Intelligent electric oven temperature control regulation management system and method

Abstract

The invention discloses a temperature control regulation management system and method for an intelligent electric oven, relates to the technical field of temperature control regulation management, and aims to solve the problems that the temperature control precision is reduced and the overheating risk of equipment is increased. The temperatures of a shell and an exhaust port of the electric oven are detected through a temperature sensor, and different temperature control regulation modes are selected according to the detection result; when entering the first mode, collecting fan sound data, detecting the environment ventilation condition and generating a first regulation and control value in combination with the fan sound, and when entering the second mode, monitoring an insulating layer at the wire connecting part, judging the fracture condition according to the result, detecting the electric power, comprehensively generating a second regulation and control value and setting a regulation and control rule; whether a regulation signal is generated or not is judged based on the first, second and third regulation values, the regulation proportion is calculated, temperature control operation is performed on the electric oven in combination with the temperature of the shell and the exhaust port, the cooling regulation efficiency is improved, and the overheating risk in the operation process of the electric oven is effectively reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of temperature control adjustment management, more particularly, the present application relates to an intelligent electric oven temperature control adjustment management system and method. BACKGROUND

[0002] The existing electric oven temperature control system relies on a single temperature sensor to control the heating power through switches or PID to make the temperature close to the desired value, but it is easily limited by the sensor position and environmental conditions, and the temperature control is lagging, which easily causes local overheating or overcooling, and at the same time, it cannot monitor the insulation layer state and electric power in real time, and there is an overheating and safety risk.

[0003] The prior art has the following disadvantages: At present, the traditional system cannot dynamically switch modes according to the shell temperature, exhaust port temperature and environmental ventilation conditions, cannot assess the insulation layer state in real time, lacks multi-parameter comprehensive control ability, intelligent temperature control strategy and precise cooling adjustment mechanism, resulting in reduced temperature control accuracy and increased risk of equipment overheating, therefore, an intelligent electric oven temperature control adjustment management system and method are proposed.

[0004] The above information disclosed in the background section is only intended to enhance the understanding of the background of the present disclosure, and therefore it can include information that does not constitute the prior art known to those of ordinary skill in the art. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide an intelligent electric oven temperature control adjustment management system and method, which solves the problems raised in the above background technology by using multi-mode temperature control strategy, multi-parameter comprehensive control model and real-time insulation safety monitoring technology.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme, an intelligent electric oven temperature control adjustment management method, comprising the following steps: Step S1: detecting the temperature of the shell and exhaust port of the electric oven through a temperature sensor, and selecting to enter a first temperature control adjustment mode or a second temperature control adjustment mode according to the temperature detection results of the shell and exhaust port; Step S2: when entering the first temperature control adjustment mode, collecting the sound data of the oven fan, processing the sound data to generate a first control value, detecting the ventilation condition of the environment where the electric oven is located, and generating a second control value based on the ventilation condition; Step S3: when entering the second temperature control adjustment mode, monitoring the insulation layer at the wire connection, judging the insulation layer rupture condition according to the monitoring result, detecting the electric power of the electric oven, and generating a third control value by comprehensively considering the insulation layer rupture condition and the electric power; Step S4: setting the control rule, judging whether to generate the control signal and calculating the control ratio based on the first control value, the second control value and the third control value, and combining the temperature of the shell and the exhaust port of the electric oven to perform temperature control operation on the electric oven.

[0007] In a preferred embodiment, in step S1, a detection time is set, and the temperature of the shell and the exhaust port of the electric oven is detected within the detection time. The minimum value of the temperature of the shell and the exhaust port of the electric oven within the detection time is taken as the detection result of the shell temperature and the detection result of the exhaust port temperature, respectively.

[0008] In a preferred embodiment, in step S1, different adjustment analysis modes are selected based on the detection result of the shell temperature and the detection result of the exhaust port temperature. The specific steps are as follows: Temperature comparison: select the minimum value from the detection result of the shell temperature and the detection result of the exhaust port temperature as the judgment temperature into the judgment rule; Threshold selection: when the judgment temperature is the detection result of the shell temperature, if the judgment temperature is lower than the preset shell temperature threshold, the first temperature control adjustment mode is entered; when the judgment temperature is the detection result of the exhaust port temperature, if the judgment temperature is lower than the preset exhaust port temperature threshold, the second temperature control adjustment mode is entered.

