A method and system for calculating the thermal efficiency of a water heater based on big data

Abstract

The present invention discloses a method and system for calculating the thermal efficiency of a water heater based on big data, belonging to the technical field of data processing, and comprising the following steps: obtaining the power interference parameters of the water heater, analyzing to obtain the power noise interference index, obtaining the electromagnetic interference parameters of the water heater, analyzing to obtain the electromagnetic noise interference index, and analyzing to obtain the external interference index of the water heater; analyzing to obtain the internal interference index of the water heater; performing filtering and correction processing on the filtered signal data; analyzing to obtain the filtering and correction quality index, and comparing it with the filtering signal quality index before the filtering and correction processing to obtain the filtering and correction result; if the filtering and correction result is qualified for filtering and correction, then calculate the thermal efficiency of the water heater, and if the filtering and correction result is unqualified for filtering and correction, then continue to perform the filtering and correction processing. It solves the problem in the prior art that the acquisition of the thermal efficiency evaluation parameters of the water heater is inaccurate due to the insufficient ability of the filter to suppress noise interference.

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 the thermal efficiency of a water heater based on big data. Background Art

[0002] With the popularization of solar water heaters in the household and commercial fields, the evaluation of their thermal efficiency and performance optimization have become the focus of technical research. The existing calculation of the thermal efficiency of water heaters is achieved by establishing a linear formula of heat production and ambient temperature through laboratory tests or generating a theoretical thermal energy conversion curve through a thermal efficiency conversion coefficient, and combining real-time water temperature data with a photoelectric switching efficiency model for performance evaluation.

[0003] For example, the heat pump water heater power saving calculation method and the heat pump water heater with the display of power saving amount announced in the invention patent announcement with the publication number of CN105989221B include: obtaining the curve formula of heat production and ambient temperature and the heat production efficiency formula through laboratory tests; according to the initial water temperature and the final water temperature when the user actually uses the heat pump water heater to produce hot water, the initial water temperature and the final water temperature determined during laboratory tests, and the formula of heat production and ambient temperature, calculating the heat production when the user actually uses the heat pump water heater to produce hot water; calculating the power consumption for producing hot water when the user uses the heat pump water heater according to the heat production efficiency of the heat pump water heater, the heat production when the user actually uses the heat pump water heater to produce hot water, and the heat production time; then calculating the power consumption for producing hot water when the user uses an electric water heater; and further obtaining the power saved when the user actually uses the heat pump water heater to produce hot water compared with using the electric water heater to produce hot water.

[0004] For example, a method and system for evaluating the heating performance of a solar water heater announced in the invention patent announcement with the publication number of CN113705113B include: obtaining a first thermal efficiency conversion coefficient; obtaining a first thermal energy conversion temperature curve according to 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 according to 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; and obtaining a first heating performance evaluation result of the first solar water heater according to the first light energy heating evaluation result and the first photoelectric switching efficiency evaluation result.

[0005] However, in the process of implementing the technical solutions of the present invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0006] In the prior art, the method for calculating the thermal efficiency of the prior art is evaluated in an ideal environment. However, in actual scenarios, there will be complex and variable noise interferences. For the calculation of the thermal efficiency of a solar water heater, high-precision data is usually required. The emergence of noise will seriously affect the refined acquisition of the thermal efficiency parameters of the water heater, resulting in deviations in the thermal efficiency parameters of the water heater and thus affecting the calculation of the thermal efficiency. Therefore, there is a problem that the acquisition of the thermal efficiency evaluation parameters of the water heater is inaccurate due to the insufficient ability of the filter to suppress noise interference. Summary of the Invention

[0007] By providing a method and system for calculating the thermal efficiency of a water heater based on big data, the embodiments of the present application solve the problem in the prior art that the acquisition of the thermal efficiency evaluation parameters of the water heater is inaccurate due to the insufficient ability of the filter to suppress noise interference, and achieve the accurate acquisition of temperature.

[0008] The embodiments of the present application provide a method for calculating the thermal efficiency of a water heater based on big data, which is characterized by including the following steps: after receiving the 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 and analyzing to obtain the internal interference index of the water heater; performing filtering and correction processing on the filtered signal data based on the external interference index and the internal interference index of the water heater; obtaining the signal quality parameter after the filtering and correction processing, analyzing to obtain the filtering and correction quality index, and comparing it with the filtering signal quality index before the filtering and correction processing to obtain the filtering and correction result; if the filtering and correction result is qualified for filtering and correction, obtaining the thermal efficiency evaluation parameter after the filtering process and inputting it into a preset thermal efficiency evaluation model of the water heater for calculating the thermal efficiency of the water heater, and if the filtering and correction result is unqualified for filtering and correction, continuing to perform the filtering and correction processing.

[0009] A system for calculating the thermal efficiency of a water heater based on big data, characterized by comprising: an external interference evaluation module, an internal interference evaluation module, a filtering and correction module, a filtering and correction result analysis module, and a thermal efficiency evaluation module; wherein, the external interference evaluation module is configured to, after receiving a signal detected by a device, obtain the power interference parameters of the water heater, analyze to obtain the power noise interference index, obtain the electromagnetic interference parameters of the water heater, analyze to obtain the electromagnetic noise interference index, and analyze to obtain the external interference index of the water heater; the internal interference evaluation module is configured to obtain the internal interference parameters of the water heater and analyze to obtain the internal interference index of the water heater; the filtering and correction module is configured to perform filtering and correction processing on the filtered signal data based on the external interference index and the internal interference index of the water heater; the filtering and correction result analysis module is configured to obtain the signal quality parameters after the filtering and correction processing, analyze to obtain the filtering and correction quality index, and compare it with the filtered signal quality index before the filtering and correction processing to obtain the filtering and correction result; the thermal efficiency evaluation module is configured to, if the filtering and correction result is qualified for filtering and correction, obtain the thermal efficiency evaluation parameters after filtering and input them into a preset water heater thermal efficiency evaluation model for calculating the thermal efficiency of the water heater, and if the filtering and correction result is unqualified for filtering and correction, continue to perform the filtering and correction processing.

[0010] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0011] 1. Perform filtering and correction processing on the filtered signal data based on the external interference index and the internal interference index of the water heater, thereby obtaining the signal quality parameters after the filtering and correction processing, analyzing to obtain the filtering and correction quality index, and comparing it with the filtered signal quality index before the filtering and correction processing, thus realizing the dynamic verification and optimization of the filtering and correction effect, ensuring the accuracy of the input data of the water heater thermal efficiency evaluation model, and effectively solving the problem in the prior art that the acquisition of the thermal efficiency evaluation parameters of the water heater is inaccurate due to the insufficient ability of the filter to suppress noise interference.

