Electric kettle operation self-checking method and device, electric kettle and computer equipment

Abstract

The invention relates to an electric kettle operation self-checking method and device, an electric kettle and computer equipment. The method comprises the steps of obtaining a weight data set obtained by detecting the electric kettle in real time by a weight sensor, determining a weight data discrete index of the weight sensor based on the weight data set, and determining that the weight sensor of the electric kettle is invalid under the condition that the weight data discrete index reaches a preset discrete value. By summarizing detection data of a weight sensor, analyzing a weight data set and marking the failure of the weight sensor according to a weight data discrete index, the failure of the weight sensor is accurately self-checked and confirmed, so that a user is reminded in time, or the operation of the electric kettle is adjusted to avoid dangerous conditions such as dry burning and the like; and the reliability and the safety of the operation of the electric kettle are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of household appliances, in particular to a kettle operation self-checking method and device, a kettle, a computer device, a computer readable storage medium and a computer program product. BACKGROUND

[0002] Household appliances are various, which facilitates people's life. In order to have a healthy diet and the convenience of drinking water, various water heating devices emerge in endlessly, and the electric kettle is relatively common and widely used. At present, the electric kettle used in the home environment usually sets a temperature sensor to detect the water temperature to judge whether the water in the electric kettle is boiling.

[0003] At present, some electric kettles are not convenient to set a temperature sensor, for example, the electric kettle made of cast iron, which has a closed kettle structure and heavy material, and it is difficult to install a temperature sensor. Therefore, such electric kettles usually use a weight sensor for boiling detection, which indirectly judges the boiling state by monitoring the weight drop caused by the evaporation of steam after the water boils.

[0004] However, when the weight sensor is not in good contact or fails, the judgment of boiling will also have errors, and the electric kettle may continue to heat, which has the risk of dry burning. SUMMARY

[0005] Therefore, it is necessary to provide a kettle operation self-checking method, device, kettle, computer device, computer readable storage medium and computer program product capable of improving the reliability of use in view of the above technical problems.

[0006] In a first aspect, the present application provides a kettle operation self-checking method, which comprises:

[0007] obtaining a weight data set obtained by a weight sensor in real time detecting an electric kettle;

[0008] determining a weight data dispersion index of the weight sensor based on the weight data set;

[0009] determining that the weight sensor of the electric kettle is invalid in a case where the weight data dispersion index reaches a preset dispersion value.

[0010] In this embodiment, the detection data of the weight sensor is summarized, the weight data set is analyzed, and the invalidation of the weight sensor is identified according to the weight data dispersion index, so as to accurately self-check and confirm the invalidation of the weight sensor, so as to timely remind the user or adjust the operation of the electric kettle to avoid the occurrence of dry burning and other dangerous situations, thereby improving the reliability and safety of the operation of the electric kettle.

[0011] In one of the embodiments, the determining the weight data dispersion index of the weight sensor based on the weight data set comprises at least one of the following:

[0012] The first item,

[0013] The range value is determined based on each weight data value in the weight data set.

[0014] The second item,

[0015] The standard deviation value is determined based on each weight data value in the weight data set.

[0016] The third item,

[0017] The repeated sampling sequence is determined based on the sequence of each weight data value in the weight data set.

[0018] In the embodiment, at least one of the range value, the standard deviation value and the repeated sampling sequence is calculated to analyze the weight data values in the weight data set in different dimensions and directions, so as to determine the accurate weight data dispersion index, and then to perform the failure inspection on the weight sensor to ensure the accurate self-checking and improve the operation reliability and safety of the electric kettle.

[0019] In one of the embodiments, the determining the range value based on each weight data value in the weight data set comprises:

[0020] The maximum weight data value and the minimum weight data value are selected from each weight data value in the weight data set, and the difference between the maximum weight data value and the minimum weight data value is calculated as the range value.

[0021] In the embodiment, how to calculate the range value from the weight data set is refined, the weight data values in the weight data set are calculated by accurate calculation and numerical analysis to obtain the range value in the weight data dispersion index, which can be directly used for self-checking. Meanwhile, the self-checking can be performed after the weight failure integral is determined, which ensures the operation self-checking reliability and accuracy of the electric kettle.

[0022] In one of the embodiments, the determining the standard deviation value based on each weight data value in the weight data set comprises:

[0023] The average value is calculated based on each weight data value in the weight data set, and the standard deviation value is calculated based on the average value.

[0024] In the embodiment, how to calculate the standard deviation value from the weight data set is refined. The weight data values in the weight data set are operated through accurate calculation and numerical analysis, the standard deviation value in the weight data dispersion index is obtained after the average value is calculated, which can be directly used for self-checking of the weight sensor. At the same time, it is also convenient for subsequent self-checking based on weight failure integral, which guarantees the reliable and accurate operation self-checking of the electric kettle.

[0025] In one of the embodiments, the sequence of weight data values in the weight data set is used to determine a repeated sampling sequence, which includes:

[0026] The weight data values in the weight data set are arranged according to the sequence of acquisition times.

[0027] The weight data values with the same value as the adjacent weight data values are subjected to secondary screening to obtain the repeated sampling sequence.

[0028] In the embodiment, the same weight data values obtained at continuous times are used as the repeated sampling sequence, which can be subjected to secondary screening in the case of continuous same data collection of the weight sensor, and then the weight data dispersion index is determined from the perspective of repetition, so as to realize the self-checking of the electric kettle, and also affect the value of the subsequent weight failure integral, judge the operation self-checking of the electric kettle, and guarantee the reliable and safe operation.

[0029] In one of the embodiments, after the weight data dispersion index of the weight sensor is determined based on the weight data set, the method further includes:

[0030] The weight failure integral of the weight sensor is determined based on the weight data dispersion index.

[0031] The weight sensor of the electric kettle is determined to be failed when the weight data dispersion index reaches a preset dispersion value, which includes:

[0032] The weight sensor of the electric kettle is determined to be failed when the weight failure integral reaches a preset failure value.

[0033] In the embodiment, the failure of the weight sensor is identified in the form of integral by integral operation according to the weight data dispersion index, so as to accurately self-check and confirm the failure of the weight sensor when the weight failure integral reaches the preset failure value, so as to timely remind the user or adjust the operation of the electric kettle to avoid dry burning and other dangerous situations, and improve the reliability and safety of the operation of the electric kettle.

