Water heater thermal efficiency calculation method and system based on big data

Abstract

The invention discloses a water heater thermal efficiency calculation method and system based on big data, and belongs to the technical field of data processing, and the method comprises the following steps: obtaining a power supply interference parameter of a water heater, analyzing to obtain a power supply noise interference index, obtaining an electromagnetic interference parameter of the water heater, analyzing to obtain an electromagnetic noise interference index, and calculating the thermal efficiency of the water heater. Analyzing to obtain external interference indexes of the water heater; internal interference indexes of the water heater are obtained through analysis; performing filtering correction processing on the filtering signal data; analyzing to obtain a filtering correction quality index, and comparing the filtering correction quality index with a filtering signal quality index before filtering correction processing to obtain a filtering correction result; if the filtering correction result shows that filtering correction is qualified, the heat efficiency of the water heater is calculated, and if the filtering correction result shows that filtering correction is not qualified, filtering correction processing continues to be executed. The problem that in the prior art, due to the fact that a filter is insufficient in noise interference suppression capacity, heat efficiency evaluation parameters of the water heater are not accurately obtained is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for calculating thermal efficiency of a water heater based on big data. Background Art

[0002] With the popularity of solar water heaters in homes and commercial areas, their thermal efficiency evaluation and performance optimization have become the focus of technical research. The existing thermal efficiency calculation of water heaters is achieved through laboratory tests to establish a linear formula simulation of heating capacity and ambient temperature, or to generate a theoretical thermal energy conversion curve through a thermal efficiency conversion coefficient, and to combine real-time water temperature data with a photoelectric switching efficiency model for performance evaluation.

[0003] For example, the invention patent with announcement number: CN105989221B announces a method for calculating power saving of a heat pump water heater and a heat pump water heater with a display of power saving, including: obtaining a curve formula of heating capacity and ambient temperature and a heating efficiency formula through laboratory testing; calculating the heating capacity when the user actually uses the heat pump water heater to make hot water based on the initial water temperature and the final water temperature when the user actually uses the heat pump water heater to make hot water, and the initial water temperature and the final water temperature determined in the laboratory test as well as the formula of heating capacity and ambient temperature to obtain the heating capacity when the user actually uses the heat pump water heater to make hot water; calculating the power consumption when the user uses the heat pump water heater to make hot water based on the heating efficiency of the heat pump water heater, the heating capacity and the heating time when the user actually uses the heat pump water heater to make hot water; and then calculating the power consumption when the user uses an electric water heater to make hot water; and then obtaining the amount of power saved when the user actually uses the heat pump water heater to make hot water compared to using an electric water heater to make hot water.

[0004] For example, the invention patent with announcement number: CN113705113B announces a method and system for evaluating the heating performance of a solar water heater, including: obtaining a first thermal efficiency conversion coefficient; obtaining a first thermal energy conversion temperature curve based on the first thermal efficiency conversion coefficient and the heat collection information of the first solar water heater; obtaining a first light energy heating evaluation result based on the first thermal energy conversion temperature curve and the first water temperature change curve; inputting the first water temperature change curve information and the first photoelectric switching response rate information into a switching efficiency evaluation model to obtain a first photoelectric switching efficiency evaluation result; obtaining a first heating performance evaluation result of the first solar water heater based on the first photoelectric heating evaluation result and the first photoelectric switching efficiency evaluation result.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the prior art, the thermal efficiency calculation method of the prior art is evaluated in an ideal environment. However, in the actual scenario, there will be complex and changeable noise interference. For the thermal efficiency calculation of solar water heaters, high-precision data is usually required, and the appearance of noise will seriously affect the refined acquisition of the thermal efficiency parameters of the water heater, causing deviations in the thermal efficiency parameters of the water heater and thus affecting the calculation of the thermal efficiency. Therefore, there is a problem of inaccurate acquisition of the thermal efficiency evaluation parameters of the water heater due to the insufficient noise interference suppression ability of the filter. Summary of the invention

[0006] The embodiment of the present application solves the problem of inaccurate acquisition of thermal efficiency evaluation parameters of water heaters due to insufficient noise interference suppression capability of filters in the prior art by providing a method and system for calculating thermal efficiency of water heaters based on big data, thereby achieving accurate acquisition of temperature.

[0007] An embodiment of the present application provides a method for calculating the thermal efficiency of a water heater based on big data, characterized in that it includes the following steps: after receiving a signal detected by a device, obtaining a power supply interference parameter of the water heater, analyzing to obtain a power supply noise interference index, obtaining an electromagnetic interference parameter of the water heater, analyzing to obtain an electromagnetic noise interference index, and analyzing to obtain an external interference index of the water heater; obtaining an internal interference parameter of the water heater, analyzing to obtain an internal interference index of the water heater; performing filter correction processing on the filtered signal data based on the external interference index of the water heater and the internal interference index of the water heater; obtaining a signal quality parameter after the filter correction processing, analyzing to obtain a filter correction quality index, and comparing it with the filter signal quality index before the filter correction processing to obtain a filter correction result; if the filter correction result is that the filter correction is qualified, then obtaining a thermal efficiency evaluation parameter after the filter processing, and inputting it into a preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater; if the filter correction result is that the filter correction is unqualified, then continuing to perform the filter correction processing.

[0008] A system for calculating the thermal efficiency of a water heater based on big data, characterized in that it comprises: an external interference evaluation module, an internal interference evaluation module, a filtering correction module, a filtering correction result analysis module and a thermal efficiency evaluation module; wherein the external interference evaluation module is used to obtain the power interference parameter of the water heater after receiving the signal detected by the device, analyze and obtain the power noise interference index, obtain the electromagnetic interference parameter of the water heater, analyze and obtain the electromagnetic noise interference index, and analyze and obtain the external interference index of the water heater; the internal interference evaluation module is used to obtain the internal interference parameter of the water heater and analyze and obtain the internal interference index of the water heater; the filtering correction module is used to perform filtering correction processing on the filtered signal data based on the external interference index of the water heater and the internal interference index of the water heater; the filtering correction result analysis module is used to obtain the signal quality parameter after filtering correction processing, analyze and obtain the filtering correction quality index, and compare it with the filtering signal quality index before filtering correction processing to obtain the filtering correction result; the thermal efficiency evaluation module is used to obtain the thermal efficiency evaluation parameter after filtering processing if the filtering correction result is qualified, input it into the preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater, and continue to perform the filtering correction processing if the filtering correction result is unqualified.

[0009] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Based on the external interference index and internal interference index of the water heater, the filtered signal data is filtered and corrected to obtain the signal quality parameters after the filtering correction processing, and the filtering correction quality index is analyzed and compared with the filtering signal quality index before the filtering processing, thereby realizing the dynamic verification and optimization of the filtering correction effect, ensuring the accuracy of the input data of the thermal efficiency evaluation model of the water heater, and effectively solving the problem of inaccurate acquisition of the thermal efficiency evaluation parameters of the water heater due to the insufficient noise interference suppression ability of the filter in the prior art.

[0010] 2. The water heater thermal efficiency calculation method based on big data provided by the present invention obtains the power interference parameters and electromagnetic interference parameters of the water heater, analyzes the power noise interference index and the electromagnetic noise interference index, and thus obtains the external interference index of the water heater, thereby realizing accurate quantitative evaluation of external interference.

[0011] 3. The present invention obtains the internal interference parameters of the water heater and analyzes the internal interference index of the water heater, thereby performing filter correction processing on the filtered signal data based on the internal interference index, thereby achieving accurate quantitative evaluation of the internal environmental interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1A flow chart of a method for calculating thermal efficiency of a water heater based on big data provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a water heater thermal efficiency calculation system based on big data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0013] The embodiment of the present application solves the problem in the prior art of inaccurate acquisition of thermal efficiency evaluation parameters of the water heater due to insufficient noise interference suppression capability of the filter by providing a method and system for calculating the thermal efficiency of the water heater based on big data, thereby achieving accurate acquisition of the temperature.

