Dual-sensor cabin intelligent light control method and system with software and hardware decoupling

Abstract

This invention relates to a hardware-software decoupled dual-sensor cabin intelligent lighting control method and system, comprising: S1 cabin environment initialization and calibration; S2 the system enters a low-power mode retaining only wake-up and monitoring functions, simultaneously acquiring human body sensor signals based on at least two different detection principles, and completing pre-trigger verification if both signals are valid simultaneously; S3 adding the signals to a sliding window and calculating the comprehensive trigger confidence value; S4 entering the dimming execution phase when the confidence value reaches the trigger threshold; S5 performing dimming control according to the adjustment command; S6 continuously updating the confidence value, and shutting down the light source drive circuit and returning to S2 when it falls below the extinguishing threshold. Through a triple mechanism of dual-sensor hardware and door pre-trigger verification, stepped time weighting, and adaptive occlusion compensation, the problems of single-sensor occlusion failure and false triggering are solved; and a hardware-independent PWM dimming drive and fault protection architecture are adopted to provide backup lighting protection in the event of MCU failure, meeting aviation airworthiness requirements.

Description

Technical Field

[0001] This invention relates to the field of aircraft cabin lighting control technology, and in particular to a dual-sensor intelligent cabin lighting control method and system with hardware and software decoupling. Background Technology

[0002] As the civil aviation passenger transport industry continues to develop, passengers are increasingly demanding higher levels of comfort and intelligent experiences in the cabin. As the core of cabin environment control, the cabin lighting system, in addition to basic lighting, must adapt to the scene-specific lighting requirements throughout all phases of flight. Simultaneously, airborne equipment must strictly comply with CAAC / FAA / EASA airworthiness regulations, with stringent constraints on low power consumption, high reliability, electromagnetic interference resistance, and wide voltage compatibility. The cabin lighting control system must simultaneously meet both functional requirements and the demanding airborne operating environment.

[0003] Currently, the main technical solutions used in cabin seat local lighting systems are as follows: (1) Some solutions attempt to use a single infrared pyroelectric sensor to detect the presence of a human body in order to automatically control the lighting and extinguishing of the reading light. However, the infrared sensor is easily blocked by non-metallic objects such as passenger luggage and clothing, resulting in the failure of light control and the inability to achieve stable and reliable automatic lighting.

[0004] (2) The software PWM dimming logic is adopted, and the cabin control system sends brightness adjustment instructions to each lighting terminal to achieve unified dimming of the whole cabin or zones. However, this solution cannot meet the personalized local lighting needs of passengers, and the PWM signal is easily affected by airborne electromagnetic interference inside the cabin, resulting in flickering, adjustment lag and other phenomena.

[0005] (3) Install an independent LED reading light next to the seat and use a manual mechanical switch or potentiometer for dimming. It does not have a human body sensing automatic control function, has a low level of intelligence, and because it uses an LDO linear voltage regulator circuit, the power conversion efficiency is usually less than 70%, and the standby power consumption is high.

[0006] Based on this, this case is proposed. Summary of the Invention

[0007] The purpose of this invention is to provide a hardware-software decoupled dual-sensor intelligent cabin lighting control method and system, which has the advantages of adapting to passengers' personalized local lighting needs, low power consumption, strong anti-interference ability, and high level of intelligence.

[0008] To achieve the above objectives, the present invention provides the following technical solution: A hardware-software decoupled dual-sensor intelligent cabin lighting control method includes the following steps: S1. Cabin environment initialization calibration; S2. The system enters a low-power mode that retains only wake-up and monitoring functions, and synchronously collects signals from at least two human body sensors with different detection principles at a preset frequency. If signals from at least two human body sensors with different detection principles are collected at the same time, the pre-triggered verification is completed and the system proceeds to step S3; otherwise, step S2 is repeated. S3. The synchronously acquired signal is preprocessed and added to a sliding window with a preset time width. The signal is then filtered and normalized to obtain an effective normalized digital signal. Based on the preset stepped time weight allocation and the adaptive compensation coefficient for the occlusion scene, the comprehensive trigger confidence value is calculated. S4. If the comprehensive trigger confidence value obtained in step S3 reaches or exceeds the preset trigger threshold, the system wakes up the main controller and powers on all modules, and proceeds to step S5; otherwise, it returns to step S2. S5. Enter the dimming execution stage, generate a light source control signal according to the adjustment command, and perform dimming control on the light source; S6. The system continuously collects signals from the human body sensor, preprocesses them, adds them to the sliding window, and performs filtering and normalization to update the sliding window. At the same time, based on the preset step-wise time weight allocation and occlusion scene adaptive compensation coefficient, the comprehensive trigger confidence value is updated in real time. When the current comprehensive trigger confidence value is not greater than the preset extinguishing threshold, it is determined that the human body has left and the system returns to step S2; otherwise, step S6 is repeated.

[0009] Furthermore, step S1 includes the following process: After the system is powered on, in the standard cabin environment, baseline data of human body sensors under different working conditions are collected, and trigger thresholds and filtering parameters are calibrated. Collect power supply output parameters across the entire voltage range and calibrate the power supply. After calibration, the parameters are stored in memory.

[0010] Furthermore, the human body sensor includes an infrared pyroelectric sensor and a microwave induction sensor.

[0011] Furthermore, step S3 includes the following process: S31. The synchronously acquired human body sensor signals are amplified and processed by analog-to-digital conversion to obtain digital signals; S32. Add the digital signal obtained in step S31 to a sliding window with a preset time width. Adding the newest digital signal removes the oldest digital signal, so that the newest sampled signal is always in the first position of the sliding window. S33. Perform validity verification on the newly added digital signal in the sliding window, remove invalid data that exceeds the physical range of the human body sensor, and normalize the retained valid data to obtain a valid normalized digital signal. S34. For the effective normalized digital signals within the sliding window, assign different levels of time weights according to the distance of their sampling time from the current time, with newer data having higher weights; S35. Based on the fluctuation of the infrared pyroelectric sensor signal within the sliding window, determine whether the infrared pyroelectric sensor is in an occluded state, and combine the preset occlusion scenario adaptive compensation coefficient matching strategy to output the latest adaptive compensation coefficient of the infrared pyroelectric sensor and the adaptive compensation coefficient of the microwave induction sensor. S36. Based on the effective normalized digital signal in step S33, the time weight allocated in step S34, the latest adaptive compensation coefficient of the infrared pyroelectric sensor and the adaptive compensation coefficient of the microwave induction sensor in step S35, the comprehensive trigger confidence value of the current sliding window is calculated by weighted summation and normalization.

