Ultraviolet radiation measurement method

Abstract

The invention discloses an ultraviolet radiation measurement method, and particularly relates to the technical field of data measurement. A photoelectric detection technology with a wide spectral response range, the waveband subdivision capability of a multi-waveband optical filter and a dynamic evaluation and environment compensation model of signal quality are combined, and the accuracy of ultraviolet waveband radiation intensity distinguishing under the multi-light-source interference condition is evaluated and improved by extracting a spectral resolution deviation value and a signal-to-noise ratio abnormal value; when the measurement precision is influenced by the environment temperature and humidity, a nonlinear compensation model is used for dynamic correction, the result stability is ensured, in addition, a low-power-consumption wireless communication module is used for achieving efficient transmission of processed data, the requirement for long-time portable use of equipment is met, and the application range is wide. High-precision and multi-band ultraviolet measurement is achieved, meanwhile, low power consumption and portability are achieved, and reliable technical guarantee is provided for ultraviolet measurement in environment monitoring, medical health and industrial application.

Description

Technical Field

[0001] The invention relates to the technical field of data measurement, and in particular to an ultraviolet radiation measurement method. Background Art

[0002] Ultraviolet radiation is widely present in the natural environment and industrial applications, and its measurement technology plays an important role in environmental monitoring, medical health, industrial production and other fields. Existing technologies mainly rely on equipment such as ultraviolet sensors, spectrometers and radiation dosimeters to meet the needs of specific scenarios by monitoring the intensity, wavelength distribution and cumulative dose of ultraviolet radiation. However, existing ultraviolet radiation measurement methods still face some technical limitations. For example, ultraviolet sensors are usually selective for wavelength ranges and cannot accurately measure the intensity distribution of multi-band ultraviolet rays at the same time. In addition, although traditional spectrometers can achieve accurate wavelength analysis, they are large in size and high in power consumption, making them difficult to use in portable devices. In actual use, environmental conditions (such as temperature, humidity, and pollutant particles) may interfere with the measurement results, further affecting the accuracy and stability of the measurement. Therefore, how to accurately distinguish the radiation intensity of ultraviolet bands (UVA, UVB, UVC) and maintain the long-term stability of the measuring equipment under the conditions of multi-light source interference or strong environmental changes, while achieving low power consumption and portability, is an important and insufficiently solved problem in the existing technology. Summary of the invention

[0003] The purpose of the present invention is to provide a method for measuring ultraviolet radiation to solve the shortcomings of the background technology.

[0004] In order to achieve the above object, the present invention provides the following technical solution: a method for measuring ultraviolet radiation, comprising the following steps:

[0005] S1: Receive ultraviolet radiation in the environment using a photodetector with a wide spectral response range and generate a corresponding electrical signal;

[0006] S2: subdividing the ultraviolet radiation into bands through a multi-band filter to obtain the radiation intensity of the UVA, UVB and UVC bands respectively;

[0007] S3: Extract the spectral resolution deviation and signal-to-noise ratio anomaly in the multi-band signal to evaluate the accuracy of UV band radiation intensity distinction under multi-light source interference conditions;

[0008] S4: When the discrimination accuracy is low, the real-time data of the temperature and humidity sensors are combined, and the established nonlinear model of temperature, humidity and UV sensor response is used to compensate the UV measurement results for environmental factors;

[0009] S5: Transmitting the processed ultraviolet radiation intensity data to an external device via a low-power wireless communication module, wherein the wireless communication module is a Bluetooth low-power module or a LoRa module to support long-term portable use of the device.

