Heating device and abnormality detection method, device, electronic device and storage medium thereof

Abstract

The present invention relates to the technical field of heating equipment, and provides a heating equipment and its abnormality detection method, device, electronic device and storage medium. The temperature abnormality detection method of the heating equipment includes: obtaining the actual temperature value of the heating equipment, the actual temperature value includes the current actual temperature value corresponding to the current moment, and the historical actual temperature value corresponding to the set time period before the current moment; obtaining the theoretical temperature value based on the actual temperature value, the theoretical temperature value includes the current theoretical temperature value corresponding to the current actual temperature value; based on the relationship between the current actual temperature value and the current theoretical temperature value meeting the set relationship, determining that the temperature of the heating equipment is abnormal. This method can detect the temperature abnormality of the heating equipment, control the heating equipment to perform relevant safety operations based on the detection results, or remind the user to perform relevant safety operations to ensure safe use and avoid danger.

Description

Technical Field

[0001] The present invention relates to the technical field of heating equipment, and in particular to heating equipment and an abnormality detection method, device, electronic equipment and storage medium thereof. Background Art

[0002] Detecting temperature anomalies in heating equipment is crucial to its safety, making it extremely important. For example, heaters can age over time. Furthermore, improper operation can lead to malfunctions. These factors can all contribute to temperature anomalies in heaters, potentially causing fires. Alternatively, a temperature anomaly could prevent the heater from providing adequate heat, potentially catching a cold. Summary of the Invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides a method for detecting temperature anomalies of a heating device to ensure the safe use and normal operation of the heating device.

[0004] The present invention also provides a device for detecting abnormal temperature of a heating device.

[0005] The present invention also provides a heating device.

[0006] The present invention also provides a server.

[0007] The present invention also provides an electronic device.

[0008] The present invention also provides a non-transitory computer-readable storage medium.

[0009] A method for detecting temperature anomaly of a heating device according to an embodiment of a first aspect of the present invention includes:

[0010] Obtaining an actual temperature value of the heating device, the actual temperature value including a current actual temperature value corresponding to the current moment and a historical actual temperature value corresponding to a set time period before the current moment;

[0011] acquiring a theoretical temperature value based on the actual temperature value, the theoretical temperature value including a current theoretical temperature value corresponding to the current actual temperature value;

[0012] Based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying a set relationship, it is determined that the temperature of the heating device is abnormal.

[0013] The temperature anomaly detection method according to an embodiment of the present invention can detect temperature anomalies in heating equipment and, based on the detection results, control the heating equipment to perform relevant safety operations or remind the user to perform relevant safety operations, thereby ensuring the safe use of the heating equipment and avoiding dangers. In particular, when a fire occurs in the heating equipment, the temperature anomaly detection method according to an embodiment of the present invention can establish a fire warning mechanism, improving the safety of the heating equipment.

[0014] 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 values ​​are sorted in chronological order.

[0015] According to one embodiment of the present invention, the step of obtaining a theoretical temperature value based on the actual temperature value includes:

[0016] Establishing a linear regression model between the actual temperature value and a timestamp corresponding to the actual temperature value;

[0017] The current theoretical temperature value is obtained based on the linear regression model.

[0018] According to one 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:

[0019] Based on the linear regression equation: T i =k*t i +b calculates the least squares solutions k0 and b0 of k and b; wherein i=1, 2, 3, ..., n, refers to the serial number of the actual temperature value, and the serial number of the current actual temperature value is n; T i is the ith actual temperature value of the heating device; k and b are constants in the linear regression equation; t i The timestamp corresponding to the i-th actual temperature value of the heating device;

[0020] The step of obtaining the current theoretical temperature value based on the linear regression model includes:

[0021] Based on the formula k0*t n +b0 obtains the current theoretical temperature value.

[0022] According to one embodiment of the present invention, the step of determining that the temperature of the heating device is abnormal based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying a set relationship includes:

[0023] Obtaining a residual sequence of the theoretical temperature value and the corresponding actual temperature value, wherein the theoretical temperature value includes historical theoretical temperature values ​​corresponding to the historical actual temperature values; performing normalization processing on the residual sequence; and determining that the temperature of the heating device is abnormally increased if a current normalized residual value obtained through the normalization processing is greater than a first set parameter, or determining that the temperature of the heating device is abnormally decreased if a current normalized residual value obtained through the normalization processing is less than a second set parameter;

[0024] and / or,

[0025] Based on the fact that the current actual temperature value is greater than the upper quantile of the actual temperature values ​​within the set time period, it is determined that the temperature of the heating device has increased abnormally; or based on the fact that the current actual temperature value is less than the lower quantile of the actual temperature values ​​within the set time period, it is determined that the temperature of the heating device has decreased abnormally.

