Anti-condensation and anti-frosting self-adaptive heating control method for infrared refrigerant sensor

Abstract

The invention provides an anti-condensation and anti-frosting self-adaptive heating control method for an infrared refrigerant sensor. The method comprises the steps that S1, a system is initialized, and heater control parameters are configured; s2, the internal temperature and humidity of the infrared refrigerant sensor are detected in real time, and a reference signal is obtained in real time through a reference signal channel; s3, the temperature change rate and the temperature and humidity coupling risk factor of the infrared refrigerant sensor are calculated, and the temperature change threshold value is dynamically updated according to the temperature change rate; dynamically updating a reference signal threshold value based on the temperature and humidity coupling risk factor; s4, a risk trend is judged based on the temperature change threshold value and the reference signal threshold value, and a heating control decision is obtained; and S5, performing heating control according to the risk trend based on the heating control decision. According to the method, the temperature change rate is used as a core criterion, risks can be predicted and intervened in advance before visible dew formation and frost formation occur, and jump from passive remediation to active prevention is achieved.

Description

An anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors Technical Field

[0001] This invention relates to the field of photoelectric sensing technology, and more particularly to an anti-condensation and anti-frost adaptive heating control method. Background Technology

[0002] Infrared gas sensors are widely used due to their high sensitivity and selectivity. However, their optical components (such as the light source, gas chamber, and detector) are extremely sensitive to ambient temperature and humidity. When the sensor operates in a high-humidity environment or experiences a rapid temperature rise (for example, outdoor equipment receiving morning sunlight after a cold night), the surface temperature of the sensor's optical cavity may drop below the dew point temperature of the ambient air, causing water vapor to condense into dew or frost at low temperatures. This condensation or frost phenomenon severely interferes with the transmission path of infrared light, leading to three main problems: optical path attenuation: water droplets or ice crystals scatter and absorb infrared light, causing a sharp decrease in the light intensity reaching the detector; measurement distortion: unexpected changes in light intensity may be misinterpreted as changes in the target gas concentration, triggering false alarms; functional failure: severe condensation may completely block the sensor's optical path, causing temporary sensor failure.

[0003] Existing technologies typically address these problems by employing simple constant heating or low-temperature threshold-triggered heating. These methods have significant drawbacks:

[0004] 1. Constant heating: Regardless of environmental needs, continuous heating results in huge energy waste, which is especially detrimental to battery-powered equipment.

[0005] 2. Static threshold heating: Heating is only activated when the sensor temperature is below a fixed safety threshold (e.g., 5°C). This method is slow to react and cannot cope with the risk of condensation that occurs instantly due to rapid temperature changes. For example, during a rapid temperature rise, the sensor body temperature rises slower than the ambient temperature, forming a "cold mirror" that is more prone to condensation. At this time, the sensor temperature may be much higher than the fixed low-temperature threshold, causing the heating function to fail to activate.

[0006] 3. Dynamic Temperature Adjustment: The performance of an infrared refrigerant sensor hinges on the inherent properties of the lenses within the optical cavity. Simply relying on general dynamic temperature adjustment methods cannot address the fundamental issues arising from different application scenarios and lens materials. Ultimately, this approach either results in poor performance or wastes energy, demonstrating poor adaptability.

[0007] In summary, existing technologies suffer from poor adaptability and an inability to proactively identify the risks of condensation and frost formation. Summary of the Invention

[0008] To address the technical problems of existing technologies, this invention proposes an adaptive heating control method for infrared refrigerant sensors to prevent condensation and frost. It utilizes the rate of temperature change as the core criterion and proposes a dynamic threshold adjustment strategy to predict risks and intervene in advance before visible physical phenomena (condensation) occur, thus achieving a shift from passive remediation to proactive prevention. Simultaneously, a reference signal is introduced to directly reflect the cleanliness of the cavity, serving as a basis for determining the risk of frost and condensation. This avoids the shortcomings of traditional methods that rely solely on dynamic temperature adjustment, improving the method's adaptability.

[0009] To achieve the above objectives, the technical solution of the present invention is implemented as follows:

[0010] An anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors includes the following steps:

[0011] S1: System initialization and configuration of heater control parameters;

[0012] S2: Real-time detection of internal temperature and humidity of the infrared refrigerant sensor, and real-time acquisition of reference signal through the reference signal channel;

[0013] S3: Calculate the temperature change rate and temperature-humidity coupling risk factor of the infrared refrigerant sensor, and dynamically update the temperature change threshold based on the temperature change rate; dynamically update the reference signal threshold based on the temperature-humidity coupling risk factor.