[0034] In one of the embodiments, the weight failure integral of the weight sensor is determined based on the weight data dispersion index, which includes:

[0035] determine the weight failure integral of the weight sensor according to at least one of the range value, the standard deviation value and the repeated sampling sequence.

[0036] In the embodiment, by recording the failure integral based on at least one of the range value, the standard deviation value and the repeated sampling sequence, the weight data values in the weight data set are integrated in different discrete dimensions, so as to determine the accurate weight failure integral, and then perform the failure test on the weight sensor, so as to ensure the accurate self-checking and improve the operation reliability and safety of the electric kettle.

[0037] In one of the embodiments, the determining the weight failure integral of the weight sensor according to at least one of the range value, the standard deviation value and the repeated sampling sequence comprises:

[0038] determining the integral in the first integral pool according to the comparison result of the range value and a preset difference value;

[0039] determining the integral in the second integral pool according to the comparison result of the standard deviation value and a preset standard deviation;

[0040] determining the integral in the third integral pool according to the comparison result of the number of weight data values in the repeated sampling sequence and a preset repetition threshold value;

[0041] determining the weight failure integral of the weight sensor based on at least one of the first integral pool, the second integral pool and the third integral pool.

[0042] In the embodiment, by establishing the integral pool according to the range value, the standard deviation value and the repeated sampling sequence respectively, and adjusting the integral in each integral pool according to the corresponding comparison or analysis result, and then taking at least one of the integrals in each integral pool as the weight failure integral of the weight sensor, the multi-dimensional data analysis is comprehensively considered, and the integral algorithm and integral recognition mechanism are adopted, so as to accurately detect the operation of the electric kettle and ensure the self-checking accuracy and reliability.

[0043] In one of the embodiments, before the acquiring the weight data set detected by the weight sensor in real time, the method further comprises:

[0044] recording the running duration when the electric kettle is in the running state;

[0045] when the running duration reaches a preset duration, performing the acquiring the weight data set detected by the weight sensor in real time.

[0046] In this embodiment, by starting the self-checking of the data collection of the weight sensor after a preset time length, the influence of the error caused by the instability of the electric kettle at the initial stage of operation can be avoided, and the accuracy of the self-checking can be improved.

[0047] In one of the embodiments, the method further comprises:

[0048] obtaining working current data of the electric kettle, and analyzing whether the electric kettle is in a heating stage based on the working current data;

[0049] In the case where the running time length reaches a preset time length and the electric kettle is in the heating stage, the weight data set obtained by the real-time detection of the weight sensor on the electric kettle is acquired.

[0050] In this embodiment, in addition to meeting the preset time length, the self-checking of the data collection of the weight sensor can also be started when the current meets the characteristics of the heating stage from the perspective of the circuit parameters, further avoiding the error caused by the instability of the weight and the current at the initial stage of the operation of the electric kettle, and further improving the accuracy of the self-checking.

[0051] In one of the embodiments, after the weight data dispersion index reaches a preset dispersion value, the method further comprises:

[0052] controlling the weight sensor to restart at a preset restart frequency, and obtaining restart weight data collected by the restarted weight sensor;

[0053] In the case where the restart weight data does not match the weight data values in the weight data set, it is determined that the weight sensor is restored to be valid.

[0054] In this embodiment, after determining that the weight sensor is invalid, the weight sensor can be restarted, and the restarted weight sensor can be analyzed again to determine whether the restarted weight sensor can be reused, so as to reduce the influence on the operation of the electric kettle, resume normal operation in time, and improve the operation reliability of the electric kettle.

[0055] In a second aspect, the application further provides an electric kettle operation self-checking device, which comprises:

[0056] a data collection module configured to obtain a weight data set obtained by the real-time detection of the weight sensor on the electric kettle;

[0057] a data processing module configured to determine a weight data dispersion index of the weight sensor based on the weight data set;

[0058] The self-checking output module is configured to determine that the weight sensor of the electric kettle is invalid when the weight data dispersion index reaches a preset dispersion value.

[0059] In a third aspect, the present application provides an electric kettle, which comprises a base, a kettle, a controller and a weight sensor, the kettle is embedded on the base, the weight sensor is arranged on the base, and the controller is connected to the weight sensor.

[0060] The base is configured to heat water in the kettle, the weight sensor is configured to detect the weight of the kettle, and the controller is configured to detect the weight sensor based on the self-checking method of the electric kettle.

[0061] In a fourth aspect, the present application provides a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0062] Obtaining a weight data set detected by a weight sensor in real time;

[0063] Determining a weight data dispersion index of the weight sensor based on the weight data set;

[0064] Determining that the weight sensor of the electric kettle is invalid when the weight data dispersion index reaches a preset dispersion value.

[0065] In a fifth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the following steps when executed by a processor:

[0066] Obtaining a weight data set detected by a weight sensor in real time;

[0067] Determining a weight data dispersion index of the weight sensor based on the weight data set;

[0068] Determining that the weight sensor of the electric kettle is invalid when the weight data dispersion index reaches a preset dispersion value.

[0069] In a sixth aspect, the present application provides a computer program product, which comprises a computer program, and the computer program implements the following steps when executed by a processor:

[0070] Obtaining a weight data set detected by a weight sensor in real time;

[0071] Determining a weight data dispersion index of the weight sensor based on the weight data set;

[0072] In a case where the weight data dispersion index reaches a preset dispersion value, it is determined that the weight sensor of the electric kettle is invalid.

