculating the current theoretical temperature value based on the linear regression model. Similarly, the theoretical temperature values correspond to the timestamps, and each theoretical temperature value has a unique corresponding timestamp.
In step S202, on the basis of the linear regression model obtained in step S201, the current theoretical temperature value may be obtained based on the linear regression model.
It should be noted that, in addition to the linear regression model to obtain the theoretical temperature value, other calculation models disclosed in the prior art may also be used to obtain the theoretical temperature value.
According to an embodiment of the present invention, step S201 includes:
based on a linear regression equation: t is a unit ofi＝k*ti+ b calculation of the least squares solution k of k and b0And b0(ii) a Wherein i is 1,2,3, …, n, i is the serial number of the actual temperature value of the heating device determined according to the chronological order, and the serial number of the current actual temperature value is n; t isiThe ith actual temperature value of the heating equipment; k and b are constants in a linear regression equation; t is tiA time stamp corresponding to the ith actual temperature value of the heating equipment;
step S202 includes: based on formula k0*tn+b0And acquiring a current theoretical temperature value.
And S3, judging that the temperature of the heating equipment is abnormal based on the fact that the relation between the current actual temperature value and the current theoretical temperature value meets the set relation.
In step S3, in general, when the difference between the actual temperature value and the theoretical temperature value is large, it indicates that the temperature of the heating device is abnormal.
In one embodiment, the relationship between the current actual temperature value and the current theoretical temperature value is directly compared, and based on the fact that the current actual temperature value is far greater than the current theoretical temperature value, it is determined that the temperature of the heating equipment is abnormal, and a fire disaster may occur. Based on this, the user can be reminded to explore the specific situation of the heating device. Or, based on that the current actual temperature value is far smaller than the current theoretical temperature value, it is determined that the temperature of the heating device is abnormal, and the heating device may not be normally started.
Of course, the direct magnitude comparison between the current actual temperature value and the current theoretical temperature value is merely used to determine whether the temperature is abnormal, and a certain probability of misjudgment occurs. Therefore, according to an embodiment of the present invention, step S3 includes:
s301, acquiring a residual error sequence of theoretical temperature values and actual temperature values corresponding to the theoretical temperature values, wherein the theoretical temperature values comprise historical theoretical temperature values corresponding to historical actual temperature values;
s302, carrying out standardization processing on the residual sequence;
and S303, judging that the temperature of the heating equipment is abnormally increased if the current residual standardized value obtained based on the standardization treatment is larger than the first set parameter, or judging that the temperature of the heating equipment is abnormally decreased if the current residual standardized value obtained based on the standardization treatment is smaller than the second set parameter.
In S301, based on the formula: r ═ k0*ti+b0-Ti|i＝1,2,3,…,n}，
And acquiring a residual sequence between a theoretical temperature value and an actual temperature value, wherein r is the residual sequence obtained by arranging the residual values of the theoretical temperature value and the actual temperature value according to a sequence of sequence numbers. The residual sequence r comprises ri，ri＝k0*ti+b0-TiWherein i is 1,2,3, …, n.
In S302, the mean value mu and the standard deviation S of the residual sequence are obtained based on a formula
Normalizing the residual sequence, wherein,
is the ith residual normalized value, i is 1,2,3, … n.
In S303, obtaining
Based on
>A first setting parameter, determiningThe temperature of the heating apparatus is abnormally increased,
the current residual is normalized. Or, obtaining
Based on
<And a second setting parameter for determining an abnormal decrease in the temperature of the heating apparatus.
In addition, in S303, if the current residual normalized value is greater than the first setting parameter, or if the current residual normalized value is less than the second setting parameter, it means that the current actual temperature value has a sudden change, and therefore, based on the fact that the current residual normalized value is greater than the first setting parameter, or the current residual normalized value is less than the second setting parameter, it can be determined that the temperature of the heating apparatus is abnormally increased or abnormally decreased.
In another embodiment, step S3 includes:
s301', based on the fact that the current actual temperature value is greater than the upper quantile of the actual temperature value in the set time length, the temperature of the heating equipment is judged to be abnormally increased, or based on the fact that the current actual temperature value is less than the lower quantile of the actual temperature value in the set time length, the temperature of the heating equipment is judged to be abnormally decreased.
In S301', the upper quantile of the actual temperature value in the set time period may be understood as the upper limit of the temperature when the heating device is operating normally, and when the actual temperature value is greater than the upper quantile, it means that there is a certain probability that the heating device is abnormal. Therefore, the current actual temperature value is larger than the upper side quantile of the actual temperature value, the current actual temperature value can be preliminarily judged to be higher than the normal working temperature value of the heating equipment, and the heating equipment is preliminarily considered to be possibly in a fire disaster.