[0012] 2. The method for calculating the thermal efficiency of a water heater based on big data provided by the present invention realizes the accurate quantitative evaluation of external interference by obtaining the power interference parameters and electromagnetic interference parameters of the water heater, analyzing to obtain the power noise interference index and the electromagnetic noise interference index, and thus obtaining the external interference index of the water heater.

[0013] 3. The present invention realizes the accurate quantitative evaluation of internal environmental interference by obtaining the internal interference parameters of the water heater, analyzing to obtain the internal interference index of the water heater, and thus performing filtering and correction processing on the filtered signal data based on the internal interference index. Description of the Drawings

[0014] Figure 1Flowchart of the method for calculating the thermal efficiency of a water heater based on big data provided by an embodiment of the present application;

[0015] Figure 2 Schematic structural diagram of the system for calculating the thermal efficiency of a water heater based on big data provided by an embodiment of the present application. Detailed implementation manners

[0016] By providing a method and a system for calculating the thermal efficiency of a water heater based on big data, an embodiment of the present application solves the problem in the prior art that the acquisition of the thermal efficiency evaluation parameters of the water heater is inaccurate due to the insufficient ability of the filter to suppress noise interference, and achieves accurate acquisition of temperature.

[0017] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0018] As Figure 1 shown, it is a flowchart of the method for calculating the thermal efficiency of a water heater based on big data provided by an embodiment of the present application. The method includes the following steps: after receiving the signal detected by the device, obtain the power interference parameter of the water heater, analyze to obtain the power noise interference index, obtain the electromagnetic interference parameter of the water heater, analyze to obtain the electromagnetic noise interference index, and analyze to obtain the external interference index of the water heater; obtain the internal interference parameter of the water heater, and analyze to obtain the internal interference index of the water heater; perform filtering and 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; obtain the signal quality parameter after the filtering and correction processing, analyze to obtain the filtering and correction quality index, and compare it with the filtering signal quality index before the filtering and correction processing to obtain the filtering and correction result; if the filtering and correction result is qualified for filtering and correction, obtain the thermal efficiency evaluation parameter after the filtering process, and input it into the preset thermal efficiency evaluation model of the water heater for calculating the thermal efficiency of the water heater. If the filtering and correction result is unqualified for filtering and correction, continue to perform the filtering and correction processing.

[0019] In this embodiment, it should be noted that by obtaining and analyzing the power interference parameters and electromagnetic interference parameters of the water heater, comprehensively considering external interference factors, and obtaining internal interference parameters to analyze internal interference indicators, a comprehensive assessment of various interference factors in the working environment of the water heater is achieved, providing a basis for subsequent filtering and correction. Filtering and correction processing are performed on the filtered signal data based on external and internal interference indicators, and the correction result is judged by comparing the signal quality parameters before and after filtering and correction. If it is unqualified, correction continues, which can effectively improve the signal quality, ensure the accuracy and reliability of the collected data, and lay a foundation for the accurate calculation of the water heater's thermal efficiency. Only after the filtering and correction are qualified, the thermal efficiency evaluation parameters after filtering are input into the preset water heater thermal efficiency evaluation model for calculating the water heater's thermal efficiency, so as to obtain a more accurate water heater thermal efficiency, avoid calculation deviations caused by data errors, and improve the accuracy and credibility of the entire calculation method. By introducing a warning mechanism, if the filtering and correction result is still unqualified within the preset number of times, a warning is issued, which is convenient for timely discovering and solving problems in the data processing process, enhancing the reliability and stability of the entire calculation method, and ensuring the smooth progress of the water heater thermal efficiency calculation process.

[0020] Further, the power interference parameters of the water heater are obtained, and the power noise interference index is analyzed. The specific steps include: obtaining the power interference parameters of the water heater, where the power interference parameters of the water heater include the 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; obtaining the preset power interference reference set in the database and comparing it with the power interference parameters of the water heater to obtain the power noise interference index; the power 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 reference value of surge voltage peak value; the power noise interference index is used to analyze the difference degree between the voltage fluctuation amplitude, current harmonic content, and surge voltage peak value and the allowable value of voltage fluctuation amplitude, the allowable value of current harmonic content, and the reference value of surge voltage peak value, and combine the voltage sag depth with the unit voltage sag depth impact factor, the maximum frequency deviation of the power supply, and the unit maximum frequency deviation impact factor to obtain the power noise interference index.

[0021] In this embodiment, by obtaining multiple power interference parameters (such as voltage fluctuation amplitude, current harmonic content, etc.) and comparing them with a preset power interference reference set, the interference situation of the power supply on the water heater can be comprehensively evaluated, ensuring the comprehensiveness and accuracy of the analysis results. By using the allowable values and influence factors in the preset power interference reference set to compare with the actual power interference parameters, the degree of power noise interference can be accurately quantified, providing a scientific basis for subsequent filtering and correction processing. Moreover, according to different power interference situations, flexible comparison and analysis can be carried out to meet the power interference assessment requirements of water heaters in different environments, improving the adaptability and practicality of the entire calculation method, providing detailed data support for subsequent filtering and correction processing. Through accurate power noise interference indicators, more targeted filtering and correction can be carried out, improving the filtering effect and the accuracy of heat efficiency calculation.

[0022] It should be noted that the voltage fluctuation amplitude refers to the magnitude of the actual voltage deviation 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 situation where the effective value of the supply voltage suddenly drops within 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 peak value of the surge voltage refers to the instantaneous overvoltage generated when connecting or disconnecting an inductive load or a large load, which can be measured by an oscilloscope.

[0023] The method for obtaining the power noise interference index is as follows:

[0024] ;

[0025] ;

[0026] ;

[0027] In the formula, YR represents the power 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 influence factor of the unit voltage sag depth, PL represents the maximum frequency deviation of the power supply, RP represents the influence factor of the unit maximum frequency deviation, LD represents the peak value of the surge voltage of the power supply, RD represents the reference value of the peak value of the surge voltage, represents the voltage influence weight, represents the current influence weight.

[0028] It should be noted that the voltage influence weight and the current influence weight can be obtained from the database. For example, the voltage influence weight can be obtained by acquiring the historical voltage stored in the database and the corresponding voltage influence weight of the historical voltage, thereby constructing a voltage mapping set. There is a one-to-one or many-to-one correspondence in this mapping set. By inputting the voltage data to be used into the voltage mapping set, the voltage influence weight can be obtained. The acquisition method of the current influence weight is the same as that of the voltage influence weight and can also be obtained by matching in the corresponding mapping set, where the current influence weight corresponds to the current mapping set.