[0014] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0015] like Figure 1 As shown, it is a flow chart of a method for calculating thermal efficiency of a water heater based on big data provided in an embodiment of the present application, and the method includes the following steps: after receiving a signal detected by the device, obtaining the power interference parameter of the water heater, analyzing to obtain the power noise interference index, obtaining the electromagnetic interference parameter of the water heater, analyzing to obtain the electromagnetic noise interference index, and analyzing to obtain the external interference index of the water heater; obtaining the internal interference parameter of the water heater, analyzing to obtain the internal interference index of the water heater; performing filter correction processing on the filtered signal data based on the external interference index of the water heater and the internal interference index of the water heater; obtaining the signal quality parameter after the filter correction processing, analyzing to obtain the filter correction quality index, and comparing it with the filter signal quality index before the filter correction processing to obtain the filter correction result; if the filter correction result is that the filter correction is qualified, then obtaining the thermal efficiency evaluation parameter after the filter processing, and inputting it into the preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater; if the filter correction result is that the filter correction is unqualified, then continuing to perform the filter correction processing.

[0016] In this embodiment, it should be noted that by acquiring and analyzing the power interference parameters and electromagnetic interference parameters of the water heater, comprehensively considering the external interference factors, and acquiring the internal interference parameters to analyze the internal interference index, a comprehensive evaluation of various interference factors in the working environment of the water heater is achieved, which provides a basis for the subsequent filtering correction. The filtered signal data is filtered and corrected based on the external and internal interference indicators, and the correction result is judged by comparing the signal quality parameters before and after the filtering correction. If it is unqualified, the correction is continued, which can effectively improve the signal quality, ensure that the collected data is accurate and reliable, and lay the foundation for the accurate calculation of the thermal efficiency of the water heater. Only after the filtering correction is qualified, the thermal efficiency evaluation parameters after filtering are input into the preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater, thereby obtaining a more accurate thermal efficiency of the water heater, avoiding the calculation deviation caused by data error, and improving the accuracy and credibility of the entire calculation method. By introducing an early warning mechanism, if the filtering correction result is still unqualified within the preset number of times, an early warning is issued, which is convenient for timely discovery and resolution of problems in the data processing process, enhances the reliability and stability of the entire calculation method, and ensures the smooth progress of the water heater thermal efficiency calculation process.

[0017] Furthermore, the power supply interference parameters of the water heater are obtained, and the power supply noise interference index is obtained by analysis. The specific steps include: obtaining the power supply interference parameters of the water heater, which include the voltage fluctuation amplitude, current harmonic content, voltage sag depth, maximum frequency deviation and surge voltage peak of the power supply within a preset time period; obtaining a power supply interference reference set preset in the database, and comparing it with the power supply interference parameters of the water heater to obtain the power supply noise interference index; the power supply interference reference set includes: the allowable value of voltage fluctuation amplitude, the allowable value of current harmonic content, the unit voltage sag depth influence factor, the unit maximum frequency deviation influence factor and the surge voltage peak reference value; the power supply noise interference index is used to analyze the degree of difference between the voltage fluctuation amplitude, the current harmonic content and the surge voltage peak and the allowable value of the voltage fluctuation amplitude, the allowable value of the current harmonic content and the surge voltage peak reference value, and combine the voltage sag depth with the unit voltage sag depth influence factor, the maximum frequency deviation of the power supply and the unit maximum frequency deviation influence factor to obtain the power supply noise interference index.

[0018] In this embodiment, by obtaining multiple power supply interference parameters (such as voltage fluctuation amplitude, current harmonic content, etc.) and comparing them with the preset power supply interference reference set, the interference of the power supply to the water heater can be comprehensively evaluated to ensure the comprehensiveness and accuracy of the analysis results. By using the various allowable values ​​and influencing factors in the preset power supply interference reference set to compare with the actual power supply interference parameters, the degree of power supply noise interference can be accurately quantified, providing a scientific basis for subsequent filtering and correction processing, and can flexibly compare and analyze according to different power supply interference conditions, adapting to the power supply interference evaluation needs of water heaters in different environments, improving the adaptability and practicality of the entire calculation method, and providing detailed data support for subsequent filtering and correction processing. Through accurate power supply noise interference indicators, filtering correction can be more targeted to improve the filtering effect and the accuracy of thermal efficiency calculation.

[0019] It should be noted that the voltage fluctuation amplitude refers to the size of the actual voltage offset value, which is obtained by detecting the difference between the maximum and minimum values ​​of the power supply voltage within a preset time period. The current harmonic content can be detected by a harmonic analyzer. The voltage sag depth refers to the sudden drop in the effective value of the power supply voltage in a short period of time, but then quickly recovers to a level close to the normal value, which can be measured by a power quality analyzer. The maximum frequency deviation refers to the maximum value of the difference between the actual value and the nominal value of the power system frequency within a preset time period, which can be measured by a power quality analyzer. The surge voltage peak refers to the instantaneous overvoltage generated when connecting or disconnecting an inductive load or a large load, which can be measured by an oscilloscope.

[0020] Get the power supply noise interference index, the specific method is: ; ; ; In the formula, YR represents the power supply noise interference index, YF represents the voltage fluctuation amplitude of the power supply, RY represents the allowable value of the voltage fluctuation amplitude, LY represents the current harmonic content of the power supply, RL represents the allowable value of the current harmonic content, AJ represents the voltage sag depth of the power supply, RA represents the unit voltage sag depth influence factor, PL represents the maximum frequency deviation of the power supply, RP represents the unit maximum frequency deviation influence factor, LD represents the surge voltage peak value of the power supply, and RD represents the surge voltage peak reference value. represents the voltage influence weight, Represents the current influence weight.

[0021] It should be noted that the voltage influence weight and the current influence weight can be obtained from a database. For example, the voltage influence weight can be obtained by obtaining the historical voltage stored in the database, and the voltage influence weight corresponding to the historical voltage, thereby constructing a voltage mapping set, wherein there is a one-to-one or many-to-one correspondence in the mapping set. The voltage influence weight can be obtained by inputting the voltage data to be used into the voltage mapping set. The current influence weight is obtained in the same way as the voltage influence weight, and can also be matched in the corresponding mapping set, wherein the current influence weight corresponds to the current mapping set.

[0022] There is a mutual influence between the voltage fluctuation amplitude, current harmonic content, voltage sag depth, maximum frequency deviation and surge voltage peak of the power supply, which work together to produce power supply noise interference. The specific influence relationship is as follows: the change of voltage fluctuation amplitude will affect the current harmonic content. When the voltage fluctuation is large, it will cause the current waveform to be distorted, thereby increasing the harmonic content. At the same time, the increase in current harmonic content will also aggravate voltage fluctuations, forming a vicious circle. The depth and duration of voltage sag will affect the stability of the power supply. When the voltage sag occurs, it will cause abnormal operation of the equipment, thereby generating more harmonic current and voltage fluctuations. The existence of maximum frequency deviation will make the frequency of the power supply unstable, affect the normal operation of the equipment, and also cause the voltage and current waveforms to be distorted, increase the harmonic content and voltage fluctuation amplitude. The appearance of surge voltage peak will cause a momentary impact on the power supply system, resulting in abnormal operation of the equipment, thereby causing voltage fluctuations, increased current harmonics, etc. These parameters influence and interact with each other, and together constitute a complex power supply noise interference environment, which affects the normal operation of equipment such as solar water heaters.

[0023] Furthermore, the electromagnetic interference parameters of the water heater are obtained, and the electromagnetic noise interference index is obtained by analysis. The specific steps include: obtaining the electromagnetic interference parameters of the water heater, which include the average magnetic field radiation intensity, average electromagnetic interference frequency, maximum electromagnetic interference fluctuation amplitude, maximum peak power density and average pulse repetition frequency of the electromagnetic interference signal within a preset time period; obtaining the electromagnetic interference limit value set preset in the database, and analyzing it with the electromagnetic interference parameters of the water heater to obtain the electromagnetic noise interference index; the electromagnetic interference limit value set includes the magnetic induction intensity limit value, the electromagnetic interference spectrum limit value, the fluctuation amplitude reference value, the peak power density reference value and the pulse repetition frequency reference value; the electromagnetic noise interference index is used to extract the electromagnetic interference parameters of the water heater, including the average magnetic field radiation intensity, average electromagnetic interference frequency, maximum electromagnetic interference fluctuation amplitude, maximum peak power density and average pulse repetition frequency of the electromagnetic interference signal within a preset time period, and respectively analyzing the difference between them and the magnetic induction intensity limit value, the electromagnetic interference spectrum limit value, the fluctuation amplitude reference value, the peak power density reference value and the pulse repetition frequency reference value, and then introducing the corresponding impact weight to obtain the electromagnetic noise interference index.