[0012] Furthermore, in step S34, the sliding window is divided into three segments according to time: front, middle, and back. The time weight of the effective normalized digital signal in the front sliding window is set to 1, the time weight of the effective normalized digital signal in the middle sliding window is set to 0.6, and the time weight of the effective normalized digital signal in the back sliding window is set to 0.4.

[0013] Furthermore, in step S35, the fluctuation degree of the infrared pyroelectric sensor signal is represented by the infrared signal fluctuation coefficient. The infrared signal fluctuation coefficient is obtained by calculating the difference between the maximum and minimum values ​​of all effective normalized infrared digital signals within the sliding window and dividing it by the arithmetic mean of all effective normalized infrared digital signals within the sliding window. The adaptive compensation coefficient matching strategy for the occlusion scene is as follows: For the adaptive compensation coefficient of the infrared pyroelectric sensor, when the infrared signal fluctuation coefficient is less than 0.2 and all effective normalized infrared digital signals are not less than 0.3, the adaptive compensation coefficient of the infrared pyroelectric sensor is set to 1; otherwise, the adaptive compensation coefficient of the infrared pyroelectric sensor is set to 0.5. For the adaptive compensation coefficient of the microwave sensor, when the infrared signal fluctuation coefficient is less than 0.2 and all valid normalized infrared digital signals are not less than 0.3, the adaptive compensation coefficient of the microwave sensor is set to 1; otherwise, the adaptive compensation coefficient of the microwave sensor is set to 1.75.

[0014] Furthermore, in steps S4 and S6, the triggering and extinguishing hysteresis determination strategy is as follows: When the overall trigger confidence value is not less than 0.75, it is determined to be a valid human body trigger, the light-up logic is executed, the system wakes up the main controller and powers on all modules; When the overall trigger confidence value is no greater than 0.33, it is determined that there is no human presence, and the lights-out sleep logic is executed, and the system enters a low-power mode that only retains wake-up and monitoring functions; When the overall trigger confidence value is between 0.33 and 0.75, maintain the current lighting state.

[0015] Furthermore, in step S4, when the comprehensive trigger confidence value is confirmed to reach or exceed the preset trigger threshold, the system will perform a secondary verification on the valid normalized digital signal within the preset time. After confirming that the data is valid, it will proceed to step S5; otherwise, invalid data will be removed and the system will return to step S2.

[0016] Furthermore, the adjustment instructions adopt a three-level adjustment instruction priority mechanism; in this mechanism, adjustment instructions are executed sequentially from highest to lowest priority, with higher priority instructions directly overriding lower priority instructions, and lower priority instructions unable to interfere with higher priority instructions. The execution logic is as follows: The first priority instruction is the flight emergency safety mandatory instruction issued by the host computer. After the instruction is issued, all modules power on and directly enter the dimming execution phase, and generate a light source control signal according to the light parameters defined by the flight emergency safety mandatory instruction to control the dimming of the light source. Before this instruction is released, all low priority instructions are ineffective. After this instruction is released, the system returns to the operating state before the instruction was triggered. The second priority commands are those issued by the host computer that cover all flight phases, including takeoff, climb, cruise, descent, landing, and ground docking. The third priority command is the passenger-local manual adjustment command, which allows passengers to manually adjust the lighting parameters based on the scene commands defined during the cruise flight phase.

[0017] Furthermore, a monitoring and protection mechanism is included; the monitoring and protection mechanism includes: during the operation of the lights, real-time monitoring of the voltage, current and operating temperature of the light circuit; if the monitored values ​​exceed a preset threshold, the faulty light circuit is cut off and an alarm is triggered.

[0018] A dual-sensor cabin intelligent lighting control system based on the aforementioned method with hardware and software decoupling includes a main controller, a power module, a Flash storage module, a communication module, a sensor module, a signal conversion and debugging module, and a hardware execution and protection module. The main controller has bidirectional communication connections with the Flash storage module, the communication module, the signal conversion and debugging module, and the hardware execution and protection module; the sensor module has communication connections with the signal conversion and debugging module; and the hardware execution and protection module has communication connections with the communication module. The power module is connected to the airborne power supply and is used to supply power to each module; The main controller is used to perform comprehensive trigger confidence calculation, dimming parameter matching and output, hysteresis triggering and shutdown control, and fault information management; The Flash storage module is used to store the cabin environment calibration parameters, scenario configuration data and timestamped fault records output by the main controller. The communication module is used to enable bidirectional interaction of commands and status information between the main controller and the host computer. The sensor module includes an infrared pyroelectric sensor and a microwave induction sensor, which are used to collect human infrared radiation signals and human movement signals in the passenger cabin seat area, respectively. The signal conversion and debugging module is used to perform pre-trigger judgment, signal amplification and analog-to-digital conversion, and filtering on the analog signal output by the sensor module, and send the conditioned digital signal to the main controller. The hardware execution and protection module includes a hardware PWM dimming drive unit and a hardware fault protection unit; The hardware PWM dimming drive unit includes a first interface connected to the main controller and a second interface connected to the communication module, used to receive adjustment commands output by the main controller or host computer and generate light source control signals for dimming control. The hardware fault protection unit is used to monitor the voltage, current and operating temperature of the lighting circuit in real time. When a fault occurs, it directly cuts off the faulty lighting circuit and sends a fault interruption signal to the main controller to generate alarm information.

[0019] Compared with the prior art, the present invention has the following advantages: 1. Complementary detection is achieved using sensors based on two different detection principles: infrared pyroelectric and microwave induction. Pre-triggered verification is implemented through hardware and gate circuits, ensuring that the subsequent judgment process only proceeds when both signals are simultaneously valid, thus filtering out single-channel interference signals at the hardware level. Furthermore, a tiered time weighting allocation is used to differentiate the weights of sampled data within the sliding window based on their temporal proximity. Newer data contributes more to the current judgment, ensuring timely seating response and avoiding misjudgments caused by abnormal data in a single frame. An adaptive compensation mechanism for occlusion scenarios automatically increases the weight of the other sensor when one sensor is obstructed or its signal attenuates, completely resolving the pain point of existing single-sensor solutions failing entirely when obstructed by luggage or clothing.