In the same way, the current actual temperature value is less than the lower quantile of the actual temperature value in the set time length, and the heating equipment can be preliminarily considered not to be normally started. That is, the lower quantile of the actual temperature value in the set time period may be understood as the lower limit value of the temperature when the heating device is normally operated, and when the actual temperature value is less than the lower quantile, it means that there is a certain probability that the heating device is abnormal, for example, the fuel heating device is not sufficiently supplied or the electric heating device is disconnected. Therefore, the current actual temperature value is smaller than the lower side quantile of the actual temperature value, the current actual temperature value can be preliminarily judged to be lower than the normal working temperature value of the heating equipment, and the problem that the heating equipment possibly has insufficient fuel or insufficient power supply is preliminarily considered.
In S301', obtaining a temperature sequence { (T) between the actual temperature value and a timestamp corresponding to the actual temperature valuei,ti)|i＝1,2,3,…,n}；
Obtaining an upper quantile α of the temperature sequenceεOr lower quantile α'εWherein epsilon is a set value;
based on the current actual temperature value Tn>αεDetermining that the temperature of the heating apparatus is abnormally increased, or based on the current actual temperature value Tn<α′εAnd judging that the temperature of the heating equipment is abnormally reduced.
Wherein the upper quantile is denoted as αεε is a set value, and when ε is 2, α isεIs an upper binary number; when ε is 4, then αεUpper quartile. Of course, the value of epsilon is not limited by the examples herein, and can be other natural numbers.
In another embodiment, S3 includes both of the above two determination means. That is, only when the current residual standardized value obtained by the standardization process is greater than the first set parameter or the current residual standardized value obtained by the standardization process is less than the second set parameter, and meanwhile, the current actual temperature value is greater than the upper quantile of the actual temperature value in the set time length or the current actual temperature value is less than the lower quantile of the actual temperature value in the set time length, the temperature abnormality of the heating equipment is determined. The possibility of misjudgment of the situation is very small, and the user experience can be improved.
The above-described determination of the temperature abnormality of the heating apparatus has two cases, the first is an abnormality in which the actual temperature value is too high, and the second is an abnormality in which the actual temperature value is too low. The practical significance is the most significant in the judgment and analysis of the current actual temperature value, and the working state of the heating equipment can be judged in time.
According to the embodiment of the invention, when the current residual standardized value obtained by the standardization processing is greater than the first set parameter and the current actual temperature value is greater than the upper quantile of the actual temperature value in the set time length, the judgment of the temperature abnormality belongs to a first abnormal condition, and the condition is more for preventing fire.
When the current residual error normalized value obtained by the normalization processing is smaller than a second set parameter and the current actual temperature value is smaller than the lower quantile of the actual temperature value in the set duration, the judgment of the temperature abnormality belongs to a second abnormal condition, and the second abnormal condition is more used for judging whether the heating equipment works normally.
In one embodiment, the first setting parameter is based on
Is determined, the second setting parameter is based on
Is determined. "
The upper quantile of the statistical distribution of (1) is obtained by sequencing according to the sequence number
Normalizing the numerical sequence in the inner part, and obtaining the upper quantile of the normalized numerical sequence. Similarly,'
The "lower quantile of the statistical distribution of (a) refers to the lower quantile of the normalized numerical sequence.
At one isIn an embodiment, the first setting parameter is 4, that is, based on the current residual normalized value
It is determined that the temperature of the heating apparatus is abnormal.
According to the temperature anomaly detection method of the heating equipment, the temperature anomaly of the heating equipment can be detected, and further the heating equipment can be controlled to carry out related safe operation based on the detection result, or the heating equipment is reminded to carry out related safe operation, so that the use safety of the heating equipment is ensured, and the occurrence of danger is avoided. Particularly, when a fire disaster occurs in the heating equipment, a fire disaster early warning mechanism can be established based on the temperature abnormity detection method of the heating equipment provided by the embodiment of the invention, so that the use safety of the heating equipment is improved.
It should be noted that the above steps S1 to S3, and steps S301 to S303 are merely for convenience of description, and do not constitute a timing limitation of each step of the temperature abnormality detection method for the heating apparatus. Moreover, some contents are described in detail in the method for detecting a temperature abnormality of a heating device according to the embodiment of the first aspect of the present invention, and since all contents in the methods for detecting a temperature abnormality of a heating device can also be applied to the device for detecting a temperature abnormality of a heating device according to the embodiment of the second aspect, further detailed descriptions are not given in the device for detecting a temperature abnormality of a heating device according to the embodiment of the second aspect in order to avoid redundancy. Similarly, the contents of the above two embodiments can be used to explain the contents of all embodiments in the following, and therefore repeated contents in the following embodiments are not repeated.
