Real-time monitoring method for water heater controller system

Abstract

The application discloses a real-time monitoring method for a water heater controller system and relates to the technical field of water heater flame monitoring and control. The real-time monitoring method for the water heater controller system comprises the following steps: flame ion current signal monitoring, flame state identification process monitoring and flame regulation state monitoring. The application monitors the flame state detection state of the water heater controller system under different flame change speeds, then performs real-time monitoring and real-time analysis on the level input and output of the flame ion current signal, performs flame state identification early warning and signal strength interference judgment, finally performs interference analysis and judgment on the flame regulation process, realizes real-time capture, dynamic identification and anti-interference regulation closed-loop optimization of the flame ion current signal, and effectively solves the problem of inaccurate actual flame detection result caused by untimely capture of the flame ion current signal in the water heater controller system in the prior art.

Description

Technical Field

[0001] This invention relates to the field of flame monitoring and control technology for water heaters, and more particularly to a real-time monitoring method for water heater controller systems. Background Technology

[0002] The main control board circuit of the water heater controller system mainly consists of a main control chip, power supply circuit, sensor circuit, control circuit, display circuit, alarm circuit, flame detection circuit and communication circuit. All parts are connected by lines to work together.

[0003] The power supply circuit rectifies and filters the 220V AC power, then regulates it to output a stable DC power supply for the main control chip (such as the 51 series or STM32), comparators, and other circuits. In the sensor circuit, the weak signals collected by the temperature and water level sensors are first sent to the comparator. After amplification and level conversion by the comparator, the signals are transmitted to the main control chip to ensure that the signals meet the input requirements of the main control chip and improve recognition accuracy. The main control chip connects to the control circuit through the I / O interface. Relays act as actuators, driving the heating rod (heating control) and the solenoid valve / water pump (water filling control), respectively. Simultaneously, a display circuit (digital tube / LCD) is connected to display the status, and an alarm circuit (buzzer) is connected to trigger the alarm. The comparator can also participate in the judgment of abnormal signals during this process, assisting in triggering alarms or protection mechanisms.

[0004] In the flame detection circuit, the signal from the flame sensor is processed, input to a comparator, and then transmitted to the main control chip. The main control chip uses this signal to control the power supply to the gas valve. The communication circuit (infrared / Wi-Fi module) is connected to the main control chip to enable remote interaction. All circuits form a closed-loop control system through wires and pins to ensure stable system operation.

[0005] The flame detection circuit is designed based on the unidirectional conductivity of flames using a negative ion flame sensing circuit. It utilizes AC voltage generated by a transformer, which, after signal transmission and processing, is output as a level signal by a comparator. The main MCU uses this level signal and two flame signals from the dual comparators to determine whether ignition is successful. A flame is only detected if both signals are lit to reduce the risk of false alarms. During system startup, if an abnormally low flame signal is detected, the system will stop. During normal operation, the flame signal controls the power supply to the gas solenoid valve to ensure safety. The monitoring program control circuit monitors and optimizes each step in real time, efficiently processing signals to ensure accurate flame detection and system safety.

[0006] For example, Chinese invention patent CN103616870B discloses a remote-controlled electric water heater fault diagnosis system, including: a WIFI module, a leakage current monitoring circuit, a heating fault detection circuit for detecting faults in the electric heating element and its driving circuit, a water temperature sensor fault detection circuit, and an ambient temperature sensor; wherein the WIFI module is wirelessly connected to a router that connects the user terminal device and the network server, the leakage current monitoring circuit is connected to the electric heating element, and the water temperature sensor fault detection circuit is connected to the water temperature sensor.

[0007] For example, Chinese invention patent CN118466282A discloses a pressure regulating plate controller, a gas water heater testing system, and a testing method, including: a microcontroller module storing an instruction set including secondary pressure regulation instructions and load test instructions; a first button for sending a first trigger signal to the microcontroller module; and a second button for sending a second trigger signal to the microcontroller module; an indicator light assembly electrically connected to the microcontroller module; furthermore, the microcontroller module is also used to acquire the status data of the power control board and send a third trigger signal to the indicator light assembly to generate a corresponding light signal.

[0008] The above-mentioned technology has at least the following technical problems:

[0009] In existing technologies, during gas supply interruptions in the flame detection stage of a water heater control system, the system is prone to misjudging the presence of a flame. Flame ion current, a key weak signal for flame detection, relies on detecting the flame ion flow generated during combustion to determine its presence. When the signal changes, the rising or falling edge of the flame detection circuit in the water heater control system experiences delays, affecting the timeliness of signal capture. This ripple interference can submerge the effective signal, making it difficult for the system to accurately identify the true flame ion current signal. This leads the system to mistakenly believe that a flame exists or does not, resulting in incorrect decisions by the water heater control system. Therefore, there is a problem of inaccurate actual flame detection results due to untimely capture of the flame ion current signal in the water heater controller system. Summary of the Invention

[0010] To address the technical problem of inaccurate flame detection results caused by untimely capture of flame ion current signals in existing water heater controller systems, this invention provides a real-time monitoring method for water heater controller systems, the technical solution of which is as follows:

[0011] A real-time monitoring method for a water heater controller system is provided. The method includes: S1, real-time monitoring of the control process of the flame detection circuit in the water heater controller system at the signal capture time point under different flame change rates, simultaneously performing real-time monitoring and analysis of the flame ion current signal capture, and determining whether there is inaccurate flame state detection due to capture monitoring delay; S2, if a capture monitoring delay exists, adjusting the signal capture parameters of the main MCU circuit in the water heater controller system, simultaneously performing real-time monitoring and analysis of the input and output levels of the flame ion current signal, and performing flame state identification and early warning and signal strength interference judgment to reduce the impact of signal amplification abnormalities. The main MCU circuit receives the flame current signal and performs calculations and analysis to generate flame status control commands. The signal capture parameters include signal gain and sampling frequency. S3, if there is signal strength interference, the status recognition parameters of the main MCU circuit are adjusted. At the same time, during the flame control process of the main MCU circuit, based on the control process of the temperature detection circuit in the water heater controller system, interference analysis and flame control status determination are performed on the flame control process to enhance the ability of the temperature detection circuit to suppress temperature signal drift caused by power fluctuations and temperature detection errors caused by electromagnetic interference. The status recognition parameters include filter cutoff frequency and status recognition frequency.

[0012] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0013] 1. Flame ion current, a key weak signal for determining flame status, is prone to delays in its rising or falling edges during signal changes, leading to untimely capture by the flame detection circuit. This is especially problematic in special scenarios such as gas supply interruptions, where the system often misjudges the presence of a flame due to signal delay. This method monitors the signal capture process in real time at different flame change rates, coupling the generation and processing times of the flame ion current signal into a "flame capture and detection impact index," quantifying the impact of delay on detection timeliness. If the index exceeds the limit, the signal gain and sampling frequency of the main MCU circuit are adjusted. Specifically, the signal gain optimizes the signal amplification factor to avoid signal attenuation or oversaturation, and the sampling frequency matches the flame change rate to reduce drift caused by clock jitter. Through a three-level progressive optimization, the system accurately identifies and resolves flame signal capture delay, amplification anomalies, and interference issues, ensuring that the system can quickly identify the true signal when the flame status changes abruptly (such as a sudden gas interruption), thus addressing the inaccurate flame status detection caused by capture delay at its source.