[0010] Preferably, in S3, the spectral resolution deviation value and the signal-to-noise ratio abnormal value in the multi-band signal are extracted, and the spectral resolution deviation value is obtained by:

[0011] Each signal corresponds to the total signal value S of a band clean , including the cumulative signal values ​​within the three bands of UVA, UVB and UVC. In each wide band range, 3 or 5 narrow-band filters are added, each narrow-band filter covers a narrower wavelength range. The signal value transmitted through the narrow-band filter is used to obtain the signal S at multiple subdivided wavelengths in the band. clean (λ);

[0012] Case of 3 narrow-band filters: Collect the signal values ​​of the central wavelength and the wavelength range on both sides symmetrically, forming 3 sampling points: Indicates the peak wavelength λ peak , the strength value of the net signal;

[0013] In the case of 5 narrow-band filters: the signal values ​​of the central wavelength and the wavelength range on both sides symmetrically are collected to form 5 sampling points:

[0014] Based on the multiple signal values ​​obtained by the narrowband filter, the spectral distribution curve within the band is reconstructed, and the actual spectral center wavelength λ is determined by the distribution shape of the curve. actual ; According to the filter design parameters, the ideal spectral center wavelength λ of the recording band ideal , and the actual spectrum center wavelength λ actual Compare with the ideal spectrum center wavelength and calculate the spectral resolution deviation value. The expression is: MK = λ actual -λ ideal ; Where MK is the spectral resolution deviation value.

[0015] Preferably, in S3, the spectral resolution deviation value and the signal-to-noise ratio anomaly value in the multi-band signal are extracted to evaluate the accuracy of distinguishing the ultraviolet band radiation intensity under the condition of multi-light source interference, wherein the method for obtaining the signal-to-noise ratio anomaly value is:

[0016] Get the original signal S from the detector raw (t), contains the target signal and the noise component, and the net signal is separated by bandpass filtering, and the expression is: S signal (t) = S raw(t)-N(t); where N(t) is the noise signal, and its power P is calculated by sampling the variance of the noise signal N(t) noise , the expression is: Where B is the time period of signal measurement, that is, the total time the signal is collected. The net signal is processed and the signal power P is calculated. signal , the expression is: The signal-to-noise ratio (SNR) is calculated using the power of the signal and the noise, as follows: Compare the actual measured signal-to-noise ratio (SNR) measured and the theoretical expected value SNR expected , calculate the signal-to-noise ratio abnormal value, the expression is: MY = SNR measured -SNR expected ; Where MY is the signal-to-noise ratio outlier.

[0017] Preferably, in S3, the accuracy of distinguishing the radiation intensity of the ultraviolet band under the condition of multi-light source interference is evaluated, specifically: the spectral resolution deviation value and the signal-to-noise ratio anomaly value are normalized, and the accuracy coefficient of distinguishing the radiation intensity of the ultraviolet band under the condition of multi-light source interference is calculated through the normalized spectral resolution deviation value and the signal-to-noise ratio anomaly value.

[0018] Preferably, in S3, the acquired accuracy coefficient of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is compared with the accuracy coefficient reference threshold value pre-set according to historical data; if the accuracy coefficient of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is greater than or equal to the accuracy coefficient reference threshold value, it means that the accuracy of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is high, and no warning signal is generated at this time, and the distinction result of the ultraviolet band radiation intensity under the multi-light source interference condition is divided into an accuracy distinction result; if the accuracy coefficient of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is less than the accuracy coefficient reference threshold value, it means that the accuracy of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is low, and a warning signal is generated at this time, and the distinction result of the ultraviolet band radiation intensity under the multi-light source interference condition is divided into an inaccuracy distinction result.

[0019] Preferably, in S4, when the discrimination accuracy is low, the environmental factor compensation is performed on the ultraviolet measurement result by combining the real-time data of the temperature and humidity sensors and utilizing the established nonlinear model of temperature, humidity and ultraviolet sensor response, specifically:

[0020] When the accuracy of distinguishing the intensity of UV radiation is low, the changes in ambient temperature and humidity affect the response of the UV sensor, and the measurement results need to be corrected through a compensation model. The initial measurement value S output by the UV sensor measuredIt is susceptible to the influence of temperature and humidity, and its expression is: S measured =S true +ΔS T +ΔS H ; S measured is the original measurement value of the sensor, S true is the actual intensity of ultraviolet rays in the environment, ΔS T is the effect of temperature on sensor response, ΔS H is the effect of humidity on sensor response; in order to obtain S true , it is necessary to T and ΔS H To compensate, the effect of temperature on sensor output is described using a nonlinear model, expressed as: ΔS T =k T (TT ref )+α T (TT ref ) 2 ; T is the current ambient temperature, T ref is the reference temperature, k T is the linear coefficient of temperature, α T is the nonlinear influence coefficient of temperature;

[0021] The effect of humidity on the sensor output is described as: ΔS H =k H (HH ref )+α H (HH ref ) 2 ; Where H is the current ambient humidity, H ref is the reference humidity, k H is the linear coefficient of humidity, α H is the nonlinear influence coefficient of humidity.