[0026] According to one embodiment of the present invention, in the step of obtaining the residual sequence of the theoretical temperature value and the corresponding actual temperature value, based on the formula: r = {k0*t i +b0-T i |i=1,2,3,…,n},

[0027] Obtain the residual sequence between the theoretical temperature value and the actual temperature value, r is the residual sequence obtained by arranging the residual values ​​of the theoretical temperature value and the actual temperature value in sequence, and the residual sequence r includes r i , r i =k0*t i +b0-T i , where i = 1, 2, 3, …, n;

[0028] In the step of normalizing the residual sequence, the mean μ and standard deviation s of the residual sequence are obtained, based on the formula The residual sequence is normalized, where is the normalized value of the i-th residual, i = 1, 2, 3, ... n;

[0029] In the step of determining that the temperature of the heating device is abnormally increased based on the current residual normalized value obtained by the normalization process is greater than the first set parameter, obtaining based on >The first setting parameter determines that the temperature of the heating device is abnormally increased, Standardized value for the current residual;

[0030] In the step of determining that the temperature of the heating device is abnormally reduced based on the current residual normalized value obtained by the normalization process is less than the second set parameter, obtaining based on <Second setting parameter, determining that the temperature of the heating device has dropped abnormally.

[0031] According to one embodiment of the present invention, the step of determining that the temperature of the heating device has abnormally increased based on the current actual temperature value being greater than the upper quantile of the actual temperature values ​​within the set time period, or determining that the temperature of the heating device has abnormally decreased based on the current actual temperature value being less than the lower quantile of the actual temperature values ​​within the set time period, includes:

[0032] Get the temperature sequence between the actual temperature value and the timestamp corresponding to the actual temperature value {(T i ,t i )|i=1,2,3,…,n};

[0033] Get the upper quantile α of the temperature series ε or the lower quantile α′ ε , where ε is the set value;

[0034] Based on the current actual temperature value T n >α ε , determine that the temperature of the heating device is abnormally increased, or, based on the current actual temperature value T n <α′ ε , it is determined that the temperature of the heating device has dropped abnormally.

[0035] According to one embodiment of the present invention, the first setting parameter is based on the The second setting parameter is determined based on the upper quantile of the statistical distribution of The lower quantile of the statistical distribution of is determined.

[0036] 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.

[0037] A temperature anomaly detection device for a heating device according to a second embodiment of the present invention includes:

[0038] A temperature acquisition module is used to obtain the actual temperature value of the heating device, wherein the actual temperature value includes the current actual temperature value corresponding to the current moment and the historical actual temperature value corresponding to the set time period before the current moment;

[0039] a calculation module, configured to obtain a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value includes a current theoretical temperature value corresponding to the current actual temperature value;

[0040] The judgment module is used to judge that the temperature of the heating device is abnormal based on whether the relationship between the current actual temperature value and the current theoretical temperature value satisfies a set relationship.

[0041] The technical effects of the device for detecting anomaly temperature of a heating device according to an embodiment of the present invention correspond to those of the method for detecting anomaly temperature of a heating device described above, and are not described in detail here.

[0042] According to the heating device of the third embodiment of the present invention,

[0043] include:

[0044] a processor, wherein when executing the computer program, the processor implements the steps of the above-mentioned method for detecting temperature anomaly of the heating device;

[0045] a temperature detector, configured to obtain an actual temperature value of the heating device and send the obtained value to the processor;

[0046] The processor sends a control signal and / or an alarm signal to the heating device based on the temperature abnormality of the heating device.

[0047] The heating device according to the embodiment of the present invention includes a processor that executes the temperature anomaly detection method for the heating device, and thus has the technical effects of the temperature anomaly detection device, which will not be described in detail here.

[0048] According to one embodiment of the present invention, the heating device is a heater, a water heater, a dryer, an induction cooker, an electric iron, an electric stove, a microwave oven, an induction cooker, an electric oven, an electric rice cooker, an electric blanket, an electric quilt or electric clothing.

[0049] According to an embodiment of the fourth aspect of the present invention, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the temperature anomaly detection method for a heating device as described above are implemented.

[0050] The technical effects of the electronic device according to the embodiment of the present invention correspond to the effects of the temperature anomaly detection method of the heating device described above, and are not described in detail here.

[0051] According to the non-transitory computer-readable storage medium of the fifth embodiment of the present invention, a computer program is stored thereon, and when the computer program is executed by a processor, the steps of the temperature anomaly detection method for the heating device as described above are implemented.

[0052] The technical effects of the non-transitory computer-readable storage medium according to an embodiment of the present invention correspond to those of the above-mentioned method for detecting temperature anomalies in heating equipment, and are not further described here.