[0020] 2. A dimming architecture combining software parameter configuration and hardware PWM generation is adopted. The hardware PWM generation circuit is based on the TL494 chip, which integrates a sawtooth wave generator, a reference voltage source, an error amplifier, and a PWM comparator to form a closed-loop analog PWM generation system. The PWM frequency is fixed by external RC parameters, and the duty cycle is determined by an external voltage divider reference. It is entirely determined by the physical characteristics of the hardware and is not affected by MCU interrupt loss or program anomalies caused by electromagnetic interference, thus eliminating the duty cycle offset and light flicker problems of software PWM at the source. The software is only responsible for sending digital dimming parameters to the hardware chip and does not participate in PWM waveform generation. The dimming accuracy is determined by the low temperature drift characteristics of the hardware reference voltage, reaching ±0.8%, which is much higher than the dimming accuracy of software PWM. At the same time, the hardware PWM generation circuit can use a fixed operating frequency of 25kHz, which avoids the 50-200Hz range that is sensitive to the human eye and the common interference frequency band of airborne avionics equipment, achieving flicker-free operation across the entire brightness range.

[0021] 3. The dimming architecture, which combines software parameter configuration with hardware PWM generation, boasts high reliability. This is because hardware circuit failures are deterministic physical failures, while software failures are random logical failures. Core safety functions such as lighting drive and fault protection are implemented through analog / digital hardware circuits independent of the MCU. Even if the MCU completely fails or the program crashes, the hardware circuit can still perform basic lighting and fault protection functions normally, thus meeting the core design principles of aviation equipment fault safety at the physical level.

[0022] 4. When there is no trigger signal, the main controller enters a low-power mode, shuts down the kernel clock and retains only the minimum peripherals required for wake-up. At the same time, the power supply to the PWM dimming drive circuit and the communication interface circuit is physically cut off through a hardware switch, reducing the standby power consumption of the whole machine to the microampere level. Compared with the existing solution, the overall power consumption is reduced by about 30%, which greatly reduces the load on the airborne power supply. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the hardware-software decoupling dual-sensor cabin intelligent lighting control method in this embodiment. Figure 2 This is a flowchart illustrating the process of combining the trigger confidence value and hysteresis determination in the embodiment. Figure 3This is a schematic diagram of the architecture of the dual-sensor cabin intelligent lighting control system with hardware and software decoupling in the embodiment. Figure 4a This is a schematic diagram of the power module configuration in the embodiment; Figure 4b This is a schematic diagram of the Flash storage module in the embodiment; Figure 4c This is a schematic diagram of the sensor module configuration in the embodiment; Figure 4d This is a schematic diagram of the signal conversion and debugging module in the embodiment; Figure 4e This is a schematic diagram illustrating the hardware execution and protection module in the embodiment; Figure 4f This is a schematic diagram illustrating the configuration of the MCU control module (i.e., the main controller) in the embodiment; Figure 4g This is a schematic diagram of the communication module configuration in the embodiment. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Terminology Explanation: 1. PWM pulse width modulation: Adjusting the pulse duty cycle to achieve precise dimming and color adjustment of LEDs.

[0027] 2. DC-DC synchronous rectification: High-efficiency DC voltage conversion technology with low power consumption and high power conversion efficiency.

[0028] 3. Microwave induction sensor: It detects human movement by reflecting microwaves and can penetrate non-metallic obstructions, thus solving the problem of infrared sensor failure due to obstruction.

[0029] 4. Infrared pyroelectric sensor: detects the presence of the human body by detecting infrared radiation, with low power consumption and low cost, suitable for close-range detection in the cabin.

[0030] 5. Decoupled hardware and software architecture: Safety-related functions such as lighting drive and fault protection are implemented by hardware circuits independent of the main controller MCU, while intelligent functions such as sensor data processing and scene scheduling are implemented by the main controller MCU software. When the main controller MCU fails, the hardware circuit can still maintain basic lighting and fault protection.

[0031] 6. Hysteresis Detection: Two different judgment thresholds are set: a trigger threshold and an off threshold. The state is maintained in the range between the two thresholds when the trigger threshold is higher than the off threshold. When the overall trigger confidence value is in this range, the current light state is maintained to avoid frequent on / off switching of the light due to signal critical jitter.

[0032] 7. Tiered time weighting: Different levels of time weight are assigned according to the distance of the sampling time from the current time. The newer the data, the higher the weight, which takes into account both response speed and anti-interference.

[0033] 8. Hardware AND gate trigger: The output triggers only when both infrared and microwave signals are valid, improving detection reliability.

[0034] This embodiment proposes a hardware-software decoupled dual-sensor intelligent cabin lighting control method, such as... Figure 1 As shown, the process includes the following steps. In this embodiment, the dual sensors refer to a microwave induction sensor and an infrared pyroelectric sensor.

[0035] Step S1. Cabin environment initialization calibration.

[0036] After installation, the cabin intelligent lighting control system (hereinafter referred to as the "system") requires a cabin environment-specific calibration upon initial power-on. Under standard cabin conditions, baseline sensor data is collected under different distances and obstruction scenarios to calibrate trigger thresholds and filtering parameters; power output parameters are collected across the 9-36V full voltage range to calibrate power stability; after calibration, the parameters are stored in memory. The standard cabin environment here refers to a benchmark calibration environment that conforms to CAAC / FAA airworthiness regulations and RTCA DO-160G standards, including uniform temperature and humidity, hardware configuration, and electrical and electromagnetic conditions.

[0037] Calibration allows the system to obtain baseline parameters for the current installation environment, eliminating the impact of individual cabin differences on the accuracy of subsequent judgments.

[0038] Step S2. The system enters low power mode and simultaneously acquires signals from two human body sensors at a frequency of 100Hz. If signals from both human body sensors are acquired simultaneously, the pre-triggered verification is completed, and the system proceeds to step S3; otherwise, step S2 is repeated.

[0039] The low-power mode here refers to an ultra-low-power operating state that the system enters when there is no valid trigger signal. In this mode, the main controller shuts down the kernel clock, retaining only the real-time clock and analog-to-digital acquisition channel to maintain wake-up and signal monitoring capabilities. Simultaneously, it physically cuts off the power supply to the PWM dimming drive circuit and communication interface circuit via hardware switches, eliminating the static power consumption of unnecessary modules at the source and reducing the overall standby current to the microamplitude level. This mode achieves a balance between standby power consumption and responsiveness through its design of "retaining only the minimum functions required for wake-up and monitoring," adapting to the stringent low-power requirements of airborne equipment.

[0040] Step S3. The two synchronously acquired signals are preprocessed and added to a sliding window with a preset time width. Filtering and normalization are performed to obtain an effective normalized digital signal. Based on the preset stepped time weight allocation and occlusion scene adaptive compensation coefficient, the comprehensive trigger confidence value is calculated.

[0041] Specifically, such as Figure 2 As shown, step S3 includes the following sub-steps.