[0073] The electric kettle operation self-checking method, device, electric kettle, computer equipment, computer readable storage medium and computer program product, including obtaining a weight data set obtained by a weight sensor in real time detecting an electric kettle, determining a weight data dispersion index of the weight sensor based on the weight data set, and determining that the weight sensor of the electric kettle is invalid in a case where the weight data dispersion index reaches a preset dispersion value. By summarizing the detection data of the weight sensor, by analyzing the weight data set, and according to the weight data dispersion index, the failure of the weight sensor is identified, the failure of the weight sensor is accurately self-checked and confirmed, so as to timely remind the user or adjust the operation of the electric kettle to avoid dry burning and other dangerous situations, thereby improving the reliability and safety of the operation of the electric kettle. BRIEF DESCRIPTION OF DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the description of the embodiments of the present application or the related art will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0075] Figure 1 A structural schematic diagram of an electric kettle in an embodiment;

[0076] Figure 2 A flowchart of an electric kettle operation self-checking method in an embodiment;

[0077] Figure 3 A flowchart of a step of determining a weight data dispersion index of a weight sensor based on a weight data set in an embodiment;

[0078] Figure 4 A flowchart of a step of determining a repeated sampling sequence based on a sequence of each weight data value of the weight data set in an embodiment;

[0079] Figure 5 A flowchart of an electric kettle operation self-checking method in another embodiment;

[0080] Figure 6 A flowchart of a step of determining a weight failure integral of a weight sensor according to at least one of a range value, a standard deviation value and a repeated sampling sequence in an embodiment;

[0081] Figure 7 A flowchart of an electric kettle operation self-checking method in another embodiment;

[0082] Figure 8 Flowchart of the self-checking method for the electric kettle in another embodiment;

[0083] Figure 9 Flowchart of the self-checking method for the electric kettle in another embodiment;

[0084] Figure 10 Structure block diagram of the self-checking device for the electric kettle in an embodiment;

[0085] Figure 11 Internal structure diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0086] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0087] It can be understood that the terms "first", "second", and the like used in the present application can be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of the present application, the first resistor can be referred to as the second resistor, and similarly, the second resistor can be referred to as the first resistor. The first resistor and the second resistor are both resistors, but they are not the same resistor.

[0088] It can be understood that "connection" in the following embodiments means "electrical connection", "communication connection", etc. if the circuits, modules, units, etc. connected to each other have the transmission of electrical signals or data.

[0089] As used herein, the singular forms "a", "an" and "the" can include plural forms unless the context clearly indicates otherwise. It should also be understood that the terms "comprise / comprising" or "have / having" specify the presence of stated features, integers, steps, operations, components, parts, or combinations thereof, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, parts, or combinations thereof. At the same time, the term "and / or" used in the specification includes any and all combinations of the related listed items.

[0090] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0091] The electric kettle operation self-checking method provided by the embodiments of the present application can be applied to various electric kettles, such as cast iron kettles. The electric kettle of cast iron material has a closed kettle structure and heavy material, and it is difficult to install a temperature sensor. Therefore, such electric kettle usually uses a weight sensor to detect boiling, and indirectly judges the boiling state by monitoring the weight decrease caused by the vapor volatilization after the water boils. In fact, the scheme of the present application can be applied to various electric kettles using a weight sensor for detection, and is not limited to cast iron kettles, which are only exemplified here.

[0092] In one embodiment, as shown in Figure 1 The present application provides an electric kettle, which includes a base, a kettle, a controller (not shown in the figure) and a weight sensor. The kettle is embedded on the base, the weight sensor is arranged on the base, and the controller is connected to the weight sensor. The base is used to heat the water in the kettle, the weight sensor is used to detect the weight of the kettle, and the controller detects the weight sensor based on the electric kettle operation self-checking method recorded in the embodiments of the present application to realize the operation self-checking of the electric kettle.

[0093] Optionally, when the controller also participates in the operation control of the electric kettle, the controller is also connected to the base, and can control the heating power or process of the water in the kettle by the base. The controller can be a control chip of the electric kettle, or an independent chip connected to the control chip of the electric kettle, and is not specifically limited.

[0094] The base is used to place the kettle, the kettle has a cavity capable of containing water, and the base has a heating element, such as a heating wire, capable of generating heat under the control of the controller to heat the water in the kettle. The weight sensor is also arranged in the base, and the weight sensor is used to detect the weight of the water in the kettle, and can judge whether the water in the kettle boils by analyzing the change of the weight data value.

[0095] Further, the electric kettle can also include a prompt module capable of prompting and displaying the running state of the electric kettle, such as an LED lamp, a wireless communication module, etc.

[0096] In one exemplary embodiment, as shown in Figure 2 An electric kettle operation self-checking method is provided, and the controller of the electric kettle is taken as an example to illustrate the method, which includes the following steps 202 to 206.

[0097] Step 202, obtaining the weight data set obtained by the weight sensor in real time detecting the electric kettle.

[0098] The weight sensor is arranged in the electric kettle and arranged in the base of the electric kettle, and can detect the weight of the water in the kettle in real time. Specifically, the controller is connected to the weight sensor, and the weight sensor can detect the weight data value of the electric kettle in real time. The controller collects the weight data value detected in real time as the weight data set.

[0099] Further, the weight data set is composed of a plurality of weight data values, and the controller acquires the weight data value detected by the weight sensor at a certain sampling interval time t (for example, 200 ms), and acquires the latest specified number n (for example, 20) of weight data values as the weight data value of the weight data set.

[0100] Step 204, determining the weight data dispersion index of the weight sensor based on the weight data set.

[0101] Specifically, the controller analyzes the weight data values in the weight data set, analyzes the numerical value size and the change size between the weight data values, and calculates the range, variance or average, etc. Various mathematical calculation methods are used to obtain the weight data dispersion index of the weight sensor. The weight data dispersion index corresponds to the dispersion relationship between the weight data values in the weight data set, including but not limited to the numerical value size relationship and the numerical trend relationship between the weight data values.

[0102] Further, the weight data dispersion index can include the range value, the standard deviation value, etc. Numerical size relationship, and can also include repeated sampling sequence numerical trend relationship.

[0103] Further, in an exemplary embodiment, as shown in Figure 3 Step 204 includes at least one of steps 302 to 306. Wherein:

[0104] Step 302, based on each weight data value in the weight data set, calculating and determining the range value.

[0105] The weight data values in the weight data set are analyzed, compared according to the numerical value size of the weight data values, and the weight data value with the maximum numerical value and the weight data value with the minimum numerical value are determined to calculate the range value.

[0106] Specifically, in one embodiment, step 302 includes step 402: from each weight data value in the weight data set, filtering the weight data value with the maximum numerical value and the weight data value with the minimum numerical value, calculating the difference between the weight data value with the maximum numerical value and the weight data value with the minimum numerical value, and marking the difference as the range value.

[0107] The maximum weight data value and the minimum weight data value are filtered from the weight data values, the maximum weight data value is subtracted by the minimum weight data value, and a difference value between the two is obtained as the range value.