[0009] In a preferred embodiment, in step S2, the fan sound data in the electric oven is the fan sound intensity in the electric oven. When the fan sound intensity is processed, a plurality of detection time points are set, and the fan sound intensity in the electric oven is detected at each detection time point. The detection results at each detection time point are combined into a sound intensity data set; The historical data is used to calculate the fan sound intensity reference. The historical data is the detection result of the electric oven fan sound intensity at a plurality of time points in the past. The median of the detection result of the electric oven fan sound intensity at a plurality of time points in the historical data is taken as the fan sound intensity reference; In the sound intensity data set, the minimum value is selected as the corrected sound intensity, and the ratio of the corrected sound intensity to the fan sound intensity reference is taken as the first control value.

[0010] In a preferred embodiment, in step S2, the ventilation condition of the environment where the electric oven is located is the air flow speed of the environment where the electric oven is located. At each detection time point, the air flow speed of the environment where the electric oven is located is detected, and the detection results are combined into a wind speed data set. The wind speed data set is processed by using the percentile method. The specific steps are as follows: The data in the wind speed data set is marked from back to front according to the sorting order until the number of marked data reaches the target screening number to stop marking to obtain a plurality of target data; The ratio of the average value in the target data to the preset wind speed reference is taken as a second protection visualization value.

[0011] In a preferred embodiment, in step S3, when entering the second temperature control adjustment mode, the insulation layer at the wire connection is detected by the online detection device; The insulation layer rupture condition is determined according to the monitoring result generated by the insulation detection device, and the insulation layer rupture condition includes a rupture area proportion and a rupture length sum; An image of the insulation surface of the wire is obtained through infrared thermal imaging information as a total surface area of the insulation layer, a rupture area image is extracted as an insulation layer rupture area, and the insulation layer rupture area is compared with the total surface area of the insulation layer to obtain the rupture area proportion; Skeletonization processing is performed in the rupture identification image, a rupture connected line segment is extracted, and the length of each rupture line segment is calculated, and the lengths of the rupture line segments are accumulated to obtain the rupture length sum.

[0012] In a preferred embodiment, in step S3, the rupture area proportion and the rupture length sum are standardized; The results of the weighted calculation of the standardized rupture area proportion and the rupture length sum are taken as the insulation layer rupture condition; By installing current sensors and voltage sensors in each circuit, current and voltage signals are collected in real time, and the instantaneous power of each circuit is calculated by multiplying the product of the power factor, and the instantaneous power of each circuit is accumulated to obtain the electric power of the electric oven; The electric power and the insulation layer rupture condition are standardized and then substituted into a product model to obtain a third control value.

[0013] In a preferred embodiment, in step S4, a control rule is set, if the first control value and the second control value are detected, it is considered that the first temperature control adjustment mode is entered, and a cooling treatment coefficient is obtained by substituting the first control value and the second control value into a polynomial regression calculation; The cooling treatment coefficient is multiplied by a preset control coefficient to obtain a control proportion of the first temperature control adjustment mode; The control proportion of the first temperature control adjustment mode is multiplied by the shell temperature of the electric oven to obtain a shell target temperature value; The shell temperature of the electric oven is cooled to the shell target temperature value according to the temperature control operation of the electric oven according to the shell target temperature value.

[0014] In a preferred embodiment, in step S4, if the third control value is detected, it is considered that the second temperature control adjustment mode is entered, and a control proportion of the second temperature control adjustment mode is obtained by multiplying the third control value by a preset control coefficient. The control proportion of the second temperature control adjustment mode is multiplied by the shell temperature of the electric oven to obtain an exhaust port target temperature value; The electric oven is controlled according to the exhaust port target temperature value, and the temperature of the exhaust port of the electric oven is cooled to the exhaust port target temperature value.