[0042] S31. The two human body sensor signals collected simultaneously are amplified and converted from analog to digital to obtain digital signals.

[0043] S32. Add the digital signal obtained in step S31 to a sliding window with a preset time width. Adding the latest digital signal removes the oldest digital signal, so that the latest sampled signal is always in the first position of the sliding window.

[0044] In this embodiment, the width of the sliding window is always set to 600ms, and the window is updated (slided) every 20ms, adding a newest sampling point and removing an oldest sampling point, so that the window at any time contains all the sampling points in the most recent 600ms, and the newest sampling data is located at the first position of the sliding window, and the older data is located at the end of the sliding window. That is to say, a sampling point is invalidated in the sliding window only after it has undergone 30 consecutive slides.

[0045] S33. Validate the newly added digital signal in the sliding window, remove invalid data exceeding the physical range of the human body sensor, normalize the retained valid data to obtain a valid normalized digital signal, and count the number of valid data within the sliding window, denoted as N(…). ).

[0046] The normalization formula for infrared signals is as follows: ; In the formula, This represents the original voltage sample value output by the i-th group of infrared sensors. This represents the normalized signal output by the i-th group of infrared sensors. This corresponds to the data sampling points within the most recent 600ms; The normalization formula for microwave signals is as follows: ; In the formula, This represents the original voltage sample value output by the i-th group of microwave sensors. This represents the normalized signal output by the i-th group of microwave sensors.

[0047] Electromagnetic interference outliers exceeding the quantization range are eliminated based on the sensor's physical measurement range, and pulse interference is eliminated from the data source. Linear normalization maps two sensor signals with different characteristics to the same dimension interval [0,1], eliminating individual hardware differences and providing an unbiased benchmark for subsequent weighted calculations.

[0048] S34. To address the issue of instantaneous jitter in cabin signals and avoid misjudgments caused by sudden changes in single-frame data, a stepped time weighting method is adopted. For valid normalized digital signals within a sliding window, different levels of time weight are assigned based on the proximity of their sampling time to the current time; newer data has a higher weight. In this embodiment, a sampling point undergoes three time weightings after sampling: the weight is 1 for the first 10 slides, 0.6 for slides 11-20, and 0.4 for slides 21-30, after which the data becomes invalid. The weighting formula is as follows: ; In the formula, This represents the step-wise time weight of the i-th data set (representing the confidence level of data collected at different times for the current judgment; the newer the data, the higher the weight).

[0049] The anti-jitter principle of stepped time weighting: The stepped weighting of the sliding window is essentially a directional low-pass filter for time series signals. The high weight of recent data ensures the trigger response speed, while the low weight of long-term data smooths out instantaneous signal jitter. Compared with linear weighting, stepped weighting avoids the excessive influence of abnormal data in a single frame on the overall result, and mathematically suppresses Gaussian white noise and impulse interference in the cabin environment.

[0050] S35. Based on the fluctuation level of the infrared pyroelectric sensor signal within the sliding window, determine whether the infrared pyroelectric sensor is in an occluded state, and combine the preset occlusion scenario adaptive compensation coefficient matching strategy to output the latest adaptive compensation coefficient of the infrared pyroelectric sensor and the adaptive compensation coefficient of the microwave induction sensor.

[0051] The fluctuation level of the infrared pyroelectric sensor signal is represented by the infrared signal fluctuation coefficient. This coefficient is obtained by calculating the difference between the maximum and minimum values ​​of all valid normalized infrared digital signals within the sliding window, and dividing this difference by the arithmetic mean of all valid normalized infrared digital signals within the sliding window. The specific formula is as follows: ; In the formula, Indicates the infrared signal fluctuation coefficient (coefficient of variation); This represents the maximum value of all valid normalized infrared data within the sliding window. This represents the minimum value of all valid normalized infrared data within the sliding window; where... This represents the arithmetic mean of all valid normalized infrared data within the sliding window: .

[0052] The adaptive compensation coefficient matching strategy for the occlusion scene is as follows: For the adaptive compensation coefficient of the infrared pyroelectric sensor, when the infrared signal fluctuation coefficient is less than 0.2 and all effective normalized infrared digital signals are not less than 0.3, the adaptive compensation coefficient of the infrared pyroelectric sensor is set to 1; otherwise, the adaptive compensation coefficient of the infrared pyroelectric sensor is set to 0.5. For the adaptive compensation coefficient of the microwave sensor, when the infrared signal fluctuation coefficient is less than 0.2 and all effective normalized infrared digital signals are not less than 0.3, the adaptive compensation coefficient of the microwave sensor is set to 1; otherwise, the adaptive compensation coefficient of the microwave sensor is set to 1.75. The formula for the adaptive compensation coefficient matching strategy in occluded scenes is expressed as follows: ; ; In the formula, This represents the adaptive compensation coefficient for infrared signals (which automatically adjusts the effective weight of the infrared signal based on whether the infrared signal is detected as blocked). This represents the adaptive compensation coefficient for microwave signals (which automatically adjusts the effective weight of the microwave signal based on whether infrared detection indicates obstruction).

[0053] The signal attenuation level is quantified by the fluctuation coefficient of the infrared signal. When an obstruction is detected, the weight of the microwave signal is automatically increased and the weight of the infrared signal is decreased. By leveraging the complementary physical characteristics of 24GHz microwaves being able to penetrate non-metallic obstructions while infrared signals are not, the algorithm addresses the industry pain point of a single infrared sensor completely failing after obstruction.

[0054] S36. Based on the effective normalized digital signal in step S33, the time weight allocated in step S34, and the latest adaptive compensation coefficients of the infrared pyroelectric sensor and the microwave induction sensor in step S35, the comprehensive trigger confidence value of the current sliding window is calculated by weighted summation and normalization. The specific formula is as follows: ; In the formula, 0.6 and 0.4 indicate that by default, infrared signals dominate, accounting for 60% and microwave signals accounting for 40%. This represents the overall trigger confidence value.

[0055] Step S4. If the comprehensive trigger confidence value obtained in step S3 reaches or exceeds the preset trigger threshold, the system wakes up the main controller and powers on all modules, proceeding to step S5; otherwise, return to step S2.

[0056] Step S5. Enter the dimming execution stage, generate a light source control signal according to the adjustment command, and perform dimming control on the light source.

[0057] Step S6. The system continuously collects signals from the human body sensor, adds them to the sliding window after preprocessing, and performs filtering and normalization to update the sliding window. At the same time, based on the preset stepped time weight allocation and occlusion scene adaptive compensation coefficient, the comprehensive trigger confidence value is updated in real time. When the current comprehensive trigger confidence value is not greater than the preset extinguishing threshold, it is determined that the human body has left and the system returns to step S2; otherwise, step S6 is repeated. The preset extinguishing threshold is less than the preset triggering threshold.