[0024] In this embodiment, it should be noted that the maximum fluctuation amplitude of electromagnetic interference refers to the maximum value of the intensity variation range of the electromagnetic interference signal within a preset period of time, that is, the difference between the maximum intensity of the electromagnetic interference signal and the minimum intensity of the electromagnetic interference signal. The maximum peak power density refers to the maximum value of the instantaneous power per unit collector area within a preset time.

[0025] The average magnetic field radiation intensity can be measured by using a Gaussmeter, the average electromagnetic interference frequency can be measured by using a spectrum analyzer, the maximum electromagnetic interference fluctuation amplitude can be measured by using an electromagnetic interference analyzer, the maximum peak power density can be measured by using a power density spectrum analyzer, and the average pulse repetition frequency can be measured by using a spectrum analyzer.

[0026] By obtaining multiple electromagnetic interference parameters (such as average magnetic field radiation intensity, average electromagnetic interference frequency, etc.) and analyzing them with the preset electromagnetic interference limit set, the impact of electromagnetic interference on the water heater can be comprehensively evaluated to ensure the comprehensiveness and accuracy of the analysis results. By using the various influencing factors and allowable values ​​in the preset electromagnetic interference limit set and analyzing with the actual electromagnetic interference parameters, the degree of electromagnetic noise interference can be accurately quantified, providing a scientific basis for subsequent filtering and correction processing, and can flexibly analyze and evaluate according to different electromagnetic interference situations, adapting to the electromagnetic interference evaluation needs of water heaters in different environments, improving the adaptability and practicality of the entire calculation method, and providing detailed data support for subsequent filtering and correction processing. Through accurate electromagnetic noise interference indicators, filtering correction can be more targeted to improve the accuracy of filtering effect and thermal efficiency calculation.

[0027] In the operating environment of solar water heaters, electromagnetic interference will seriously affect the signal acquisition and parameter measurement of solar water heaters. Signal transmission is easily affected by electromagnetic radiation from interference sources such as low-voltage lines, high-voltage lines, and signal towers. The early signal output was an analog signal with serious signal distortion. Electromagnetic interference will cause inaccurate data collected by the sensor, which will affect the control accuracy of the controller. For example, the detection of water temperature and water level sensors is susceptible to electromagnetic interference, and the collected data is not accurate enough, which seriously affects the control accuracy of the controller. Electromagnetic interference can also cause abnormal operation, performance degradation, and even damage to the equipment. For example, electromagnetic interference will interfere with the signal transmission of the sensor, resulting in inaccurate collected data, which will affect the control accuracy of the controller. These electromagnetic interference parameters affect each other and act on the power supply system together to generate power supply noise interference. For example, an increase in the average magnetic field radiation intensity and the average electromagnetic interference frequency will lead to an increase in the induced electromotive force, thereby increasing the noise amplitude. An increase in the maximum peak power density and the average pulse repetition frequency will lead to more transient interference, further increasing the noise level of the power supply system. The impact of these electromagnetic interferences on the power supply system is serious, which will cause abnormal operation, performance degradation, and even damage to the equipment.

[0028] The electromagnetic noise interference index is obtained by analyzing the electromagnetic interference parameters of the water heater (the average magnetic field radiation intensity of the electromagnetic interference signal, the average electromagnetic interference frequency, the maximum fluctuation amplitude of the electromagnetic interference, the maximum peak power density and the average pulse repetition frequency). This is based on the mutual influence relationship between these parameters. For example, the average magnetic field radiation intensity and the average electromagnetic interference frequency of the electromagnetic interference signal work together to increase the induced electromotive force and noise amplitude. The increase in the maximum fluctuation amplitude of the electromagnetic interference further aggravates the noise intensity, causing the voltage and current waveforms of the power supply system to be distorted. The increase in the maximum peak power density causes a greater instantaneous impact on the power supply system, while the increase in the average pulse repetition frequency leads to more pulse interference. These factors interact with each other and together lead to the aggravation of power supply noise interference.

[0029] The electromagnetic noise interference index is obtained by: ; In the formula, CR represents the electromagnetic noise interference index, FQ represents the average magnetic field radiation intensity of the electromagnetic interference signal, CF represents the magnetic induction intensity limit, FR represents the average electromagnetic interference frequency of the electromagnetic interference signal, CR represents the electromagnetic interference spectrum limit, FB represents the maximum electromagnetic interference fluctuation amplitude of the electromagnetic interference signal, CB represents the fluctuation amplitude reference value, FM represents the maximum peak power density of the electromagnetic interference signal, CM represents the peak power density reference value, FL represents the average pulse repetition frequency of the electromagnetic interference signal, CL represents the pulse repetition frequency reference value, Indicates the influence weight of magnetic field radiation intensity, Indicates the impact weight of electromagnetic interference frequency, Indicates that the fluctuation range affects the weight, represents the maximum peak power density impact weight, Represents the pulse repetition frequency impact weight.

[0030] The magnetic field radiation intensity influence weight, electromagnetic interference frequency influence weight, fluctuation amplitude influence weight, maximum peak power density influence weight and pulse repetition frequency influence weight can be obtained from the database. For example, the magnetic field radiation intensity influence weight can be obtained by obtaining the historical magnetic field radiation intensity stored in the database, and the magnetic field radiation intensity influence weight corresponding to the historical magnetic field radiation intensity, thereby constructing a magnetic field radiation intensity mapping set, wherein there is a one-to-one correspondence or a many-to-one correspondence in the mapping set, and the magnetic field radiation intensity influence weight can be obtained by inputting the magnetic field radiation intensity data to be used into the magnetic field radiation intensity mapping set. The acquisition method of other influence weights such as the electromagnetic interference frequency influence weight, the fluctuation amplitude influence weight, the maximum peak power density influence weight and the pulse repetition frequency influence weight is the same as the acquisition method of the magnetic field radiation intensity influence weight, and can all be matched in the corresponding mapping set, for example, the electromagnetic interference frequency influence weight corresponds to the electromagnetic interference frequency mapping set, the fluctuation amplitude influence weight corresponds to the fluctuation amplitude mapping set, the maximum peak power density influence weight corresponds to the maximum peak power density mapping set, and the pulse repetition frequency influence weight corresponds to the pulse repetition frequency mapping set.

[0031] Furthermore, the external interference index of the water heater is obtained by analysis, and the specific steps include: obtaining the power supply interference influence weight corresponding to the power supply noise interference index and the electromagnetic interference influence weight corresponding to the electromagnetic noise interference index preset in the database; obtaining the external interference index of the water heater based on the comprehensive analysis of the power supply noise interference index, the power supply interference influence weight, the electromagnetic noise interference index and the electromagnetic interference influence weight; the external interference index of the water heater is used to characterize the comprehensive interference degree of the power supply noise and electromagnetic noise of the water heater on the water heater by coupling analysis of the power supply noise interference index of the water heater with its corresponding power supply interference influence weight and combining the coupling result of the electromagnetic noise interference index with its corresponding electromagnetic interference influence weight.

[0032] In this embodiment, the external interference index of the water heater is obtained by multiplying the power supply noise interference index and the electromagnetic noise interference index by the corresponding interference degree coefficients and then summing them, thereby realizing a comprehensive evaluation of the external interference of the water heater, taking into account the joint effect of multiple interference factors, making the evaluation result more comprehensive and accurate, and quantifying the external interference index into a specific value, which is convenient for comparing and analyzing the external interference degree of different water heaters or under different working conditions, and providing a clear basis for subsequent filtering correction processing. By adjusting the power supply interference influence weight and the electromagnetic interference influence weight, the external interference degree under different circumstances can be flexibly reflected, with strong versatility and adaptability, providing detailed external interference data for subsequent filtering correction processing, and helping to perform filtering correction more targetedly, and improving the filtering effect and the accuracy of thermal efficiency calculation.