[0108] For example, the weight data set includes n weight data values, which are marked as W1, W2, …, Wn respectively. The maximum weight data value max(Wi) is filtered from the n weight data values, and the minimum weight data value min(Wi) is filtered. Then, the range value AW = max(Wi) - min(Wi) is obtained.

[0109] In this embodiment, how to calculate the range value from the weight data set is refined. Through accurate calculation and numerical analysis, the range value in the weight data dispersion index is obtained by operating the weight data values in the weight data set, which can be directly used for self-checking. At the same time, it can also be used for self-checking after determining the weight failure integral, which guarantees the reliable and accurate operation self-checking of the electric kettle.

[0110] It should be noted that since the weight data set is updated in real time, the range value calculated from the weight data values in the weight data set is also updated in real time. The values of the range values obtained at different times may be the same or different. The specified time for calculation is used as the reference, and the calculation of other weight data dispersion indexes is the same.

[0111] In step 304, the standard deviation value is calculated based on each weight data value in the weight data set.

[0112] Each weight data value in the weight data set is analyzed, and the standard deviation of each weight data value in the weight data value is calculated according to the numerical value of the weight data value to determine the standard deviation value. Further, in one embodiment, step 304 includes step 404: calculating the average value based on each weight data value in the weight data set, and calculating the standard deviation value based on the average value.

[0113] Specifically, when calculating the standard deviation value, the average value is first calculated according to each weight data value in the weight data set, and then the standard deviation value of the weight data set is determined according to the standard deviation formula. For example, the weight data set includes n weight data values, which are marked as W1, W2, …, Wn. The average value W is calculated from the n weight data values, and then each weight data value is subtracted by the average value W to obtain the deviation of each weight data value. The sum of the deviations is then divided by the number of data n to obtain the average deviation. Then, the arithmetic square root of the average deviation is taken to obtain the standard deviation value.

[0114] In the embodiment, how to calculate the standard deviation value from the weight data set is refined. The weight data values in the weight data set are calculated through accurate calculation and numerical analysis, the average value is calculated, and the standard deviation value in the weight data dispersion index is obtained, which can be directly used for self-checking of the weight sensor. At the same time, it is also convenient for subsequent self-checking based on weight failure integral, and the operation self-checking of the electric kettle is reliable and accurate.

[0115] In step 306, a repeated sampling sequence is determined based on the sequence of the weight data values in the weight data set.

[0116] Specifically, based on the weight data values in the weight data set, since each weight data value is collected by the weight sensor at different times, the sequence of the weight data values in the weight data set is arranged in the order of acquisition time. The newer the weight data value sequence, the earlier it can be arranged, or the newer the weight data value sequence, the later it can be arranged. According to the sequence of the weight data values in the weight data set, the weight data values with the same value are filtered out to obtain the repeated sampling sequence.

[0117] In the embodiment, at least one of the range value, the standard deviation value, and the repeated sampling sequence is calculated to analyze the weight data values in the weight data set in different dimensions and directions, so as to determine accurate weight data dispersion indexes, and then to facilitate failure inspection of the weight sensor, to ensure accurate self-checking, and to improve the operation reliability and safety of the electric kettle.

[0118] Further, in one of the embodiments, as shown in FIG. 5, step 306 includes steps 502 to 504. Figure 4

[0119] In step 502, the weight data values in the weight data set are arranged in the sequence of acquisition time.

[0120] When analyzing the weight data values in the weight data set, in order to ensure that the sequence of the weight data values strictly corresponds to the acquisition time, the weight data values are sorted in the sequence of acquisition time before the weight data values are filtered, so as to ensure that the weight data values are accurately filtered.

[0121] In step 504, the weight data values with the same value as the adjacent weight data values are secondarily filtered to obtain the repeated sampling sequence.

[0122] ​Specifically, after the weight data values are sorted, it is necessary to screen the repeated sampling sequence, that is, in the sorted weight data values, if there are adjacent weight data values with the same value, the weight data values meeting the condition are screened again to obtain the repeated sampling sequence. Among them, adjacent weight data values in the sorted weight data values means that the acquisition time of the two is close and adjacent, and the same value means that the weight data values collected by the two are the same, that is, the weight of the kettle does not change in this period of time.

[0123] Optionally, the repeated sampling data can be multiple, and each weight data value of the second screened value has a repeated sampling sequence.

[0124] In this embodiment, by taking the same weight data values obtained in continuous time as the repeated sampling sequence, the second screening can be performed for the case that the collection data of the weight sensor is the same, and then the weight data dispersion index is determined from the repetitive perspective, so as to realize the self-checking of the electric kettle, and also can affect the value of the subsequent weight failure integral, judge the operation self-checking of the electric kettle, and protect the operation reliability and safety.

[0125] Step 206, in the case that the weight data dispersion index reaches the preset dispersion value, it is determined that the weight sensor of the electric kettle is failed.

[0126] Specifically, the controller stores a preset dispersion value, which is used to determine whether the weight sensor of the electric kettle is failed. After obtaining the weight data dispersion index, the controller compares the weight data dispersion index with the preset dispersion value, and in the case that the weight data dispersion index reaches the preset dispersion value, it is determined that the weight sensor of the electric kettle is failed.

[0127] For example, when the weight data dispersion index is the range value, the preset dispersion value is less than 1 (g), and in the case that the range value of the weight data dispersion index is less than 1 (g), it is determined that the weight sensor of the electric kettle is failed; when the weight data dispersion index is the standard deviation value, the preset dispersion value is less than 0.5, and in the case that the standard deviation value of the weight data dispersion index is less than 0.5, it is determined that the weight sensor of the electric kettle is failed; when the weight data dispersion index is the repeated sampling sequence, the preset dispersion value is greater than 10, and in the case that the number of weight data values in the repeated sampling sequence of the weight data dispersion index is greater than 10, it is determined that the weight sensor of the electric kettle is failed. Otherwise, it is not failed, which will not be described here.

[0128] In the above method for performing self-checking on the electric kettle, the weight data set obtained by the weight sensor in real time is acquired, the weight data dispersion index of the weight sensor is determined based on the weight data set, and the weight sensor of the electric kettle is determined to be invalid when the weight data dispersion index reaches a preset dispersion value. The detection data of the weight sensor is summarized, the weight data set is analyzed, and the failure of the weight sensor is identified according to the weight data dispersion index, so as to accurately self-check and confirm the failure of the weight sensor, to timely remind the user or adjust the operation of the electric kettle to avoid dry burning and other dangerous situations, thereby improving the reliability and safety of the operation of the electric kettle.