[0058] The preset trigger threshold and preset extinguishing threshold in steps S4 and S6 are pre-set trigger and extinguishing hysteresis determination strategies, as detailed below: when When a valid human body triggers the light, the light-on logic is executed. when When no human is present, the lights-out sleep logic is executed. when At the same time, prevent shaking and maintain the current state.

[0059] The hysteresis determination strategy described above avoids frequent signal jumps near the critical value, fundamentally eliminating the problem of frequent light flickering under critical conditions.

[0060] It is important to note that in step S3, signals from two human body sensors are required simultaneously to complete the pre-triggered entry into the sliding window. However, in step S6, it is different. Since the presence of a person has already been determined in S6, any sensor signal can be added to the sliding window.

[0061] Preferably, in step S4, when the overall trigger confidence value reaches or exceeds the preset trigger threshold, the system will perform a secondary verification on the valid normalized digital signal within 100ms. After confirming that the data is valid, it will proceed to step S5. Otherwise, invalid data will be removed and the system will return to step S2 to avoid false lighting caused by cabin environment interference.

[0062] In this embodiment, the adjustment instructions adopt a three-level adjustment instruction priority mechanism. In this mechanism, adjustment instructions are executed sequentially from highest to lowest priority. Higher priority instructions can directly override lower priority instructions, and lower priority instructions cannot interfere with higher priority instructions. The execution logic is as follows: The first priority instruction is the mandatory flight emergency safety instruction issued by the host computer, which is required by civil aviation regulations for emergency evacuation, cabin depressurization, in-flight fire, emergency landing, etc. After the instruction is issued, all modules power on and directly enter the dimming execution phase, and generate light source control signals according to the lighting parameters defined by the mandatory flight emergency safety instruction to control the dimming of the light source; before the instruction is released, all low priority instructions are ineffective; after the instruction is released, the system returns to the operating state before the instruction was triggered. The second priority commands are those issued by the host computer that cover all flight phases, including takeoff, climb, cruise, descent, landing, and ground docking. The third priority command is the passenger-local manual adjustment command, which allows passengers to manually adjust the lighting parameters based on the scene commands defined during the cruise flight phase.

[0063] When no valid adjustment command is input, the module defaults to executing the standard cruise mode parameters. The standard cruise mode parameters are defined as follows: Brightness: 50% of rated brightness, corresponding to 50% PWM duty cycle; Color temperature: Neutral white light 4000K; Gradual control: 300ms linear soft start and soft stop; Power consumption control: Power conversion efficiency ≥85% under rated load.

[0064] In addition, the control method of this embodiment also includes a monitoring and protection mechanism. The monitoring and protection mechanism includes: during the operation of the lights, real-time monitoring of the voltage, current and operating temperature of the light circuit; if the monitored values ​​exceed a preset threshold, cutting off the faulty light circuit and triggering an alarm within 3ms.

[0065] Based on the above control method, this embodiment also proposes a hardware and software decoupled dual-sensor cabin intelligent lighting control system, including a main controller, a power supply module, a Flash storage module, a communication module, a sensor module, a signal conversion and debugging module, and a hardware execution and protection module. The selection and function of each module are detailed in Table 1 below.

[0066] Table 1: Hardware Architecture Selection Table for Dual-Sensor Cabin Intelligent Lighting Control System The following is a further detailed explanation of each selected component in Table 1: The STM32F103C8T6 microcontroller (MCU) is an industrial-grade 32-bit ARM Cortex-M3 core microcontroller. It serves as the core for intelligent computing and scheduling in this module, supports low-power sleep mode, and is responsible for sensor data processing, core trigger algorithm calculation, scene-based dimming scheduling, communication interaction, and fault log management. It also coordinates the module's non-safety-related intelligent functions and is completely decoupled from the hardware execution loop.

[0067] Flash memory: Serial non-volatile memory used to store cabin environment calibration parameters, scenario configuration data, and timestamped fault logs of the module. Data is not lost after power failure, meeting the airworthiness requirements for traceable airborne equipment parameters.

[0068] HC-SR501 Infrared Pyroelectric Sensor: A passive human infrared detection device that detects human infrared radiation to sense human presence. It features low power consumption, is suitable for close-range detection, and is one of the core acquisition terminals of this solution's dual-sensor fusion trigger mechanism.

[0069] RD-624 Microwave Sensor: A 24GHz microwave detection device based on the Doppler effect, capable of penetrating non-metallic obstructions to detect human movement, overcoming the shortcomings of infrared sensors that are easily blocked by luggage, and serving as another core acquisition end for the dual-sensor fusion triggering mechanism.

[0070] 12-bit ADC acquisition channel: The microcontroller's built-in 12-bit analog-to-digital converter channel is used to convert the analog voltage signals output by infrared and microwave sensors into computable digital signals, ensuring the accuracy of sensor data acquisition and providing quantization input for the core triggering algorithm.

[0071] π-type LC filter network: A π-type low-pass filter circuit composed of inductors and capacitors is deployed at the power input end to filter out conducted interference, voltage spikes and ripples of the airborne power grid, stabilize the power supply of the module, and adapt to the complex electrical environment of the airborne system.

[0072] MP2451 DC-DC synchronous rectification chip: Wide-voltage input synchronous rectification buck converter, supporting a wide voltage input of 4.5V-50V, power conversion efficiency ≥85%, adaptable to onboard 9-36V grid fluctuations, providing stable power supply for the module and reducing overall power consumption.

[0073] TL494 Hardware PWM Generator Chip: An industrial-grade fixed-frequency pulse width modulation chip with built-in complete PWM generation, reference source, and error amplification circuits. It can generate stable PWM dimming signals independently of the MCU and is the core actuator for anti-flicker dimming in this solution. Even if the MCU fails, basic lighting can still be guaranteed.

[0074] The IRF3205 MOSFET is an N-channel power MOSFET used as a driver switch for LED light sources. It features low on-resistance, fast response, and receives PWM signals to achieve precise LED switching and brightness adjustment, making it suitable for cabin lighting drive requirements.

[0075] MAC97A6 thyristor: a bidirectional silicon controlled rectifier (SCR) device deployed in the power input overvoltage protection circuit. It is rapidly triggered to conduct when the input voltage exceeds the limit, realizing power short-circuit protection and avoiding damage to subsequent circuits. It is the core component of the hardware overvoltage protection in this solution.