[0033] The external interference index of the water heater is obtained by: ; In the formula, WB represents the external interference index of the water heater, YR represents the power supply noise interference index, and CR represents the electromagnetic noise interference index. Indicates the weight of power supply interference, Represents the electromagnetic interference impact weight.

[0034] It should be noted that the power supply interference impact weight and the electromagnetic interference impact weight can be obtained from a database. For example, the power supply interference impact weight can be obtained by obtaining the historical power supply interference stored in the database, and the power supply interference impact weight corresponding to the historical power supply interference, thereby constructing a power supply interference mapping set, wherein there is a one-to-one or many-to-one correspondence in the mapping set. The power supply interference impact weight can be obtained by inputting the power supply interference data to be used into the power supply interference mapping set. The method for obtaining the electromagnetic interference impact weight is the same as the method for obtaining the power supply interference impact weight, and can also be matched in the corresponding mapping set. The mapping set corresponding to the electromagnetic interference impact weight is the electromagnetic interference mapping set.

[0035] Furthermore, internal interference parameters of the water heater are obtained, and the internal interference index of the water heater is obtained by analysis. The specific steps include: obtaining the internal interference parameters of the water heater, which include the average surface temperature of the collector, the average water pressure, the maximum water pressure fluctuation and the average water flow velocity of the water heater within a preset time period; obtaining the internal interference reference set preset in the database, and comparing it with the internal interference parameters of the water heater to obtain the internal interference index of the water heater; the internal interference reference set includes a temperature reference value, a water pressure reference value, an allowable value of water pressure fluctuation and a water flow velocity reference value; the internal interference index of the water heater is used to perform a difference analysis on the average surface temperature of the collector and the corresponding temperature reference value, to compare the average water pressure and the maximum water pressure fluctuation with the water pressure reference value and the allowable value of water pressure fluctuation respectively, to compare the average water flow velocity with the water flow velocity reference value, and to introduce their corresponding influence weights respectively and perform coupling processing to obtain the internal interference index of the water heater.

[0036] In this embodiment, through comprehensive consideration of the internal interference parameters of the water heater, the interference status inside the water heater is fully reflected, providing systematic data support for subsequent processing. By obtaining the preset internal interference reference set in the database and comparing the actual internal interference parameters with the reference values, the degree of internal interference can be accurately quantified, making the evaluation of internal interference more scientific and accurate, and facilitating the subsequent targeted filtering correction measures. The average surface temperature of the collector can be measured by an infrared thermometer or a temperature sensor (such as a thermocouple or thermistor), the voltage fluctuation amplitude can be measured by a voltage fluctuation tester, the maximum water pressure fluctuation can be measured by using a water pressure sensor or a pressure transmitter, and the average water flow rate can be measured by using a water flow sensor or a flow meter.

[0037] In the operating environment of the water heater, there is a mutual influence relationship between the parameters such as the average temperature of the collector surface, the average water pressure, the maximum water pressure fluctuation and the average water flow rate. For example: the change of the average temperature of the collector surface will affect the thermal efficiency of the water heater, and the change of thermal efficiency will affect the power consumption of the water heater, resulting in changes in water pressure and water flow rate. The change of average water pressure will affect the water flow rate. At the same time, the change of water flow rate will also affect the stability of water pressure, further affecting the maximum water pressure fluctuation. The change of maximum water pressure fluctuation will affect the operating stability of the water heater, causing the operating state of the water heater's heating element and water pump to change, which in turn affects the temperature of the collector surface. The interaction between these parameters jointly affects thermal efficiency and operating stability.

[0038] The internal interference index of the water heater is obtained by: ; ; ; ; Where, NR represents the internal interference index of the water heater, W represents the average surface temperature of the collector of the water heater, NW represents the temperature reference value, F represents the average water pressure, NF represents the water pressure reference value, B represents the maximum water pressure fluctuation, NB represents the allowable value of water pressure fluctuation, S represents the average water flow velocity, NS represents the water flow velocity reference value, represents the collector surface temperature influence weight, represents the average water pressure impact weight, represents the influence weight of water pressure fluctuation, Indicates the water flow velocity influence weight.

[0039] The collector surface temperature influence weight, average water pressure influence weight, water pressure fluctuation influence weight and water flow velocity influence weight can be obtained from the database. For example, the collector surface temperature influence weight can be obtained by obtaining the historical collector surface temperature stored in the database, and the collector surface temperature influence weight corresponding to the historical collector surface temperature, thereby constructing a collector surface temperature mapping set, wherein there is a one-to-one or many-to-one correspondence in the mapping set. The collector surface temperature influence weight can be obtained by inputting the collector surface temperature data to be used into the collector surface temperature mapping set. The acquisition method of other influence weights such as the average water pressure influence weight, the water pressure fluctuation influence weight and the water flow velocity influence weight is the same as the acquisition method of the collector surface temperature influence weight, and can all be matched in the corresponding mapping set, wherein the average water pressure influence weight corresponds to the average water pressure mapping set, the water pressure fluctuation influence weight corresponds to the water pressure fluctuation amplitude mapping set, and the water flow velocity influence weight corresponds to the water flow velocity mapping set.

[0040] Furthermore, based on the external interference index of the water heater and the internal interference index of the water heater, the filtered signal data is filtered and corrected, and the specific steps include: obtaining the external interference threshold and the internal interference threshold preset in the database, and comparing them with the external interference index of the water heater and the internal interference index of the water heater, respectively, to obtain the interference regulation execution judgment result; the interference regulation execution judgment result includes the first interference execution plan, the second interference execution plan, the third interference execution plan and the fourth interference execution plan; if the external interference index of the water heater is below the external interference threshold and the internal interference index of the water heater is below the internal interference threshold, then the interference regulation execution judgment result is to adopt the first interference execution plan; if the external interference index of the water heater is below the external interference threshold and the internal interference index of the water heater is greater than the internal interference threshold, then the interference regulation The execution judgment result is to adopt the second interference execution plan; if the external interference index of the water heater is greater than the external interference threshold and the internal interference index of the water heater is below the internal interference threshold, the interference regulation execution judgment result is to adopt the third interference execution plan; if the external interference index of the water heater is greater than the external interference threshold and the internal interference index of the water heater is greater than the internal interference threshold, the interference regulation execution judgment result is to adopt the fourth interference execution plan; based on the interference regulation execution judgment result, the filter correction adjustment coefficient is analyzed to obtain the filter correction adjustment coefficient, thereby performing filter correction processing on the filtered signal data; the filter correction adjustment coefficient includes a first filter correction adjustment coefficient, a second filter correction adjustment coefficient, a third filter correction adjustment coefficient and a fourth filter correction adjustment coefficient; the filtered signal data includes the cutoff frequency of the filter, the filter order, the sliding window and the window function β value.

[0041] In this embodiment, by obtaining the external interference threshold and the internal interference threshold, and comparing them with the actual external interference index and the internal interference index, the interference adjustment execution scheme can be flexibly determined, and corresponding filtering correction measures can be taken for different interference situations, thereby improving the flexibility and adaptability of filtering correction. Based on the interference adjustment execution determination result, the filtering correction adjustment coefficient is analyzed to obtain the filtering signal data for accurate filtering correction processing. By dynamically adjusting the actual interference situation, the filtering effect can be effectively improved to ensure the quality of the collected signal. By analyzing the impact of external interference and internal interference on the filtered signal, different interference execution schemes are formulated, and various interference factors are comprehensively processed to ensure the comprehensiveness and effectiveness of the filtering correction process. By using the preset external interference threshold and internal interference threshold, as well as the filtering signal data (such as the cutoff frequency of the filter, the filter order, the sliding window, and the window function β value), decisions can be made according to the actual data to improve the scientificity and accuracy of the filtering correction. Through effective filtering correction processing, the signal quality is improved, thereby providing reliable data support for the calculation of the thermal efficiency of the water heater, ensuring the accuracy and reliability of the thermal efficiency calculation.