[0053] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 1 is a flow chart of a method for detecting temperature anomaly of a heating device provided by an embodiment of the present invention;

[0056] Figure 2 This is a schematic diagram of a module of a temperature anomaly detection device for a heating device provided by an embodiment of the present invention;

[0057] Figure 3 2 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0059] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0060] Before describing the embodiments of the present invention in detail, the entire application scenario is described. The temperature anomaly detection method for heating equipment, the temperature anomaly detection device for heating equipment, the electronic device, and the readable storage medium of the embodiments of the present invention can be applied to cloud platforms in the field of the Internet of Things, cloud platforms in other types of Internet fields, or third-party devices, or heating equipment. Among them, third-party devices may include various types such as mobile phones, tablet computers, laptops, car computers, and other smart home appliances.

[0061] See Figure 1 According to the method for detecting temperature anomaly of a heating device according to the first embodiment of the present invention, please refer to Figure 1 ,include:

[0062] S1. Acquire the actual temperature value of the heating device. The actual temperature value includes the current actual temperature value corresponding to the current moment and the historical actual temperature value corresponding to the set time period before the current moment.

[0063] For example, in the case of a heating device temperature anomaly detection method applied to a cloud platform, the cloud platform obtains the actual temperature value from the heating device. The current actual temperature value refers to the currently detected temperature data of the heating device, or it can also be understood as the most recently measured temperature data of the heating device in chronological order.

[0064] Assume that during each temperature anomaly detection process, the cloud platform obtains the past hour's temperature data from the heating device, and the heating device uploads this data every ten minutes. In addition to the current actual temperature value, the cloud platform also obtains the six historical actual temperature values ​​uploaded by the heating device within the past hour. In this case, the set duration is one hour. Of course, the set duration can vary based on different circumstances. For example, for heating devices with large temperature fluctuations, the set duration can be longer, such as for a water heater, obtaining temperature data from the past 24 hours. For devices with smaller temperature fluctuations, the set duration can be shorter, such as for a heater, obtaining temperature data from the past 12 hours. This is merely an example; the set duration can be within any reasonable range and can be less than half a day, more than a day, or between half a day and a day. Furthermore, the heating device can report its actual temperature values ​​at any regular interval; for example, it can report every ten minutes or at any other frequency.

[0065] According to embodiments of the present invention, generally, the longer the set time period, or the more frequently the heating device reports actual temperature values, the more accurate the theoretical temperature value ultimately obtained based on the actual temperature values. Of course, if the set time period is too long, more actual temperature values ​​need to be obtained, which may also affect the efficiency of calculating the theoretical temperature value.

[0066] In one embodiment, for example, the cloud platform obtains the actual temperature value reported by the heating device. The heating device can package the actual temperature value and the timestamp corresponding to the actual temperature value and send them to the cloud platform, thereby establishing a one-to-one correspondence between the actual temperature value and the timestamp. Of course, the timestamp does not necessarily need to be obtained from the heating device. For example, after the cloud platform obtains the actual temperature value from the heating device, it can also establish a mapping relationship between the actual temperature value and the timestamp on the cloud platform.

[0067] According to an embodiment of the present invention, the type of heating device is not limited, and may be a heater, water heater, dryer, induction cooker, electric iron, electric stove, microwave oven, induction cooker, electric oven, electric rice cooker, electric blanket, electric quilt or electric clothing, etc.

[0068] For example, heaters are often left on for extended periods during winter in northern China, making temperature anomaly detection crucial. If temperature anomalies are detected, a fire could be brewing. This temperature anomaly detection method can identify the situation promptly, preventing the fire from escalating and ensuring user safety.

[0069] In one embodiment, one on and one off of the heating device corresponds to one working process. During the working process, the cloud platform obtains the current actual temperature value and the historical actual temperature values ​​within a set time period.

[0070] According to an embodiment of the present invention, the current actual temperature value and the historical actual temperature values ​​are sorted in chronological order. On this basis, subsequent steps perform relevant processing based on the sorted actual temperature values.

[0071] S2. 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.

[0072] After obtaining multiple actual temperature values, a current theoretical temperature value corresponding to the current actual data can be obtained based on analysis and processing of the multiple actual temperature values. For example, the theoretical current temperature data can be obtained through finite element analysis of the multiple actual temperature values. Alternatively, the theoretical current temperature data can be obtained through finite element analysis of the multiple actual temperature values ​​using simulation analysis.

[0073] For heating equipment, the temperature data changes within a set time period often show a specific pattern. Based on this pattern, the current theoretical temperature value can be calculated.

[0074] In one embodiment, step S2 includes:

[0075] S201, establishing a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value;

[0076] S202: Obtain the current theoretical temperature value based on the linear regression model.