[0029] There are mutual influence relationships among these parameters such as the voltage fluctuation amplitude of the power supply, the current harmonic content, the voltage sag depth, the maximum frequency deviation, and the surge voltage peak value, and they jointly act to generate power supply noise interference. The specific influence relationships are as follows: The change in the voltage fluctuation amplitude will affect the current harmonic content. When the voltage fluctuates greatly, it will cause the distortion of the current waveform, thereby increasing the harmonic content. At the same time, the increase in the current harmonic content will also exacerbate the voltage fluctuation, forming a vicious cycle. The voltage sag depth and duration will affect the stability of the power supply. When a voltage sag occurs, it will cause abnormal operation of the equipment, and then generate more harmonic currents and voltage fluctuations. The existence of the maximum frequency deviation will make the frequency of the power supply unstable, affect the normal operation of the equipment, and will also cause the distortion of the voltage and current waveforms, increasing the harmonic content and the voltage fluctuation amplitude. The appearance of the surge voltage peak value will cause an instantaneous impact on the power supply system, resulting in abnormal operation of the equipment, thereby triggering voltage fluctuations, an increase in current harmonics, etc. These parameters influence and interact with each other, jointly constituting a complex power supply noise interference environment, which affects the normal operation of equipment such as solar water heaters.

[0030] Further, obtain the electromagnetic interference parameters of the water heater, and analyze to obtain the electromagnetic noise interference index. The specific steps include: obtaining the electromagnetic interference parameters of the water heater, where the electromagnetic interference parameters of the water heater include the average magnetic field radiation intensity, average electromagnetic interference frequency, maximum fluctuation amplitude of electromagnetic interference, maximum peak power density, and average pulse repetition frequency of the electromagnetic interference signal within a preset time period; obtaining the preset electromagnetic interference limit set 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 set includes the magnetic induction intensity limit, electromagnetic interference spectrum limit, fluctuation amplitude reference value, peak power density reference value, and pulse repetition frequency reference value; the electromagnetic noise interference index is used to extract the average magnetic field radiation intensity, average electromagnetic interference frequency, maximum fluctuation amplitude of electromagnetic interference, maximum peak power density, and average pulse repetition frequency of the electromagnetic interference signal of the water heater within a preset time period, and analyze the degree of 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 respectively, and then introduce the corresponding influence weights to obtain the electromagnetic noise interference index.

[0031] In this embodiment, it should be noted that the maximum fluctuation amplitude of electromagnetic interference refers to the maximum value of the intensity change range of the electromagnetic interference signal within a preset time period, that is, the difference between the maximum intensity and the minimum intensity of the electromagnetic interference signal. The maximum peak power density refers to the maximum value of the instantaneous power within the unit collector area within a preset time.

[0032] 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 fluctuation amplitude of electromagnetic interference 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.

[0033] 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, it is possible to comprehensively evaluate the impact of electromagnetic interference on the water heater and 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 to analyze with the actual electromagnetic interference parameters, it is possible to accurately quantify the degree of electromagnetic noise interference, provide a scientific basis for subsequent filtering and correction processing, and be able to flexibly analyze and evaluate according to different electromagnetic interference situations to meet the electromagnetic interference evaluation requirements of water heaters in different environments, improve the adaptability and practicality of the entire calculation method, and provide detailed data support for subsequent filtering and correction processing. Through the accurate electromagnetic noise interference index, it is possible to perform filtering and correction more targeted, improve the filtering effect and the accuracy of heat efficiency calculation.

[0034] In the operating environment of a solar water heater, electromagnetic interference can seriously affect the signal acquisition and parameter measurement of the solar water heater. Signal transmission is vulnerable to electromagnetic radiation from interference sources such as low-voltage lines, high-voltage lines, and signal towers. In the early stage, the signal output was analog signals, and the signal distortion was serious. Electromagnetic interference can cause the data collected by the sensor to be inaccurate, thereby affecting the control accuracy of the controller. For example, the detection of the water temperature and water level sensor is vulnerable to electromagnetic interference, and the collected data is not accurate enough, seriously affecting 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 can interfere with the signal transmission of the sensor, resulting in inaccurate collected data, thereby affecting the control accuracy of the controller. These electromagnetic interference parameters interact with each other and act on the power supply system together, generating power noise interference. For example, an increase in the average magnetic field radiation intensity and the average electromagnetic interference frequency will cause 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 cause 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 can cause abnormal operation, performance degradation, and even damage to the equipment.

[0035] By analyzing the electromagnetic interference parameters of the water heater (the average magnetic field radiation intensity, average electromagnetic interference frequency, maximum fluctuation amplitude of electromagnetic interference, maximum peak power density, and average pulse repetition frequency of the electromagnetic interference signal), the electromagnetic noise interference index is obtained. This is considering the mutual influence relationship between these parameters. For example, the average magnetic field radiation intensity and average electromagnetic interference frequency of the electromagnetic interference signal act together to increase the induced electromotive force and noise amplitude. The increase in the maximum fluctuation amplitude of electromagnetic interference further exacerbates the noise intensity, resulting in distortion of the voltage and current waveforms of the power supply system. 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 results in more pulse interferences. These factors interact with each other, jointly leading to the aggravation of power noise interference.

[0036] The method for obtaining the electromagnetic noise interference index is as follows:

[0037] ;

[0038] 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 value, FR represents the average electromagnetic interference frequency of the electromagnetic interference signal, CR represents the electromagnetic interference spectrum limit value, FB represents the maximum 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, and CL represents the pulse repetition frequency reference value. represents the influence weight of magnetic field radiation intensity, represents the influence weight of electromagnetic interference frequency, represents the influence weight of fluctuation amplitude, represents the influence weight of maximum peak power density, represents the influence weight of pulse repetition frequency.

[0039] The influence weight of magnetic field radiation intensity, the influence weight of electromagnetic interference frequency, the influence weight of fluctuation amplitude, the influence weight of maximum peak power density, and the influence weight of pulse repetition frequency can be obtained by retrieving from the database. For example: the influence weight of magnetic field radiation intensity can be obtained by retrieving the historical magnetic field radiation intensity stored in the database and the corresponding influence weight of magnetic field radiation intensity, thereby constructing a magnetic field radiation intensity mapping set, where there is a one-to-one or many-to-one correspondence in this mapping set. By inputting the magnetic field radiation intensity data to be used into the magnetic field radiation intensity mapping set, the influence weight of magnetic field radiation intensity can be obtained. The acquisition methods of other influence weights, such as the influence weight of electromagnetic interference frequency, the influence weight of fluctuation amplitude, the influence weight of maximum peak power density, and the influence weight of pulse repetition frequency, are the same as that of the influence weight of magnetic field radiation intensity, and can all be obtained by matching in the corresponding mapping sets. For example, the influence weight of electromagnetic interference frequency corresponds to the electromagnetic interference frequency mapping set, the influence weight of fluctuation amplitude corresponds to the fluctuation amplitude mapping set, the influence weight of maximum peak power density corresponds to the maximum peak power density mapping set, and the influence weight of pulse repetition frequency corresponds to the pulse repetition frequency mapping set.