[0076] LM358 Operational Amplifier: A dual-channel general-purpose operational amplifier used for pre-amplification of sensor signals, voltage comparison and signal conditioning of hardware protection circuits, improving signal acquisition accuracy and protection circuit response speed, and adapting to the signal processing and safety protection requirements of this solution.

[0077] RS485 transceiver chip: an industrial-grade serial bus transceiver device used to enable long-distance, anti-interference communication between the module and the cabin centralized control system, receive scene dimming commands during flight, report module operating status and fault information, and adapt to the bus communication requirements of airborne equipment.

[0078] MAX3485 Level Shifter Chip: A dedicated RS485 level shifter chip powered by 3.3V, enabling bidirectional conversion between microcontroller TTL levels and RS485 bus levels. It has strong resistance to electromagnetic interference and ensures the communication stability of the module in complex airborne electromagnetic environments.

[0079] Based on the components listed in Table 1, construct the components of a dual-sensor cabin intelligent lighting control system. For example... Figure 3 and Figures 4a to 4g As shown, the main controller has bidirectional communication connections with the Flash storage module, the communication module, the signal conversion and debugging module, and the hardware execution and protection module. The sensor module has a communication connection with the signal conversion and debugging module, and the hardware execution and protection module has a communication connection with the communication module.

[0080] The power module is connected to the airborne power supply and is used to supply power to each module.

[0081] The main controller MCU is used to perform comprehensive trigger confidence calculation, dimming parameter matching and output, hysteresis triggering and shutdown control, and fault information management.

[0082] The Flash storage module is used to store the cabin environment calibration parameters, scene configuration data, and timestamped fault records output by the main controller.

[0083] The communication module is used to enable bidirectional interaction of instructions and status information between the main controller and the host computer, and is also used to issue flight emergency safety mandatory instructions to the hardware PWM dimming drive unit in the hardware execution and protection module.

[0084] The sensor module includes an infrared pyroelectric sensor and a microwave induction sensor, which are used to collect human infrared radiation signals and human movement signals in the passenger cabin seat area, respectively.

[0085] The signal conversion and debugging module is used to perform pre-trigger judgment, signal amplification and analog-to-digital conversion, and filtering on the analog signal output by the sensor module, and then send the conditioned digital signal to the main controller.

[0086] The hardware execution and protection module includes a hardware PWM generation unit, an LED driving and switching unit, an LED light source unit, and a hardware fault protection unit; The hardware PWM generation unit includes a first interface connected to the main controller and a second interface connected to the communication module. It receives adjustment commands from the main controller or host computer and generates light source control signals for dimming control. The connection between the hardware PWM generation unit and the communication module is primarily used to receive mandatory flight emergency safety commands. This allows the LED light source control to be directly enforced through a hardware loop, bypassing the influence of MCU software status or passenger manual adjustments. This fills a safety management loophole in existing solutions while simultaneously addressing both passengers' personalized lighting needs and the crew's scenario-based safety management throughout the entire flight.

[0087] The hardware fault protection unit is used to monitor the voltage, current and operating temperature of the lighting circuit in real time. When a fault occurs, it directly cuts off the faulty lighting circuit and sends a fault interrupt signal to the main controller to form an alarm message. After receiving the interrupt, the MCU immediately records the fault log and sends the alarm message to the cabin system, realizing hardware fallback protection and software traceability reporting.

[0088] Based on the above system, the high reliability of the hardware and software decoupled architecture can be explained as follows: the failure mode of the hardware circuit is deterministic physical failure, while the software failure is random logical failure. Core safety functions such as lighting drive and fault protection are implemented through analog / digital hardware circuits independent of the MCU. Even if the MCU fails completely and the program crashes, the hardware circuit can still perform basic lighting and fault protection functions normally, thus meeting the core design principles of fault safety for aviation equipment from a physical perspective.

[0089] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0090] The following practical examples illustrate that the above technical approach can indeed achieve the proposed technical effects.

[0091] The experimental environment is set up as follows: This experiment was conducted in a real cabin environment, including aluminum alloy seat structures, overhead luggage racks, cabin interior panels, and equipped with onboard electrical, electromagnetic, and extreme environment simulation systems to achieve precise and controllable variable testing. The components were installed under the overhead luggage racks, inside the passenger seat armrests, and inside the reading light brackets on the top of the seat backs. (Of course, this can also be extended to luggage racks, cabin aisles, etc.).

[0092] Table 2: Trigger Comparison in Different Scenarios As can be seen from Table 2, the solution in this embodiment achieves a comprehensive breakthrough in addressing the pain points of the prior art: Stable improvement in sensor control: Through the dual redundancy mechanism of "infrared + microwave dual sensor hardware and door direct triggering + step-by-step confidence algorithm", the trigger accuracy in normal scenarios reaches 100%, and the false trigger rate in interference scenarios is reduced to 0%. This solves the pain point of existing solutions not triggering when luggage is completely blocked, and significantly reduces the false trigger rate in strong magnetic field interference scenarios and aisle personnel movement interference scenarios, making it suitable for the complex use environment of the cabin.

[0093] Table 3: Comparative Test Results of Environmental Adaptability to RTCA DO-160G Standard Table 3 verifies the airworthiness and adaptability of this embodiment in aviation scenarios: The solution meets all airborne airworthiness mandatory standards under all operating conditions: All test items of the solution in this embodiment meet the requirements of RTCA DO-160G standard. Under harsh airborne environments such as wide voltage fluctuations, strong electromagnetic interference, and vibration, the function and performance are completely stable. In contrast, existing traditional solutions cannot meet airworthiness requirements in most test items, thus verifying the aviation scenario-specific adaptability of the present invention.

[0094] Table 4: Analysis of Dual-Sensor Ladder-Type Confidence Trigger Algorithm Records - From Empty Seats to Seated Seats Table 4 shows the scenarios that verify the algorithm's response sensitivity and progressive convergence ability to normal sitting actions. The conclusions are as follows: (1) The algorithm perfectly matches the timing of a person sitting down. It can stably reach the trigger threshold within 200ms after the person begins to sit down, which not only ensures the response speed, but also avoids false triggering caused by people passing by or staying briefly through the step-like time weight. (2) The confidence level gradually increases as people sit down and remains basically unchanged after subsequent people do not make large movements. There are no sudden changes or jitters. Through sliding window filtering and weight allocation, the signal fluctuations caused by human movement during the seating process are effectively suppressed, and the bad experience of frequent light switching is avoided. (3) The basic weight design of the algorithm, which is “infrared-dominant and microwave-assisted”, was verified. The infrared signal rises steadily as people sit down, effectively complementing the microwave signal and ensuring the accuracy of the trigger judgment.