[0014] 2. By coupling analysis of signal fluctuation spectral density deviation and harmonic distortion position offset, the degree of interference is accurately quantified. If the indicators exceed the standard, the filter cutoff frequency is first adjusted to keep the signal within the optimal processing range of the main MCU, avoiding signal clipping. Then, the state recognition frequency is enhanced to filter out high-frequency interference and improve the circuit signal-to-noise ratio. This layered optimization strategy specifically suppresses ripple interference, ensuring that the flame ion current signal can still be clearly identified in complex electromagnetic environments. For example, in a kitchen environment with strong electromagnetic interference, it can effectively avoid dangerous misjudgments caused by interference, such as "the gas has been cut off but the flame is judged to be present," or malfunctions such as "the flame is normal but it is judged to be extinguished," significantly improving the stability of signal recognition.

[0015] 3. A dual-protection system is constructed from two dimensions: water flow rate and temperature, through an interference analysis mechanism. For flow rate deviations, the flame power adjustment gradient of the temperature detection circuit is used to suppress power ripple, reducing interference from AC components in flow detection. For temperature deviations, feedback from the water flow-temperature linkage adjustment level determines whether to trigger temperature regulation, achieving precise temperature control. This dual-dimensional interference suppression strategy ensures that the flame regulation process is unaffected by water flow fluctuations, power ripple, and other factors. Even with dynamic changes in gas supply and water flow status, the system can still accurately regulate the flame size, avoiding "over-regulation" or "under-regulation" caused by interference, thus ensuring stable water temperature and efficient gas usage. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the structure of a real-time monitoring method for a water heater controller system provided in an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of the structure of the flame detection circuit provided in an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of the temperature detection circuit provided in an embodiment of the present invention;

[0020] Figure 4 This is one of the structural schematic diagrams of the main MCU circuit provided in the embodiments of the present invention;

[0021] Figure 5 This is a second schematic diagram of the main MCU circuit provided in an embodiment of the present invention;

[0022] Figure 6 This is a flowchart corresponding to the flame ion current signal monitoring provided in an embodiment of the present invention;

[0023] Figure 7 The flowchart corresponding to flame status identification and monitoring provided in the embodiments of the present invention;

[0024] Figure 8 The flowchart corresponding to the flame control status monitoring provided in the embodiments of the present invention. Detailed Implementation

[0025] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0026] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0027] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0028] This invention provides a real-time monitoring method for a water heater controller system, such as... Figure 1The flowchart shown is for a real-time monitoring method for a water heater controller system. The processing flow of this method may include the following steps: S1, under different flame change rates, monitor the control process of the flame detection circuit in the water heater controller system regarding the signal capture time point in real time, simultaneously perform real-time monitoring and analysis of the flame ion current signal capture, and determine whether there is inaccurate flame state detection due to capture monitoring delay; S2, if there is a capture monitoring delay, adjust the signal capture parameters of the main MCU circuit in the water heater controller system, simultaneously monitor and analyze the level input and output of the flame ion current signal in real time, and perform flame state identification warning and signal strength interference judgment. The signal capture parameters are used to reflect the signal distortion of the flame ion current signal under signal gain and sampling frequency; S3, if there is signal strength interference, adjust the state identification parameters of the main MCU circuit. Simultaneously, during the flame control process of the main MCU circuit, based on the control process of the temperature detection circuit in the water heater controller system, perform interference analysis and flame control state judgment on the flame control process. The state identification parameters are used to reflect the noise suppression capability of the flame ion current signal at the filter cutoff frequency and state identification frequency. The Unit circuit consists of a main MCU (U2) and a watchdog MCU (U10); S4, if the flame control status is determined to be unqualified, power ripple suppression is performed on the water heater controller system to prevent high-frequency noise generated by power circuits (such as fans and solenoid valves) from being coupled to the flame detection circuit through the ground plane.

[0029] It should be added that, such as Figure 2 The schematic diagram of the flame detection circuit shown is based on the unidirectional conductivity of flames. Its core function is to accurately identify the presence of flames, providing a basis for the safe combustion of water heaters. The circuit mainly consists of a flame sensing needle, an oscillation circuit (B1), comparators (U2, U13), a resistor network (R191, R192, R194, R195, etc.), and capacitors (C64, etc.).

[0030] The working principle is as follows: The AC voltage generated by B1 is transmitted to the flame sensing needle through components such as C60 and R191. When a flame is established, its negative ion characteristics cause positive charges to be conducted to the signal ground and negative charges to be conducted to the non-inverting input of comparator U5. At this time, the comparator outputs a low level, indicating that there is a flame; when there is no flame, the comparator outputs a high level. To improve reliability, the circuit is designed with two flame signals (HY1, HY2). The main MCU (U2) only determines that a flame exists when both signals detect a flame, avoiding misjudgment due to a single circuit failure.

[0031] In addition, the circuit has a fault self-check function: when the system starts up (theoretically no flame), if HY1 or HY2 is at a low level, the circuit is judged to be abnormal and the system is stopped; during normal combustion, the flame signal controls the power supply of the gas valve at the same time; if the flame disappears unexpectedly, the gas valve is disconnected through U10, providing double protection to avoid gas leakage.

[0032] like Figure 3 The diagram shows the structure of the temperature detection circuit. The temperature detection circuit is used to collect the inlet and outlet water temperatures in real time, providing key parameters for the constant temperature control of the water heater. It mainly consists of an NTC temperature probe, resistors (R124, R126, R127, etc.), capacitors (C27, C28, C29, etc.) and an AD conversion interface.

[0033] The working principle is based on the resistance change characteristic of the NTC probe with temperature: after the NTC probe senses the water temperature, its resistance changes accordingly, and the temperature signal is converted into a voltage signal through a resistor network; after the voltage signal is filtered by a capacitor, it is transmitted to the AD conversion pin of the main MCU (U2) (such as P20 / ANI0, P21 / ANI1, etc.). The MCU converts the voltage signal into a digital quantity (AD value) and then calculates the actual temperature.

[0034] The circuit needs to detect multiple temperatures, including inlet water (RTjs) and outlet water (RTcs): After the user sets the target temperature via the wired controller, the controller adjusts the opening of the gas proportional valve based on parameters such as inlet water temperature and flow rate to stabilize the outlet water temperature at the set value. Capacitors (such as C27 104 specification) are used to filter out high-frequency interference, ensuring a stable temperature signal and laying the foundation for accurate temperature control.