[0042] Furthermore, based on the interference regulation execution judgment result, the filter correction adjustment coefficient is analyzed and obtained, and the specific steps include: based on the interference regulation execution judgment result, the filter correction adjustment coefficient is analyzed and obtained, and the filter correction adjustment coefficient includes a first filter correction adjustment coefficient, a second filter correction adjustment coefficient, a third filter correction adjustment coefficient and a fourth filter correction adjustment coefficient; if the interference regulation execution judgment result is the first interference execution scheme, the first filter correction adjustment coefficient is analyzed and obtained; if the interference regulation execution judgment result is the second interference execution scheme, the second filter correction adjustment coefficient is analyzed and obtained; if the interference regulation execution judgment result is the third interference execution scheme, the third filter correction adjustment coefficient is analyzed and obtained; if the interference regulation execution judgment result is the fourth interference execution scheme, the fourth filter correction adjustment coefficient is analyzed and obtained.

[0043] In this embodiment, it should be noted that if the interference adjustment execution determination result is the first interference execution scheme, the first coefficient of the filter correction adjustment is obtained by analysis, and the specific steps include: based on the external interference index of the water heater and the internal interference index of the water heater, the comprehensive interference index of the water heater is obtained by analysis, and the calculation method of the comprehensive interference index of the water heater is: ; In the formula, ZR represents the comprehensive interference index of the water heater, WB represents the external interference index of the water heater, and NR represents the internal interference index of the water heater. represents the external interference impact weight, Represents the internal interference impact weight.

[0044] The specific steps for matching the first coefficient of the filter correction adjustment include: obtaining the comprehensive interference index intervals of each water heater preset in the database and the reference adjustment coefficients corresponding to the comprehensive interference index intervals of each water heater; if the comprehensive interference index of the water heater is within a certain comprehensive interference index interval of the water heater, then obtaining the reference adjustment coefficient corresponding to the interval as the first coefficient of the filter correction adjustment.

[0045] It should also be noted that the external interference impact weights and internal interference impact weights can be obtained through a database. For example, the external interference impact weights can be obtained by obtaining the historical external interference impact weights and historical external interference indicators in the database, thereby constructing an external interference mapping set, wherein there is a one-to-one or many-to-one correspondence in the mapping set. The external interference impact weights can be obtained by inputting the external interference indicators to be used into the external coefficient mapping set. The internal interference impact weights are obtained in the same way as the external interference impact weights, and can be matched in the corresponding internal interference mapping set, wherein the internal interference impact weights correspond to the internal interference mapping set.

[0046] If the interference adjustment execution judgment result is the second interference execution scheme, the second coefficient of the filter correction adjustment is analyzed, and the specific steps include: obtaining each external interference index interval preset in the database, based on the second reference correction coefficient corresponding to each external interference index interval, if the external interference index is within a preset external interference index interval, then obtaining the second reference correction coefficient corresponding to the interval as the second coefficient of the filter correction adjustment.

[0047] If the interference adjustment execution judgment result is the third interference execution scheme, the third coefficient of the filter correction adjustment is analyzed, and the specific steps include: obtaining each internal interference index interval preset in the database, based on the third reference correction coefficient corresponding to each internal interference index interval, if the internal interference index is within a preset internal interference index interval, then obtaining the third reference correction coefficient corresponding to the interval as the third coefficient of the filter correction adjustment.

[0048] If the interference adjustment execution judgment result is the fourth interference execution scheme, the fourth coefficient of the filter correction adjustment is obtained by analysis. The specific steps include: obtaining the water heater comprehensive interference threshold preset in the database, and performing comprehensive processing with the water heater comprehensive interference index to obtain the water heater execution adjustment reference value, obtaining each water heater execution adjustment reference value interval preset in the database and the fourth reference correction coefficient corresponding to each water heater execution adjustment reference value interval, if the water heater execution adjustment reference value is within a preset water heater execution adjustment reference value interval, then the fourth reference correction coefficient corresponding to the interval is obtained as the fourth coefficient of the filter correction adjustment. It should be noted that the specific method for obtaining the water heater execution adjustment reference value is: ; In the formula, SCZ represents the reference value for the water heater to perform adjustment, It represents the comprehensive interference threshold of the water heater, and ZR represents the comprehensive interference index of the water heater.

[0049] According to different interference execution schemes, the filter correction adjustment coefficient is matched based on external interference indicators, internal interference indicators or comprehensive interference indicators, which can more accurately adapt to various complex interference situations and improve the pertinence and effectiveness of filter correction. Different matching mechanisms are used for different interference execution schemes. For example, the first interference execution scheme is matched based on the comprehensive interference indicator, the second and third interference execution schemes are matched with the preset interval based on the external and internal interference indicators respectively, and the fourth interference execution scheme is matched with the preset interval by calculating the adjustment execution coefficient. The multi-level matching mechanism can more carefully reflect the impact of different interference levels on filter correction and improve the accuracy of adjustment.

[0050] By using the preset external interference index interval, internal interference index interval and adjustment execution coefficient interval, combined with the actual interference index data, data-driven filter correction adjustment is realized, which is conducive to more scientific determination of the filter correction adjustment coefficient and improves the filtering effect and the accuracy of thermal efficiency calculation. Through reasonable filter correction adjustment, the influence of interference on the thermal efficiency calculation of water heaters can be effectively reduced, the stability and reliability of calculation can be improved, the accuracy and credibility of thermal efficiency evaluation can be ensured, and it can adapt to different types of water heaters and different working environments. By adjusting the preset intervals and matching rules, it can be flexibly applied to various scenarios, with strong versatility and adaptability.

[0051] Furthermore, filter correction processing is performed on the filtered signal data, and the specific steps include: analyzing based on the interference adjustment execution judgment result, if the interference adjustment execution judgment result is the first interference execution scheme, then adjusting the first coefficient according to the filter correction to adjust the filter order downward, and keeping the filter cutoff frequency, sliding window and window function β value unchanged; if the interference adjustment execution judgment result is the second interference execution scheme, then adjusting the second coefficient according to the filter correction to adjust the filter sliding window upward, and keeping the filter cutoff frequency, filter order and window function β value unchanged; if the interference adjustment execution judgment result is the third interference execution scheme, then adjusting the third coefficient according to the filter correction to adjust the filter order and the filter window function β value upward, adjusting the filter cutoff frequency downward, and keeping the filter sliding window unchanged; if the interference adjustment execution judgment result is the fourth interference execution scheme, then adjusting the fourth coefficient according to the filter correction under preset conditions to adjust the filter order, the filter sliding window, the window function β value upward, and the filter cutoff frequency downward.

[0052] In this embodiment, it should be noted that the preset conditions are that the cutoff frequency is not higher than the cutoff frequency upper limit preset in the database and the sliding window is not lower than the sliding window lower limit preset in the database. If the cutoff frequency is greater than the cutoff frequency upper limit preset in the database, the cutoff frequency is set to the cutoff frequency upper limit size. If the sliding window is below the sliding window lower limit preset in the database, the sliding window is set to the sliding window lower limit size, wherein the filter order and the window function β value have no limited interval.

[0053] It should be noted that, assuming that the initial filter parameters are as follows: the filter order is 5, the cutoff frequency is 1500HZ, the sliding window is 50, and the window function β value is 0.5, if the interference adjustment execution judgment result is the first interference execution scheme, the filter order is adjusted downward according to the first coefficient of the filter correction adjustment, for example: if the first coefficient of the filter correction adjustment is 0.8, the filter order is 5, then the adjusted filter order is 5×0.8=4, and the filter cutoff frequency, sliding window and window function β value are kept unchanged. It should be understood that the external interference index is below the external interference threshold and the internal interference index is below the internal interference threshold, and the filter order is adjusted downward according to the first coefficient of the filter correction adjustment, and the filter cutoff frequency, sliding window and window function β value are kept unchanged. This is because both the external and internal interferences are relatively low in this case, so the purpose of filter adjustment can be achieved without complex filtering processing. Reducing the filter order can reduce the computational complexity, while keeping other parameters unchanged to maintain the basic characteristics of the signal.