[0040] Furthermore, the external interference index of the water heater is analyzed. The specific steps include: retrieving the power interference influence weight corresponding to the preset power noise interference index and the electromagnetic interference influence weight corresponding to the electromagnetic noise interference index in the database; comprehensively analyzing the external interference index of the water heater based on the power noise interference index, the power 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 noise and electromagnetic noise of the water heater on the water heater by coupling and analyzing the power noise interference index of the water heater with its corresponding power interference influence weight and combining the coupling result of the electromagnetic noise interference index with its corresponding electromagnetic interference influence weight to obtain the external interference index of the water heater.

[0041] In this embodiment, by multiplying the power supply noise interference index and the electromagnetic noise interference index by their corresponding interference degree coefficients respectively and then summing them up, the external interference index of the water heater is obtained, realizing the comprehensive evaluation of the external interference of the water heater. Considering the combined action of various interference factors, the evaluation result is more comprehensive and accurate. Quantifying the external interference index into a specific value facilitates the comparison and analysis of the external interference degrees of different water heaters or under different working conditions, providing a clear basis for subsequent filtering and correction processing. By adjusting the power interference influence weight and the electromagnetic interference influence weight, the external interference degree in different situations can be flexibly reflected, with strong versatility and adaptability, providing detailed external interference data for subsequent filtering and correction processing, which helps to perform filtering and correction more targeted, improving the filtering effect and the accuracy of thermal efficiency calculation.

[0042] The external interference index of the water heater is obtained by the following specific method:

[0043] ;

[0044] In the formula, WB represents the external interference index of the water heater, YR represents the power supply noise interference index, CR represents the electromagnetic noise interference index, represents the power interference influence weight, represents the electromagnetic interference influence weight.

[0045] It should be noted that the power interference influence weight and the electromagnetic interference influence weight can be obtained from the database. For example, the power interference influence weight can be obtained by acquiring the historical power supply interference stored in the database and the corresponding power interference influence weight, thereby constructing a power interference mapping set, in which there is a one-to-one or many-to-one correspondence relationship. By inputting the power supply interference data to be used into the power interference mapping set, the power interference influence weight can be obtained. The acquisition method of the electromagnetic interference influence weight is the same as that of the power interference influence weight, and it can also be obtained by matching in the corresponding mapping set. The mapping set corresponding to the electromagnetic interference influence weight is the electromagnetic interference mapping set.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] The internal interference index of the water heater is obtained by:

[0050] ;

[0051] ;

[0052] ;

[0053] ;

[0054] wherein, NR represents the internal interference index of the water heater, W represents the average temperature of the collector surface 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 amount, NB represents the allowable value of the water pressure fluctuation amount, S represents the average water flow velocity, NS represents the water flow velocity reference value, represents the influence weight of the collector surface temperature, represents the influence weight of the average water pressure, represents the influence weight of the water pressure fluctuation amount, represents the influence weight of the water flow velocity.

[0055] The influence weight of the collector surface temperature, the influence weight of the average water pressure, the influence weight of the water pressure fluctuation amount, and the influence weight of the water flow velocity can be obtained from the database. For example, the influence weight of the collector surface temperature can be obtained by acquiring the historical collector surface temperature stored in the database and the influence weight of the collector surface temperature corresponding to the historical collector surface temperature, thereby constructing a collector surface temperature mapping set, in which there is a one-to-one or many-to-one correspondence relationship. By inputting the collector surface temperature data to be used into the collector surface temperature mapping set, the influence weight of the collector surface temperature can be obtained. The acquisition methods of other influence weights such as the influence weight of the average water pressure, the influence weight of the water pressure fluctuation amount, and the influence weight of the water flow velocity are the same as the acquisition method of the influence weight of the collector surface temperature, and can all be matched and obtained in the corresponding mapping sets. Among them, the influence weight of the average water pressure corresponds to the average water pressure mapping set, the influence weight of the water pressure fluctuation amount corresponds to the water pressure fluctuation amount mapping set, and the influence weight of the water flow velocity corresponds to the water flow velocity mapping set.

[0056] Further, perform filtering and correction processing on the filtered signal data based on the external interference index and the internal interference index of the water heater. The specific steps include: obtaining the preset external interference threshold and internal interference threshold in the database, and comparing them with the external interference index and the internal interference index of the water heater respectively to obtain the interference adjustment execution determination result; the interference adjustment execution determination 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, 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 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 adjustment execution determination result is to adopt the fourth interference execution plan; based on the interference adjustment execution determination result, analyze and obtain the filtering and correction adjustment coefficient, and thus perform filtering and correction processing on the filtered signal data; the filtering and correction adjustment coefficient includes the first filtering and correction adjustment coefficient, the second filtering and correction adjustment coefficient, the third filtering and correction adjustment coefficient, and the fourth filtering and correction adjustment coefficient; the filtered signal data includes the cut-off frequency of the filter, the filter order, the sliding window, and the window function β value.

[0057] In this embodiment, by obtaining the external interference threshold and the internal interference threshold and comparing them with the actual external interference index and internal interference index, the interference adjustment execution plan can be flexibly determined, and corresponding filtering and correction measures can be taken for different interference situations, improving the flexibility and adaptability of filtering and correction. Based on the interference adjustment execution determination result, analyze and obtain the filtering and correction adjustment coefficient, so as to perform precise filtering and correction processing on the filtered signal data. Through dynamic adjustment of the actual interference situation, the filtering effect can be effectively improved, ensuring the quality of the collected signal. By analyzing the influence of external interference and internal interference on the filtered signal, different interference execution plans are formulated to comprehensively process various interference factors, ensuring the comprehensiveness and effectiveness of the filtering and correction process. Using the preset external interference threshold and internal interference threshold, as well as the filtered signal data (such as the cut-off frequency of the filter, the filter order, the sliding window, and the window function β value), decisions can be made based on the actual data, improving the scientificity and accuracy of filtering and correction. Through effective filtering and correction processing, the signal quality is improved, thus providing reliable data support for the calculation of the thermal efficiency of the water heater and ensuring the accuracy and reliability of the thermal efficiency calculation.

[0058] Further, based on the interference adjustment execution determination result, a filtering correction adjustment coefficient is analyzed. The specific steps include: based on the interference adjustment execution determination result, a filtering correction adjustment coefficient is analyzed. The filtering correction adjustment coefficient includes a first filtering correction adjustment coefficient, a second filtering correction adjustment coefficient, a third filtering correction adjustment coefficient, and a fourth filtering correction adjustment coefficient. If the interference adjustment execution determination result is the first interference execution scheme, then the first filtering correction adjustment coefficient is analyzed. If the interference adjustment execution determination result is the second interference execution scheme, then the second filtering correction adjustment coefficient is analyzed. If the interference adjustment execution determination result is the third interference execution scheme, then the third filtering correction adjustment coefficient is analyzed. If the interference adjustment execution determination result is the fourth interference execution scheme, then the fourth filtering correction adjustment coefficient is analyzed.