[0035] like Figure 4 The diagram shown is one of the structural schematics of the main MCU circuit, namely the main MCU (U2) control circuit diagram. This main MCU circuit uses the Renesas R5F100GE as the main control chip. Its core function is to coordinate the overall operation of the water heater, including start-up control, combustion adjustment, fault detection and safety protection. It is the "decision center" of the system. The circuit mainly consists of the main MCU (U2), watchdog MCU (U10), crystal oscillator (Y1), reset circuit, power supply module and pin interface.

[0036] The main MCU (U2) connects to various sensors and actuators via pins: it receives inputs such as flame detection signals (HY1, HY2), temperature signals (RTcs, RTjs), and water flow signals (SLL); and outputs control commands to gas valves (KGF, BLF, etc.), fans (FJ), igniters (DH), etc. Its built-in AD converter processes analog signals, and the PWM module adjusts the proportional valve opening to achieve constant temperature control.

[0037] The watchdog MCU (U10) serves as the core of the safety system. It monitors the 50Hz timing of the main MCU via the WDT pin. If the timing deviation exceeds ±20%, the main MCU is deemed faulty, and the gas valve (KJ3) is immediately shut off via Q12 and Q11. Simultaneously, it detects the flame signal; when the flame disappears, the valve is directly closed, forming a dual safety mechanism. The circuit also includes a reset circuit (Rst) and a crystal oscillator (8MHz) to ensure stable MCU operation.

[0038] like Figure 5 The second schematic diagram of the main MCU circuit shown is the watchdog MCU (U10) control circuit diagram. This main MCU circuit focuses more on pin functions and interface logic. Its core is to realize accurate signal transmission and system collaborative control. It is mainly composed of the pin network of the main MCU (U2), external resistors and capacitors, and functional module interfaces.

[0039] The 48 pins of the main MCU (U2) have clearly defined functions: input pins include flame detection (HY1, HY2), temperature detection (RTcs, RTjs), fan speed (ZSXH), water flow signal (SLL), etc., used to receive external status parameters; output pins include gas valve control (KGF, BLF, XFDF, etc.), fan control (FJ), ignition control (DH), communication (TXD1, RXD1), etc., used to output control commands.

[0040] For example, P20 / ANI0 (RTcs) receives the outlet water temperature signal, P16 / TO01 (FJ) outputs a PWM signal to control the fan speed, P15 (SW) outputs the proportional valve operating frequency, and P33 (FDY) controls the gas valve power supply. The circuit stabilizes pin levels using resistors (such as R83) and capacitors (such as C41) to reduce interference; it also provides a pre-programmed interface (such as CN4) to support firmware updates. This circuit is the core hub for interaction between the main MCU and peripheral devices, ensuring the real-time execution of system instructions and status feedback.

[0041] Specifically, step S1 focuses on the signal capture performance of the flame detection circuit: based on the unidirectional conductivity of the flame detection circuit (including the flame sensing needle, oscillation circuit B1, comparators U2 / U13, and two flame signals HY1 / HY2), the signal path of the AC voltage generated by B1 transmitted to the sensing needle via C60 and R191 is monitored in real time under different flame change rates, simultaneously monitoring the capture process of the flame ion current signal. When a flame is present, the negative ion characteristic causes the comparator to output a low level (HY1 and HY2 must both be low to determine the presence of a flame), and outputs a high level when there is no flame. By analyzing the matching degree between the signal capture time point and the actual flame change, combined with the filtering effect of the resistor network (R191, etc.) and capacitor C64, it is determined whether the flame state detection is inaccurate due to capture delay (e.g., delayed triggering of a single signal HY1 may lead to misjudgment).

[0042] Step S2 optimizes the main MCU circuit performance to address the capture delay issue: If a delay exists, the main MCU (U2) optimizes the processing by adjusting the signal capture parameters (signal gain, sampling frequency). The signal gain is related to the amplification factor of the flame ion current signal (matching the AD conversion accuracy of the main MCU), and the sampling frequency determines the frequency at which the main MCU acquires the HY1 and HY2 signals (e.g., 1kHz sampling to adapt to rapid flame changes). Simultaneously, the stability of the signal input and output levels through the main MCU pins is monitored. The watchdog MCU (U10) monitors the timing of the main MCU through the WDT pin to help determine whether the signal is distorted due to abnormal gain or insufficient sampling, and synchronously triggers flame status recognition and early warning (e.g., U10 prepares to close the valve when it detects an abnormal signal).

[0043] Step S3, combined with the temperature detection circuit, deepens interference suppression: If signal strength interference exists, adjust the status recognition parameters (filter cutoff frequency, status recognition frequency). The filter cutoff frequency matches the high-frequency filtering characteristics of capacitor C27 (104 specification) in the temperature detection circuit to suppress noise when the NTC probe collects water temperature (converted to a voltage signal by a resistor network such as R124, and then received by the main MCU P20 / ANI0 pin); the status recognition frequency is associated with the main MCU's synchronous sampling frequency of the flame signal (HY1 / HY2) and temperature signal (RTcs / RTjs) (e.g., 50ms / sample to ensure the accuracy of temperature-fire linkage analysis). Based on the real-time data from the temperature detection circuit, the main MCU and the watchdog MCU (U10) work together to perform interference analysis and determine whether the flame control status is qualified (e.g., when the temperature signal drifts, the cutoff frequency adjustment enhances the resistance to power fluctuations).

[0044] Step S4 strengthens the system's anti-interference baseline: If the flame control status is deemed unqualified, power step optimization is immediately performed. For high-frequency noise generated by the power circuit (fan FJ, solenoid valve KGF, etc.), ripple is suppressed to prevent it from coupling to the resistor network and comparator of the flame detection circuit via the ground plane, ensuring that the HY1 and HY2 signals are not interfered with. During this process, the power module of the main MCU (U2) and the safety mechanism of the watchdog U10 work together to ensure stable control of critical components such as the gas valve during ripple suppression, ultimately forming a closed-loop monitoring system from flame signal capture to noise isolation.

[0045] In this embodiment, the method employs a three-step progressive analysis and optimization approach. Its advantage lies in constructing a full-link dynamic control mechanism, from signal capture to parameter adjustment and then to operational condition linkage, achieving closed-loop optimization of flame status monitoring and overcoming the limitations of traditional single-link monitoring. The speed of flame change directly affects the timeliness of signal capture; delays lead to detection distortion. Parameters such as signal gain and sampling frequency determine signal fidelity, and deviations can cause intensity interference. Flame stability is closely related to water flow and temperature, requiring coordinated control to match combustion conditions. Each link is strongly correlated; optimizing a single step alone can lead to monitoring gaps and compromise overall reliability. Through phased targeted optimization, signal delay and interference can be accurately eliminated, and dynamic adaptation to operating conditions can be achieved, significantly improving the real-time performance and accuracy of flame detection and ensuring the safe and stable operation of the water heater.