[0022] Preferably, the actual UV intensity S is calculated by combining nonlinear compensation of temperature and humidity. true , the expression is: S true =S measured -(ΔS T +ΔS H ); the effects of temperature and humidity are corrected through each compensation value.

[0023] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0024] 1. The present invention combines a photoelectric detector with a multi-band filter to subdivide the ultraviolet signal; then, by extracting the spectral resolution deviation value and the signal-to-noise ratio anomaly value, the multi-light source interference is effectively evaluated and dynamically adjusted. In view of the low accuracy of differentiation, the present invention introduces temperature and humidity sensors, and uses a nonlinear compensation model to correct the influence of environmental interference on the measurement results in real time, which significantly improves the stability and accuracy of the measurement.

[0025] 2. The present invention uses a low-power wireless communication module (such as Bluetooth low energy or LoRa) to achieve convenient transmission of measurement data, supports stable operation of the device in long-term portable use scenarios, and is suitable for applications in multiple fields such as environmental monitoring, medical health, and industrial production. Compared with traditional measurement methods, the present invention has the characteristics of high precision, multi-function and low power consumption, provides comprehensive technical support for ultraviolet radiation measurement technology, and helps to broaden its practical value in various application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0027] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] For examples, see Figure 1 As shown, the ultraviolet radiation measurement method described in this embodiment includes the following steps:

[0030] S1: Receive ultraviolet radiation in the environment using a photodetector with a wide spectral response range and generate a corresponding electrical signal;

[0031] S2: subdividing the ultraviolet radiation into bands through a multi-band filter to obtain the radiation intensity of the UVA, UVB and UVC bands respectively;

[0032] S3: Extract the spectral resolution deviation and signal-to-noise ratio anomaly in the multi-band signal to evaluate the accuracy of UV band radiation intensity distinction under multi-light source interference conditions;

[0033] S4: When the discrimination accuracy is low, the real-time data of the temperature and humidity sensors are combined, and the established nonlinear model of temperature, humidity and UV sensor response is used to compensate the UV measurement results for environmental factors;

[0034] S5: Transmitting the processed ultraviolet radiation intensity data to an external device via a low-power wireless communication module, wherein the wireless communication module is a Bluetooth low-power module or a LoRa module to support long-term portable use of the device.

[0035] Among them, in S1, a photoelectric detector with a wide spectral response range is used to receive ultraviolet radiation in the environment and generate a corresponding electrical signal, specifically:

[0036] A photodetector is a device that converts light signals (such as ultraviolet radiation) into electrical signals. Its working principle is based on the photoelectric effect or photovoltaic effect. Photoelectric effect: When ultraviolet photons hit the detector material, electrons are released, which form a current or voltage signal. Photovoltaic effect: When ultraviolet light is irradiated, electron-hole pairs are generated inside the semiconductor, which in turn forms a photocurrent.

[0037] A wide spectral response range means that the photodetector can respond to multiple UV bands (UVA, UVB, UVC). To achieve this feature, materials with high UV sensitivity are usually selected: Silicon (Si) detectors: common and low cost, sensitive to UVA and some UVB, but weak response to UVC. Gallium nitride (GaN) detectors: have a wide band gap, especially suitable for detecting UVB and UVC bands, and stable performance in high temperature environments. Zinc oxide (ZnO) or diamond detectors: sensitive to the UVC band, strong anti-interference ability, suitable for extreme environments. The choice of these materials and the design of the detector directly determine the efficiency and band range of UV measurement.