[0059] In this embodiment, it should be noted that if the interference adjustment execution determination result is the first interference execution scheme, then the first filtering correction adjustment coefficient is analyzed. The specific steps include: analyzing the comprehensive interference index of the water heater based on the external interference index and the internal interference index of the water heater. The calculation method of the comprehensive interference index of the water heater is: ; where ZR represents the comprehensive interference index of the water heater, WB represents the external interference index of the water heater, NR represents the internal interference index of the water heater, represents the external interference influence weight, represents the internal interference influence weight.

[0060] The specific steps for matching the first filtering correction adjustment coefficient include: obtaining each preset comprehensive interference index interval of the water heater and the reference adjustment coefficient corresponding to each comprehensive interference index interval in the database. If the comprehensive interference index of the water heater is within a certain comprehensive interference index interval of the water heater, then obtain the reference adjustment coefficient corresponding to this interval as the first filtering correction adjustment coefficient.

[0061] It should also be noted that the external interference influence weight and the internal interference influence weight can be obtained from the database. For example: the external interference influence weight can be obtained by obtaining the historical external interference influence weight and the historical external interference index in the database, thereby constructing an external interference mapping set. There is a one-to-one or many-to-one correspondence relationship in this mapping set. By inputting the external interference index to be used into the external coefficient mapping set, the external interference influence weight can be obtained. The acquisition method of the internal interference influence weight is the same as that of the external interference influence weight and can be obtained by matching in the corresponding internal interference mapping set, where the internal interference influence weight corresponds to the internal interference mapping set.

[0062] If the interference adjustment execution determination result is the second interference execution scheme, the filtering correction adjustment second coefficient is obtained through analysis. The specific steps are as follows: Obtain each preset external interference index interval 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 certain preset external interference index interval, obtain the second reference correction coefficient corresponding to this interval as the filtering correction adjustment second coefficient.

[0063] If the interference adjustment execution determination result is the third interference execution scheme, the filtering correction adjustment third coefficient is obtained through analysis. The specific steps are as follows: Obtain each preset internal interference index interval 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 certain preset internal interference index interval, obtain the third reference correction coefficient corresponding to this interval as the filtering correction adjustment third coefficient.

[0064] If the interference adjustment execution determination result is the fourth interference execution scheme, the filtering correction adjustment fourth coefficient is obtained through analysis. The specific steps are as follows: Obtain the preset comprehensive interference threshold of the water heater in the database, and perform comprehensive processing with the comprehensive interference index of the water heater to obtain the adjustment reference value for the water heater execution. Obtain each preset adjustment reference value interval for the water heater execution in the database and the fourth reference correction coefficient corresponding to each interval. If the adjustment reference value for the water heater execution is within a certain preset adjustment reference value interval for the water heater execution, obtain the fourth reference correction coefficient corresponding to this interval as the filtering correction adjustment fourth coefficient. It should be noted that the method for obtaining the adjustment reference value for the water heater execution is as follows: ; where SCZ represents the adjustment reference value for the water heater execution, represents the comprehensive interference threshold of the water heater, and ZR represents the comprehensive interference index of the water heater.

[0065] According to different interference execution schemes, the filtering correction adjustment coefficients are respectively matched based on external interference indexes, internal interference indexes, or comprehensive interference indexes, which can more precisely adapt to various complex interference situations and improve the pertinence and effectiveness of filtering correction. Different matching mechanisms are adopted for different interference execution schemes. For example, the first interference execution scheme is matched based on the comprehensive interference index, the second and third interference execution schemes are respectively matched based on external and internal interference indexes and preset intervals, and the fourth interference execution scheme is matched by calculating the adjustment execution coefficient and the preset interval. Through the multi-level matching mechanism, the influence of different interference degrees on filtering correction can be more carefully reflected, and the accuracy of adjustment can be improved.

[0066] By using the preset external interference index range, internal interference index range, and adjustment execution coefficient range, combined with the actual interference index data, data-driven filtering correction adjustment is realized, which is beneficial to more scientifically determine the filtering correction adjustment coefficient, improve the filtering effect and the accuracy of thermal efficiency calculation. Through reasonable filtering correction adjustment, the influence of interference on the calculation of the water heater's thermal efficiency can be effectively reduced, the stability and reliability of the operation can be improved, the accuracy and credibility of the thermal efficiency evaluation can be ensured, and it can adapt to different types of water heaters and different working environments. By adjusting the preset range and matching rules, it can be flexibly applied to various scenarios, with strong versatility and adaptability.

[0067] Furthermore, perform filtering correction processing on the filtered signal data. The specific steps include: analyzing based on the interference adjustment execution determination result. If the interference adjustment execution determination result is the first interference execution scheme, then adjust the filter order downward according to the first filtering correction adjustment coefficient, and keep the cut-off frequency, sliding window, and window function β value of the filter unchanged; if the interference adjustment execution determination result is the second interference execution scheme, then adjust the sliding window of the filter upward according to the second filtering correction adjustment coefficient, and keep the cut-off frequency, filter order, and window function β value of the filter unchanged; if the interference adjustment execution determination result is the third interference execution scheme, then adjust the filter order and the window function β value of the filter upward according to the third filtering correction adjustment coefficient, adjust the cut-off frequency of the filter downward, and keep the sliding window of the filter unchanged; if the interference adjustment execution determination result is the fourth interference execution scheme, then adjust the filter order, the sliding window of the filter, and the window function β value upward according to the fourth filtering correction adjustment coefficient under the preset conditions, and adjust the cut-off frequency of the filter downward.

[0068] In this embodiment, it should be noted that the preset conditions are that the cut-off frequency is not higher than the preset cut-off frequency upper limit in the database and the sliding window is not lower than the preset sliding window lower limit in the database. If the cut-off frequency is greater than the preset cut-off frequency upper limit in the database, then set the cut-off frequency to the size of the cut-off frequency upper limit. If the sliding window is below the preset sliding window lower limit in the database, then set the sliding window to the size of the sliding window lower limit, where there is no limited range for the filter order and the window function β value.

[0069] It should be noted that assume the initial filter parameters are as follows: the filter order is 5, the cut-off frequency is 1500 HZ, the sliding window is 50, the β value of the window function is 0.5. If the interference adjustment execution determination result is the first interference execution scheme, then according to the filter correction, adjust the first coefficient to decrease the filter order downward. For example, if the filter correction adjusts the first coefficient to 0.8 and the filter order is 5, then the adjusted filter order is 5 × 0.8 = 4, and keep the cut-off frequency, the sliding window and the β value of the window function of the filter unchanged. It should be understood that when the external interference index is below the external interference threshold and the internal interference index is below the internal interference threshold, adjusting the first coefficient downward according to the filter correction to decrease the filter order and keeping the cut-off frequency, the sliding window and the β value of the window function of the filter unchanged is because in this case, both external and internal interferences are relatively low. Therefore, complex filtering processing is not required to achieve the purpose of filter adjustment. Decreasing the filter order can reduce the computational complexity, and at the same time keep other parameters unchanged to maintain the basic characteristics of the signal.