[0046] Furthermore, during the capture of the flame ion current signal, the generation time T of the acquired flame ion current signal is... FD The duration T of flame ion current signal processing FC After harmonic averaging, the flame capture detection influence index F is obtained. CD Its specific expression is: The harmonic averaging process in this example, by comprehensively considering the signal generation and processing time, can more reasonably reflect the combined impact of the two on flame capture and detection, and avoid inaccurate evaluation caused by a single time deviation.

[0047] The flame ion current signal generation time represents the time interval from receiving the flame state change command to detecting the changed flame ion current signal. The flame ion current signal processing time represents the total time from the generation of the flame ion current signal to the system outputting the flame state detection result, including sensor response, signal conditioning, analog-to-digital conversion, digital signal processing, and decision algorithm execution time. The flame capture and detection impact index represents the quantitative data on the degree of influence of the flame ion current signal generation time and the flame ion current signal processing time on the capture timeliness of the flame detection circuit. If the obtained flame signal capture and detection impact index is greater than the preset flame signal capture and detection impact index in the database, there is a capture monitoring delay and the signal capture parameters are adjusted. Otherwise, flame identification monitoring is performed, that is, the input and output levels of the flame ion current signal are monitored in real time.

[0048] The aforementioned database is a database established before the design of the real-time monitoring method for the water heater controller system to store various set data. The database includes, but is not limited to, preset flame signal capture and detection impact indicators, historical signal gain, historical voltage divider resistance ratio, and preset signal strength interference indicators. The preset fault risk assessment value can be set based on the actual monitoring scenario of the water heater controller system. For example, the preset flame signal capture and detection impact indicators are represented by the summation and averaging of historical flame signal capture and detection impact indicators during the historical flame control status monitoring process.

[0049] The steps for obtaining historical flame signal capture and detection impact indicators are as follows: Historical flame signal capture and detection impact indicators from the historical flame control status monitoring process in the database are input into the calculation formula for flame signal capture and detection impact indicators to obtain the historical flame signal capture and detection impact indicators. Similarly, historical signal gain, historical voltage divider resistance ratio, and preset signal strength interference indicators are also calculated based on their respective formulas, substituting relevant historical monitoring data into the calculations. Technicians can flexibly set and precisely fine-tune these calculated values ​​based on the actual monitoring results.

[0050] In this embodiment, both the flame ion current signal processing time and the flame ion current signal generation time are monitored and obtained through the timer built into the controller. The time interval from the issuance of the flame status command to the actual detection of the signal is defined as the generation time, while the cumulative time from signal capture to output of the judgment result is defined as the processing time. The flame ion current signal processing time and the flame ion current signal generation time are harmonic averaged to calculate the flame detection impact index that dynamically reflects the real-time performance of signal capture.

[0051] It is important to understand that the impact of flame signal capture and detection on the signal increases with the increase of the flame ion current signal processing time and the flame ion current signal generation time. When the signal generation time increases, more flame feature data to be processed will accumulate, leading to an increase in the signal processing time. The extension of the processing time will delay the real-time response to the flame state, which may cause further changes in the flame combustion state, which in turn will aggravate the fluctuations in the signal generation process and cause the generation time to increase further.

[0052] By considering this mutual influence, it is helpful to construct a dynamically correlated signal monitoring model, accurately quantify the coupling effect of the two on the flame signal capture and detection indicators, and thus achieve synergistic optimization when adjusting signal capture parameters (such as sampling frequency and signal gain). This not only shortens the redundant time of signal generation but also improves processing efficiency, avoids the imbalance of indicators caused by the adjustment of a single parameter, and ultimately improves the real-time performance and accuracy of flame status detection, reducing the safety risks caused by signal capture deviations in water heaters.

[0053] like Figure 6 The flowchart shown is a process for monitoring the flame ion current signal provided in an embodiment of the present invention. It determines whether the obtained flame capture and detection influence index is greater than a preset value. If so, the signal gain is adjusted and the flame capture and detection influence index is monitored. It also monitors whether the reduction of the deviation is within a preset range. If so, the process of adjusting the signal gain continues, the sampling frequency is switched and the flame capture and detection influence index is re-acquired. It is determined whether this index is greater than a preset value in the database. If so, a signal capture warning is issued; otherwise, the flame status identification process is monitored.

[0054] Further understanding is needed regarding signal capture parameter adjustment, specifically: adjusting the deviation of the acquired flame signal capture and detection indicators. (Influence index F of flame signal capture and detection) SC1 Compared with the preset flame signal capture and detection impact index F SC0 The difference between the two values ​​and the preset flame signal capture and detection influence index F SC0 After ratio processing, the deviation score F of the flame signal capture and detection influence index is obtained. SS Its specific expression is: The deviation of the flame signal capture and detection impact index represents the difference between the obtained flame signal capture and detection impact index and the preset flame signal capture and detection impact index in the database.

[0055] Obtain the signal gain S in the current flame detection circuit. GS1 and compared with the historical signal gain S in the database. GS0 The ratio is processed to obtain the signal gain fraction S. AS Its specific expression is: .

[0056] The acquired flame signal capture and detection affects the deviation score F. SS With signal gain fraction S AS The summed result is input into the database. Based on the mapping relationship between the corresponding signal gain increases in the database, the signal gain adjustment value is obtained. The signal gain adjustment value is used to quantify the degree of increase in signal gain and the degree of increase in comparator sensitivity to compensate for the detection deviation caused by temperature changes. During the signal gain adjustment process, the changes in the indicators affecting flame signal capture and detection are monitored in real time.

[0057] Specifically, the changes in the flame signal capture and detection impact index are monitored in real time. Specifically, after a signal gain adjustment, if the reduction in the acquired flame signal capture and detection impact index deviation is not within the preset range of the flame signal capture and detection impact index deviation reduction in the database, the signal gain adjustment is paused and the sampling frequency is adjusted. If the reduction in the flame signal capture and detection impact index deviation is within the preset range of the flame signal capture and detection impact index deviation reduction, the signal gain adjustment process continues to be monitored until the acquired flame signal capture and detection impact index is not greater than the preset flame signal capture and detection impact index in the database. The reduction in the flame signal capture and detection impact index deviation represents the difference between the flame signal capture and detection impact index acquired before signal gain adjustment and the flame signal capture and detection impact index acquired after a signal gain adjustment. The preset range of the flame signal capture and detection impact index deviation reduction represents the closed interval corresponding to the maximum and minimum values ​​of the historical flame signal capture and detection impact index deviation reduction.