[0014] S4: Determine risk trends based on temperature change thresholds and reference signal thresholds to obtain heating control decisions;

[0015] S5: Heating control is performed based on risk trends according to heating control decisions.

[0016] Furthermore, configure the heater control parameters, including:

[0017] For the maximum heating power P_max, an automatic calculation based on the scene baseline is introduced:

[0018] ;

[0019] in, This is the actual supply voltage. Rated voltage;

[0020] For the baseline heating power P_base, an automatic calculation based on the scene baseline is introduced:

[0021] ;

[0022] in, The current average relative humidity. This is the humidity correction index. The higher the value, the higher the P_base.

[0023] Furthermore, the infrared refrigerant sensor incorporates a dual-channel detector, which includes a signal channel and a reference channel. The signal channel is used for detecting relevant gases, while the reference channel is unaffected by relevant gases and is used to determine whether condensation or frost has occurred by sensing changes in the light path.

[0024] Furthermore, the temperature change rate is calculated, including: a corrected temperature change rate calculation incorporating the thermal conductivity of the sensor housing.

[0025] ;

[0026] in, For standard thermal conductivity, The thermal conductivity of the current sensor lens;

[0027] The calculation method for the temperature and humidity coupling risk factor is as follows:

[0028] ;

[0029] in, For real-time temperature, The dew point temperature is calculated using the August-Roche-Magnus formula, and the temperature and humidity coupling risk factor is... The smaller the value, the higher the risk of condensation.

[0030] Furthermore, the calculation method for dynamically updating the temperature change threshold based on the temperature change rate is as follows:

[0031] ;

[0032] in, The temperature change threshold, As the benchmark correction factor, This is the installation angle correction factor. The angle between the sensor cavity and the horizontal plane. The larger the size, the harder it is for water vapor to adhere. The larger the value, the higher the temperature change threshold. The higher the value, the less likely it is to be accidentally triggered.

[0033] Furthermore, the reference signal threshold is dynamically updated based on the temperature and humidity coupling risk factor, including:

[0034] ;

[0035] in, The reference signal threshold, The threshold for safety risk factors, temperature and humidity coupling risk factors The smaller, The lower, when hour, ,when At that time, the risk of condensation increases. reduce.

[0036] Furthermore, risk trends are determined based on temperature change thresholds and reference signal thresholds, including:

[0037] Based on temperature change rate and temperature change threshold Determine if there is potential condensation due to rapid temperature changes:

[0038] like This indicates that the cavity heats up significantly slower than the environment, making it prone to forming a cold mirror and posing a risk of condensation to the sensor.

[0039] Based on the change in the reference signal Determine the state of condensation:

[0040] At that time, there was a risk of condensation in the optical cavity, but condensation had not yet begun;

[0041] The optical cavity is in the early stage of condensation;

[0042] The optical cavity is in the late stage of condensation. This indicates the parameters for stage classification.

[0043] Furthermore, obtaining heating control decisions includes:

[0044] when and At this time, with low risk, the output decision is: Level 1 heating control; although condensation has not started, heating continues to suppress risk.

[0045] when and The risk is moderate, and the output decision is: secondary heating control;

[0046] when and The risk is relatively high, and the output decision is: three-level heating control.

[0047] Heating control decisions are based on risk trends, including:

[0048] For primary heating control, the first-stage power adjustment coefficient is used. Heating the optical cavity:

[0049] ;

[0050] For two-stage heating control, the second-stage power adjustment coefficient is used. Heating the optical cavity:

[0051] ;

[0052] For three-stage heating control, the third-stage power adjustment coefficient is used. Heating the optical cavity:

[0053] ;

[0054] in, For heating power, .

[0055] It also includes multi-feature interference differentiation and monitoring:

[0056] After acquiring the reference signal, calculate the signal attenuation characteristics of the reference signal. and the standard deviation of the amplitude of multiple reference signals ;

[0057] Only when the reference signal changes and and If condensation is detected, it is considered an interference; otherwise, heating adjustment is not triggered. The signal attenuation threshold of the reference signal, The standard deviation threshold of the reference signal amplitude.