[0038] Ultraviolet radiation in the environment enters the photosensitive area of ​​the photodetector, and some wavelengths of ultraviolet light are absorbed by the detector material. The photosensitive area of ​​the detector is usually coated with an anti-reflection coating to minimize light loss and increase absorption. When ultraviolet photons are absorbed, their energy causes electrons to jump from the valence band of the detector material to the conduction band (photoelectric effect or photovoltaic effect). This process produces electron-hole pairs, and these charged particles are separated by the built-in electric field or external bias voltage to form a current or voltage signal. Broad-spectrum detectors can respond to ultraviolet light in different bands, and the intensity of the generated electrical signal is positively correlated with the intensity of ultraviolet radiation. Response to the UVA band: The signal is usually strong because UVA has lower energy but higher radiation intensity. Response to the UVB and UVC bands: The signal is weaker, but its energy is higher, and the sensor requires highly sensitive materials to accurately capture it.

[0039] In order to ensure that the generated electrical signal can accurately reflect the characteristics of ultraviolet radiation, the signal needs to be processed and optimized: the weak electrical signal is amplified for subsequent processing. The background noise (such as thermal noise or multi-light source interference) is suppressed by filtering circuits or algorithms. The signal components of UVA, UVB and UVC are distinguished by using multi-band filters or spectroscopic elements.

[0040] S2: The ultraviolet radiation is subdivided into bands through a multi-band filter to obtain the radiation intensity of the UVA, UVB and UVC bands respectively.

[0041] A multi-band filter is an optical element that selectively transmits or blocks light based on wavelength. Through optical effects such as interference, absorption or diffraction, the filter allows only specific wavelengths of light to pass through, while filtering out other wavelengths. The UV radiation entering the detector is divided into three bands: UVA (315–400nm), UVB (280–315nm) and UVC (100–280nm).

[0042] In order to effectively subdivide the UV band, filters are usually designed as follows: Each filter focuses on a narrow band range, such as UVA, UVB or UVC, with high transmittance and steep cut-off edges to avoid signal overlap between bands. Filters are constructed using multi-layer dielectric films (such as silicon dioxide and calcium fluoride), and precise wavelength separation is achieved by optimizing the film thickness and number of layers. Multiple narrow-band filters are integrated into a single filter component to simultaneously subdivide the UV radiation band.

[0043] Ultraviolet radiation (including UVA, UVB and UVC) in the environment passes through the photosensitive area of ​​the photodetector. The filters divide the full-spectrum ultraviolet radiation into three bands: UVA, UVB and UVC according to the order of the bands: UVA filter: transmits light waves of 315-400nm and blocks radiation of other wavelengths. UVB filter: transmits light waves of 280-315nm and blocks radiation of other wavelengths. UVC filter: transmits light waves of 100-280nm and blocks radiation of other wavelengths. The intensity of the light signal after each filter corresponds to the intensity of ultraviolet radiation in the corresponding band. The banded ultraviolet radiation passes through the filter and reaches the corresponding detector. Each detector independently captures the signal of a band, thereby achieving accurate separation of the intensity of UVA, UVB and UVC.

[0044] S3: Extract the spectral resolution deviation value and signal-to-noise ratio anomaly value in the multi-band signal to evaluate the accuracy of UV band radiation intensity distinction under multi-light source interference conditions.

[0045] Extracting spectral resolution deviation values ​​and signal-to-noise ratio anomalies from multi-band signals can accurately evaluate the device's ability to distinguish the radiation intensity of ultraviolet bands (UVA, UVB, UVC) under multi-light source interference conditions. By monitoring the spectral resolution deviation value, it is possible to quantify changes in the accuracy of band separation by filters or detectors, such as identifying overlap or offset in wavelength ranges. This analysis method helps to discover possible sources of error in equipment in complex optical environments and guide the optimization of filter design or detector calibration solutions, thereby improving overall measurement accuracy.

[0046] The extraction of signal-to-noise ratio outliers can help evaluate the impact of multi-light source interference (such as visible light or infrared light) on the target UV signal. A decrease in the signal-to-noise ratio usually indicates that the noise signal significantly interferes with the UV signal. By locating the outliers, the characteristics of the interfering light source and its mechanism of action can be clarified. This evaluation method helps to select better optical isolation technology (such as enhancing the blocking effect of filters) and signal processing algorithms (such as digital filtering), thereby ensuring that the measurement equipment can reliably distinguish the radiation intensity of each UV band even in complex environments.