[0070] If the interference adjustment execution determination result is the second interference execution scheme, then according to the filter correction, adjust the second coefficient to increase the sliding window of the filter, and keep the cut-off frequency and the β value of the window function of the filter unchanged. For example, if the filter correction adjusts the second coefficient to 1.2, then the adjusted sliding window is 50 × 1.2 = 60, and keep the cut-off frequency, the filter order and the β value of the window function of the filter unchanged. It should be understood that when the external interference index is below the external interference threshold and the internal interference index is greater than the internal interference threshold, adjusting the second coefficient upward according to the filter correction to increase the sliding window of the filter and keeping the cut-off frequency, the filter order and the β value of the window function of the filter unchanged is because in this case, relatively speaking, the external interference is low, but the internal interference is high. Increasing the sliding window can better capture the dynamic changes of the internal interference and improve the filtering effect, and at the same time keep other parameters unchanged to maintain the basic characteristics of the signal.

[0071] If the interference adjustment execution determination result is the third interference execution scheme, then according to the filter correction, adjust the third coefficient to upward adjust the filter order and the window function β value of the filter, downward adjust the cut-off frequency of the filter, and keep the sliding window of the filter unchanged. For example, assume that the filter correction adjusts the third coefficient to 1.5. The adjusted filter order is 1.5×5 = 7.5 (rounded up to 8), the adjusted window function β value is 1.5×0.5 = 0.75, and the adjusted cut-off frequency is 1500÷1.5 = 1000, while keeping the sliding window of the filter unchanged. It should be understood that when the external interference index is greater than the external interference threshold and the internal interference index is below the internal interference threshold, adjusting the third coefficient upward to adjust the filter order and the window function β value of the filter, and downward adjusting the cut-off frequency of the filter while keeping the sliding window of the filter unchanged is considered because in this case, relatively speaking, the external interference is higher but the internal interference is lower. 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, reducing the cut-off frequency can better retain the low-frequency components of the signal and avoid the interference of high-frequency noise.

[0072] If the interference adjustment execution determination result is the fourth interference execution scheme, then under preset conditions, according to the filter correction, adjust the fourth coefficient to upward adjust the filter order, the sliding window of the filter, and the window function β value, and downward adjust the cut-off frequency of the filter. For example, assume that the filter correction adjusts the fourth coefficient to 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 cut-off 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, under preset conditions, adjusting the fourth coefficient upward to adjust the filter order, the sliding window of the filter, and the window function β value, and downward adjusting the cut-off frequency of the filter is considered because in this case, both the external interference and the internal interference are higher and more complex filtering processing is required. Such adjustment helps to improve the performance of the filter, enabling it to better handle larger external and internal interferences. By increasing the filter order, the selectivity of the filter can be improved. By increasing the sliding window, the smoothing effect on the signal can be enhanced. By increasing the window function β value, the sidelobe suppression ability can be improved. Reducing the cut-off frequency helps to reduce the passage of high-frequency interference signals, thereby improving the purity of the signal.

[0073] It should be noted that if the values of the filter order, the sliding window, or the cut-off frequency are decimals, then select the adjacent integer. The rule for selecting the adjacent integer is that if the adjustment method is upward adjustment, select the integer that is closest to and greater than the decimal; if the adjustment method is downward adjustment, select the integer that is closest to and less than the decimal.

[0074] According to different interference execution schemes, the cut-off frequency, order, sliding window, and window function β value of the filter are adjusted accordingly, which can more precisely 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 simultaneously adjusts the filter order, window function β value, and cut-off frequency, and the fourth interference execution scheme comprehensively adjusts the filter parameters under preset conditions. Through the multi-level matching mechanism of this scheme, the influence of different interference degrees on filter correction can be more carefully reflected, and the accuracy of adjustment can be improved.

[0075] By using the preset upper limit of the cut-off frequency and the lower limit of the sliding window, combined with the actual filter correction adjustment coefficient, data-driven filter correction adjustment is realized, which can more scientifically determine the filter parameters, improve the filtering effect and the accuracy of heat efficiency calculation. Through reasonable filter correction adjustment, the influence of interference on the heat 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 heat efficiency evaluation can be ensured. By adjusting the preset parameters and matching rules, it can be flexibly applied to various scenarios and has strong versatility and adaptability.

[0076] Furthermore, obtain the signal quality parameters after filter correction processing, analyze to obtain the filter correction quality index, and compare it with the filter signal quality index before filter correction processing to obtain the filter correction result. The specific steps include: obtaining the signal quality parameters within the second preset time period after filter correction processing, where the signal quality parameters include the maximum signal-to-noise ratio, average signal delay duration, average signal intensity, and average echo loss of the filter signal; obtaining the preset signal quality reference set in the database and performing differential processing with the signal quality parameters after filter correction processing to obtain the filter correction quality index; obtaining the preset optimization effect threshold in the database, and based on the filter signal quality index before filtering processing and comparing it 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 for filter correction, otherwise it is unqualified for filter correction; the signal quality reference set includes the signal-to-noise ratio reference value, signal delay duration allowable value, signal intensity reference value, and echo loss allowable error.

[0077] In this embodiment, it should be noted that the preset time period is different from the second preset time period. The second preset time period is a time period after the preset time period and has nothing to do with the preset time period.

[0078] It should be noted that the method for obtaining the quality index of the filtered signal before filtering is the same as that for obtaining the quality index of the filtered signal after filtering. Both can be obtained by acquiring signal quality parameters and analyzing them with a preset signal quality reference set in the database. However, it should be noted that the quality index of the filtered signal before filtering is obtained by analyzing the signal quality parameters within a preset reference period before the filtering process. The time dimensions of the quality index of the filtered signal before filtering and that after filtering are different.

[0079] It should be noted that if the filtering correction result is unqualified for filtering correction, the filtering correction process shall be continued. The specific steps include: if the filtering correction result is unqualified for filtering correction, obtain the external interference index and the internal interference index of the water heater after filtering correction, and analyze the secondary correction filtering adjustment coefficient therefrom. Then, perform the filtering process again within a preset number of times until the filtering correction result is qualified for filtering correction. If the filtering correction result is still unqualified for filtering correction within the preset number of times, a warning shall be issued.