[0058] The specific steps for sampling frequency adjustment are as follows: the deviation of the flame signal capture and detection impact index obtained after one signal gain adjustment is input into the database and matched with the corresponding sampling frequency adjustment value to obtain the actual sampling frequency adjustment value. The sampling frequency adjustment value is used to quantify the degree of increase in sampling frequency and the stability of the clock signal in the flame detection monitoring circuit, so as to reduce the drift impact caused by clock jitter. After the signal capture parameter adjustment, if the re-acquired flame signal capture and detection impact index is not greater than the preset flame signal capture and detection impact index in the database, flame identification and monitoring are performed; otherwise, signal capture warning is issued.

[0059] In this embodiment, an adaptive filtering algorithm is used to increase the signal gain and sampling frequency in a timely manner based on the current signal gain and sampling frequency adjustment value until the acquired flame signal capture and detection impact index is not greater than the preset flame signal capture and detection impact index in the database. At the same time, the historical signal gain, the deviation of the flame signal capture and detection impact index and the sampling frequency adjustment value are used as sample data and input into the convolutional neural network model. The model is trained based on the adaptive filtering algorithm to obtain a feedback sampling-neural network model. The acquired signal gain and sampling frequency are input into the feedback sampling-neural network model to output the corresponding signal gain and sampling frequency adjustment values.

[0060] This system establishes a multi-dimensional superposition of index deviation, current signal gain, and historical control records. It converts the deviation and resistance parameters into fractions, which are then mapped to precise signal gain control values ​​using pre-defined rules in the database. During the control process, the system simultaneously introduces a sampling frequency matching optimization mechanism: dynamically adjusting the sampling frequency based on the index deviation, and suppressing time base jitter introduced by high-frequency noise by improving clock signal stability, thereby reducing drift errors in the signal processing link. Through coordinated control of gain and sampling frequency, it dynamically compensates for temperature deviation and clock jitter, improving signal capture accuracy and stability, forming a closed-loop optimization, enhancing the flame detection anti-interference capability, and ensuring the safe operation of the water heater.

[0061] In a specific application scenario, during flame ion current signal capture, it is assumed that the initial monitoring duration of flame ion current signal generation is 0.2s, and the flame ion current signal processing duration is 0.3s. After harmonic averaging, the flame capture detection impact index is obtained as 0.24s (harmonic average formula: 2 / (1 / 0.2+1 / 0.3)), while the preset flame signal capture detection impact index in the database is 0.2s.

[0062] Since 0.24s > 0.2s, the system determines that there is a capture and monitoring delay and initiates signal capture parameter adjustment. Calculations show that the deviation score affecting the flame signal capture and detection index is 0.2 ((0.24-0.2) / 0.2), and the current signal gain score is 1.2 (the ratio of the current signal gain of 12dB to the historical signal gain of 10dB). Adding these two together, and based on the database mapping relationship, the signal gain adjustment value is determined to be an increase of 3dB.

[0063] After adjustment, monitoring is performed again. If the flame capture and detection impact index drops to 0.18s, and the deviation decreases by 0.06s (0.24 - 0.18), which is within the database's preset deviation reduction range (0.05s - 0.08s), then monitoring continues. If the re-acquired index is still greater than the preset value, a signal capture warning is issued; if it is not greater, the flame status identification process is monitored, and adjustments are made dynamically through real-time data to ensure the accuracy and safety of the water heater's flame detection.

[0064] Furthermore, the input and output levels of the flame ionization current signal are monitored and analyzed in real time. Specifically, the process involves: obtaining the signal fluctuation spectral density deviation D... SFS With the signal harmonic distortion position offset D SHL Harmonic averaging is performed to obtain the signal strength interference index S. SJI Its specific expression is: The harmonic averaging process in this example can comprehensively consider the impact of both factors on signal interference, avoid the bias of a single indicator, more accurately reflect the degree of interference to signal strength, and facilitate precise monitoring and analysis of signals.

[0065] Among them, the signal fluctuation spectral density deviation is used to reflect the difference between the spectral energy distribution density of the actual ion current signal at each frequency point and the preset spectral energy distribution density in the database; the signal harmonic distortion position offset is used to reflect the difference between the phase obtained by the oscilloscope and the preset phase in the database after the ion current signal is distorted by interference, and the preset phase is represented by the result of summing and averaging the historical phases in the historical flame status identification process monitoring; the signal strength interference index is used to quantify the degree of influence of the signal fluctuation spectral density deviation and the signal fluctuation spectral density deviation on the level input and output process; if the obtained signal strength interference index is greater than the preset signal strength interference index in the database, there is signal strength interference and the status identification parameter is adjusted; otherwise, flame status judgment monitoring is performed.

[0066] In this embodiment, the signal fluctuation spectral density deviation is detected and obtained using a spectrum analyzer, and the signal harmonic distortion position offset is obtained by interpolation processing of phase information in the frequency domain. The preset spectral energy distribution density is represented by the summation and averaging of historical signal fluctuation spectral densities during the historical flame state identification process monitoring. The signal strength interference index increases with the increase of the signal fluctuation spectral density deviation and the signal harmonic distortion position offset. The trend of deviation (such as increase or decrease) directly reflects the stability of the signal frequency domain characteristics. In practical applications, it is necessary to analyze the source of deviation in conjunction with specific scenarios (such as noise level and equipment accuracy).

[0067] By analyzing the internal correlation of signal fluctuation spectral density, the spectral deviation data is covariantly coupled into an intensity interference index that comprehensively reflects the degree of signal distortion, quantifying the combined impact of external noise and equipment anomalies on the integrity of the flame signal. This coupling mechanism combines spectral energy distribution characteristics and distortion modes to accurately identify the differences between pulse-type transient interference and persistent background noise, and the parameter selection deeply integrates circuit characteristics and interference types.

[0068] like Figure 7 The flowchart shown is a process for flame status recognition and monitoring provided in an embodiment of the present invention. It determines whether the acquired signal strength interference index is greater than a preset value in the data. If so, it adjusts the filter cutoff frequency and monitors the signal strength interference index. It determines whether the reduction in the deviation of the index is within a preset range. If so, it continues the detection and adjustment process, performs status recognition frequency adjustment, and determines whether the reacquired signal strength interference index is greater than a preset value in the database. If so, it performs flame status recognition and early warning; otherwise, it performs flame control status monitoring.

[0069] Furthermore, the state recognition parameter adjustment involves the following steps: inputting the sum of the obtained signal strength interference index deviation score and the current voltage divider resistor ratio into the database; obtaining the filter cutoff frequency adjustment value based on the mapping relationship between the corresponding filter cutoff frequency increment in the database; and monitoring the signal strength interference index in real time after each filter cutoff frequency adjustment. The signal strength interference index deviation score represents the result of the ratio processing between the obtained signal strength interference index deviation and the preset signal strength interference index deviation.