[0047] Each signal corresponds to the total signal value S of a band clean , including the cumulative signal values ​​within the three bands of UVA, UVB and UVC. In each wide band range (for example, UVA band 315-400nm), 3 or 5 narrow-band filters are added, and each narrow-band filter covers a narrower wavelength range (for example, ±10nm). The signal value transmitted through the narrow-band filter is used to obtain the signal S at multiple subdivided wavelengths in the band. clean (λ).

[0048] Case of 3 narrow-band filters: Collect the signal values ​​of the central wavelength and the wavelength range on both sides symmetrically, forming 3 sampling points: Indicates the peak wavelength λ peak , the strength value of the net signal;

[0049] In the case of 5 narrow-band filters: the signal values ​​of the central wavelength and more wavelength ranges on both sides are collected to form 5 sampling points:

[0050] Based on the multiple signal values ​​obtained by the narrowband filter, the spectral distribution curve in the band is reconstructed by interpolation or fitting methods (such as Gaussian fitting). The actual spectral center wavelength λ is determined by the distribution shape of the curve. actual ; According to the filter design parameters, the ideal spectral center wavelength λ of the recording band ideal , and the actual spectrum center wavelength λ actual Compare with the ideal spectrum center wavelength and calculate the spectral resolution deviation value. The expression is: MK = λ actual -λ ideal ; Among them, MK is the spectral resolution deviation value, which is used to reflect the degree of deviation in the wavelength direction.

[0051] When the spectral resolution deviation value is larger, it means that there is a significant deviation between the actual measured spectral center wavelength and the ideal center wavelength of the filter design. This deviation may be caused by multi-light source interference, filter performance degradation, or insufficient detector sensitivity, which directly reflects the reduced accuracy of the equipment in multi-band separation. Too large a deviation value will lead to overlapping or confusion of band signals, making the radiation intensity measurement of UVA, UVB, and UVC inaccurate, affecting the reliability of the results. In this case, it is necessary to optimize the filter performance or introduce more advanced signal processing algorithms to compensate for the impact of interference.

[0052] On the contrary, when the spectral resolution deviation value is close to zero (very small), it means that the actual spectral center wavelength is highly consistent with the ideal value, and the equipment can accurately distinguish the radiation intensity of different ultraviolet bands. In this case, the synergy between the detector and the filter is better, and the influence of multi-light source interference on the measurement results is effectively suppressed. This means that the equipment has high band resolution and anti-interference performance in complex environments, providing technical guarantee for the accurate measurement of ultraviolet radiation. Therefore, the size of the deviation value can be directly used as an evaluation criterion for the resolution accuracy of the measurement system.

[0053] Get the original signal S from the detector raw (t), contains the target signal and the noise component, and the net signal is separated by bandpass filtering, and the expression is: S signal (t) = S raw(t)-N(t); where N(t) is the noise signal, and its power P is calculated by sampling the variance of the noise signal N(t) noise , the expression is: Where B is the time period of signal measurement, that is, the total time the signal is collected. The net signal is processed and the signal power P is calculated. signal , the expression is: The signal-to-noise ratio (SNR) is calculated using the power of the signal and the noise, as follows: Compare the actual measured signal-to-noise ratio (SNR) measured and the theoretical expected value SNR expected , calculate the signal-to-noise ratio abnormal value, the expression is: MY = SNR measured -SNR expected ; Where MY is the signal-to-noise ratio outlier.

[0054] When the signal-to-noise ratio outlier is larger (deviates more from the expected value, especially decreases significantly), it means that the measurement system cannot effectively suppress noise under the condition of multi-light source interference, and the ability to distinguish the target signal decreases. The increase in outliers means that the noise component may interfere with the net signal, resulting in the inability to accurately extract the radiation intensity of UVA, UVB, and UVC, especially in complex environments. Band signal confusion is more likely to occur. This situation reflects the system's high sensitivity to interference, and it is necessary to further optimize the filtering technology, improve the detector sensitivity, or enhance the optical isolation capability to improve the measurement accuracy.