[0015] An intelligent electric oven temperature control adjustment management system includes a temperature detection module, a mode selection module, a control analysis module, and a control execution module, and each module is electrically connected; The functions of each module are as follows: The temperature detection module is used to collect the temperatures of the shell and the exhaust port of the electric oven and transmit them to the mode selection module; The mode selection module selects a temperature control adjustment mode based on the temperature detection results of the shell and the exhaust port of the electric oven, and sets the collected signals to be transmitted to the control analysis module according to different selection results; The control analysis module collects the fan sound data in the oven and the ventilation condition of the environment of the electric oven or collects the insulation layer rupture condition and the electric power of the electric oven connected at the electric wire, and transmits the collected results to the control execution module; The control execution module generates a first control value based on the fan sound data in the oven of the electric oven, generates a second control value based on the ventilation condition of the environment of the electric oven, generates a third control value based on the insulation layer rupture condition and the electric power, determines whether to generate a control signal according to the three control values through a control rule, and calculates a control proportion, and controls the electric oven through temperature control according to the temperatures of the shell and the exhaust port of the electric oven.

[0016] The technical effects and advantages of the present application are as follows: The temperature sensor detects the temperatures of the shell and the exhaust port of the electric oven, selects different temperature control adjustment modes according to the temperature detection results of the shell and the exhaust port, collects the fan sound data in the oven when entering the first temperature control adjustment mode, detects the ventilation condition of the environment of the electric oven, generates a first control value based on the fan sound data, monitors the insulation layer at the electric wire connection when entering the second temperature control adjustment mode, determines the insulation layer rupture condition according to the monitoring result, detects the electric power of the electric oven, generates a second control value based on the insulation layer rupture condition and the electric power, sets a control rule, determines whether to generate a control signal based on the first control value, the second control value, and the third control value, calculates a control proportion, and controls the electric oven through temperature control according to the temperatures of the shell and the exhaust port of the electric oven, so as to realize more accurate cooling control, improve the cooling control efficiency, effectively reduce the overheating risk during the operation of the electric oven, prolong the service life of the equipment, and improve the use safety. BRIEF DESCRIPTION OF DRAWINGS

[0017] Fig. 1This is a flow chart of a method for temperature control and regulation management of an intelligent electric oven according to the present invention.

[0018] Fig. 2 This is a module schematic diagram of an intelligent electric oven temperature control and management system of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] The present invention detects the temperatures of the outer shell and the exhaust port of the electric oven through a temperature sensor, and selects to enter different temperature control adjustment modes according to the temperature detection results of the outer shell and the exhaust port. When entering the first temperature control adjustment mode, the sound data of the fan in the oven is collected, the ventilation conditions of the environment in which the electric oven is located are detected, and a first control value is generated in combination with the fan sound data. When entering the second temperature control adjustment mode, the insulation layer at the connection of the wires is monitored, and the rupture of the insulation layer is judged according to the monitoring results. The electric power of the electric oven is detected, and the second control value is generated by comprehensively considering the rupture of the insulation layer and the electric power. A control rule is set, and it is determined whether to generate a control signal and calculate the control ratio based on the first control value, the second control value and the third control value. The electric oven is temperature-controlled in combination with the temperatures of the outer shell and the exhaust port of the electric oven, thereby achieving more accurate temperature reduction control and improving the temperature reduction control efficiency.

[0021] Example 1, a method for temperature control and management of an intelligent electric oven, such as Figs. 1-2 As shown, the following steps are included: Step S1: detecting the temperature of the outer shell and the exhaust port of the electric oven through a temperature sensor, and selecting to enter the first temperature control adjustment mode or the second temperature control adjustment mode according to the temperature detection results of the outer shell and the exhaust port; Step S2: When entering the first temperature control mode, collecting sound data of the fan in the oven, processing the sound data to generate a first control value, detecting the ventilation condition of the environment where the electric oven is located, and generating a second control value based on the ventilation condition; Step S3: When entering the second temperature control mode, the insulation layer at the connection point of the electric wire is monitored, the insulation layer cracking condition is determined based on the monitoring result, the electric power of the electric oven is detected, and the insulation layer cracking condition and the electric power are comprehensively considered to generate a third control value; Step S4: Setting control rules, determining whether to generate a control signal and calculating a control ratio based on the first control value, the second control value, and the third control value, and performing temperature control on the electric oven in combination with the temperature of the outer shell and the exhaust port of the electric oven.