[0058] The beneficial effects of this invention are as follows:

[0059] Proactive protection: It is the first to use the rate of temperature change as the core criterion, which can predict risks and intervene in advance before visible physical phenomena (condensation) occur, realizing a leap from "passive remediation" to "proactive prevention".

[0060] Precise control and high energy efficiency: By dynamically adjusting the heating power, "on-demand distribution" is achieved, which can provide sufficient heat when the risk is high and save electricity to the maximum extent when the risk is low, thus solving the problem of high power consumption for constant heating.

[0061] High reliability: It effectively avoids optical path problems caused by condensation and frost, ensuring the measurement accuracy and working stability of the sensor under various harsh working conditions, and greatly reducing false alarms and downtime.

[0062] Highly adaptable: The algorithm does not rely on a single threshold of absolute temperature, thus effectively addressing the blind spot of traditional methods such as "rapid temperature rise," making it more universally applicable.

[0063] Highly targeted: By using optical reference signals, the trend of condensation and frost can be further determined, and the relevant responses can be processed in a targeted manner. Attached Figure Description

[0064] 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 some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 is a general flowchart of the anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to the present invention.

[0066] Figure 2 is a system structure block diagram of the present invention.

[0067] Figure 3 shows the relationship between temperature, humidity, and dew point. Detailed Implementation

[0068] 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.

[0069] An anti-condensation and frosting adaptive heating control method for an infrared refrigerant sensor, as shown in Figure 2, includes an infrared refrigerant sensor module. This module comprises an optical cavity, an infrared light source, and a dual-channel detector. The optical cavity provides a fixed transmission path for infrared light and serves as the core space for the interaction between the measured gas and the infrared light, where the gas absorbs infrared light of a specific wavelength. The infrared light source's core function is to emit infrared light that meets the detection requirements. The dual-channel detector includes a signal channel and a reference channel, converting optical signals into electrical signals. The signal channel (wavelength 3.4µm) is used to detect changes in the concentration of the target refrigerant gas. The reference channel (wavelength 3.91µm) is unaffected by the refrigerant and other common gases, thus providing feedback on changes in the optical link. Combined with temperature and humidity signals, reliable condensation / frost detection can be achieved.

[0070] A temperature sensing module is disposed on or inside the optical cavity and is used to measure the cavity temperature.

[0071] A humidity sensing module is disposed on or inside the optical cavity and is used to measure the humidity of the cavity.

[0072] Heating module: Heating element integrated into the optical cavity; such as thin film heating element, miniature PTC heater, miniature heating wire / heating coil, etc.

[0073] Microcontroller (MCU): Connects to and controls the infrared sensing module, temperature sensing module, humidity sensing module and heating module;

[0074] Control algorithm module: As a software program running on the MCU, it is configured to execute a method for anti-condensation and anti-frost adaptive heating control for infrared refrigerant sensors. Its core is to predict risks and dynamically adjust heating power based on the rate of temperature change.

[0075] As shown in Figure 1, the steps of the anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors include:

[0076] S1: System initialization and configuration of heater control parameters.

[0077] In this embodiment of the application, after the system is started, the heater control parameters are configured, including the maximum heating power P_max, the reference heating power P_base, and the power adjustment coefficient K; the maximum heating power P_max is the highest power allowed by the heating element to avoid overload damage, and the power adjustment coefficient is calibrated by standard experiments.

[0078] In addition, the maximum heating power P_max can be automatically calculated based on the scene baseline:

[0079] ;

[0080] in, This is the actual supply voltage. Use the rated voltage to avoid insufficient heating power or overload caused by voltage fluctuations.

[0081] For the baseline heating power P_base, automatic calculation based on the scene baseline can be introduced:

[0082] ;

[0083] in, The current average relative humidity. This is the humidity correction index. , The higher the value, the higher the P_base, which is suitable for basic protection needs in high humidity scenarios.

[0084] S2: Real-time detection of internal temperature and humidity of the infrared refrigerant sensor, and real-time acquisition of reference signal through the reference signal channel.

[0085] In this embodiment, the infrared refrigerant sensor includes a dual-channel detector, which includes a signal channel and a reference channel. The signal channel is mainly used for the detection of related gases, while the signal strength of the reference channel is basically unaffected by the gas being measured. At the same time, a temperature sensing module and a humidity sensing module are provided in the optical cavity to detect the internal temperature and humidity of the infrared refrigerant sensor in real time, respectively.