[0054] If the interference adjustment execution judgment result is the second interference execution scheme, the sliding window of the filter is adjusted upward according to the second coefficient of the filter correction, and the cutoff frequency and the β value of the filter are kept unchanged. For example, if the second coefficient of the filter correction is adjusted to 1.2, the adjusted sliding window is 50×1.2=60, and the cutoff frequency, filter order and window function β value of the filter are kept unchanged. It should be understood that the external interference index is below the external interference threshold and the internal interference index is greater than the internal interference threshold. The sliding window of the filter is adjusted upward according to the second coefficient of the filter correction, and the cutoff frequency, filter order and window function β value of the filter are kept unchanged. This is because in this case, the external interference is relatively low, but the internal interference is relatively high. Increasing the sliding window can better capture the dynamic changes of internal interference and improve the filtering effect, while keeping other parameters unchanged to maintain the basic characteristics of the signal.

[0055] If the interference adjustment execution judgment result is the third interference execution scheme, the filter order and the filter window function β value are adjusted upward according to the filter correction adjustment third coefficient, the filter cutoff frequency is adjusted downward, and the sliding window of the filter is kept unchanged. For example, assuming that the filter correction adjustment third coefficient is 1.5, the adjusted filter order is 1.5×5=7.5 (taken as an integer of 8), the adjusted window function β value is 1.5×0.5=0.75, the adjusted cutoff frequency is 1500÷1.5=1000, and the filter sliding window is kept unchanged. It should be understood that the external interference index is greater than the external interference threshold and the internal interference index is below the internal interference threshold. According to the filter correction adjustment third coefficient, the filter order and the filter window function β value are adjusted upward, and the filter cutoff frequency is adjusted downward, while the filter sliding window is kept unchanged. This is because in this case, the external interference is relatively high, but the internal interference is relatively low. Increasing the filter order and the window function β value can better filter out external interference and improve the filtering effect. At the same time, lowering the cutoff frequency can better retain the low-frequency components of the signal and avoid interference from high-frequency noise.

[0056] If the interference adjustment execution judgment result is the fourth interference execution scheme, the filter order, the sliding window of the filter, and the window function β value are adjusted upward according to the fourth coefficient of the filter correction under the preset conditions, and the cutoff frequency of the filter is adjusted downward. For example: assuming that the fourth coefficient of the filter correction adjustment is 1.8, the adjusted filter order is 1.8×5=9, the adjusted sliding window is 1.8×50=90, the adjusted window function β value is 1.8×0.5=0.9, and the adjusted cutoff frequency is . It should be understood that if the external interference index of the water heater is greater than the external interference threshold and the internal interference index of the water heater is greater than the internal interference threshold, the filter order, the sliding window of the filter, and the window function β value are adjusted upward according to the filter correction adjustment fourth coefficient under preset conditions, and the filter cutoff frequency is adjusted downward. This is because in this case, both the external interference and the internal interference are high, and more complex filtering processing is required. Such adjustments help improve the performance of the filter so that it can better cope with larger external and internal interferences. By increasing the filter order, the selectivity of the filter can be improved, and by increasing the sliding window, the smoothing effect on the signal can be enhanced. By increasing the window function β value, the sidelobe suppression capability can be improved, and lowering the cutoff frequency helps reduce the passage of high-frequency interference signals, thereby improving the purity of the signal.

[0057] It should be noted that if the value of the filter order, sliding window or cutoff frequency is a decimal, adjacent integers are selected. The rule for selecting adjacent integers is that if the adjustment method is upward adjustment, the integer closest to the decimal and greater than the decimal is selected; if the adjustment method is downward adjustment, the integer closest to the decimal and less than the decimal is selected.

[0058] According to different interference execution schemes, the filter's cutoff frequency, order, sliding window and window function β value are adjusted accordingly, which can more accurately adapt to various complex interference situations and improve the pertinence and effectiveness of filter correction. Different adjustment strategies are adopted for different interference execution schemes. For example, the first interference execution scheme mainly adjusts the filter order, the second interference execution scheme mainly adjusts the sliding window, the third interference execution scheme adjusts the filter order, the window function β value and the cutoff frequency at the same time, and the fourth interference execution scheme comprehensively adjusts the filter parameters under preset conditions. The multi-level matching mechanism of this scheme can more carefully reflect the impact of different interference levels on filter correction, and improve the accuracy of adjustment.

[0059] By using the preset upper limit of the cutoff frequency and the lower limit of the sliding window, combined with the actual filter correction adjustment coefficient, data-driven filter correction adjustment can be achieved, which can more scientifically determine the filter parameters and improve the accuracy of the filter effect and thermal efficiency calculation. Through reasonable filter correction adjustment, the impact of interference on the thermal efficiency calculation of the water heater can be effectively reduced, the stability and reliability of the system can be improved, and the accuracy and credibility of the thermal efficiency evaluation can be ensured. By adjusting the preset parameters and matching rules, it can be flexibly applied to various scenarios, with strong versatility and adaptability.

[0060] Furthermore, the signal quality parameters after the filtering correction processing are obtained, the filtering correction quality index is obtained by analysis, and the filtering correction quality index is compared with the filtering signal quality index before the filtering correction processing to obtain the filtering correction result. The specific steps include: obtaining the signal quality parameters after the filtering correction processing in the second preset time period, the signal quality parameters include the maximum signal-to-noise ratio, average signal delay time, average signal strength and average return loss of the filtered signal; obtaining the signal quality reference set preset in the database and performing differentiation processing with the signal quality parameters after the filtering correction processing to obtain the filtering correction quality index; obtaining the optimization effect threshold preset in the database, based on the filtering signal quality index before the filtering processing and comparing it with the filtering correction quality index, to obtain the filtering correction result, if the filtering correction quality index is greater than the filtering signal quality index before the filtering processing, and the difference between the filtering correction quality index and the filtering signal quality index before the filtering processing is above the optimization effect threshold, then the filtering correction result is qualified filtering correction, otherwise it is unqualified filtering correction; the signal quality reference set includes a signal-to-noise ratio reference value, an allowable value of signal delay time, a signal strength reference value and an allowable error of return loss.

[0061] In this embodiment, it should be noted that the preset period is different from the second preset period, and the second preset period is a period after the preset period and is completely irrelevant to the preset period.

[0062] It should be noted that the method for obtaining the filtering signal quality indicator before filtering processing is the same as the method for obtaining the filtering signal quality indicator after filtering processing, and both can be obtained by obtaining signal quality parameters and analyzing them with the signal quality reference set preset in the database. However, it should be noted that the filtering signal quality indicator before filtering processing is obtained by obtaining the signal quality parameters within a reference preset time period before filtering processing, and the time dimension of the filtering signal quality indicator before filtering processing is not the same as that of the filtering signal quality indicator after filtering processing.

[0063] It should be noted that if the filter correction result is that the filter correction fails, the filter correction process will continue to be executed. The specific steps include: if the filter correction result is that the filter correction fails, the external interference index of the water heater and the internal interference index of the water heater after the filter correction are obtained, and the secondary correction filter adjustment coefficient is obtained by analysis, and the filtering process is re-performed within a preset number of times until the filter correction result is that the filter correction is qualified. If the filter correction result is still that the filter correction fails within the preset number of times, an early warning is issued.

[0064] By obtaining the external interference index and internal interference index after filter correction, the secondary correction filter adjustment coefficient is analyzed, which can adapt to various complex interference situations more accurately and improve the pertinence and effectiveness of filter correction. Re-filtering within the preset number of times until the filter correction result is qualified can more carefully reflect the influence of different interference levels on filter correction and improve the accuracy of adjustment. By using the preset external interference index and internal interference index, combined with the actual filter correction adjustment coefficient, data-driven filter correction adjustment can be realized, which can more scientifically determine the filter parameters, improve the accuracy of filter effect and thermal efficiency calculation, effectively reduce the influence of interference on the thermal efficiency calculation of water heater, improve stability and reliability, and ensure the accuracy and credibility of thermal efficiency evaluation. If the filter correction result is still unqualified within the preset number of times, an early warning will be issued to facilitate timely discovery and resolution of problems in the data acquisition process and ensure the smooth progress of the water heater thermal efficiency calculation process.