[0022] The implementation is as follows: In step S1, when detecting the current electric oven, a detection time is set, and the temperature of the shell and the exhaust port of the electric oven is detected by using the temperature sensor in the detection time. The minimum value of the temperature of the shell and the exhaust port of the electric oven in the detection time is taken as the detection result of the shell temperature and the detection result of the exhaust port temperature, respectively; Based on the detection result of the shell temperature and the detection result of the exhaust port temperature, different adjustment analysis modes are selected, and the specific steps are as follows: Temperature comparison: the minimum value is selected from the detection result of the shell temperature and the detection result of the exhaust port temperature as the determination temperature into the determination rule; Threshold selection: when the determination temperature is the detection result of the shell temperature, it is compared with the shell temperature threshold value; when the determination temperature is the detection result of the exhaust port temperature, it is compared with the exhaust port temperature threshold value; Judgment detection mode: when the determination temperature is the detection result of the shell temperature and is lower than the shell temperature threshold value, the first temperature control adjustment mode is entered; when the determination temperature is the detection result of the exhaust port temperature and is lower than the exhaust port temperature threshold value, the second temperature control adjustment mode is entered.

[0023] It should be noted that the temperature sensor is a device for measuring temperature. In this example, the temperature sensor is arranged on the shell and the port of the electric oven to detect the temperature respectively. The shell temperature threshold value and the exhaust port temperature threshold value are set by the professionals in the field according to the actual situation, which is not described here.

[0024] In step S2, the electric oven fan sound data is the electric oven fan sound intensity. The higher the electric oven fan sound intensity, the more heat the electric oven needs to dissipate, and the more the electric oven needs to reduce the temperature. On the contrary, when the electric oven fan sound intensity is low, it does not need to dissipate a large amount of heat and does not need to be cooled.

[0025] When processing the fan sound intensity, a plurality of detection time points are set, and the electric oven fan sound intensity is detected at each detection time point. The detection results at each detection time point are combined into a sound intensity data set; The historical data is used to calculate the oven fan sound intensity reference. The historical data is the electric oven fan sound intensity detection result at a plurality of time points in the past. The median of the electric oven fan sound intensity detection result at a plurality of time points in the historical data is taken as the oven fan sound intensity reference; The minimum value in the sound intensity data set is selected as the corrected sound intensity, and the ratio of the corrected sound intensity to the fan sound intensity reference is taken as the first control value.

[0026] It needs to be explained that the higher the sound intensity of the correction or the lower the sound intensity of the fan, the higher the first control value, and the more the electric oven needs to be cooled.

[0027] The air flow speed of the environment where the electric oven is located is detected by the wind speed sensor, and the wind speed sensor digitizes and displays the detection result to generate a wind speed value after detecting the air flow speed of the environment where the electric oven is located. The air flow speed of the environment where the electric oven is located is detected at each detection time point, and the detection results are combined into a wind speed data set. The wind speed data set is processed using the percentile method, and the specific steps are as follows: The data in the wind speed data set is sorted in descending order of numerical value, and a plurality of target data is selected by a percentile ratio. The total number of data in the wind speed data set is counted, and the target selection number is obtained by multiplying the total number by the percentile ratio. The data in the wind speed data set is marked from back to front according to the sorting order until the number of marks reaches the target selection number to stop marking to obtain a plurality of target data.

[0028] For example, there are 10 data in the wind speed data set, and the percentile ratio is 50%. After sorting the data in the wind speed data set in descending order of numerical value, each data is sequentially marked from back to front, and five marked data are selected as target data.

[0029] The ratio of the average value in the target data to the preset wind speed reference is used as the second control value. The faster the air flow speed of the environment where the electric oven is located, the faster the heat dissipation efficiency of the electric oven, and the larger the second control value, the less the need for cooling.

[0030] It should be noted that the wind speed reference described above is not unique and can be set according to actual conditions, for example, the wind speed reference is set to 2 m / s, etc. This will not be analyzed in detail.