[0086] S3: Calculate the temperature change rate and temperature-humidity coupling risk factor of the infrared refrigerant sensor, and dynamically update the temperature change threshold based on the temperature change rate; dynamically update the reference signal threshold based on the temperature-humidity coupling risk factor.

[0087] In this embodiment, the influence of the sensor housing's thermal conductivity on the temperature response is considered; therefore, a corrected rate of temperature change is used to calculate the temperature response based on the sensor housing's thermal conductivity.

[0088]

[0089] in, For standard thermal conductivity, The thermal conductivity of the current sensor lens is preset by the sensor hardware parameters; the worse the thermal conductivity, the lower the thermal conductivity. The smaller the size, the better it matches the actual temperature lag of the cavity.

[0090] In this embodiment, the real-time dynamic changes in ambient humidity are considered to calculate the temperature-humidity coupling risk factor:

[0091]

[0092] in, For the sensor's real-time temperature, Dew point temperature, The smaller the value, the higher the risk of condensation, providing additional information for subsequent judgments.

[0093] Dew point calculation is based on the August-Roche-Magnus approximation formula:

[0094] ;

[0095] ;

[0096] Among them, sensor temperature RH (relative humidity) is measured in degrees Celsius and expressed as a percentage (%). , The fitting coefficients in the Magnus empirical formula are, in the embodiments of this application, It is 17.27. It is 237.7. It refers to the natural logarithm.

[0097] In this embodiment, the fixed threshold of the prior art cannot adapt to different temperature and humidity environments. For example, in a high-humidity environment, condensation may still occur even if dT / dt is small. This step dynamically adjusts the threshold using a formula, making the risk assessment more consistent with the actual environment. This solves the problems of the fixed threshold's delayed response and missed detection of rapid temperature rise risks, improving the accuracy of risk assessment in different scenarios. It also considers actual working conditions such as temperature changes and the influence of sensor installation angle on water vapor adhesion. The method for dynamically updating the temperature change threshold based on the rate of temperature change is as follows:

[0098] ;

[0099] and It is activated at the correct time, and cooling will not cause condensation.

[0100] in, The temperature change threshold, As the benchmark correction factor, This is the installation angle correction factor. The angle between the sensor cavity and the horizontal plane. The larger the size, the harder it is for water vapor to adhere. The larger the value, the higher the temperature change threshold. The higher the value, the less likely it is to be accidentally triggered.

[0101] In this embodiment of the application, the reference signal threshold is dynamically updated based on the temperature and humidity coupling risk factor, including:

[0102] ;

[0103] in, The reference signal threshold, The threshold for safety risk factors, temperature and humidity coupling risk factors The smaller, The lower, when hour, ,when At that time, the risk of condensation increases. reduce.

[0104] S4: Determine risk trends based on temperature change thresholds and reference signal thresholds to obtain heating control decisions.

[0105] The relationship between dew point and temperature and humidity is shown in Figure 3. The conditions for dew point condensation are:

[0106] 1) When the indoor temperature and humidity are at a certain level;

[0107] 2) The air temperature is higher than the temperature of the surface of the object where condensation forms;

[0108] 3) And the temperature of the surface of the object to which condensation forms is lower than the dew point temperature.

[0109] Therefore, in environments above 20°C, the higher the humidity, the higher the dew point. The data shows that the smaller the difference between the current temperature and the dew point, the easier it is for condensation to occur. When the sensor temperature is lower than the ambient temperature and is in a passive heating process, the greater the temperature difference, the faster the sensor heats up, and the easier it is for condensation to occur.

[0110] When the cavity is smooth and normal, the reference signal is stable; when there is a slight change, the optical signal will be significantly affected. Taking condensation as an example, when condensation begins to appear, the optical signal will drop rapidly. In the early stage of condensation or when there is a condensation trend, the reference signal will begin to drop. This signal can be used to further determine the current state of condensation or frost.

[0111] In this embodiment of the application, the risk trend is determined based on a temperature change threshold and a reference signal threshold, including:

[0112] Based on temperature change rate Determine if there is potential condensation due to rapid temperature changes:

[0113] like This indicates that the cavity heats up significantly slower than the environment, which can easily lead to the formation of a cold mirror and poses a risk of condensation on the sensor, requiring proactive heating.

[0114] like This situation mainly occurs when the temperature rises slowly. At this time, the product temperature is close to the ambient temperature, and condensation is less likely to occur.