[0077] In step S201, the timestamp can be obtained together with the actual temperature value, that is, the timestamp corresponding to the actual temperature value is obtained at the same time as the heating device is obtained in step S1. For example, the heating device can package the actual temperature value and the timestamp together to form actual temperature data and send it to the cloud.

[0078] For example, if the time duration is set to 1 hour, then within that hour, assuming the total number of actual temperature values, including the current actual temperature value and historical actual temperature values, is n, then the number of timestamps corresponding to the actual temperature values ​​is also n. A linear regression model is established based on the actual temperature value and timestamp, and the current theoretical temperature value is calculated based on the linear regression model. Similarly, the theoretical temperature value is also associated with the timestamp, and each theoretical temperature value has its own unique timestamp.

[0079] In step S202 , based on the linear regression model obtained in step S201 , the current theoretical temperature value may be obtained based on the linear regression model.

[0080] Of course, it should be noted that, in addition to using the linear regression model to obtain the theoretical temperature value, the theoretical temperature value can also be obtained through other calculation models disclosed in the prior art.

[0081] According to an embodiment of the present invention, step S201 includes:

[0082] Based on the linear regression equation: T i =k*t i +b calculates the least squares solutions k0 and b0 of k and b; where i = 1, 2, 3, ..., n, i is the serial number of the actual temperature value of the heating device determined in chronological order, and the serial number of the current actual temperature value is n; T i is the actual temperature value of the heating equipment i; k and b are constants in the linear regression equation; t i The timestamp corresponding to the i-th actual temperature value of the heating device;

[0083] Step S202 includes: based on the formula k0*t n+b0 obtains the current theoretical temperature value.

[0084] S3. Based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying the set relationship, it is determined that the temperature of the heating device is abnormal.

[0085] In step S3, generally, when the actual temperature value differs greatly from the theoretical temperature value, it indicates that the temperature of the heating device is abnormal.

[0086] In one embodiment, a direct comparison is made between the current actual temperature value and the current theoretical temperature value. If the current actual temperature value is significantly greater than the current theoretical temperature value, the heating device temperature is determined to be abnormal, indicating a possible fire. Based on this, the user can be prompted to investigate the specific condition of the heating device. Alternatively, if the current actual temperature value is significantly less than the current theoretical temperature value, the heating device temperature is determined to be abnormal, indicating that the heating device may not be properly turned on.

[0087] Of course, judging whether a temperature anomaly occurs based solely on a direct comparison of the current actual temperature value with the current theoretical temperature value may result in a certain probability of misjudgment. Therefore, according to one embodiment of the present invention, step S3 includes:

[0088] S301, obtaining a residual sequence of theoretical temperature values ​​and corresponding actual temperature values, wherein the theoretical temperature values ​​include historical theoretical temperature values ​​corresponding to historical actual temperature values;

[0089] S302, performing standardization processing on the residual sequence;

[0090] S303: If the current residual normalized value obtained by the normalization process is greater than the first setting parameter, it is determined that the temperature of the heating device has abnormally increased; or if the current residual normalized value obtained by the normalization process is less than the second setting parameter, it is determined that the temperature of the heating device has abnormally decreased.

[0091] In S301, based on the formula: r={k0*t i +b0-T i |i=1,2,3,…,n},

[0092] Obtain the residual sequence between the theoretical temperature value and the actual temperature value, r is the residual sequence obtained by arranging the residual values ​​of the theoretical temperature value and the actual temperature value in sequence. The residual sequence r includes r i , r i =k0*t i +b0-T i , where i = 1, 2, 3,…, n.

[0093] In S302, the mean μ and standard deviation s of the residual sequence are obtained, based on the formula The residual sequence is normalized, where is the normalized value of the i-th residual, i = 1, 2, 3, ... n.

[0094] In S303, obtain based on >The first setting parameter determines that the temperature of the heating device is abnormally increased, Normalize the current residual. Alternatively, get based on <Second setting parameter, determining that the temperature of the heating device has dropped abnormally.

[0095] In addition, in S303, if the current residual normalization value is greater than the first setting parameter, or the current residual normalization value is less than the second setting parameter, it means that the current actual temperature value has undergone a sudden change. Therefore, based on the fact that the current residual normalization value is greater than the first setting parameter, or the current residual normalization value is less than the second setting parameter, it can be determined that the temperature of the heating equipment has increased or decreased abnormally.

[0096] In another embodiment, step S3 includes:

[0097] S301', based on the current actual temperature value being greater than the upper quantile of the actual temperature values ​​within the set time length, determine that the temperature of the heating device has abnormally increased, or based on the current actual temperature value being less than the lower quantile of the actual temperature values ​​within the set time length, determine that the temperature of the heating device has abnormally decreased.