Referring to fig. 2, according to a second aspect of the present invention, there is provided a temperature abnormality detection apparatus for a heating device, including:
the temperature obtaining module 201 is configured to obtain an actual temperature value of the heating device, where the actual temperature value includes a current actual temperature value corresponding to a current time and a historical actual temperature value corresponding to a set time period before the current time;
a calculating module 202, configured to obtain a theoretical temperature value based on the actual temperature value, where the theoretical temperature value includes a current theoretical temperature value corresponding to the current actual temperature value;
the judging module 203 is configured to judge that the temperature of the heating device is abnormal based on that a relationship between the current actual temperature value and the current theoretical temperature value satisfies a set relationship.
According to the temperature abnormity detection device of the heating equipment, the use safety of the heating equipment can be improved, and whether the heating equipment works normally or not can be judged.
In one embodiment, the calculation module 202 includes:
the model establishing submodule is used for establishing a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value;
and the theoretical temperature value obtaining submodule is used for obtaining the current theoretical temperature value based on the linear regression model.
In one embodiment, the model building submodule is based on a linear regression equation:
Ti＝k*ti+ b calculation of the least squares solution k of k and b0And b0；
Wherein, i is 1,2,3, …, n, which refers to the serial number of the actual temperature value, and the serial number of the current actual temperature value is n; t isiThe ith actual temperature value of the heating equipment; k and b are constants in a linear regression equation; t is tiAnd the time stamp corresponds to the ith actual temperature value of the heating equipment.
The current theoretical temperature value acquisition submodule is based on a formula k0*tn+b0And acquiring a current theoretical temperature value.
In one embodiment, the determining module 203 comprises:
the residual sequence building submodule is used for obtaining a theoretical temperature value and a residual sequence of an actual temperature value corresponding to the theoretical temperature value;
the standardization submodule is used for carrying out standardization processing on the residual sequence;
and the first temperature judgment submodule is used for judging that the temperature of the heating equipment is abnormally increased when the current residual standardized value obtained based on the standardization treatment is larger than the first set parameter, or judging that the temperature of the heating equipment is abnormally decreased when the current residual standardized value obtained based on the standardization treatment is smaller than the second set parameter.
In one embodiment, the determining module 203 comprises:
and the second temperature judgment submodule is used for judging that the temperature of the heating equipment is abnormally increased based on the fact that the current actual temperature value is greater than the upper quantile of the actual temperature value in the set duration, or judging that the temperature of the heating equipment is abnormally reduced based on the fact that the current actual temperature value is less than the lower quantile of the actual temperature value in the set duration.
In one embodiment, the residual sequence building submodule is based on the formula:
r＝{k0*ti+b0-Tiobtaining a residual sequence between a theoretical temperature value and an actual temperature value, wherein r is a residual sequence obtained by arranging residual values of the theoretical temperature value and the actual temperature value according to a sequence number, and the residual sequence r comprises ri，ri＝k0*ti+b0-Ti。
Where i is 1,2,3, …, n, i.e. r includes r1、r2、r3……rn；
A normalization submodule for obtaining a mean value mu and a standard deviation s of the residual sequence and based on a formula
The residual sequence is normalized, wherein,
is the ith residual normalized value, i ═ 1,2,3, … n;
a first temperature judgment submodule for obtaining
Based on
>And a first setting parameter for determining that the temperature of the heating device is abnormal.
In one embodiment, the determining module 203 comprises:
the temperature sequence building submodule is used for obtaining the temperature sequence between the actual temperature value and the timestamp corresponding to the actual temperature value (T { (T)i,ti)|i＝1,2,3,…,n}；
A quantile obtaining module for obtaining the upper quantile alpha of the temperature sequenceεOr lower quantile α'εWherein epsilon is a set value;
the second temperature judgment submodule is used for judging the current actual temperature value Tn>αεOr, alternatively, Tn<α′εIt is determined that the temperature of the heating apparatus is abnormal.
According to an embodiment of a third aspect of the present invention, there is provided a heating apparatus comprising a processor and a temperature detector. When the processor executes the computer program, the method for detecting the temperature abnormity of the heating equipment is realized, the temperature detector is used for acquiring the actual temperature value of the heating equipment and sending the actual temperature value to the processor, and the processor sends the control signal and/or the alarm signal of the heating equipment based on the temperature abnormity of the heating equipment.