[0115] Based on the change in the reference signal Determine the state of condensation:

[0116] At that time, there was a risk of condensation in the optical cavity, but condensation had not yet begun;

[0117] The optical cavity is in the early stage of condensation;

[0118] The optical cavity is in the late stage of condensation. This indicates the parameters for stage classification.

[0119] In this embodiment of the application, obtaining the heating control decision includes:

[0120] when and At this time, with low risk, the output decision is: Level 1 heating control; although condensation has not started, low-power heating is still performed to suppress risk.

[0121] when and The risk is moderate, and the output decision is: secondary heating control;

[0122] when and The risk is relatively high, and the output decision is: three-level heating control.

[0123] S5: Heating control is performed based on risk trends according to heating control decisions.

[0124] For primary heating control, a first-level control strategy is adopted, using a first-level power adjustment coefficient to heat the optical cavity at a relatively low coefficient:

[0125] ;

[0126] For secondary heating control, a secondary control strategy is adopted, using a secondary power adjustment coefficient to heat the optical cavity with a moderate coefficient:

[0127] ;

[0128] For the three-stage heating control, the third-stage control strategy is adopted, which uses a third-stage power adjustment coefficient to heat the optical cavity at a higher coefficient:

[0129] ;

[0130] in, .

[0131] In this embodiment of the application, in order to distinguish between signal attenuation caused by condensation and signal attenuation caused by dust / vibration, multi-feature interference differentiation monitoring is also added:

[0132] After obtaining the reference signal, the signal attenuation characteristics of the reference signal were also calculated. and the standard deviation of the amplitude of the 10th reference signal ;

[0133] Because condensation is the rapid formation of a uniform water vapor layer on the sensor lens surface—a physical process involving rapid and uniform coverage—this water vapor layer quickly weakens the signal, resulting in a rapid signal drop. The signal strength will be relatively high; at the same time, the water vapor layer continuously and uniformly covers the lens, and the signal decreases steadily and continuously. The numerical fluctuations of the signal in the last 10 tests are very small, so the standard deviation describing its fluctuation will be relatively small.

[0134] Regarding signal attenuation caused by dust / vibration, dust accumulates slowly on the lens and does not rapidly weaken the signal, while vibration is an intermittent interference and does not continuously accelerate signal attenuation. The signal will be smaller; at the same time, uneven dust accumulation and intermittent vibration will cause the signal to fluctuate, resulting in large fluctuations in the value of the signal in the last 10 tests, thus the standard deviation will be larger.

[0135] Therefore, the logic for distinguishing multi-feature interference is: only when the reference signal changes... and and If condensation is detected, it is considered an interference; otherwise, heating adjustment is not triggered. The signal attenuation threshold of the reference signal, The standard deviation threshold of the reference signal amplitude.

[0136] Ultimately, closed-loop maintenance is achieved. During the heating process, the sensor temperature T, the rate of temperature change, and... .when Restore to threshold Below, once the sensor temperature T is consistently higher than the estimated dew point temperature by a certain margin, and the temperature change rate returns to a stable level, the heating power is gradually reduced or heating is stopped, forming a dynamic closed-loop control to ensure that the sensor always operates within a safe, non-condensing temperature range.

[0137] This invention discloses an adaptive heating control method for infrared sensors to prevent condensation and frost. The core of this method lies in proactively predicting the risk of condensation and frost in rapidly changing or high-humidity environments by real-time monitoring of the sensor's own temperature, humidity, and the rate of change of the optical reference signal. When a rapid temperature change is detected, the system does not simply rely on an absolute temperature threshold but immediately activates the heating function and dynamically and linearly adjusts the heating power according to the severity of the temperature change. Furthermore, it determines whether condensation is occurring based on changes in the optical signal intensity within the infrared sensor, further adjusting the defrosting power to improve the defrosting effect. This invention uses a dual-channel detector. The signal channel is primarily used for detecting relevant gases, while the signal intensity of the reference channel is largely unaffected by the measured gas. Condensation and frost can significantly weaken the optical signal. Adjusting the defrosting power further at the initial stage of condensation effectively improves the anti-condensation and frost performance. This invention effectively avoids problems such as optical path attenuation, measurement inaccuracies, and functional failures caused by condensation and frost in the infrared sensor's optical cavity. Simultaneously, it minimizes energy consumption to the maximum extent during non-risk periods, significantly improving the reliability and durability of the sensor in harsh environments.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for adaptive heating control against condensation and frosting in infrared refrigerant sensors, characterized in that, The steps include: S1: System initialization and configuration of heater control parameters; S2: Real-time detection of internal temperature and humidity of the infrared refrigerant sensor, and real-time acquisition of reference signal through the reference signal channel; S3: Calculate the temperature change rate and temperature-humidity coupling risk factor of the infrared refrigerant sensor, and dynamically update the temperature change threshold based on the temperature change rate; dynamically update the reference signal threshold based on the temperature-humidity coupling risk factor. S4: Determine risk trends based on temperature change thresholds and reference signal thresholds to obtain heating control decisions; S5: Heating control is performed based on risk trends according to heating control decisions.

2. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 1, characterized in that, Configure heater control parameters, including: introducing automatic calculation based on scenario baseline for maximum heating power P_max. ;in, This is the actual supply voltage. For the rated voltage; for the reference heating power P_base, an automatic calculation based on the scenario baseline is introduced: ;in, The current average relative humidity. This is the humidity correction index. The higher the value, the higher the P_base.

3. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 2, characterized in that, The infrared refrigerant sensor has a built-in dual-channel detector, which includes a signal channel and a reference channel. The signal channel is used for detecting related gases, while the reference channel is unaffected by related gases and is used to determine whether condensation or frost has occurred by sensing changes in the light path.

4. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 3, characterized in that, The calculation of the temperature change rate includes: a corrected temperature change rate calculation incorporating the thermal conductivity of the sensor housing. ;in, For standard thermal conductivity, The thermal conductivity of the current sensor lens is given; the method for calculating the temperature and humidity coupling risk factor is as follows: ;in, For real-time temperature, The dew point temperature is calculated using the August-Roche-Magnus formula, and the temperature and humidity coupling risk factor is... The smaller the value, the higher the risk of condensation.

5. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 4, characterized in that, The calculation method for dynamically updating the temperature change threshold based on the rate of temperature change is as follows: ;in, The temperature change threshold, As the benchmark correction factor, This is the installation angle correction factor. The angle between the sensor cavity and the horizontal plane. The larger the size, the harder it is for water vapor to adhere. The larger the value, the higher the temperature change threshold. The higher the value, the less likely it is to be accidentally triggered.

6. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 5, characterized in that, Dynamically updating the reference signal threshold based on temperature and humidity coupling risk factors includes: ;in, The reference signal threshold, The threshold for safety risk factors, temperature and humidity coupling risk factors The smaller, The lower, when hour, ,when At that time, the risk of condensation increases. reduce.

7. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 6, characterized in that, Risk trends are determined based on temperature change thresholds and reference signal thresholds, including: based on the rate of temperature change. and temperature change threshold Determine if there is potential condensation due to rapid temperature changes: If This indicates that the cavity heats up significantly slower than the environment, easily forming a cold mirror, and the sensor faces the risk of condensation; based on the change in the reference signal Determine the state of condensation: At that time, there was a risk of condensation in the optical cavity, but condensation had not yet begun; The optical cavity is in the early stage of condensation; The optical cavity is in the late stage of condensation. This indicates the parameters for stage classification.

8. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 7, characterized in that, Obtaining heating control decisions includes: when and When the risk is low, the output decision is: Level 1 heating control; although condensation has not started, heating continues to suppress the risk. and The risk is moderate, and the output decision is: secondary heating control; when and The risk is relatively high, and the output decision is: three-level heating control.

9. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 8, characterized in that, Heating control decisions are based on risk trends, including: for primary heating control, using the primary power adjustment coefficient. Heating the optical cavity: For two-stage heating control, the second-stage power adjustment coefficient is used. Heating the optical cavity: For three-stage heating control, the third-stage power adjustment coefficient is used. Heating the optical cavity: ;in, For heating power, 。 10. The anti-condensation and frosting adaptive heating control method for infrared refrigerant sensors according to claim 9, characterized in that, It also includes multi-feature interference differentiation and monitoring: after acquiring the reference signal, the signal attenuation characteristics of the reference signal are calculated. and the standard deviation of the amplitude of multiple reference signals Only when the reference signal changes and and If condensation is detected, it is considered an interference; otherwise, heating adjustment is not triggered. The signal attenuation threshold of the reference signal, The standard deviation threshold of the reference signal amplitude.

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