[0098] In S301', the upper quantile of the actual temperature value within the set time period can be understood as the upper temperature limit for normal operation of the heating device. If the actual temperature value exceeds the upper quantile, there is a certain probability that the heating device has experienced an abnormality. Therefore, if the current actual temperature value exceeds the upper quantile, it can be preliminarily determined that the current actual temperature value is higher than the normal operating temperature of the heating device, and a fire may be preliminarily suspected in the heating device.

[0099] By the same token, if the current actual temperature value is less than the lower percentile of the actual temperature value within the set duration, it can be preliminarily determined that the heating device has not been turned on normally. In other words, the lower percentile of the actual temperature value within the set duration can be understood as the lower temperature limit for normal operation of the heating device. Once the actual temperature value is less than the lower percentile, it means that there is a certain probability that the heating device has an abnormality, such as insufficient fuel supply for a fuel heating device or a short circuit in an electric heating device. Therefore, if the current actual temperature value is less than the lower percentile of the actual temperature value, it can be preliminarily determined that the current actual temperature value is lower than the normal operating temperature value of the heating device, and it can be preliminarily determined that the heating device may have problems such as insufficient fuel or insufficient power supply.

[0100] In S301′, the temperature sequence {(T i ,t i )|i=1,2,3,…,n};

[0101] Get the upper quantile α of the temperature series ε or the lower quantile α′ ε , where ε is the set value;

[0102] Based on the current actual temperature value T n >α ε , determine that the temperature of the heating device is abnormally increased, or, based on the current actual temperature value T n <α′ ε , it is determined that the temperature of the heating device has dropped abnormally.

[0103] Among them, the upper quantile is recorded as α ε , ε is the set value, when ε is 2, α ε is the upper quartile; when ε is 4, α ε Of course, the value of ε is not limited to the example given here, and it can also be other natural numbers.

[0104] In another embodiment, S3 includes both of the above judgment methods. That is, the heating device temperature is determined to be abnormal only if the current normalized residual value obtained from the normalization process is greater than the first set parameter or less than the second set parameter, and at the same time, the current actual temperature value is greater than the upper quantile of the actual temperature values ​​within the set time period or less than the lower quantile of the actual temperature values ​​within the set time period. This minimizes the likelihood of misjudgment, thereby improving user experience.

[0105] There are two types of abnormalities in the heating device temperature: the first is when the actual temperature value is too high, and the second is when the actual temperature value is too low. Of these, analyzing the current actual temperature value is the most practical, allowing for timely assessment of the heating device's operating status.

[0106] According to an embodiment of the present invention, when the current residual normalization 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 within the set time, the judgment of the temperature anomaly at this time belongs to the first abnormal situation, which is more for fire prevention.

[0107] When the normalization processing results in a current normalized residual value that is less than the second set parameter, and the current actual temperature value is less than the lower quantile of the actual temperature value within the set time, the judgment of the temperature anomaly at this time belongs to the second abnormal situation, which is more for judging whether the heating equipment is working normally.

[0108] In one embodiment, the first setting parameter is based on The second parameter setting is based on the upper quantile of the statistical distribution of The lower quantile of the statistical distribution of is determined. " The upper quantile of the statistical distribution of the "upper quantile" refers to the number of the statistical distribution of the upper quantile. The normalized numerical sequence of , and obtain the upper quantile of the normalized numerical sequence of . Similarly, " The lower quantile of the statistical distribution of " refers to the lower quantile of the normalized numerical sequence.

[0109] In one embodiment, the first setting parameter is set to 4, that is, based on the current residual normalization value Determine if the temperature of the heating equipment is abnormal.

[0110] The method for detecting temperature anomalies in heating equipment according to an embodiment of the present invention can detect temperature anomalies in the heating equipment and, based on the detection results, control the heating equipment to perform relevant safety operations or remind the user to perform relevant safety operations, thereby ensuring the safe use of the heating equipment and avoiding dangers. In particular, in the event of a fire in the heating equipment, the method for detecting temperature anomalies in the heating equipment according to an embodiment of the present invention can establish a fire warning mechanism, improving the safety of the heating equipment.

[0111] It should be noted that the above steps S1 to S3, and steps S301 to S303 are only for the convenience of expression, and do not constitute a time sequence limitation for each step of the method for detecting a temperature anomaly of a heating device. In addition, some contents are described in detail in the method for detecting a temperature anomaly of a heating device provided in the embodiment of the first aspect of the present invention. Since the contents of all the methods for detecting a temperature anomaly of a heating device are also applicable to the temperature anomaly detection device for a heating device provided in the embodiment of the second aspect, in order to avoid repetition, the temperature anomaly detection device for a heating device provided in the embodiment of the second aspect is not described in detail. Similarly, the contents of the above two aspects of the embodiments can be used to explain the contents of all subsequent embodiments, so the repeated contents will not be repeated in the subsequent embodiments.