[0129] Optionally, as shown in step 204, step 205 can also be performed after step 204: determining the weight failure integral of the weight sensor based on the weight data dispersion index. Figure 5

[0130] Specifically, after the controller analyzes the weight data value in the weight data set to obtain the weight data dispersion index, the weight failure integral of the weight data dispersion index can be calculated under certain conditions. For example, when the value represented by the weight data dispersion index is lower than a preset value, the weight failure integral is increased; when the value represented by the weight data dispersion index is higher than or equal to the preset value, the weight failure integral is decreased.

[0131] Based on the performance of step 205, the corresponding step 206 will be replaced by step 207: determining that the weight sensor of the electric kettle is invalid when the weight failure integral reaches a preset failure value.

[0132] Specifically, the controller stores a preset failure value, which is used to determine whether the weight sensor of the electric kettle is invalid. After obtaining the weight failure integral, the controller compares the weight failure integral with the preset failure value, and determines that the weight sensor of the electric kettle is invalid when the weight failure integral reaches the preset failure value. Exemplarily, the preset failure value is 10 points, and the weight sensor of the electric kettle is determined to be invalid when the weight failure integral is equal to or greater than 10 points, otherwise it is not invalid.

[0133] Further, based on the determination that the weight sensor of the electric kettle is invalid, that is, after step 206 or after step 207, the controller can also control the prompt module to generate prompt information, such as controlling the buzzer, LED indicator light or communication module of the smart device to correspondingly emit sound, light signal or remote notification representing the failure of the weight sensor.

[0134] ​In the embodiment, the failure of the weight sensor is identified in the form of integral by integral operation according to the weight data discrete index, so that when the weight failure integral reaches the preset failure value, the weight sensor failure is accurately self-checked, so as to timely remind the user or adjust the operation of the electric kettle to avoid dry burning and other dangerous situations, thereby improving the reliability and safety of the electric kettle operation.

[0135] Further, in one of the embodiments, the step 205 includes a step 602 of determining the weight failure integral of the weight sensor according to at least one of the range value, the standard deviation value and the repeated sampling sequence.

[0136] Specifically, after the range value, the standard deviation value and the repeated sampling sequence are calculated and analyzed, the weight failure integral can be calculated based on the range value, the standard deviation value and the repeated sampling sequence, for example, the three are used to calculate the integral respectively, and the three integrals are finally summarized as the weight failure integral, or one of them is selected as the weight failure integral.

[0137] In the embodiment, by recording the failure integral based on at least one of the range value, the standard deviation value and the repeated sampling sequence, the weight data values in the weight data set can be integrated in different discrete dimensions, so as to determine the accurate weight failure integral, and then perform failure inspection on the weight sensor, to ensure accurate self-checking and improve the operation reliability and safety of the electric kettle.

[0138] Further, in one of the embodiments, as shown in Figure 6 The step 602 includes steps 702 to 708.

[0139] In step 702, the integral in the first integral pool is determined according to the comparison result of the range value and the preset difference value.

[0140] Specifically, the controller stores a preset preset difference value for comparison with the range value and determination of the integral in the first integral pool. After obtaining the range value, the obtained range value is compared with the preset difference value to obtain a comparison result, and the integral in the first integral pool is determined according to the comparison result.

[0141] For example, the preset difference value can be 1, and the range value is compared with the preset difference value. When the range value is less than the preset difference value, it is considered that the weight is stable, and the integral in the first integral pool is increased by 1.

[0142] In step 704, the integral in the second integral pool is determined according to the comparison result of the standard deviation value and the preset standard deviation.

[0143] Specifically, the controller stores a preset standard deviation, which is used to compare with the standard deviation value and determine the score in the second integral pool. After obtaining the standard deviation value, the obtained standard deviation value is compared with the preset standard deviation to obtain a comparison result, and the score in the second integral pool is determined according to the comparison result.

[0144] Exemplarily, the preset standard deviation can be 0.5, and the standard deviation value is compared with the preset standard deviation. When the standard deviation value is less than the preset standard deviation, it is considered that the weight fluctuation is small, and the score in the second integral pool is increased by 1.

[0145] Step 706, according to the number of weight data values in the repeated sampling sequence and the comparison result of the preset repetition threshold, the score in the third integral pool is determined.

[0146] Specifically, the controller stores a preset repetition threshold, which is used to determine the score in the third integral pool. The number of each repeated sampling sequence in the obtained repeated sampling sequence, that is, the number of consecutive samplings with the same weight data value, is recorded. The repeated sampling sequence with the number greater than or equal to the preset repetition threshold is marked as an effective sequence, and the score in the third integral pool is changed correspondingly when there is one effective sequence.

[0147] Exemplarily, the preset repetition threshold can be 10 times, and the number of repeated data values in the repeated sampling sequence is compared with the preset repetition threshold. When there is one effective sequence, the score in the third integral pool is increased by 2.

[0148] Step 708, based on at least one of the first integral pool, the second integral pool and the third integral pool, the weight failure score of the weight sensor is determined.

[0149] Specifically, at least one of the scores in the first integral pool, the second integral pool and the third integral pool can be taken as the weight failure score, which can be one of them or the sum of the scores of the three can be taken as the weight failure score of the weight sensor. By establishing the integral pool according to the range value, the standard deviation value and the repeated sampling sequence respectively, and adjusting the score in each integral pool according to the corresponding comparison or analysis result, and then taking at least one of the scores in each integral pool as the weight failure score of the weight sensor, the multi-dimensional data analysis is comprehensively considered, the integral algorithm and integral recognition mechanism are adopted, the robustness is increased, so as to accurately detect the operation of the electric kettle and ensure the accuracy and reliability of the self-checking.

[0150] In one of the embodiments, as shown in Figure 7 before step 202, the electric kettle operation self-checking method further includes step 802: recording the running time when the electric kettle is in the running state.

[0151] Specifically, the controller can detect the state of the electric kettle, record the heating duration when the electric kettle is in the running state, that is, during heating, and obtain the running duration. The controller stores a preset duration (for example, 480 seconds). When the running duration is recorded synchronously, the running duration is compared with the preset duration. In the case where the running duration reaches the preset duration, step 204 is executed to obtain the weight data set detected by the weight sensor in real time.