[0031] In step S3, when entering the second temperature control adjustment mode, the insulating layer at the wire connection is detected by the online detection device; It should be noted that the insulating layer at the wire connection is detected by the insulation detection device, wherein the insulation detection device is used to obtain the integrity information of the surface area of the insulating layer, which will not be described here; Further, the insulation detection device includes but is not limited to a resistance test module, a partial discharge sensing module, an infrared thermal imaging module, etc. The selection and installation position of the specific device are determined by the experimenters through insulation state evaluation and temperature control safety rules, which are not limited here. The monitoring results generated by the insulation detection device are used to determine the insulating layer breakage, including the breakage area ratio and the total breakage length. Further, the monitoring result is a multi-channel synchronous data (including resistance distribution, partial discharge signal, infrared thermal imaging information, etc.) collected by the insulation detection device, which is used for comprehensive evaluation of the port insulation layer rupture condition; The acquisition logic of the rupture area ratio is to obtain an image of the wire insulation surface as the total surface area of the insulation layer through infrared thermal imaging information, extract a rupture area image as the insulation layer rupture area, and calculate the ratio of the insulation layer rupture area to the total surface area of the insulation layer to obtain the rupture area ratio. Wherein, in order to improve the recognition accuracy, those skilled in the art can think of using a multi-modal image acquisition and fusion method, for example, simultaneously using visible light imaging, infrared thermal imaging and laser profile scanning to obtain the surface and local information of the wire insulation layer, and combining image preprocessing, denoising, enhancement and deep learning image segmentation algorithm to accurately identify the rupture area, etc., which will not be repeated here. The acquisition logic of the total rupture length is to perform skeletonization processing in the rupture recognition image, extract the rupture connected line segments and calculate the rupture line segment length of each rupture line segment, and then accumulate and calculate the lengths of the rupture line segments to obtain the total rupture length. Wherein, the skeletonization processing is to thin each rupture region in the rupture region image and compress it into a single-pixel-wide center line while maintaining the topological structure and connectivity of the rupture, so as to accurately calculate the crack length. The specific operation method is the common knowledge of those skilled in the art, which will not be repeated here. Further, the rupture area ratio and the total rupture length are standardized to make the rupture area ratio and the total rupture length in the same dimension and the numerical expression between 0 and 1. It should be noted that the standardization processing method includes but is not limited to standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application method of standardization processing will not be repeated here. The result of weighted calculation of the standardized rupture area ratio and the total rupture length is used as the insulation layer rupture condition. Specifically, the common methods in the weighted calculation process include simple weighted average method, weighted method based on risk index, or adaptive weight allocation method, which are the common knowledge of those skilled in the art. In the calculation of the insulation layer rupture condition, weighted calculation is adopted, wherein the weighting coefficient can be determined according to the importance proportion of the rupture area ratio and the total rupture length, historical failure statistics or real-time temperature control risk assessment. Other weighting strategies or parameters can be set by those skilled in the art according to actual application, which will not be repeated here. The electric power of the electric oven refers to the electric energy rate consumed or transmitted by each loop load in the running process of the electric oven, and the acquisition logic is to acquire the current and voltage signals in real time by installing current sensors and voltage sensors on each loop, and to obtain the instantaneous power of each loop by multiplying the power factor, and to obtain the electric power of the electric oven by accumulating the instantaneous power of each loop; The electric power and the insulation layer rupture condition are standardized, so that the electric power of the electric oven and the insulation layer rupture condition are kept in the same numerical range, i.e. 0-1; The electric power and the insulation layer rupture condition after standardization are substituted into the product model to obtain a third control value, and the specific formula expression is as follows: ; In the formula, the third control value, the insulation layer rupture condition after standardization, the electric power after standardization, a nonlinear response adjustment parameter; It should be noted that the greater the insulation layer rupture condition and the electric power, the higher the temperature risk of the equipment and the poorer the insulation state, and the temperature rise needs to be limited to ensure safe operation, so the greater the third control value, the more the electric oven needs to be cooled.