[0070] The real-time monitoring of signal strength interference indicators is as follows: after one adjustment of the filter cutoff frequency, if the reduction in the obtained signal strength interference indicator deviation is not within the preset range of the signal strength interference indicator deviation reduction in the database, the adjustment of the filter cutoff frequency is paused and state identification frequency adjustment is performed; if the reduction in the obtained signal strength interference indicator deviation is within the preset range of the signal strength interference indicator deviation reduction in the database, the adjustment process of the filter cutoff frequency continues to be monitored until the obtained signal strength interference indicator is not greater than the preset signal strength interference indicator in the database.

[0071] The specific steps for state recognition frequency adjustment are as follows: The result of summing the acquired signal strength interference index deviation score and the current state recognition frequency score is input into the database. Based on the mapping relationship between the corresponding state recognition frequency increase in the database, the state recognition frequency adjustment value is obtained. This value is used to quantify the increase in state recognition frequency and the signal-to-noise ratio of the flame detection monitoring circuit, thereby improving the detection accuracy and system response speed. The state recognition frequency score represents the result of the ratio of the state recognition frequency to the preset state recognition frequency. If, after state recognition frequency adjustment, the reacquired signal strength interference index is not greater than the preset signal strength interference index in the database, the state recognition parameter adjustment is completed and flame control of the main MCU circuit is performed; otherwise, a flame state recognition warning is issued.

[0072] In this embodiment, the signal strength interference index deviation represents the difference between the acquired signal strength interference index and the preset signal strength interference index in the database. The preset signal strength interference index is obtained by summing and averaging the historical signal strength interference indices during the historical flame state identification process monitoring. The preset signal strength interference index deviation is represented by the result of summing and averaging the historical signal strength interference index deviations during the historical flame state identification process monitoring. The preset state identification frequency is represented by the result of summing and averaging the historical state identification frequencies during the historical flame state identification process monitoring. The reduction magnitude of the signal strength interference index deviation represents the difference between the signal strength interference index obtained before and after the filter cutoff frequency adjustment. The range of the reduction magnitude of the preset signal strength interference index deviation represents the closed interval corresponding to the maximum and minimum values ​​of the reduction magnitude of the historical signal strength interference index deviation.

[0073] Based on the current filter cutoff frequency, signal strength interference index deviation, and state recognition frequency obtained by the least mean square filtering algorithm, the filter cutoff frequency and state recognition frequency are increased in a timely manner. At the same time, the historical filter cutoff frequency, signal strength interference index deviation, and state recognition frequency are used as sample data and input into the reinforcement learning model. After training, a filter cutoff frequency-state recognition frequency learning model is obtained. The obtained filter cutoff frequency and state recognition frequency are input into the cutoff frequency-state recognition frequency learning model to obtain the corresponding filter cutoff frequency and state recognition frequency adjustment values.

[0074] In a specific application scenario, taking industrial kiln flame detection as an example, during signal monitoring, assuming the initial signal strength interference index deviation is 0.5 and the preset deviation is 0.3, the ratio is processed to obtain a signal strength interference index deviation score of approximately 1.67. The current voltage divider resistor ratio is 1.2, and the sum of these two values ​​is input into the database. Based on the mapping relationship, the filter cutoff frequency adjustment value is increased by 10Hz.

[0075] After one adjustment, real-time monitoring is performed. If the reduction in signal strength interference index deviation is not within the preset range of 0.1-0.2, filter adjustment is paused, and state recognition frequency adjustment is performed. Assuming the current state recognition frequency score is 1.1, after summing it with the deviation score, the state recognition frequency adjustment value obtained from the database is increased by 5Hz. If the signal strength interference index re-acquired after adjustment is not greater than the preset value, the state recognition parameter adjustment is completed, and flame control of the main MCU circuit is performed; otherwise, a flame state recognition early warning is issued to ensure stable kiln flame detection.

[0076] This example dynamically compensates for signal strength interference by coordinating the filter cutoff frequency and the state recognition frequency, thereby improving the signal-to-noise ratio and detection accuracy. By combining algorithms and learning models, parameter control becomes more intelligent and adapts to real-time interference conditions, forming a closed-loop optimization. This enhances the anti-interference capability and response speed of flame state recognition, ensures the reliability of flame control in the main MCU circuit, and improves the operational safety of the water heater.

[0077] like Figure 8 The flowchart shown is a process corresponding to the flame control status monitoring provided in this embodiment of the invention. It is divided into a first interference analysis and a second interference analysis. The first interference analysis is for water flow rate, and the second interference analysis is for water temperature. Since the analysis process is similar, only the first interference analysis process is introduced here. It should be understood that 1 and 2 in the flowchart represent that the obtained water flow rate deviation / water temperature deviation is in a qualified state. Then, the results of the first / second interference analysis are waited for to determine whether to output a warning or a qualified result. There is only one possibility: the water flow rate deviation and the water temperature deviation are both not greater than the preset value in the database, which completes the flame control status monitoring.

[0078] Determine if the obtained water flow rate deviation is greater than the preset value. If so, determine if it is within the preset deviation closed range. If so, adjust the flame power gradient and monitor the water flow rate deviation. Determine if the reduction in deviation is within the preset range in the database. If so, continue monitoring the parallel resistor adjustment process until the deviation is not greater than the preset allowable water flow rate deviation and wait for the result of the second interference analysis to decide whether to output an analysis qualified or a warning command. The water flow rate deviation represents the absolute value of the difference between the water flow rate output by the temperature detection circuit and the preset water flow rate set by the user.

[0079] It is further necessary to understand that the interference analysis and flame control status determination of the flame control process specifically include: interference analysis of the flame control process and flame control status determination. The interference analysis is divided into a first interference analysis and a second interference analysis, and the first interference analysis and the second interference analysis are performed simultaneously.

[0080] Specifically, the first interference analysis is as follows: if the obtained water flow deviation is less than the preset allowable water flow deviation in the database, the first interference analysis is qualified and the second interference analysis is awaited; if the obtained water flow deviation is greater than the maximum historical water flow deviation in the database, a temperature detection circuit control warning is issued, and the preset allowable water flow deviation is represented by the sum and average of the historical water flow deviations in the historical flame control process; if the obtained water flow deviation is within the closed interval corresponding to the minimum and maximum historical water flow deviations in the database, power step optimization is performed, and the minimum and maximum historical water flow deviations are represented by the sum and average of the minimum and maximum historical water flow deviations in each historical flame control process in the database.

[0081] Specifically, the power step optimization involves: inputting the sum of the obtained water flow deviation and the average of the flame power adjustment gradient deviation in the current temperature detection circuit into the database; obtaining the flame power adjustment gradient control value based on the mapping relationship between the corresponding flame power adjustment gradient increase in the database; quantifying the degree of increase in the flame power corresponding to the step amplitude in the temperature detection circuit to suppress the AC component in the power supply and reduce interference caused by power supply in the circuit; after one power step optimization, if the reduction in the obtained water flow deviation is not within the preset allowable reduction range of water flow deviation in the database, the power step optimization is paused and a power step warning is issued; otherwise, the power supply ripple suppression process continues to be monitored until the obtained water flow deviation is not greater than the preset allowable water flow deviation in the database, indicating that the first interference analysis is qualified and the results of the second interference analysis are awaited.