[0152] In this embodiment, by starting the self-checking of the data collection of the weight sensor after the preset duration, the influence of the error caused by the instability of the electric kettle at the initial stage of operation can be avoided, which is beneficial to improve the accuracy of the self-checking.

[0153] Further, in one of the embodiments, as shown in Figure 8 After step 802, the electric kettle operation self-checking method further includes step 804: obtaining working current data of the electric kettle, and analyzing whether the electric kettle is in the heating stage based on the working current data.

[0154] Specifically, the controller can record the running duration when the electric kettle is in the running state, and continuously obtain the working current data of the electric kettle, and analyze whether the electric kettle is in the heating stage according to the curve or power change of the working current data. In the case where the running duration reaches the preset duration and the electric kettle is in the heating stage, step 204 is executed.

[0155] In this embodiment, in addition to meeting the preset duration, the self-checking of the data collection of the weight sensor is started when the current meets the characteristics of the heating stage from the perspective of the circuit parameters, further avoiding the error caused by the instability of the weight and the current at the initial stage of the operation of the electric kettle, and further improving the accuracy of the self-checking.

[0156] In one of the embodiments, after step 206, as shown in Figure 9 The electric kettle operation self-checking method further includes steps 902 to 904.

[0157] Step 902: controlling the weight sensor to restart according to a preset restart frequency, and obtaining the restart weight data collected by the restarted weight sensor.

[0158] After determining that the weight sensor is invalid, the controller can control the weight sensor to restart according to a preset restart frequency (for example, every 60 seconds), and the restart process includes cutting off the power supply, cutting off the circuit power supply, and then restoring the power supply to start the weight sensor. After restarting, the restart weight value collected by the restarted weight sensor is obtained.

[0159] Step 904: in the case where the restart weight data and the weight data in the weight data set do not match, it is determined that the weight sensor is restored to be valid.

[0160] Specifically, the restart weight data is analyzed based on the weight data values in the weight data set, the latest weight data value in the weight data set is compared with the restart weight data, if the two values are the same, it indicates that the weight of the electric kettle detected by the weight sensor does not change, while the weight of the electric kettle in heating should decrease with the evaporation of boiling water, at this time it is judged that the weight sensor is still invalid. If there is a change between the two data, it indicates that the weight sensor is still detecting new weight data values and can continue to be used, so at this time it is judged that the weight sensor recovers to be valid and can continue to be enabled.

[0161] In the embodiment, after determining that the weight sensor is invalid, the weight sensor can be restarted, and the restarted weight sensor is analyzed again to determine whether the restarted weight sensor can be reused, so as to reduce the influence on the operation of the electric kettle, resume normal operation in time, and improve the operation reliability of the electric kettle.

[0162] Based on the same technical concept, the application also provides an electric kettle, which comprises a base, a kettle, a controller and a weight sensor. The kettle is embedded on the base, the weight sensor is arranged on the base, and the controller is connected to the weight sensor. The base is used for heating water in the kettle, the weight sensor is used for detecting the weight of the kettle, and the controller detects the weight sensor based on the electric kettle operation self-checking method described in the embodiments of the application to realize the operation self-checking of the electric kettle. The above has been described, and will not be repeated here.

[0163] In order to better understand the above scheme, the following will be explained and described in detail in combination with a specific embodiment.

[0164] As shown in Figure 1 In one embodiment, an electric kettle comprises a base, a kettle, a controller, a prompt module and a weight sensor. The base is a cast iron kettle base, which is used for heating the cast iron kettle. The weight sensor is installed on the kettle base and is used for detecting the overall weight of the kettle in real time and outputting a weight signal. The controller is an MCU control module, which is connected to the weight circuit to which the weight sensor belongs, can receive the weight signal of the weight sensor and calculate the weight change, judges the working state of the kettle according to the time signal and the weight change, and controls the heating element in the base to be powered off or the prompt module to trigger an alarm when an abnormal state is detected. The prompt module, also known as the alarm module, comprises a buzzer, an LED indicator or a communication module with a smart device, and is used for emitting sound, light signals or remote notification. The base comprises a heating element, which is used for heating water in the kettle and is controlled by the MCU control module.

[0165] In practical application, the specific steps are as follows:

[0166] First, the kettle is powered on and heating is started, confirming that the electric kettle is in the heating stage of operation.

[0167] A weight failure protection judgment delay time T_delay (for example: 480 seconds) is set, t is the time of the electric kettle heating, when t is less than T_delay (that is, in the early stage of heating), the MCU control module does not perform weight failure judgment, so as to avoid the normal situation that the weight change is weak when the water has not started to boil being misjudged; once t is greater than or equal to T_delay, the subsequent judgment process steps are started.

[0168] Optionally, cross verification can also be combined with current power consumption fluctuation. The MCU control module simultaneously collects the change of heating current, if the current continuously stays in the heating power segment, the weight data can be analyzed in combination with the weight failure protection judgment delay time, for example, when the kettle has been in the heating power segment for a long time, but the weight has been stable for a long time, that is, the water has not been significantly reduced, it is considered that there is an abnormal risk of weight data. In this way, through multi-dimensional signal fusion judgment, the judgment accuracy is improved, which is suitable for excluding false triggering scenarios.

[0169] Enter the judgment process:

[0170] When t is greater than or equal to T_delay, synchronous weight data periodic collection is started, the sampling interval is △t seconds (for example: 200 ms); the array length N (for example: 20) is initialized, which is used to store the weight data W1, W2... Wn collected each time.

[0171] Calculate the maximum value and minimum value difference △W, if △W is less than a preset value ε1 (for example: 1), it is considered that the weight is stable; calculate the standard deviation σ, if σ is less than a preset value ε2 (for example: 0.5), it is considered that the fluctuation is minimal. The calculation methods of the difference △W (range value) and the standard deviation σ (standard deviation value) have been recorded in the foregoing, and will not be repeated here.

[0172] The weight failure integral P mechanism is introduced to enhance robustness, 1 point is added for each time the above difference is stable, 1 point is added for each time the above standard deviation is minimal, and 2 points are added for each time the weight data sampling is consistent for M times (for example: 10 times). After the integral P reaches the set threshold (for example: 10 points), it is confirmed that the weight sensor abnormal state is established.