[0032] Further, the change of the third control value directly drives the electric oven temperature control system to dynamically adjust the heating power and the fan speed, and when the third control value is large, the temperature control system will automatically reduce the heating power or increase the fan speed to speed up heat dissipation and reduce the temperature in the oven. In step S4, the control rule is set, and if the first control value and the second control value are detected, it is considered that the first temperature control adjustment mode is entered, and the first control value and the second control value are substituted into the polynomial regression calculation to obtain a cooling treatment coefficient, and the specific formula expression is as follows: ; In the formula, the cooling treatment coefficient, the first control value, the second control value, an adjustment parameter, and the weight coefficient corresponding to the first control value and the second control value; It should be noted that the order and form of the polynomial regression function in the present application can be selected according to actual application requirements, and the specific order and function form are not limited here, and those skilled in the art can determine them according to the actual electric oven running characteristics, which will not be described here. The greater the cooling treatment coefficient is, the higher the internal temperature of the electric oven is and the worse the heat dissipation condition is, and then the cooling treatment measures need to be increased, including reducing the heating power, increasing the fan speed or enhancing the air flow, so as to ensure that the equipment temperature is kept within a safe range. The cooling treatment coefficient is multiplied by the preset control coefficient to obtain a control ratio of the first temperature control adjustment mode. It should be noted that the preset control coefficient is set by the experimenters according to the running experience of the electric oven and the safety temperature threshold, and will not be repeated here. The control ratio of the first temperature control adjustment mode is multiplied by the shell temperature of the electric oven to obtain a shell target temperature value. According to the shell target temperature value, the temperature control operation is performed on the electric oven, and the shell temperature of the electric oven is cooled to the shell target temperature value. Specifically, the temperature control operation includes adjusting the heating power, changing the fan speed, starting the auxiliary cooling device, etc., and the specific selection of the temperature control operation implementation is not limited, but is selected by the experimenters according to the equipment heat dissipation performance and real-time temperature control requirements, which will not be repeated here. If the third control value is detected, it is considered that the second temperature control adjustment mode is entered, and the third control value is multiplied by the preset control coefficient to obtain a control ratio of the second temperature control adjustment mode. The control ratio of the second temperature control adjustment mode is multiplied by the shell temperature of the electric oven to obtain an exhaust port target temperature value. According to the exhaust port target temperature value, the temperature control operation is performed on the electric oven, and the exhaust port temperature of the electric oven is cooled to the exhaust port target temperature value. It should be noted that the cooling treatment of the exhaust port temperature of the electric oven includes increasing the exhaust fan speed, starting the auxiliary cooling device, adjusting the exhaust port ventilation guide, etc., and the specific cooling treatment implementation is selected by the experimenters according to the real-time temperature data of the exhaust port and the environmental air flow condition, which will not be repeated here.

[0033] Example 2 Please refer to Fig. 2 An intelligent electric oven temperature control adjustment management system, comprising a temperature detection module, a mode selection module, a control analysis module and a control execution module, and each module is electrically connected. The functions of each module are as follows: The temperature detection module is used to collect the temperatures of the shell and the exhaust port of the electric oven and transmit them to the mode selection module. The mode selection module selects the temperature control adjustment mode based on the temperature detection results of the shell and the exhaust port of the electric oven, and sets the collected signals to be transmitted to the control analysis module according to different selection results. The regulation analysis module selects to collect the fan sound data of the electric oven and the ventilation condition of the environment where the electric oven is located or to collect the insulation layer rupture condition of the electric wire connection of the electric oven and the electric power, and transmits the collection result to the regulation execution module; The regulation execution module generates a first regulation value based on the fan sound data of the electric oven, generates a second regulation value based on the ventilation condition of the environment where the electric oven is located, generates a third regulation value based on the insulation layer rupture condition and the electric power, judges whether to generate a regulation signal and calculates a regulation proportion according to the three regulation values through a regulation rule, and performs temperature control operation on the electric oven in combination with the temperature of the shell and the exhaust port of the electric oven.

[0034] The above formulas are all dimensionless values, and the formulas are obtained by software simulation of a large amount of data to obtain a formula of the nearest real situation, and the preset parameters in the formula are set by the person skilled in the art according to the actual situation.