[0065] The filter correction quality index is obtained by analyzing the signal quality parameters in the second preset time period after the filter correction processing, taking into account the mutual influence relationship between these parameters, for example: the higher the maximum signal-to-noise ratio, the stronger the signal is relative to the noise, and the better the signal quality, while the shorter the average signal delay time, the faster the signal transmission and the better the real-time performance, and these two work together to affect the signal transmission quality. The higher the average signal strength, the less attenuation and interference the signal suffers during transmission, which helps to improve the maximum signal-to-noise ratio. The larger the average return loss, the faster the reflected signal attenuates, and the smaller the reflected interference of the signal during transmission, which helps to improve the signal integrity and maximum signal-to-noise ratio. These parameters influence each other and jointly determine the quality of the signal. When designing and optimizing the signal processing system, these parameters should be comprehensively considered to ensure high-quality transmission and processing of the signal.

[0066] The filter correction quality index is obtained by: ; In the formula, JZ represents the filter correction quality index, JX represents the maximum signal-to-noise ratio of the filter signal, represents the reference value of signal-to-noise ratio, JY represents the average signal delay time of the filtered signal, Indicates the allowable value of signal delay time, JQ indicates the average signal strength of the filtered signal, Indicates the signal strength reference value, JS indicates the average return loss of the filtered signal, Indicates the allowable error of return loss, represents the signal-to-noise ratio impact weight, Indicates that the signal delay duration affects the weight, Indicates the signal strength influence weight, Indicates the return loss impact weight.

[0067] The signal-to-noise ratio influence weight, signal delay time influence weight, signal strength influence weight and return loss influence weight can be obtained from a database. For example, the signal-to-noise ratio influence weight can be obtained by obtaining the historical signal-to-noise ratio stored in the database, and the signal-to-noise ratio influence weight corresponding to the historical signal-to-noise ratio, thereby constructing a signal-to-noise ratio mapping set, wherein there is a one-to-one or many-to-one correspondence in the mapping set. The signal-to-noise ratio influence weight can be obtained by inputting the signal-to-noise ratio data to be used into the signal-to-noise ratio mapping set. The other influence weights, such as the signal delay time influence weight, the signal strength influence weight and the return loss influence weight, are obtained in the same way as the signal-to-noise ratio influence weight, and can all be matched in the corresponding mapping set, wherein the signal delay time influence weight corresponds to the signal delay time mapping set, the signal strength influence weight corresponds to the signal strength mapping set, and the return loss influence weight corresponds to the return loss mapping set.

[0068] like Figure 2As shown, it is a structural schematic diagram of the thermal efficiency calculation system of the water heater based on big data provided in the embodiment of the present application. The thermal efficiency calculation system of the water heater based on big data provided in the embodiment of the present application includes: an external interference evaluation module, an internal interference evaluation module, a filter correction module, a filter correction result analysis module and a thermal efficiency evaluation module; wherein the external interference evaluation module is used to obtain the power interference parameters of the water heater after receiving the signal detected by the equipment, analyze and obtain the power noise interference index, obtain the electromagnetic interference parameters of the water heater, analyze and obtain the electromagnetic noise interference index, and analyze and obtain the external interference index of the water heater; the internal interference evaluation module is used to obtain the internal interference parameters of the water heater, analyze and obtain The internal interference index of the water heater; a filter correction module, which is used to perform filter correction processing on the filter signal data based on the external interference index of the water heater and the internal interference index of the water heater; a filter correction result analysis module, which is used to obtain the signal quality parameters after the filter correction processing, analyze the filter correction quality index, and compare it with the filter signal quality index before the filter correction processing to obtain the filter correction result; a thermal efficiency evaluation module, which is used to obtain the thermal efficiency evaluation parameters after the filter processing if the filter correction result is qualified, and input them into the preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater; if the filter correction result is unqualified, continue to execute the filter correction processing.

[0069] To sum up, this embodiment obtains the power supply interference parameters and electromagnetic interference parameters of the water heater, analyzes the power supply noise interference index and the electromagnetic noise interference index, and thus obtains the external interference index of the water heater, thereby realizing accurate quantitative evaluation of the external interference, and effectively solves the problem of inaccurate acquisition of thermal efficiency evaluation parameters of the water heater due to insufficient noise interference suppression ability of the filter in the prior art.

[0070] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0072] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0074] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0075] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for calculating thermal efficiency of water heaters based on big data, characterized in that: The following steps are involved: After receiving the signal detected by the device, the power interference parameter of the water heater is obtained, the power noise interference index is obtained by analysis, the electromagnetic interference parameter of the water heater is obtained, the electromagnetic noise interference index is obtained by analysis, and the external interference index of the water heater is obtained by analysis; Obtain the internal interference parameters of the water heater and analyze and obtain the internal interference index of the water heater; Performing filtering correction processing on the filtering signal data based on the external interference index of the water heater and the internal interference index of the water heater; Acquire the signal quality parameter after the filtering correction processing, analyze and obtain the filtering correction quality index, and compare it with the filtering signal quality index before the filtering correction processing to obtain the filtering correction result; If the filter correction result is qualified, the thermal efficiency evaluation parameters after filtering are obtained and input into the preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater. If the filter correction result is unqualified, the filter correction process continues.

2. The method for calculating thermal efficiency of water heaters based on big data according to claim 1, characterized in that: The steps of obtaining the power supply interference parameter of the water heater and analyzing to obtain the power supply noise interference index include: Obtaining power supply interference parameters of the water heater, wherein the power supply interference parameters of the water heater include voltage fluctuation amplitude, current harmonic content, voltage sag depth, maximum frequency deviation and surge voltage peak value of the power supply within a preset time period; Obtain the preset power interference reference set in the database, and perform differential analysis with the power interference parameters of the water heater to obtain the power noise interference index; The power supply interference reference set includes: the allowable value of voltage fluctuation amplitude, the allowable value of current harmonic content, the unit voltage sag depth impact factor, the unit maximum frequency deviation impact factor and the surge voltage peak reference value; The power supply noise interference index is used to analyze the difference between the voltage fluctuation amplitude, the current harmonic content and the surge voltage peak value and the allowable value of the voltage fluctuation amplitude, the allowable value of the current harmonic content and the surge voltage peak reference value, and combines the voltage sag depth and the unit voltage sag depth influence factor, the maximum frequency deviation of the power supply and the unit maximum frequency deviation influence factor to obtain the power supply noise interference index.

3. The method for calculating thermal efficiency of water heaters based on big data according to claim 1, characterized in that: The steps of obtaining the electromagnetic interference parameters of the water heater and analyzing to obtain the electromagnetic noise interference index include: Obtaining electromagnetic interference parameters of the water heater, wherein the electromagnetic interference parameters of the water heater include an average magnetic field radiation intensity, an average electromagnetic interference frequency, a maximum electromagnetic interference fluctuation amplitude, a maximum peak power density, and an average pulse repetition frequency of an electromagnetic interference signal within a preset time period; Obtain the preset electromagnetic interference limit set in the database, and analyze it with the electromagnetic interference parameters of the water heater to obtain the electromagnetic noise interference index; The electromagnetic interference limit value set includes a magnetic induction intensity limit value, an electromagnetic interference spectrum limit value, a fluctuation amplitude reference value, a peak power density reference value and a pulse repetition frequency reference value; The electromagnetic noise interference index is used to extract the electromagnetic interference parameters of the water heater, including the average magnetic field radiation intensity, average electromagnetic interference frequency, maximum electromagnetic interference fluctuation amplitude, maximum peak power density and average pulse repetition frequency of the electromagnetic interference signal within a preset time period, and analyze the difference between them and the magnetic induction intensity limit, electromagnetic interference spectrum limit, fluctuation amplitude reference value, peak power density reference value and pulse repetition frequency reference value, and then introduce the corresponding impact weight to obtain the electromagnetic noise interference index.