[0173] If the weight failure integral exceeds the standard, the system judges that the weighing system fails, and the MCU control module performs one or any two or more combinations of the following operations:

[0174] 1. disconnect the power supply and stop heating. 2. the buzzer emits a sound or the LED light alarm reminds the user 3. send an abnormal state notification through the communication module and the smart device (such as a mobile phone APP) connected to the kettle.

[0175] After determining that the weight sensor is invalid, the weighing circuit power can be automatically cut off and the weighing module can be restarted every interval set time (e.g., 60 seconds), and whether the first weight value after the restart is significantly different from the last value is observed to determine whether the sensor is still working effectively. If the reading is still unchanged or abnormal after the restart, it is determined that the weight data is abnormal. This method increases the detection dimension by actively disturbing and improves the recognition ability of the invalid phenomenon.

[0176] In this embodiment, by setting the delay judgment time, difference analysis, standard deviation analysis and integral abnormality recognition algorithm, the determination of the weight sensor abnormality, data stuck and the like is realized, and the protection or reminder is triggered. Focusing on the determination of the potential dangerous state of "no change in weight for a long time during heating", the fault tolerance and safety of the electric kettle control system are improved, which is suitable for cast iron electric kettles and other products without temperature sensing capability, and the use reliability and safety are improved.

[0177] It should be understood that although each step in the flowchart involved in each of the above embodiments is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each of the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps.

[0178] Based on the same inventive concept, the present application also provides an electric kettle operation self-checking device for implementing the above-mentioned electric kettle operation self-checking method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more electric kettle operation self-checking device embodiments provided below can refer to the limitations of the electric kettle operation self-checking method described above, which will not be repeated here.

[0179] In one exemplary embodiment, as shown in Figure 10 An electric kettle operation self-checking device is provided, comprising: a data collection module 1002, a data processing module 1004 and a self-checking output module 1006, wherein:

[0180] The data collection module 1002 is configured to obtain a weight data set obtained by a weight sensor arranged in the electric kettle through real-time detection of the electric kettle.

[0181] The data processing module 1004 is configured to determine a weight data dispersion index of the weight sensor based on the weight data set.

[0182] The self-check output module 1006 is configured to determine that the weight sensor of the electric kettle is invalid when the weight data dispersion index reaches a preset dispersion value.

[0183] In one of the embodiments, the data processing module 1004 is further configured to perform at least one of the following:

[0184] The first one is to calculate and determine an extreme difference value based on each weight data value in the weight data set; the second one is to calculate and determine a standard deviation value based on each weight data value in the weight data set; and the third one is to determine a repeated sampling sequence based on a sequence of each weight data value in the weight data set.

[0185] In one of the embodiments, the data processing module 1004 is further configured to filter a maximum weight data value and a minimum weight data value from each weight data value in the weight data set, calculate a difference value between the maximum weight data value and the minimum weight data value, and mark the difference value as the extreme difference value.

[0186] In one of the embodiments, the data processing module 1004 is further configured to calculate an average value based on each weight data value in the weight data set, and calculate the standard deviation value based on the average value.

[0187] In one of the embodiments, the data processing module 1004 is further configured to arrange each weight data value in the weight data set according to a sequence of acquisition time, and perform secondary filtering on weight data values with the same value of adjacent weight data values to obtain the repeated sampling sequence.

[0188] In one of the embodiments, the electric kettle operation self-check device further comprises an integral self-check module configured to determine a weight failure integral of the weight sensor based on the weight data dispersion index after the data processing module 1004 is executed, and the corresponding self-check output module 1006 is adjusted to be configured to determine that the weight sensor of the electric kettle is invalid when the weight failure integral reaches a preset failure value.

[0189] In one of the embodiments, the integral self-check module is further configured to determine the weight failure integral of the weight sensor according to at least one of the extreme difference value, the standard deviation value and the repeated sampling sequence.

[0190] In one of the embodiments, the integral self-checking module is further configured to determine the integral in the first integral pool according to a comparison result of the range value and a preset range value; determine the integral in the second integral pool according to a comparison result of the standard deviation value and a preset standard deviation; and determine the integral in the third integral pool according to a comparison result of the number of the weight data values in the repeated sampling sequence and a preset repetition threshold. The weight failure integral of the weight sensor is determined based on at least one of the first integral pool, the second integral pool and the third integral pool.

[0191] In one of the embodiments, the electric kettle running self-checking device further comprises a delay detection module configured to record a running duration when the electric kettle is in a running state before the data collection module 1002 acquires the weight data set detected by the weight sensor in real time. The data processing module 1004 is executed when the running duration reaches a preset duration.

[0192] In one of the embodiments, the electric kettle running self-checking device further comprises a current inspection module configured to acquire working current data of the electric kettle after the delay detection module, and analyze whether the electric kettle is in a heating stage based on the working current data. The data processing module 1004 is executed when the running duration reaches the preset duration and the electric kettle is in the heating stage.

[0193] In one of the embodiments, the electric kettle running self-checking device further comprises a restart verification module configured to control the weight sensor to restart at a preset restart frequency and acquire restart weight data collected by the weight sensor after the restart, and determine that the weight sensor is restored to be effective when the restart weight data does not match the weight data values in the weight data set.

[0194] The above-mentioned modules in the electric kettle running self-checking device can be all or partially realized by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of a processor in a computer device in a hardware form, or stored in a memory in a computer device in a software form, so as to be called and executed by a processor to perform the operations corresponding to the above-mentioned modules.

[0195] In one of the embodiments, a computer device is provided, which can be a terminal, and an internal structure diagram of the computer device can be as shown in Figure 11The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus. The communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to perform wired or wireless communication with external terminals. The wireless communication can be achieved through WIFI, mobile cellular network, near field communication (NFC) or other technologies. The computer program is executed by the processor to implement a method for performing self-checking on an electric kettle. The display unit of the computer device is configured to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, a trackball or a touchpad arranged on the shell of the computer device, or an external keyboard, a touchpad or a mouse, etc.

[0196] Those skilled in the art can understand that Figure 11 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0197] In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps:

[0198] In one embodiment, a computer device is also provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps in the above method embodiments.