[0095] Table 5: Dual-sensor ladder-style confidence triggering algorithm record - Analysis table of someone reading in a seat and the light is on, and someone passing by. Table 5 shows the scenarios that verify the algorithm's anti-interference ability and anti-accidental touch characteristics. The conclusions are as follows: (1) Even if the microwave signal rises momentarily when people pass by, the algorithm, through the design of step-time weight and infrared-dominated basic weight, will have a comprehensive confidence level that rises and falls above the lighting threshold or is in the hysteresis zone of the lighting state at the moment people pass by, without any jitter, and there is no situation of light flickering or accidental extinguishing. This completely avoids the pain point of the existing solution being sensitive to interference from people in the passageway. (2) The rationality of the dual-sensor fusion logic was verified: the infrared signal of the person in the seat is stable, which serves as the core benchmark for judgment. This ensures the stability of the current seat light and does not interfere with the light control of other seats, perfectly adapting to the use scenario of dense seats in the cabin.

[0096] Table 6: Analysis of Dual-Sensor Ladder-Level Confidence Trigger Algorithm Records - Someone Reading in a Seat with the Light On, Suddenly Obstructed by Clothing Table 6 shows the scenarios that validate the algorithm's adaptive compensation capability in occluded scenes, and the conclusions are as follows: (1) When the infrared sensor is completely blocked by clothing and the signal is greatly attenuated, the algorithm accurately determines the blocking state through the infrared signal fluctuation coefficient, and synchronously triggers the compensation coefficient (Kir drops to 0.5 and Kmw rises to 1.75), automatically increasing the weight of the microwave signal. Finally, the overall confidence level remains stable in the hysteresis zone after the light is turned on, and the light stays on throughout the process, completely solving the pain point of the existing single infrared sensor completely failing after being blocked. (2) The occlusion judgment and compensation coefficient update are completed within 50ms, without any delay or light jitter, realizing seamless switching in occlusion scenarios and ensuring the continuity and comfort of cabin lighting.

[0097] Table 7: Analysis of Aisle Passage When No One is Seated by Dual-Sensor Ladder-Level Confidence Trigger Algorithm Records - Table of Aisle Passage When No One is Seated Table 7 verifies the algorithm's ability to prevent accidental touches in empty seat scenarios, and the conclusions are as follows: (1) Even if the microwave signal rises significantly due to people passing by in the aisle, the algorithm, through infrared-dominated weight design, has a comprehensive confidence level of only 0.585, which is always lower than the lighting trigger threshold of 0.75. There is no false lighting trigger throughout the process, and the false trigger rate is 0, which solves the problem that empty seats are easily triggered by people passing by in the aisle to light up. (2) With the cooperation of the front-end hardware and the door direct triggering mechanism, the software verification stage will only be entered when both infrared and microwave signals are valid at the same time. This further avoids false triggering caused by single-channel signal interference from the hardware level, and realizes the dual protection against false touch by hardware and software, which is perfectly adapted to the high-frequency flow of cabin personnel.

[0098] Table 8: Analysis of Cases Where a Person Reading in Their Seat Leaves Their Seat - Records from the Dual-Sensor Ladder-Level Confidence Trigger Algorithm Table 8 verifies the algorithm's ability to recognize seat-leaving actions and the effectiveness of its hysteresis judgment logic. The conclusions are as follows: the algorithm's confidence level gradually decreases as the person leaves their seat, accurately triggering the light-off logic after the person has completely left. This ensures timely light extinguishing after leaving the seat, reducing standby power consumption, while the hysteresis judgment prevents accidental light extinguishing due to temporary standing or brief absence, balancing energy efficiency and user experience. The hysteresis width formed by the 0.75 trigger threshold and the 0.33 extinguishing threshold effectively avoids frequent light on / off cycles caused by signal jitter during the person's standing process, fundamentally eliminating the light flickering problem and meeting the comfort requirements of cabin use.

[0099] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. Furthermore, the above embodiments only illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. For those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A dual-sensor cabin intelligent light control method decoupled from software and hardware, characterized in that, Includes the following steps: S1. Cabin environment initialization calibration; S2. The system enters a low-power mode that retains only wake-up and monitoring functions, and synchronously collects signals from at least two human body sensors with different detection principles at a preset frequency. If signals from at least two human body sensors with different detection principles are collected at the same time, the pre-triggered verification is completed and the system proceeds to step S3; otherwise, step S2 is repeated. S3. The synchronously acquired signal is preprocessed and added to a sliding window with a preset time width. After filtering and normalization, an effective normalized digital signal is obtained. Based on the preset stepped time weight allocation and occlusion scene adaptive compensation coefficient, the comprehensive trigger confidence value is calculated. S4. If the comprehensive trigger confidence value obtained in step S3 reaches or exceeds the preset trigger threshold, the system wakes up the main controller and powers on all modules, and proceeds to step S5; otherwise, it returns to step S2. S5. Enter the dimming execution stage, generate a light source control signal according to the adjustment command, and perform dimming control on the light source; S6. The system continuously collects signals from the human body sensor, preprocesses them, adds them to the sliding window, and performs filtering and normalization to update the sliding window. At the same time, based on the preset stepped time weight allocation and occlusion scene adaptive compensation coefficient, the comprehensive trigger confidence value is updated in real time. When the current comprehensive trigger confidence value is not greater than the preset extinguishing threshold, it is determined that the human body has left and the system returns to step S2; otherwise, step S6 is repeated. The preset extinguishing threshold is less than the preset triggering threshold.

2. The dual-sensor cabin intelligent light control method decoupled from hardware and software according to claim 1, wherein, Step S1 includes the following process: After the system is powered on, in the standard cabin environment, baseline data of human body sensors under different working conditions are collected, and trigger thresholds and filtering parameters are calibrated. Collect power supply output parameters across the entire voltage range and calibrate the power supply. After calibration, the parameters are stored in memory.

3. The dual-sensor cabin intelligent light control method decoupled from hardware and software of claim 1, wherein, The human body sensor includes an infrared pyroelectric sensor and a microwave induction sensor.