[0080] By obtaining the external interference index and the internal interference index after filtering correction and analyzing the secondary correction filtering adjustment coefficient, it is possible to more precisely adapt to various complex interference situations and improve the pertinence and effectiveness of filtering correction. Performing the filtering process again within a preset number of times until the filtering correction result is qualified can more carefully reflect the influence of different interference degrees on filtering correction and improve the accuracy of adjustment. Using the preset external interference index and internal interference index, combined with the actual filtering correction adjustment coefficient, to achieve data-driven filtering correction adjustment can more scientifically determine the filter parameters, improve the filtering effect and the accuracy of heat efficiency calculation, effectively reduce the influence of interference on the heat efficiency calculation of the water heater, improve the stability and reliability, and ensure the accuracy and credibility of heat efficiency evaluation. If the filtering correction result is still unqualified within the preset number of times, a warning shall be issued, which is convenient for timely discovering and solving problems in the data acquisition process and ensuring the smooth progress of the heat efficiency calculation process of the water heater.

[0081] The filtering correction quality index is obtained by analyzing the signal quality parameters within the second preset time period after filtering correction processing. This takes into account the mutual influence relationships among these parameters. For example, the higher the maximum signal-to-noise ratio, the stronger the signal relative to the noise and the better the signal quality. And the shorter the average signal delay duration, the faster the signal transmission and the better the real-time performance. These two factors jointly affect the signal transmission quality. The higher the average signal intensity, the less attenuation and interference the signal undergoes during transmission, which helps improve the maximum signal-to-noise ratio. The larger the average return loss, the faster the reflected signal attenuates and the less reflection interference there is during signal transmission, which helps improve the signal integrity and the maximum signal-to-noise ratio. These parameters influence each other and jointly determine the signal quality. When designing and optimizing the signal processing system, these parameters should be comprehensively considered to ensure high-quality signal transmission and processing.

[0082] The filtering correction quality index is obtained through the following specific method:

[0083] ;

[0084] In the formula, JZ represents the filtering correction quality index, JX represents the maximum signal-to-noise ratio of the filtered signal, represents the signal-to-noise ratio reference value, JY represents the average signal delay duration of the filtered signal, represents the allowable value of the signal delay duration, JQ represents the average signal intensity of the filtered signal, represents the signal intensity reference value, JS represents the average return loss of the filtered signal, represents the allowable error of the return loss, represents the signal-to-noise ratio influence weight, represents the signal delay duration influence weight, represents the signal intensity influence weight, represents the return loss influence weight.

[0085] The signal-to-noise ratio influence weight, the signal delay duration influence weight, the signal intensity influence weight, and the return loss influence weight can be obtained from the database. For example, the signal-to-noise ratio influence weight can be obtained by acquiring the historical signal-to-noise ratios stored in the database and the corresponding signal-to-noise ratio influence weights, thereby constructing a signal-to-noise ratio mapping set. There is a one-to-one or many-to-one correspondence relationship in this mapping set. By inputting the signal-to-noise ratio data to be used into the signal-to-noise ratio mapping set, the signal-to-noise ratio influence weight can be obtained. The acquisition methods of other influence weights, such as the signal delay duration influence weight, the signal intensity influence weight, and the return loss influence weight, are the same as that of the signal-to-noise ratio influence weight and can all be obtained by matching in the corresponding mapping sets. Among them, the signal delay duration influence weight corresponds to the signal delay duration mapping set, the signal intensity influence weight corresponds to the signal intensity mapping set, and the return loss influence weight corresponds to the return loss mapping set.

[0086] As shown Figure 2 in the figure, it is a schematic structural diagram of a water heater thermal efficiency calculation system based on big data provided by an embodiment of the present application. The water heater thermal efficiency calculation system based on big data provided by the embodiment of the present application includes: an external interference evaluation module, an internal interference evaluation module, a filtering and correction module, a filtering and correction result analysis module, and a thermal efficiency evaluation module; among them, 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 and correction module is used to perform filtering and 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 and correction result analysis module is used to obtain the signal quality parameters after the filtering and correction processing, analyze and obtain the filtering and correction quality index, and compare it with the filtering signal quality index before the filtering and correction processing to obtain the filtering and correction result; the thermal efficiency evaluation module is used to, if the filtering and correction result is qualified for filtering and correction, obtain the thermal efficiency evaluation parameters after filtering and input them into a preset water heater thermal efficiency evaluation model for calculating the water heater thermal efficiency, and if the filtering and correction result is unqualified for filtering and correction, continue to perform the filtering and correction processing.

[0087] In summary, in this embodiment, by obtaining the power interference parameters and electromagnetic interference parameters of the water heater, analyzing and obtaining the power noise interference index and electromagnetic noise interference index, the external interference index of the water heater is obtained, thereby realizing the accurate quantitative evaluation of external interference, and effectively solving the problem that the acquisition of the thermal efficiency evaluation parameters of the water heater is inaccurate due to the insufficient ability of the filter to suppress noise interference in the prior art.

[0088] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can 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.

[0089] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one block or more blocks.

[0090] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one block or more blocks.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one block or more blocks.

[0092] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0093] 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 equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. 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 the signal detected by the device, obtain the power interference parameters of the water heater, analyze to obtain the power noise interference index, obtain the electromagnetic interference parameters of the water heater, analyze to obtain the electromagnetic noise interference index, and analyze to obtain the external interference index of the water heater; Obtain the internal interference parameters of the water heater, and analyze to obtain the internal interference index of the water heater; Perform filtering and 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; Obtain the signal quality parameters after the filtering and correction processing, analyze to obtain the filtering and correction quality index, and compare it with the filtering signal quality index before the filtering and correction processing to obtain the filtering and correction result; If the filtering and correction result is qualified for filtering and correction, obtain the thermal efficiency evaluation parameters after filtering, and input them into the preset water heater thermal efficiency evaluation model for water heater thermal efficiency calculation. If the filtering and correction result is unqualified for filtering and correction, continue to perform the filtering and correction processing; The power interference parameters of the water heater include the 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; The electromagnetic interference parameters of the water heater 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.

2. The method for calculating the thermal efficiency of a water heater based on big data according to claim 1, wherein: The specific steps for obtaining the power interference parameters of the water heater and analyzing to obtain the power noise interference index include: Obtain the power interference parameters of the water heater; 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 interference reference set includes: allowable value of voltage fluctuation amplitude, allowable value of current harmonic content, unit voltage sag depth impact factor, unit maximum frequency deviation impact factor, and surge voltage peak value reference; The power noise interference index is used to analyze the difference degree between the voltage fluctuation amplitude, current harmonic content, and surge voltage peak value and the allowable value of voltage fluctuation amplitude, allowable value of current harmonic content, and surge voltage peak value reference, and combine the voltage sag depth with the unit voltage sag depth impact factor, the maximum frequency deviation of the power supply, and the unit maximum frequency deviation impact factor to obtain the power noise interference index.