[0035] Finally, it should be noted that in this document, the terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0036] Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0037] In this document, the singular forms "a", "an" and "the" can also include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the terms "include", "contain" or "have" and the like specify the presence of the 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. The possibility, while the term "and / or" is used in this specification, includes any and all combinations of the related listed items.

[0038] The various embodiments in the specification are described in a progressive manner, each embodiment focuses on the difference from other embodiments, and each embodiment can be combined as needed, and the same and similar parts refer to each other.

[0039] Those skilled in the art will appreciate that the foregoing description is by way of example only, and is not intended to limit the application solely thereto. Numerous modifications and adaptations will be apparent to those skilled in this art. Therefore, the true scope of the application is indicated by the appended claims, rather than by the foregoing description, and all modifications which come within the scope of the claims are intended to be embraced therein.

Claims

1. A method for temperature control and management of an intelligent electric oven, characterized in that: The following steps are included: Step S1: detecting the temperature of the outer shell and the exhaust port of the electric oven through a temperature sensor, and selecting to enter the first temperature control adjustment mode or the second temperature control adjustment mode according to the temperature detection results of the outer shell and the exhaust port; Step S2: When entering the first temperature control mode, collecting sound data of the fan in the oven, processing the sound data to generate a first control value, detecting the ventilation condition of the environment where the electric oven is located, and generating a second control value based on the ventilation condition; Step S3: When entering the second temperature control mode, the insulation layer at the connection point of the electric wire is monitored, the insulation layer cracking condition is determined based on the monitoring result, the electric power of the electric oven is detected, and the insulation layer cracking condition and the electric power are comprehensively considered to generate a third control value; Step S4: Setting control rules, determining whether to generate a control signal and calculating a control ratio based on the first control value, the second control value, and the third control value, and performing temperature control on the electric oven in combination with the temperature of the outer shell and the exhaust port of the electric oven.

2. The intelligent electric oven temperature control and adjustment management method according to claim 1, characterized in that: In step S1, a detection time is set, and the temperatures of the outer shell and the exhaust port of the electric oven are detected within the detection time. The minimum temperatures of the outer shell and the exhaust port of the electric oven within the detection time are respectively used as the detection results of the outer shell temperature and the exhaust port temperature.

3. The intelligent electric oven temperature control and adjustment management method according to claim 2, characterized in that: In step S1, different adjustment and analysis modes are selected based on the detection results of the housing temperature and the exhaust port temperature. The specific steps are as follows: Temperature comparison: The minimum value of the shell temperature detection result and the exhaust port temperature detection result is selected as the judgment temperature and input into the judgment rule; Threshold selection: When the temperature is determined to be the shell temperature, if the temperature is lower than the preset shell temperature threshold, the first temperature control adjustment mode is entered; when the temperature is determined to be the exhaust port temperature, if the temperature is lower than the preset exhaust port temperature threshold, the second temperature control adjustment mode is entered.

4. The intelligent electric oven temperature control and adjustment management method according to claim 1, characterized in that: In step S2, the sound data of the fan in the electric oven is the sound intensity of the fan in the electric oven. When processing the fan sound intensity, multiple detection time points are set, the sound intensity of the fan in the electric oven is detected at each detection time point, and the detection results of each detection time point are merged into a sound intensity data set; The sound intensity benchmark of the oven fan is calculated by calling historical data. The historical data includes the sound intensity test results of the oven fan at multiple time points in the past. The median of the sound intensity test results of the oven fan at multiple time points in the historical data is taken as the sound intensity benchmark of the oven fan. The minimum value in the sound intensity data set is selected as the calibration sound intensity, and the ratio of the calibration sound intensity to the fan sound intensity benchmark is used as the first control value.

5. The intelligent electric oven temperature control and adjustment management method according to claim 1, characterized in that: In step S2, the ventilation condition of the environment where the electric oven is located is the air flow speed of the environment where the electric oven is located; The air flow velocity in the environment where the electric oven is located is tested at each test time point, and the test results are combined into a wind speed data set. The wind speed data set is processed using the percentile method. The specific steps are as follows: Mark the data in the wind speed dataset from back to front in sorted order until the number of marks reaches the target screening number and then stop marking to obtain multiple target data; The ratio of the average value in the target data to the preset wind speed reference is used as the second protection manifestation value.