[0082] In this embodiment, the preset allowable deviation of water flow rate is represented by the summation and averaging of historical water flow rate deviations during the historical flame control process. The flame power adjustment gradient deviation represents the difference between the current flame power adjustment gradient and the preset flame power adjustment gradient. The preset flame power adjustment gradient is represented by the summation and averaging of historical flame power adjustment gradients during the historical flame control process. The reduction magnitude of water flow rate deviation represents the difference between the water flow rate deviation obtained before power step optimization and the water flow rate deviation obtained after power step optimization. The preset allowable reduction magnitude range of water flow rate deviation represents the closed interval corresponding to the maximum and minimum values ​​of the historical water flow rate deviation reduction magnitude.

[0083] This example uses a sliding mode control algorithm to increase the flame power adjustment gradient in a timely manner based on the current flame power adjustment gradient. At the same time, the historical flame power adjustment gradient and water flow deviation are used as sample data to be input into the feedback neural network model for training to obtain the flame power adjustment gradient-neural network model. The obtained flame power adjustment gradient is input into the flame power adjustment gradient-neural network model to output the corresponding flame power adjustment gradient control value.

[0084] Further, the second interference analysis specifically involves: if the obtained water flow temperature deviation is not greater than the preset water flow temperature deviation in the database, then the second interference analysis is considered qualified and completed. Simultaneously, a real-time monitoring command for the next stage of the water heater controller system is sent. The water flow temperature deviation represents the absolute value of the difference between the water flow temperature output by the temperature detection circuit and the preset water flow temperature set by the user. If the obtained water flow temperature deviation is greater than the maximum value of the historical water flow temperature deviation in the database, a water flow temperature deviation warning is issued. If the obtained water flow temperature deviation is within the closed interval corresponding to the minimum and maximum values ​​of the historical water flow temperature deviation in the database, then the level feedback of water flow-temperature linkage adjustment is performed. The minimum and maximum values ​​of the historical water flow temperature deviation are represented by the average of the minimum and maximum values ​​of the historical water flow temperature deviation in each historical flame control process in the database.

[0085] Specifically, the feedback of the water flow-temperature linkage regulation is as follows: if the obtained water flow temperature deviation is not greater than the preset water flow temperature allowable deviation in the database, then the first-level feedback is performed and the results of the first interference analysis are waited for. The first-level feedback indicates that the water flow and temperature are in a stable linkage range, which is manifested as: the indicator light on the controller panel is always green, the display screen shows the current water temperature of 50℃ and the water flow rate of 1.5L / min in real time, and the linkage status is marked as: normal.

[0086] If the obtained water flow temperature deviation is greater than the preset allowable water flow temperature deviation in the database, secondary feedback is performed and a temperature adjustment action command is generated to output the real-time status of water flow-temperature linkage adjustment. Secondary feedback indicates that there is an abnormal deviation in the linkage between water flow and temperature, and active adjustment needs to be initiated. Specifically, the indicator light on the controller panel flashes yellow, the display screen highlights the deviation as: current -3℃, allowable ±1℃, and the progress of the adjustment command execution is updated synchronously, such as flame power increase of 15% and dynamic correction of water flow ratio. At the same time, the buzzer emits an intermittent prompt sound, such as once every 2 seconds, until the water flow temperature deviation is no greater than the preset allowable water flow temperature deviation in the database, and then switches to primary feedback state.

[0087] After the temperature adjustment action, if the obtained water flow temperature deviation is not greater than the preset water flow temperature deviation in the database, it indicates that the second interference analysis is qualified and the next stage of the water heater controller system real-time monitoring instruction is sent; otherwise, a water flow temperature warning is issued. The preset allowable deviation of water flow temperature is represented by the result of summing and averaging the historical water flow temperature deviations in the historical flame control process.

[0088] In this embodiment, a hierarchical feedback mechanism is used to achieve accurate response and visualization of temperature deviation. The first-level feedback ensures the transparency of the stable state, while the second-level feedback quickly converges the deviation through real-time adjustment and prompts. Combined with historical data, the allowable deviation threshold is optimized to improve the dynamic adaptability and user perception of temperature control, forming a closed-loop monitoring logic that effectively reduces the risk of temperature anomalies and enhances the reliability and safety of water heater temperature control.

[0089] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0090] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0091] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0092] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0093] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0094] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A real-time monitoring method for a water heater controller system, characterized in that, Includes the following steps: S1, under different flame change rates, monitor in real time the control process of the flame detection circuit in the water heater controller system on the signal capture time point, and at the same time perform real-time monitoring and real-time analysis of the flame ion current signal capture, and determine whether there is inaccurate flame state detection due to capture monitoring delay. S2, if there is a capture and monitoring delay, the signal capture parameters of the main MCU circuit in the water heater controller system are adjusted, and the input and output levels of the flame ion current signal are monitored and analyzed in real time. Flame status identification and warning and signal strength interference judgment are also performed. The signal capture parameter adjustment means adjusting the signal gain and sampling frequency to reduce the distortion of the flame ion current signal caused by abnormal signal amplification. The main MCU circuit is used to receive the flame current signal and perform calculation and analysis to generate flame status control commands. S3, if there is signal strength interference, the state identification parameter of the main MCU circuit is adjusted. At the same time, during the flame control process of the main MCU circuit, based on the control process of the temperature detection circuit in the water heater controller system, interference analysis and flame control state determination are performed on the flame control process. The state identification parameter adjustment means adjusting the filter cutoff frequency and the state identification frequency to enhance the temperature detection circuit's ability to suppress temperature signal drift caused by power fluctuations and temperature detection errors caused by electromagnetic interference. The specific process of real-time monitoring and analysis of the input and output levels of the flame ion current signal is as follows: The obtained signal fluctuation spectral density deviation and signal harmonic distortion position offset are harmonicly averaged to obtain a signal strength interference index. The signal strength interference index is used to quantify the degree of influence of the signal fluctuation spectral density deviation and signal harmonic distortion position offset on the level input and output process. If the obtained signal strength interference index is greater than the preset signal strength interference index in the database, then there is signal strength interference and the status identification parameter is adjusted; otherwise, the flame status is judged and monitored. The specific steps for adjusting the state recognition parameters are as follows: Based on the fitting results of the obtained signal strength interference index deviation score and the historical voltage divider resistor ratio, the filter cutoff frequency adjustment value is mapped in the database, and the signal strength interference index is monitored in real time after one filter cutoff frequency adjustment. The aforementioned interference analysis and flame control state determination of the flame control process specifically include: interference analysis and flame control state determination of the flame control process. The interference analysis is divided into a first interference analysis and a second interference analysis, and the first interference analysis and the second interference analysis are performed simultaneously. The first interference analysis is as follows: If the obtained water flow rate deviation is less than the preset allowable water flow rate deviation in the database, it indicates that the first interference analysis is qualified and the second interference analysis is pending. If the obtained water flow rate deviation is greater than the maximum historical water flow rate deviation in the database, a temperature detection circuit control warning will be issued. If the obtained water flow deviation is within the closed interval corresponding to the minimum and maximum values ​​of the historical water flow deviation in the database, then power step optimization is performed.