4. The dual-sensor cabin intelligent light control method of decoupling software and hardware of claim 3, wherein, Step S3 Includes the following processes: S31. The synchronously acquired human body sensor signals are amplified and processed by analog-to-digital conversion to obtain digital signals; S32. Add the digital signal obtained in step S31 to a sliding window with a preset time width. Adding the newest digital signal removes the oldest digital signal, so that the newest sampled signal is always in the first position of the sliding window. S33. Perform validity verification on the newly added digital signal in the sliding window, remove invalid data that exceeds the physical range of the human body sensor, and normalize the retained valid data to obtain a valid normalized digital signal. S34. For the effective normalized digital signals within the sliding window, assign different levels of time weights according to the distance of their sampling time from the current time, with newer data having higher weights; S35. Based on the fluctuation of the infrared pyroelectric sensor signal within the sliding window, determine whether the infrared pyroelectric sensor is in an occluded state, and combine the preset occlusion scenario adaptive compensation coefficient matching strategy to output the latest adaptive compensation coefficient of the infrared pyroelectric sensor and the adaptive compensation coefficient of the microwave induction sensor. S36. Based on the effective normalized digital signal in step S33, the time weight allocated in step S34, the latest adaptive compensation coefficient of the infrared pyroelectric sensor and the adaptive compensation coefficient of the microwave induction sensor in step S35, the comprehensive trigger confidence value of the current sliding window is calculated by weighted summation and normalization.

5. The dual-sensor cabin intelligent light control method decoupled from hardware and software of claim 4, wherein, In step S34, the sliding window is divided into three segments according to time: front, middle and back. The time weight of the effective normalized digital signal in the front sliding window is set to the first weight preset value, the time weight of the effective normalized digital signal in the middle sliding window is set to the second weight preset value, and the time weight of the effective normalized digital signal in the back sliding window is set to the third weight preset value. The first preset weight value is greater than the second preset weight value, and the second preset weight value is greater than the third preset weight value.

6. The dual sensor cabin intelligent light control method of claim 4, wherein, In step S35, the fluctuation degree of the infrared pyroelectric sensor signal is represented by the infrared signal fluctuation coefficient. The infrared signal fluctuation coefficient is obtained by calculating the difference between the maximum and minimum values ​​of all effective normalized infrared digital signals within the sliding window and dividing it by the arithmetic mean of all effective normalized infrared digital signals within the sliding window. The adaptive compensation coefficient matching strategy for the occlusion scene is as follows: For the adaptive compensation coefficient of the infrared pyroelectric sensor, when the infrared signal fluctuation coefficient is less than the preset fluctuation threshold and all effective normalized infrared digital signals are not less than the infrared attenuation threshold, the adaptive compensation coefficient of the infrared pyroelectric sensor is set to the first infrared compensation coefficient value; otherwise, the adaptive compensation coefficient of the infrared pyroelectric sensor is set to the second infrared compensation coefficient value, and the first infrared compensation coefficient value is greater than the second infrared compensation coefficient value. For the adaptive compensation coefficient of the microwave sensor, when the infrared signal fluctuation coefficient is less than the preset fluctuation threshold and all valid normalized infrared digital signals are not less than the infrared attenuation threshold, the adaptive compensation coefficient of the microwave sensor is set to the first microwave compensation coefficient value; otherwise, the adaptive compensation coefficient of the microwave sensor is set to the second microwave compensation coefficient value, where the first microwave compensation coefficient value is less than the second microwave compensation coefficient value.

7. The dual-sensor cabin intelligent light control method decoupled from hardware and software of claim 1, wherein, In step S4, when the comprehensive trigger confidence value is confirmed to reach or exceed the preset trigger threshold, the system will perform a secondary verification on the valid normalized digital signal within the preset time. After confirming that the data is valid, it will proceed to step S5; otherwise, invalid data will be removed and the system will return to step S2.

8. The dual-sensor cabin intelligent light control method decoupled from hardware and software of claim 1, wherein, The adjustment instructions employ a three-level adjustment instruction priority mechanism. In this mechanism, adjustment instructions are executed sequentially from highest to lowest priority. Higher priority instructions can directly override lower priority instructions, and lower priority instructions cannot interfere with higher priority instructions. The execution logic is as follows: The first priority instruction is the flight emergency safety mandatory instruction issued by the host computer. After the instruction is issued, all modules power on and directly enter the dimming execution phase, and generate a light source control signal according to the light parameters defined by the flight emergency safety mandatory instruction to control the dimming of the light source. Before this instruction is released, all low priority instructions are ineffective. After this instruction is released, the system returns to the operating state before the instruction was triggered. The second priority commands are those issued by the host computer that cover all flight phases, including takeoff, climb, cruise, descent, landing, and ground docking. The third priority command is the passenger-local manual adjustment command, which allows passengers to manually adjust the lighting parameters based on the scene commands defined during the cruise flight phase.

9. The dual-sensor cabin intelligent light control method decoupled from hardware and software of claim 1, wherein, It includes a monitoring and protection mechanism; the monitoring and protection mechanism includes: during the operation of the lights, real-time monitoring of the voltage, current and operating temperature of the light circuit; if the monitored values ​​exceed a preset threshold, the faulty light circuit is cut off and an alarm is triggered.

10. A dual-sensor cabin intelligent lighting control system based on the hardware and software decoupling of the method according to any one of claims 1 to 9, characterized in that, It includes a main controller, power supply module, Flash storage module, communication module, sensor module, signal conversion and debugging module, and hardware execution and protection module; The main controller has bidirectional communication connections with the Flash storage module, the communication module, the signal conversion and debugging module, and the hardware execution and protection module; the sensor module has communication connections with the signal conversion and debugging module; and the hardware execution and protection module has communication connections with the communication module. The power module is connected to the airborne power supply and is used to supply power to each module; The main controller is used to perform comprehensive trigger confidence calculation, dimming parameter matching and output, hysteresis triggering and shutdown control, and fault information management; The Flash storage module is used to store the cabin environment calibration parameters, scenario configuration data and timestamped fault records output by the main controller. The communication module is used to enable bidirectional interaction of commands and status information between the main controller and the host computer. The sensor module includes an infrared pyroelectric sensor and a microwave induction sensor, which are used to collect human infrared radiation signals and human movement signals in the passenger cabin seat area, respectively. The signal conversion and debugging module is used to perform pre-trigger judgment, signal amplification and analog-to-digital conversion, and filtering on the analog signal output by the sensor module, and send the conditioned digital signal to the main controller. The hardware execution and protection module includes a hardware PWM dimming drive unit and a hardware fault protection unit; The hardware PWM dimming drive unit includes a first interface connected to the main controller and a second interface connected to the communication module, used to receive adjustment commands output by the main controller or host computer and generate light source control signals for dimming control. The hardware fault protection unit is used to monitor the voltage, current and operating temperature of the lighting circuit in real time. When a fault occurs, it directly cuts off the faulty lighting circuit and sends a fault interruption signal to the main controller to generate alarm information.

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