4. The method for calculating thermal efficiency of water heaters based on big data according to claim 1, characterized in that: The analysis obtains the external interference index of the water heater, and the specific steps include: Obtaining a power supply interference impact weight corresponding to a power supply noise interference index and an electromagnetic interference impact weight corresponding to an electromagnetic noise interference index preset in a database; The external interference index of the water heater is obtained by comprehensive analysis based on the power noise interference index, power interference influence weight, electromagnetic noise interference index and electromagnetic interference influence weight; The external interference index of the water heater is used to characterize the comprehensive interference degree of the power supply noise and electromagnetic noise of the water heater on the water heater by coupling analysis of the power supply noise interference index of the water heater and its corresponding power supply interference influence weight and combining the coupling result of the electromagnetic noise interference index and its corresponding electromagnetic interference influence weight to obtain the external interference index of the water heater.

5. The method for calculating thermal efficiency of water heaters based on big data according to claim 1, characterized in that: The steps of obtaining the internal interference parameters of the water heater and analyzing to obtain the internal interference index of the water heater include: Acquire internal interference parameters of the water heater, wherein the internal interference parameters of the water heater include average surface temperature of the collector of the water heater, average water pressure, maximum water pressure fluctuation and average water flow velocity within a preset time period; Obtaining a preset internal interference reference set in a database, and comparing it with the internal interference parameters of the water heater to obtain an internal interference index of the water heater; The internal interference reference set includes a temperature reference value, a water pressure reference value, a water pressure fluctuation allowable value and a water flow velocity reference value; The internal interference index of the water heater is used to perform difference analysis between the average temperature of the collector surface and the corresponding temperature reference value, compare the average water pressure and the maximum water pressure fluctuation with the water pressure reference value and the allowable value of the water pressure fluctuation respectively, compare the average water flow velocity with the water flow velocity reference value, and introduce their corresponding influence weights respectively for coupling processing to obtain the internal interference index of the water heater.

6. The method for calculating thermal efficiency of water heaters based on big data according to claim 1, characterized in that: The filtering signal data is filtered and corrected based on the external interference index of the water heater and the internal interference index of the water heater, and the specific steps include: Obtaining an external interference threshold and an internal interference threshold preset in a database, and comparing them with the external interference index of the water heater and the internal interference index of the water heater, respectively, to obtain an interference regulation execution determination result; If the external interference index of the water heater is below the external interference threshold and the internal interference index of the water heater is below the internal interference threshold, the interference adjustment execution determination result is to adopt the first interference execution plan; If the external interference index of the water heater is below the external interference threshold and the internal interference index of the water heater is greater than the internal interference threshold, the interference adjustment execution determination result is to adopt the second interference execution plan; If the external interference index of the water heater is greater than the external interference threshold and the internal interference index of the water heater is below the internal interference threshold, the interference adjustment execution determination result is to adopt the third interference execution scheme; If the external interference index of the water heater is greater than the external interference threshold and the internal interference index of the water heater is greater than the internal interference threshold, the interference adjustment execution determination result is to adopt the fourth interference execution scheme; Based on the interference regulation execution determination result, a filter correction adjustment coefficient is analyzed and obtained, thereby performing filter correction processing on the filter signal data; The filter correction adjustment coefficients include a first filter correction adjustment coefficient, a second filter correction adjustment coefficient, a third filter correction adjustment coefficient and a fourth filter correction adjustment coefficient; The filtered signal data includes the filter cutoff frequency, filter order, sliding window and window function β value.

7. The method for calculating thermal efficiency of water heaters based on big data as claimed in claim 6, characterized in that: The interference adjustment is performed based on the result of the determination, and the filter correction adjustment coefficient is obtained by analysis, and the specific steps include: Based on the interference regulation execution determination result, analyzing and obtaining the filter correction adjustment coefficient, if the interference regulation execution determination result is the first interference execution scheme, analyzing and obtaining the first filter correction adjustment coefficient; If the interference adjustment execution determination result is the second interference execution scheme, the second coefficient of the filter correction adjustment is obtained by analysis; If the interference adjustment execution determination result is the third interference execution scheme, the third coefficient of the filter correction adjustment is obtained by analysis; If the interference adjustment execution determination result is the fourth interference execution scheme, the fourth coefficient of the filter correction adjustment is obtained by analysis.

8. The method for calculating thermal efficiency of water heaters based on big data as claimed in claim 6, characterized in that: The filtering correction process for the filtered signal data specifically comprises the following steps: Performing analysis based on the interference adjustment execution determination result, if the interference adjustment execution determination result is the first interference execution scheme, adjusting the filter order downward according to the first coefficient of the filter correction, and keeping the filter cutoff frequency, sliding window and window function β value unchanged; If the interference adjustment execution determination result is the second interference execution scheme, the sliding window of the filter is adjusted upward according to the filter correction adjustment second coefficient, and the cutoff frequency of the filter, the filter order and the window function β value are kept unchanged; If the interference adjustment execution determination result is the third interference execution scheme, the filter order and the filter window function β value are adjusted upward according to the filter correction adjustment third coefficient, the filter cutoff frequency is adjusted downward, and the sliding window of the filter is kept unchanged; If the interference adjustment execution judgment result is the fourth interference execution scheme, the filter order, the sliding window of the filter, and the window function β value are adjusted upward according to the fourth coefficient of the filter correction under preset conditions, and the cutoff frequency of the filter is adjusted downward.

9. The method for calculating thermal efficiency of water heaters based on big data according to claim 1, characterized in that: The signal quality parameter after the filtering correction processing is obtained, the filtering correction quality index is obtained by analysis, and the filtering correction quality index is compared with the filtering signal quality index before the filtering correction processing to obtain the filtering correction result. The specific steps include: Acquire signal quality parameters within a second preset time period after filtering and correction processing, wherein the signal quality parameters include a maximum signal-to-noise ratio of the filtered signal, an average signal delay time, an average signal strength, and an average return loss; Obtaining a preset signal quality reference set in a database and performing differential processing on the signal quality parameters after filtering and correction processing to obtain a filtering and correction quality index; Obtaining the optimization effect threshold preset in the database, and comparing the filter signal quality index before filtering processing with the filter correction quality index to obtain the filter correction result. If the filter correction quality index is greater than the filter signal quality index before filtering processing, and the difference between the filter correction quality index and the filter signal quality index before filtering processing is above the optimization effect threshold, then the filter correction result is qualified, otherwise, the filter correction is unqualified; The signal quality reference set includes a signal-to-noise ratio reference value, a signal delay time allowable value, a signal strength reference value, and a return loss allowable error.

10. A system using a method for calculating thermal efficiency of a water heater based on big data as claimed in any one of claims 1 to 9, characterized in that: include: External interference assessment module, internal interference assessment module, filter correction module, filter correction result analysis module and thermal efficiency assessment module; The external interference evaluation module is used to obtain the power interference parameters of the water heater, analyze and obtain the power noise interference index, obtain the electromagnetic interference parameters of the water heater, analyze and obtain the electromagnetic noise interference index, and analyze and obtain the external interference index of the water heater after receiving the signal detected by the device; The internal interference evaluation module is used to obtain the internal interference parameters of the water heater and analyze and obtain the internal interference index of the water heater; The filtering correction module is used to perform filtering correction processing on the filtering signal data based on the external interference index of the water heater and the internal interference index of the water heater; The filter correction result analysis module is used to obtain the signal quality parameters after the filter correction processing, analyze and obtain the filter correction quality index, and compare it with the filter signal quality index before the filter correction processing to obtain the filter correction result; The thermal efficiency evaluation module is used to obtain the thermal efficiency evaluation parameters after filtering if the filtering correction result is qualified, and input them into a preset water heater thermal efficiency evaluation model to calculate the thermal efficiency of the water heater; if the filtering correction result is unqualified, continue to perform the filtering correction process.

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