3. The method for calculating the thermal efficiency of a water heater based on big data according to claim 1, wherein: The specific steps for obtaining the electromagnetic interference parameters of the water heater and analyzing to obtain the electromagnetic noise interference index include: Obtain the electromagnetic interference parameters of the water heater; 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 set includes magnetic induction intensity limit, electromagnetic interference spectrum limit, fluctuation amplitude reference value, peak power density reference value, and 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 fluctuation amplitude of electromagnetic interference, maximum peak power density, and average pulse repetition frequency of the electromagnetic interference signal within a preset time period. Then, the differences are analyzed by comparing them with the magnetic induction intensity limit value, electromagnetic interference spectrum limit value, fluctuation amplitude reference value, peak power density reference value, and pulse repetition frequency reference value respectively. Corresponding influence weights are introduced to obtain the electromagnetic noise interference index.

4. The method for calculating the thermal efficiency of a water heater based on big data according to claim 1, wherein: The specific steps for analyzing and obtaining the external interference index of the water heater are as follows: Obtain the power interference influence weight corresponding to the preset power noise interference index and the electromagnetic interference influence weight corresponding to the electromagnetic noise interference index in the database; Based on the power noise interference index, power interference influence weight, electromagnetic noise interference index, and electromagnetic interference influence weight, comprehensively analyze to obtain the external interference index of the water heater; The external interference index of the water heater is used to characterize the comprehensive interference degree of the power noise and electromagnetic noise of the water heater on the water heater by coupling and analyzing the power noise interference index of the water heater with its corresponding power interference influence weight and combining the coupling result of the electromagnetic noise interference index with its corresponding electromagnetic interference influence weight to obtain the external interference index of the water heater.

5. The method for calculating the thermal efficiency of a water heater based on big data according to claim 1, characterized in that: The specific steps for obtaining the internal interference parameters of the water heater, analyzing and obtaining the internal interference index of the water heater are as follows: Obtain the internal interference parameters of the water heater. The internal interference parameters of the water heater include the average temperature of the collector surface, average water pressure, maximum water pressure fluctuation, and average water flow velocity of the water heater within a preset time period; Obtain the preset internal interference reference set in the database and compare 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 difference analysis on 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 water pressure fluctuation respectively, compare the average water flow velocity with the water flow velocity reference value, and perform coupling processing after introducing their corresponding influence weights respectively to obtain the internal interference index of the water heater.

6. The method for calculating the thermal efficiency of a water heater based on big data according to claim 1, characterized in that: The specific steps for performing filtering and correction processing on the filtered signal data based on the external interference index and internal interference index of the water heater are as follows: Obtain the preset external interference threshold and internal interference threshold in the database and compare them with the external interference index and internal interference index of the water heater respectively to obtain the interference adjustment 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 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 adjustment execution determination result is to adopt the fourth interference execution plan; Based on the interference adjustment execution determination result, a filter correction adjustment coefficient is analyzed, and the filter signal data is subjected to filter correction processing accordingly; 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 filter signal data includes the cut-off frequency of the filter, the filter order, the sliding window, and the window function β value.

7. The method for calculating the thermal efficiency of a water heater based on big data according to claim 6, wherein: The specific steps for analyzing the filter correction adjustment coefficient based on the interference adjustment execution determination result include: Based on the interference adjustment execution determination result, if the interference adjustment execution determination result is the first interference execution plan, the first filter correction adjustment coefficient is analyzed; If the interference adjustment execution determination result is the second interference execution plan, the second filter correction adjustment coefficient is analyzed; If the interference adjustment execution determination result is the third interference execution plan, the third filter correction adjustment coefficient is analyzed; If the interference adjustment execution determination result is the fourth interference execution plan, the fourth filter correction adjustment coefficient is analyzed.

8. The method for calculating the thermal efficiency of a water heater based on big data according to claim 6, characterized in that: The specific steps for performing filter correction processing on the filter signal data include: Based on the analysis of the interference adjustment execution determination result, if the interference adjustment execution determination result is the first interference execution plan, the filter order is adjusted downward according to the first filter correction adjustment coefficient, and the cut-off frequency of the filter, the sliding window, and the window function β value are kept unchanged; If the interference adjustment execution determination result is the second interference execution plan, the sliding window of the filter is adjusted upward according to the second filter correction adjustment coefficient, and the cut-off 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 plan, the filter order and the window function β value of the filter are adjusted upward, the cut-off frequency of the filter is adjusted downward, and the sliding window of the filter is kept unchanged; If the interference adjustment execution determination result is the fourth interference execution plan, under preset conditions, the filter order, the sliding window of the filter, and the window function β value are adjusted upward according to the fourth filter correction adjustment coefficient, and the cut-off frequency of the filter is adjusted downward.

9. The method for calculating the thermal efficiency of a water heater based on big data according to claim 1, characterized in that: The specific steps for obtaining the signal quality parameter after filter correction processing, analyzing the filter correction quality index, and comparing it with the filter signal quality index before filter correction processing to obtain the filter correction result include: Obtain the signal quality parameter within the second preset time period after filter correction processing, and the signal quality parameter includes the maximum signal-to-noise ratio of the filter signal, the average signal delay duration, the average signal intensity, and the average echo loss; Obtain the preset signal quality reference set in the database and perform a differential process with the signal quality parameters after filtering and correction to obtain the filtering and correction quality index; Obtain the preset optimization effect threshold in the database, compare it based on the filtering signal quality index before filtering and the filtering and correction quality index to obtain the filtering and correction result. If the filtering and correction quality index is greater than the filtering signal quality index before filtering, and the difference between the filtering and correction quality index and the filtering signal quality index before filtering is above the optimization effect threshold, then the filtering and correction result is qualified for filtering and correction, otherwise it is unqualified for filtering and correction; The signal quality reference set includes the signal-to-noise ratio reference value, the allowable value of signal delay duration, the signal intensity reference value, and the allowable error of return loss.

10. A system applying a method for calculating the thermal efficiency of a water heater based on big data according to any one of claims 1-9, characterized in that, It includes: An external interference evaluation module, an internal interference evaluation module, a filtering and correction module, a filtering and correction result analysis module, and a thermal efficiency evaluation module; Among them, the external interference evaluation module is used to obtain the power interference parameters of the water heater and analyze the power noise interference index when receiving the signal detected by the device, obtain the electromagnetic interference parameters of the water heater and analyze the electromagnetic noise interference index, and analyze 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 and analyze the internal interference index of the water heater; The filtering and correction module is used to perform filtering and 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 filtering and correction result analysis module is used to obtain the signal quality parameters after filtering and correction processing, analyze the filtering and correction quality index, and compare it with the filtering signal quality index before filtering and correction processing to obtain the filtering and correction result; The thermal efficiency evaluation module is used to obtain the thermal efficiency evaluation parameters after filtering if the filtering and correction result is qualified for filtering and correction, input them into the preset water heater thermal efficiency evaluation model for water heater thermal efficiency calculation, and if the filtering and correction result is unqualified for filtering and correction, continue to perform filtering and correction processing.

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