6. The intelligent electric oven temperature control and adjustment management method according to claim 1, characterized in that: In step S3, when entering the second temperature control mode, the insulation layer at the connection of the wire is inspected by an online inspection device; Determine the insulation layer rupture status based on the monitoring results generated by the insulation detection device, including the rupture area ratio and the total rupture length; The image of the wire insulation surface is obtained through infrared thermal imaging information as the total surface area of ​​the insulation layer, and the image of the cracked area is extracted as the cracked area of ​​the insulation layer. The ratio of the cracked area of ​​the insulation layer to the total surface area of ​​the insulation layer is calculated to obtain the cracked area ratio; The skeletonization process is performed on the fracture recognition image, the fracture connected segments are extracted and the fracture segment length is calculated for each fracture segment. The lengths of the fracture segments are accumulated to obtain the total fracture length.

7. The intelligent electric oven temperature control and adjustment management method according to claim 6, characterized in that: In step S3, the rupture area ratio and the total rupture length are normalized; The results of weighted calculation of the standardized crack area ratio and the total crack length are used as the insulation layer crack situation; By installing current sensors and voltage sensors in each circuit, the current and voltage signals are collected in real time, and the instantaneous power of each circuit is calculated by multiplying them with the power factor. The instantaneous power of each circuit is accumulated to obtain the electric power of the electric oven. The electric power and the insulation layer rupture condition are standardized and then input into the product model to obtain the third control value.

8. The intelligent electric oven temperature control and adjustment management method according to claim 1, characterized in that: In step S4, a control rule is set. If the first control value and the second control value are detected, it is considered that the first temperature control adjustment mode is entered. The first control value and the second control value are substituted into the polynomial regression calculation to obtain the temperature reduction treatment coefficient; The temperature reduction processing coefficient is multiplied by the preset control coefficient to obtain the control ratio of the first temperature control adjustment mode; The target temperature value of the outer shell is calculated by multiplying the control ratio of the first temperature control adjustment mode by the outer shell temperature of the electric oven; The electric oven is temperature-controlled according to the target shell temperature value, and the shell temperature of the electric oven is cooled down to the target shell temperature value.

9. The intelligent electric oven temperature control and adjustment management method according to claim 8, characterized in that: In step S4, if the third control value is detected, it is considered that the second temperature control adjustment mode has been entered, and the control ratio of the second temperature control adjustment mode is obtained by multiplying the third control value by the preset control coefficient; The target temperature value of the exhaust port is calculated by multiplying the control ratio of the second temperature control mode by the outer shell temperature of the electric oven; The electric oven is temperature-controlled according to the exhaust port target temperature value, and the exhaust port temperature of the electric oven is cooled down to the exhaust port target temperature value.

10. An intelligent electric oven temperature control and regulation management system, based on the intelligent electric oven temperature control and regulation management method according to any one of claims 1 to 9, characterized in that: It includes a temperature detection module, a mode selection module, a control analysis module and a control execution module, and each module is connected by electrical signals; The functions of each module are as follows: The temperature detection module is used to collect the temperature of the outer shell and exhaust port of the electric oven and transmit it to the mode selection module; The mode selection module selects the temperature control mode based on the temperature detection results of the outer shell and the exhaust port of the electric oven, and sets the collected signal to be transmitted to the control and analysis module according to different selection results; The control and analysis module selects the sound data of the fan in the electric oven and the ventilation conditions of the environment according to the collected signal, or collects the insulation layer cracking condition and electric power at the connection of the electric oven wire, and transmits the collected results to the control execution module; The control execution module generates a first control value based on the sound data of the fan inside the electric oven, generates a second control value based on the ventilation conditions of the environment where the electric oven is located, and generates a third control value based on the insulation layer rupture conditions and electric power. The control rules are used to determine whether to generate a control signal and calculate the control ratio based on the three control values, and the electric oven is temperature-controlled in combination with the temperature of the outer shell and exhaust port of the electric oven.

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