[0112] See Figure 2 According to an embodiment of the second aspect of the present invention, there is provided a device for detecting temperature anomaly of a heating device, comprising:

[0113] The temperature acquisition module 201 is used to obtain the actual temperature value of the heating device, which includes the current actual temperature value corresponding to the current moment and the historical actual temperature value corresponding to the set time period before the current moment;

[0114] A calculation module 202 is configured to obtain a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value includes a current theoretical temperature value corresponding to the current actual temperature value;

[0115] The judgment module 203 is configured to judge that the temperature of the heating device is abnormal based on whether the relationship between the current actual temperature value and the current theoretical temperature value satisfies a set relationship.

[0116] The device for detecting temperature anomalies of a heating device according to an embodiment of the present invention can improve the safety of use of the heating device and determine whether the heating device is operating normally.

[0117] In one embodiment, the calculation module 202 includes:

[0118] A model building submodule is used to build a linear regression model between the actual temperature value and the timestamp corresponding to the actual temperature value;

[0119] The theoretical temperature value acquisition submodule is used to obtain the current theoretical temperature value based on the linear regression model.

[0120] In one embodiment, the model building submodule is based on the linear regression equation:

[0121] T i =k*t i +b calculates the least squares solutions k0 and b0 of k and b;

[0122] Wherein, i=1, 2, 3, ..., n refers to the serial number of the actual temperature value, and the serial number of the current actual temperature value is n; T i is the actual temperature value of the heating equipment i; k and b are constants in the linear regression equation; t i The timestamp corresponding to the i-th actual temperature value of the heating device.

[0123] The current theoretical temperature value acquisition submodule is based on the formula k0*t n +b0 obtains the current theoretical temperature value.

[0124] In one embodiment, the determination module 203 includes:

[0125] The residual sequence building submodule is used to obtain the residual sequence of the theoretical temperature value and the corresponding actual temperature value;

[0126] Normalization submodule, used to standardize the residual sequence;

[0127] The first temperature judgment submodule is used to determine that the temperature of the heating device has abnormally increased if the current residual normalized value obtained by the normalization processing is greater than the first set parameter, or to determine that the temperature of the heating device has abnormally decreased if the current residual normalized value obtained by the normalization processing is less than the second set parameter.

[0128] In one embodiment, the determination module 203 includes:

[0129] The second temperature judgment submodule is used to determine that the temperature of the heating equipment has increased abnormally based on the current actual temperature value being greater than the upper quantile of the actual temperature values ​​within the set time length, or to determine that the temperature of the heating equipment has decreased abnormally based on the current actual temperature value being less than the lower quantile of the actual temperature values ​​within the set time length.

[0130] In one embodiment, the residual sequence building submodule is based on the formula:

[0131] r={k0*t i +b0-T i |i=1,2,3,…,n}, obtain the residual sequence between the theoretical temperature value and the actual temperature value, r is the residual sequence obtained by arranging the residual values ​​of the theoretical temperature value and the actual temperature value in sequence, and the residual sequence r includes r i , r i =k0*t i +b0-T i .

[0132] Where i = 1, 2, 3, ..., n, that is, r includes r1, r2, r3 ... r n ;

[0133] The standardization submodule is used to obtain the mean μ and standard deviation s of the residual sequence, and based on the formula Normalize the residual sequence, where is the normalized value of the i-th residual, i = 1, 2, 3, ... n;

[0134] The first temperature judgment submodule is used to obtain based on >The first setting parameter determines whether the temperature of the heating device is abnormal.

[0135] In one embodiment, the determination module 203 includes:

[0136] The temperature sequence submodule is used to obtain the temperature sequence between the actual temperature value and the timestamp corresponding to the actual temperature value {(T i ,t i )|i=1,2,3,…,n};

[0137] Quantile acquisition module, used to obtain the upper quantile α of the temperature series ε or the lower quantile α′ ε , where ε is the set value;

[0138] The second temperature judgment submodule is used to determine the actual temperature based on the current actual temperature value T n >α ε , or, T n <α′ ε Determine if the temperature of the heating equipment is abnormal.

[0139] According to an embodiment of a third aspect of the present invention, a heating device is provided, comprising a processor and a temperature detector. When the processor executes a computer program, the processor implements the steps of the method for detecting a temperature anomaly in a heating device, wherein the temperature detector is configured to obtain an actual temperature value of the heating device and transmit the value to the processor, and the processor transmits a control signal and / or an alarm signal to the heating device based on the temperature anomaly in the heating device.