[0199] In one embodiment, a computer readable storage medium is provided, storing a computer program, and the computer program is executed by a processor to implement the steps in the above method embodiments.

[0200] In an embodiment, a computer program product is provided including a computer program which, when executed by a processor, implements the steps of any of the above method embodiments. It will be understood by those of ordinary skill in the art that implementing all or part of the processes of the above embodiments can be through computer program instructions. These computer program instructions can be provided to relevant hardware by a computer program product, which can be stored in a nonvolatile memory. When the computer program is executed, it can include the processes of the above embodiments. Any reference in the embodiments of the present application to a memory, a database, or other medium can include at least one of a nonvolatile memory and a volatile memory. The nonvolatile memory can include a read-only memory (ROM), a magnetic tape, a floppy disk, a flash memory, an optical memory, a high-density embedded nonvolatile memory, a resistive random access memory (ReRAM), a magnetoresistive random access memory (MRAM), a ferroelectric random access memory (FRAM), a phase change memory (PCM), a graphene memory, and the like. The volatile memory can include a random access memory (RAM) or an external cache memory, and the like. As an illustration but not limitation, the RAM can be in a variety of forms, such as a static random access memory (SRAM) or a dynamic random access memory (DRAM), and the like. The database involved in the embodiments of the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, and the like, but is not limited thereto. The processor involved in the embodiments of the present application can be a general processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, and the like, but is not limited thereto.

[0201] Any of the technical features of the above embodiments can be combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not contradict, they should be considered within the scope of the present application.

[0202] The above-described embodiments are merely illustrative of several embodiments of the present application, and the description is relatively specific and detailed, but should not be understood as a limitation on the scope of the patent. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of protection of the present application should be subject to the appended claims.

Claims

1. A self-test method for electric kettle operation, characterized in that, The method includes: Obtain the weight dataset of an electric kettle obtained in real time from a weight sensor; Based on the weight dataset, determine the discrete index of the weight data of the weight sensor; If the weight data dispersion index reaches a preset dispersion value, the weight sensor of the electric kettle is determined to be faulty.

2. The method according to claim 1, characterized in that, The determination of the weight data discrete index of the weight sensor based on the weight dataset includes at least one of the following: First item, Based on the weight data values ​​in the weight dataset, the range value is calculated and determined. The second item, Based on the weight data values ​​in the weight dataset, the standard deviation is calculated and determined. The third item, Based on the sequence of weight data values ​​in the weight dataset, a repeat sampling sequence is determined.

3. The method according to claim 2, characterized in that, The step of calculating and determining the range value based on each weight data value in the weight dataset includes: From the weight data values ​​in the weight dataset, the largest and smallest weight data values ​​are selected, the difference between the largest and smallest weight data values ​​is calculated, and the difference is marked as the range value.

4. The method according to claim 2, characterized in that, The step of calculating and determining the standard deviation based on each weight data value in the weight dataset includes: The average value is calculated based on each weight data value in the weight dataset, and the standard deviation is calculated based on the average value.

5. The method according to claim 2, characterized in that, The determination of the repeated sampling sequence based on the sequence of weight data values ​​in the weight dataset includes: Arrange the weight data values ​​in the weight dataset according to the sequence of acquisition time; Weight data values ​​with the same value but adjacent weight data values ​​are further filtered to obtain a repeated sampling sequence.

6. The method according to claim 2, characterized in that, After determining the discrete index of the weight data of the weight sensor based on the weight dataset, the method further includes: The weight failure integral of the weight sensor is determined based on the discrete index of the weight data. The step of determining that the weight sensor of the electric kettle is faulty when the weight data dispersion index reaches a preset dispersion value includes: If the weight failure integral reaches a preset failure value, the weight sensor of the electric kettle is determined to be faulty.

7. The method according to claim 6, characterized in that, The determination of the weight failure integral of the weight sensor based on the discrete index of the weight data includes: The weight failure integral of the weight sensor is determined based on at least one of the range, the standard deviation, and the repeated sampling sequence.

8. The method according to claim 7, characterized in that, Determining the weight failure integral of the weight sensor based on at least one of the range value, the standard deviation value, and the repeated sampling sequence includes: The integral in the first integral pool is determined based on the comparison result between the range value and the preset difference value; Based on the comparison between the standard deviation value and the preset standard deviation, the integral in the second integration pool is determined; The integral in the third integration pool is determined by comparing the number of weight data values ​​in the repeated sampling sequence with the preset repetition threshold. The weight failure integral of the weight sensor is determined based on at least one of the first integral pool, the second integral pool, and the third integral pool.

9. The method according to claim 1, characterized in that, Before acquiring the weight dataset obtained by the weight sensor in real time from the electric kettle, the method further includes: While the electric kettle is running, record the running time; If the runtime reaches the preset duration, the process of obtaining the weight dataset obtained by the weight sensor in real time from the electric kettle is executed.

10. The method according to claim 9, characterized in that, The method further includes: Obtain the operating current data of the electric kettle, and analyze whether the electric kettle is in the heating stage based on the operating current data; When the running time reaches the preset duration and the electric kettle is in the heating stage, the process of obtaining the weight dataset obtained by the weight sensor in real time is executed.

11. The method according to claim 1, characterized in that, After determining that the weight sensor of the electric kettle has failed when the weight data dispersion index reaches a preset dispersion value, the method further includes: The weight sensor is restarted according to a preset restart frequency, and the restart weight data collected by the weight sensor after restart is obtained. If the restarted weight data does not match the weight data value in the weight dataset, it is determined that the weight sensor has been successfully restored.

12. A self-testing device for an electric kettle, characterized in that, The device includes: The data collection module is used to acquire the weight dataset obtained by the weight sensor in real time from the electric kettle. The data processing module is used to determine the discrete index of the weight data of the weight sensor based on the weight dataset; The self-test output module is used to determine that the weight sensor of the electric kettle is faulty when the weight data discrete index reaches a preset discrete value.

13. An electric kettle, characterized in that, The electric kettle includes a base, a kettle, a controller, and a weight sensor. The kettle is fitted onto the base, the weight sensor is disposed on the base, and the controller is connected to the weight sensor. The base is used to heat the water in the kettle, the weight sensor is used to detect the weight of the kettle, and the controller detects the weight sensor based on the electric kettle operation self-test method according to any one of claims 1-11.

14. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 11.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 11.

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