2. The real-time monitoring method for a water heater controller system as described in claim 1, characterized in that, The specific steps for capturing, monitoring, and analyzing the flame ion current signal in real time are as follows: During the capture of the flame ion current signal, the generation time and processing time of the acquired flame ion current signal are harmonicly averaged to obtain a flame capture and detection impact index. The generation time of the flame ion current signal represents the time interval from receiving the flame state change command to detecting the changed flame ion current signal. The processing time of the flame ion current signal represents the total time from the generation of the flame ion current signal to the system outputting the flame state detection result. The flame capture and detection impact index represents the quantitative data on the degree of influence of the combined generation time and processing time of the flame ion current signal on the capture timeliness of the flame detection circuit. If the acquired flame signal capture and detection impact index is greater than the preset flame signal capture and detection impact index in the database, there is a capture and monitoring delay and the signal capture parameters are adjusted; otherwise, flame identification and monitoring are performed.

3. The real-time monitoring method for a water heater controller system as described in claim 2, characterized in that, The signal capture parameter adjustment is specifically as follows: The obtained flame signal capture and detection influence index deviation is proportionally processed with the preset flame signal capture and detection influence index to obtain the flame signal capture and detection influence index deviation score. Obtain the signal gain in the current flame detection circuit and perform a ratio calculation with the historical signal gain in the database to obtain the signal gain score; Based on the sum of the deviation score and the signal gain score of the flame signal capture and detection impact index, the signal gain adjustment value is mapped in the database and used to quantify the increase in signal gain and the increase in sensitivity of the comparator in the flame detection circuit. During the signal gain adjustment process, the changes in the flame signal capture and detection impact index are monitored in real time.

4. The real-time monitoring method for a water heater controller system as described in claim 3, characterized in that, The real-time monitoring of flame signal capture and detection of changes in influencing indicators specifically includes: If, after one signal gain adjustment, the reduction in the deviation of the flame signal capture and detection impact index is not within the preset range of the reduction in the deviation of the flame signal capture and detection impact index in the database, then the signal gain adjustment is paused and the sampling frequency is adjusted. If the reduction in the deviation of the flame signal capture and detection impact index is within the preset range of the reduction in the flame signal capture and detection impact index, then the signal gain adjustment process will continue to be monitored until the obtained flame signal capture and detection impact index is not greater than the preset flame signal capture and detection impact index in the database. The sampling frequency control is specifically as follows: the deviation of the flame signal capture and detection influence index obtained after one signal gain control is input into the database, and the mapping relationship between it and the corresponding sampling frequency control value is matched to obtain the actual sampling frequency control value. After adjusting the signal capture parameters, if the reacquired flame signal capture and detection impact index is not greater than the preset flame signal capture and detection impact index in the database, then flame identification and monitoring will be performed; otherwise, a signal capture warning will be issued.

5. The real-time monitoring method for a water heater controller system as described in claim 1, characterized in that, The process for real-time monitoring of signal strength interference indicators is as follows: If, after one adjustment of the filter cutoff frequency, the reduction in the obtained signal strength interference index deviation is not within the preset range of the reduction in signal strength interference index deviation in the database, the adjustment of the filter cutoff frequency is paused and state recognition frequency adjustment is performed. If the reduction in the obtained signal strength interference index deviation is within the preset range of the signal strength interference index deviation reduction in the database, then continue to monitor the adjustment process of the filter cutoff frequency until the obtained signal strength interference index is no greater than the preset signal strength interference index in the database. The state recognition frequency control is specifically as follows: based on the summation of the acquired signal strength interference index deviation score and the current state recognition frequency score, the state recognition frequency control value is mapped in the database. If the signal strength interference index re-acquired after the status recognition frequency adjustment is not greater than the preset signal strength interference index in the database, then the status recognition parameter adjustment is completed and the flame control of the main MCU circuit is performed; otherwise, a flame status recognition warning is issued.

6. The real-time monitoring method for a water heater controller system as described in claim 1, characterized in that, The power step optimization specifically refers to: Based on the summation and average of the obtained water flow deviation and the flame power adjustment gradient deviation in the current temperature detection circuit, the flame power adjustment gradient control value is mapped in the database to quantify the degree of increase in the flame power corresponding to the step amplitude in the temperature detection circuit. After a power step optimization, if the reduction in the obtained water flow rate deviation is not within the preset allowable reduction range of water flow rate deviation in the database, the power step optimization is paused and a power step warning is issued. Otherwise, the power step optimization process continues to be monitored until the obtained water flow rate deviation is not greater than the preset allowable deviation of water flow rate in the database. This indicates that the first interference analysis is qualified and the results of the second interference analysis are awaited.

7. The real-time monitoring method for a water heater controller system as described in claim 6, characterized in that, The second interference analysis is as follows: If the obtained water flow temperature deviation is not greater than the preset water flow temperature deviation in the database, it indicates that the second interference analysis is qualified and the interference analysis is completed. At the same time, the real-time monitoring command of the water heater controller system in the next stage is sent. The water flow temperature deviation represents the absolute value of the difference between the water flow temperature output by the temperature detection circuit and the set water flow temperature. If the obtained water flow temperature deviation is greater than the maximum value of the historical water flow temperature deviation in the database, a water flow temperature deviation warning will be issued. If the obtained water flow temperature deviation is within the closed interval corresponding to the minimum and maximum values ​​of the historical water flow temperature deviation in the database, then the level feedback of water flow-temperature linkage regulation is performed.

8. The real-time monitoring method for a water heater controller system as described in claim 7, characterized in that, The feedback mechanism for the water flow-temperature linkage regulation is specifically as follows: If the obtained water flow temperature deviation is not greater than the preset water flow temperature allowable deviation in the database, then first-level feedback is performed and the results of the first interference analysis are awaited. The first-level feedback indicates that the water flow and temperature are in a stable linkage range. If the obtained water flow temperature deviation is greater than the preset allowable water flow temperature deviation in the database, secondary feedback is performed and a temperature adjustment action command is generated to output the real-time status of water flow-temperature linkage adjustment. The secondary feedback indicates that there is an abnormal deviation in the linkage between water flow and temperature, and active adjustment needs to be initiated. After the temperature adjustment action, if the obtained water flow temperature deviation is not greater than the preset water flow temperature deviation in the database, it indicates that the second interference analysis is qualified and the next stage of the water heater controller system real-time monitoring command is sent; otherwise, a water flow temperature warning is issued.

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