[0140] In one embodiment, the processor sends a control signal to the heating device based on the determination module 203 that the temperature of the heating device is abnormal. Specifically, if the temperature of the heating device is detected to be too high, the heating device is controlled to be turned off to prevent a fire or to prevent a fire from worsening. If the temperature of the heating device is detected to be too low, the heating device is controlled to be automatically turned on.

[0141] In another embodiment, the processor sends an alarm signal based on the judgment module 203 determining that the temperature of the heating device is abnormal.

[0142] In yet another embodiment, the processor sends an alarm signal and a control signal based on the determination by the determination module 203 that the temperature of the heating device is abnormal.

[0143] In one embodiment, the processor sends the alarm signal to the user terminal, so that the user terminal can monitor the working status of the heating device in real time.

[0144] 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 device can be detected.

[0145] According to an embodiment of the fourth aspect of the present invention, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for detecting temperature anomalies of a heating device when executing the computer program.

[0146] Figure 3 An example of a physical structure diagram of an electronic device is shown below. Figure 3As shown, the electronic device may include: a processor 310, a communication interface 320, a 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 the logic instructions in the memory 330 to execute the following method: obtaining the actual temperature value of the heating device, the actual temperature value including the current actual temperature value corresponding to the current moment and the historical actual temperature values ​​corresponding to the set time period before the current moment; obtaining the theoretical temperature value based on the actual temperature value, the theoretical temperature value including the current theoretical temperature value corresponding to the current actual temperature value; and determining that the temperature of the heating device is abnormal based on whether the relationship between the current actual temperature value and the current theoretical temperature value satisfies the set relationship.

[0147] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0148] Furthermore, an embodiment of the present invention discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided by the above-mentioned method embodiments, for example, including: obtaining the actual temperature value of the heating equipment, the actual temperature value including the current actual temperature value corresponding to the current moment, and the historical actual temperature values ​​corresponding to the set time period before the current moment; obtaining a theoretical temperature value based on the actual temperature value, the theoretical temperature value including the current theoretical temperature value corresponding to the current actual temperature value; and determining that the temperature of the heating equipment is abnormal based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying the set relationship.

[0149] On the other hand, an embodiment of the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the temperature anomaly detection method for the heating equipment provided in the above-mentioned embodiments, for example, including: obtaining the actual temperature value of the heating equipment, the actual temperature value including the current actual temperature value corresponding to the current moment, and the historical actual temperature values ​​corresponding to the set time period before the current moment; obtaining a theoretical temperature value based on the actual temperature value, the theoretical temperature value including the current theoretical temperature value corresponding to the current actual temperature value; and determining that the temperature of the heating equipment is abnormal based on the relationship between the current actual temperature value and the current theoretical temperature value satisfying the set relationship.

[0150] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. That is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0151] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or certain parts of the embodiment.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for detecting temperature anomaly of a heating device, characterized in that: include: Obtaining actual temperature values ​​of the heating device, the actual temperature values ​​including the current actual temperature value corresponding to the current moment and the historical actual temperature values ​​corresponding to a set time period before the current moment, and sorting the current actual temperature value and the historical actual temperature values ​​in chronological order; acquiring a theoretical temperature value based on the actual temperature value, the theoretical temperature value including a current theoretical temperature value corresponding to the current actual temperature value; Determining that the temperature of the heating device is abnormal based on that the relationship between the current actual temperature value and the current theoretical temperature value satisfies a set relationship includes: Obtaining a residual sequence of the theoretical temperature value and the actual temperature value corresponding thereto, wherein the theoretical temperature value includes a historical theoretical temperature value corresponding to the historical actual temperature value; and performing standardization on the residual sequence; Based on the fact that the current normalized residual value obtained by the normalization processing is greater than the first set parameter, and based on the fact that the current actual temperature value is greater than the upper quantile of the actual temperature values ​​within the set time period, it is determined that the temperature of the heating device has increased abnormally, and a fire has occurred; Based on the fact that the current residual normalized value obtained through the normalization processing is less than the second setting parameter, and based on the fact that the current actual temperature value is less than the lower quantile of the actual temperature value within the set time period, it is determined that the temperature of the heating device has dropped abnormally, and that the heating device has not been turned on normally.

2. The method for detecting temperature anomaly of a heating device according to claim 1, wherein: The step of obtaining a theoretical temperature value based on the actual temperature value comprises: Establishing a linear regression model between the actual temperature value and a timestamp corresponding to the actual temperature value; The current theoretical temperature value is obtained based on the linear regression model.