In one embodiment, the processor sends a control signal for the heating device based on the determination by the determination module 203 that the temperature of the heating device is abnormal. When the temperature of the heating equipment is detected to be too high, the heating equipment is controlled to be switched off in order to prevent fire or avoid the deterioration of the fire condition; and when the temperature of the heating equipment is detected to be too low, controlling the heating equipment to be automatically started.
In another embodiment, the processor sends an alarm signal based on the determination of the temperature anomaly of the heating device by the determination module 203.
In yet another embodiment, the processor sends an alarm signal and a control signal based on the determination of the temperature anomaly of the heating device by the determination module 203.
In one embodiment, the processor sends the alarm signal to the user terminal, and the user terminal can monitor the working state of the heating device in real time.
According to the embodiment of the present invention, the installation position of the temperature sensor is not limited as long as the temperature of the heating apparatus can be detected.
According to an embodiment of the fourth aspect of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for detecting a temperature abnormality of a heating device described above when executing the computer program.
Fig. 3 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 3: a processor (processor)310, a communication Interface (communication Interface)320, a memory (memory)330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. The processor 310 may call logic instructions in the memory 330 to perform the following method: acquiring an actual temperature value of heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a corresponding historical actual temperature value within a set time length before the current moment; obtaining a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value; and judging that the temperature of the heating equipment is abnormal based on the condition that the relation between the current actual temperature value and the current theoretical temperature value meets a set relation.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Further, an embodiment of the present invention discloses a computer program product, the computer program product includes a computer program stored on a non-transitory computer readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer can execute the method provided by the above method embodiments, for example, the method includes: acquiring an actual temperature value of heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a corresponding historical actual temperature value within a set time length before the current moment; obtaining a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value; and judging that the temperature of the heating equipment is abnormal based on the condition that the relationship between the current actual temperature value and the current theoretical temperature value meets a set relationship.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to, when executed by a processor, perform the method for detecting a temperature abnormality of a heating apparatus provided in the foregoing embodiments, for example, the method includes: acquiring an actual temperature value of heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a corresponding historical actual temperature value within a set time length before the current moment; obtaining a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value; and judging that the temperature of the heating equipment is abnormal based on the condition that the relation between the current actual temperature value and the current theoretical temperature value meets a set relation.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (14)
1. A method of detecting temperature abnormality of a heating apparatus, characterized by comprising:
acquiring an actual temperature value of heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a corresponding historical actual temperature value within a set time length before the current moment;
obtaining a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value;
and judging that the temperature of the heating equipment is abnormal based on the condition that the relation between the current actual temperature value and the current theoretical temperature value meets a set relation.
2. The method according to claim 1, wherein in the step of obtaining the actual temperature value of the heating apparatus, the current actual temperature value and the historical actual temperature value are sorted in chronological order.
3. The method according to claim 1, wherein the step of obtaining the theoretical temperature value based on the actual temperature value includes:
establishing a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value;
and acquiring the current theoretical temperature value based on the linear regression model.
4. The method according to claim 3, wherein the step of establishing a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value comprises:
based on a linear regression equation: t isi＝k*ti+ b calculate the least squares solution k of k and b0And b0(ii) a Wherein, i is 1,2,3, …, n, which refers to the serial number of the actual temperature value, and the serial number of the current actual temperature value is n; t isiThe ith actual temperature value of the heating equipment is obtained; k and b are constants in the linear regression equation; t is tiA time stamp corresponding to the ith actual temperature value of the heating equipment;
the step of obtaining the current theoretical temperature value based on the linear regression model includes:
based on formula k0*tn+b0And acquiring the current theoretical temperature value.
5. The method according to any one of claims 1 to 4, wherein the step of determining that the temperature of the heating apparatus is abnormal based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying a set relationship includes:
acquiring a residual error sequence of the theoretical temperature value and the actual temperature value corresponding to the theoretical temperature value, wherein the theoretical temperature value comprises a historical theoretical temperature value corresponding to the historical actual temperature value; carrying out standardization processing on the residual error sequence; judging that the temperature of the heating equipment is abnormally increased if the current residual standardized value obtained based on the standardization processing is larger than a first set parameter, or judging that the temperature of the heating equipment is abnormally decreased if the current residual standardized value obtained based on the standardization processing is smaller than a second set parameter;
and/or the presence of a gas in the gas,
and judging that the temperature of the heating equipment is abnormally increased based on the fact that the current actual temperature value is greater than the upper quantile of the actual temperature value in the set time length, or judging that the temperature of the heating equipment is abnormally decreased based on the fact that the current actual temperature value is less than the lower quantile of the actual temperature value in the set time length.