3. The method for detecting temperature anomaly of a heating device according to claim 2, wherein: 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 the linear regression equation: Calculate the least squares solution of k and b ; , refers to the serial number of the actual temperature value, and the serial number of the current actual temperature value is ; is the i-th actual temperature value of the heating device; and is the constant in the linear regression equation; The heating device The timestamp corresponding to the actual temperature value; The step of obtaining the current theoretical temperature value based on the linear regression model includes: Based on the formula Obtain the current theoretical temperature value.

4. The method for detecting temperature anomaly of a heating device according to claim 3, wherein: In the step of obtaining the residual sequence of the theoretical temperature value and the corresponding actual temperature value, based on the formula: ， Get the residual sequence between the theoretical temperature value and the actual temperature value, The residual sequence is obtained by arranging the residual values ​​of the theoretical temperature value and the actual temperature value in sequence. include , ,in, ; In the step of normalizing the residual sequence, the mean of the residual sequence is obtained. μ and standard deviation s , based on the formula The residual sequence is normalized, where For the i The standardized residual values, ; In the step of determining that the temperature of the heating device is abnormally increased based on the current residual normalized value obtained by the normalization process is greater than the first set parameter, obtaining , , determining that the temperature of the heating device is abnormally increased, Standardized value for the current residual; In the step of determining that the temperature of the heating device is abnormally reduced based on the normalization process to obtain a current residual normalized value that is less than a second set parameter, obtaining , , it is determined that the temperature of the heating device has dropped abnormally.

5. The method for detecting temperature anomaly of a heating device according to claim 3, wherein: The step of determining that the temperature of the heating device has abnormally increased based on the current actual temperature value being greater than the upper quantile of the actual temperature values ​​within the set time period, or determining that the temperature of the heating device has abnormally decreased based on the current actual temperature value being less than the lower quantile of the actual temperature values ​​within the set time period, includes: Get the temperature sequence between the actual temperature value and the timestamp corresponding to the actual temperature value ; Get the upper quantile of the temperature series or lower quantile , where ε is the set value; Based on the current actual temperature value , determine that the temperature of the heating device is abnormally increased, or, based on the current actual temperature value , it is determined that the temperature of the heating device has dropped abnormally.

6. The method for detecting temperature anomaly of a heating device according to claim 4, wherein: The first setting parameter is based on the The second setting parameter is determined based on the upper quantile of the statistical distribution of The lower quantile of the statistical distribution of is determined.

7. The method for detecting temperature anomaly of a heating device according to any one of claims 1 to 3, characterized in that: 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.

8. A device for detecting abnormal temperature of a heating device, characterized in that: include: a temperature acquisition module, configured to acquire the actual temperature value of the heating device, the actual temperature value including the current actual temperature value corresponding to the current moment and the historical actual temperature values ​​corresponding to the set time period before the current moment, and to sort the current actual temperature value and the historical actual temperature values ​​in chronological order; a calculation module, configured to obtain a theoretical temperature value based on the actual temperature value, wherein the theoretical temperature value includes a current theoretical temperature value corresponding to the current actual temperature value; A judgment module, for judging that the temperature of the heating device is abnormal based on that the relationship between the current actual temperature value and the current theoretical temperature value satisfies a set relationship, including: obtaining a residual sequence of the theoretical temperature value and the corresponding actual temperature value, wherein the theoretical temperature value includes a historical theoretical temperature value corresponding to the historical actual temperature value; performing standardization on the residual sequence; judging that the temperature of the heating device has abnormally increased and that a fire has occurred based on that the current residual standardized value obtained through the standardization is greater than a first set parameter, and based on that the current actual temperature value is greater than the upper quantile of the actual temperature values ​​within the set time period; judging that the temperature of the heating device has abnormally decreased and that the heating device has not been turned on normally based on that the current residual standardized value obtained through the standardization is less than a second set parameter, and based on that the current actual temperature value is less than the lower quantile of the actual temperature values ​​within the set time period.

9. A heating device, characterized in that: include: a processor, wherein when executing the computer program, the processor implements the steps of the method for detecting temperature anomaly of a heating device according to any one of claims 1 to 7; a temperature detector, configured to obtain an actual temperature value of the heating device and send the obtained value to the processor; The processor sends a control signal and / or an alarm signal to the heating device based on the temperature abnormality of the heating device.

10. The heating device according to claim 9, characterized in that The heating device is a heater, a water heater, a dryer, an induction cooker, an electric iron, an electric stove, a microwave oven, an induction cooker, an electric oven, an electric rice cooker, an electric blanket, an electric quilt or electric clothing.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for detecting temperature anomaly in a heating device according to any one of claims 1 to 7 are implemented.

12. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for detecting temperature anomaly of a heating device according to any one of claims 1 to 7 are implemented.

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