6. The method according to claim 5, wherein the step of obtaining the residual sequence of the theoretical temperature value and the actual temperature value corresponding to the theoretical temperature value is based on a formula:
r＝{k0*ti+b0-Ti|i＝1，2，3，...，n}，
obtaining a residual sequence between a theoretical temperature value and an actual temperature value, wherein r is the residual sequence obtained by arranging the residual values of the theoretical temperature value and the actual temperature value according to a sequence number, and the residual sequence r comprises ri，ri＝k0*ti+b0-TiWherein, i ═ 1,2, 3.., n;
said pair ofIn the step of carrying out standardization processing on the residual sequence, the mean value mu and the standard deviation S of the residual sequence are obtained based on a formula
Normalizing the sequence of residuals, wherein,
is the ith residual normalized value, i ═ 1,2,3, … n;
in the step of determining that the temperature of the heating device is abnormally increased when the current residual error normalized value obtained based on the normalization processing is larger than a first set parameter
Based on
It is determined that the temperature of the heating apparatus abnormally increases,
normalizing the current residual error;
in the step of determining that the current residual error normalized value obtained based on the normalization processing is smaller than a second set parameter and the temperature of the heating equipment is abnormally reduced, the method obtains
Based on
It is determined that the temperature of the heating apparatus abnormally decreases.
7. The method according to claim 5, wherein the step of determining that the temperature of the heating apparatus is abnormally increased based on the current actual temperature value being greater than an upper quantile of the actual temperature value for the set period of time, or determining that the temperature of the heating apparatus is abnormally decreased based on the current actual temperature value being less than a lower quantile of the actual temperature value for the set period of time, comprises:
obtaining a temperature sequence between the actual temperature value and a timestamp corresponding to the actual temperature value { (T)i，ti)|i＝1，2，3，...，n}；
Obtaining an upper quantile α of the temperature sequenceεOr lower quantile α'εWherein epsilon is a set value;
based on the current actual temperature value Tn＞αεDetermining that the temperature of the heating apparatus is abnormally increased, or based on the current actual temperature value Tn＜α′εAnd judging that the temperature of the heating equipment is abnormally reduced.
8. The temperature abnormality detection method of a heating apparatus according to claim 6, characterized in that the first setting parameter is based on the first setting parameter
Is determined based on the upper quantile of the statistical distribution of (a), the second setting parameter is based on
Is determined.
9. The method according to any one of claims 1 to 8, wherein in the step of obtaining the actual temperature value of the heating device, the actual temperature value of the local heating device is obtained, or the actual temperature value reported by the heating device is obtained.
10. A temperature abnormality detection device of a heating apparatus, characterized by comprising:
the temperature acquisition module is used for acquiring an actual temperature value of the heating equipment, wherein the actual temperature value comprises a current actual temperature value corresponding to the current moment and a historical actual temperature value corresponding to the current moment within a set time length;
the calculation module is used for acquiring a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value comprises a current theoretical temperature value corresponding to the current actual temperature value;
and the judging module is used for judging the temperature abnormality of the heating equipment based on the condition that the relationship between the current actual temperature value and the current theoretical temperature value meets a set relationship.
11. A heating apparatus, comprising:
a processor implementing the steps of the method of detecting temperature anomalies of a heating device according to any one of claims 1 to 9 when the processor executes a computer program;
the temperature detector is used for acquiring the actual temperature value of the heating equipment and sending the actual temperature value to the processor;
the processor sends a control signal and/or an alarm signal of the heating equipment based on the temperature abnormity of the heating equipment.
12. The heating device of claim 11, wherein the heating device is a warmer, a water heater, a dryer, an induction cooker, an electric iron, an electric cooker, a microwave oven, an induction cooker, an electric oven, a rice cooker, an electric blanket, an electric quilt, or an electric garment.
13. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method for detecting temperature anomalies of a heating device according to any one of claims 1 to 9 when executing the computer program.
14. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for detecting a temperature anomaly of a heating device according to any one of claims 1 to 9.
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| CN116516456A (en) * | 2023-07-05 | 2023-08-01 | 深圳中宝新材科技有限公司 | Method for automatically overvoltage protection equipment of intelligent electroplating line production heating system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116516456A (en) * | 2023-07-05 | 2023-08-01 | 深圳中宝新材科技有限公司 | Method for automatically overvoltage protection equipment of intelligent electroplating line production heating system |
| CN116516456B (en) * | 2023-07-05 | 2023-09-12 | 深圳中宝新材科技有限公司 | Method for automatically overvoltage protection equipment of intelligent electroplating line production heating system |
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