[0055] On the contrary, when the signal-to-noise ratio outlier value is smaller (close to zero), it means that the actual signal-to-noise ratio is basically consistent with the expected value, and the measurement system has a strong ability to distinguish the radiation intensity of the ultraviolet band. In this case, the system can effectively suppress background noise, retain the integrity of the target signal, and accurately distinguish the radiation intensity of UVA, UVB and UVC even under multi-light source interference conditions. This reflects that the system has good anti-interference performance and high signal processing accuracy, providing reliable guarantee for ultraviolet measurement in complex environments.

[0056] The spectral resolution deviation value and the signal-to-noise ratio anomaly value are normalized, and the accuracy coefficient of distinguishing the radiation intensity of the ultraviolet band under the condition of multi-light source interference is calculated based on the normalized spectral resolution deviation value and the signal-to-noise ratio anomaly value.

[0057] For example, the present invention can use the following formula to calculate the accuracy coefficient of ultraviolet band radiation intensity distinction under multi-light source interference conditions, and the calculation expression is: Where LK is the accuracy coefficient of distinguishing the radiation intensity of the ultraviolet band under the condition of multi-light source interference, MK is the spectral resolution deviation value, MY is the signal-to-noise ratio anomaly value, a1 and a2 are the proportional coefficients of the spectral resolution deviation value and the signal-to-noise ratio anomaly value, and a2>a1>0.

[0058] The obtained accuracy coefficient of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is compared with the accuracy coefficient reference threshold value pre-set according to historical data. If the accuracy coefficient of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is greater than or equal to the accuracy coefficient reference threshold value, it means that the accuracy of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is high. At this time, no warning signal is generated, and the distinction result of the ultraviolet band radiation intensity under the multi-light source interference condition is classified as an accuracy distinction result; if the accuracy coefficient of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is less than the accuracy coefficient reference threshold value, it means that the accuracy of the ultraviolet band radiation intensity distinction under the multi-light source interference condition is low. At this time, a warning signal is generated, and the distinction result of the ultraviolet band radiation intensity under the multi-light source interference condition is classified as an inaccuracy distinction result.

[0059] S4: When the discrimination accuracy is low, the real-time data of the temperature and humidity sensors are combined and the established nonlinear model of temperature, humidity and UV sensor response is used to compensate the UV measurement results for environmental factors.

[0060] When the accuracy of distinguishing the intensity of UV radiation is low, the change of ambient temperature and humidity may affect the response of the UV sensor, so the measurement result needs to be corrected through the compensation model. measured Usually affected by temperature and humidity, its expression is: S measured =S true +ΔS T +ΔS H ; S measured is the original measurement value of the sensor, S true is the actual intensity of ultraviolet rays in the environment (true value), ΔS T is the effect of temperature on sensor response, ΔS H is the effect of humidity on the sensor response. In order to obtain S true , it is necessary to T and ΔS H To compensate, the effect of temperature on sensor output is described using a nonlinear model, expressed as: ΔS T =k T (TT ref )+α T (TT ref ) 2 ; T is the current ambient temperature, Tref is the reference temperature (the standard temperature at which the sensor is calibrated), k T is the temperature linear coefficient (the dependence of sensor sensitivity on temperature), α T is the nonlinear influence coefficient of temperature (higher-order temperature effect).

[0061] The effect of humidity on sensor output can also be described by a nonlinear model: ΔS H =k H (HH ref )+α H (HH ref ) 2 ; Where H is the current ambient humidity, H ref is the reference humidity (the standard humidity at which the sensor is calibrated), k H is the linear coefficient of humidity, α H is the nonlinear influence coefficient of humidity. Combining the nonlinear compensation of temperature and humidity, the actual UV intensity S is calculated. true , the expression is: S true =S measured -(ΔS T +ΔS H ); Each compensation value corrects the effects of temperature and humidity respectively.

[0062] k T , α T , k H , α H The specific value of T is obtained through experimental calibration. These parameters are usually fitted based on the response curve of the sensor at different temperatures and humidity. ref and H ref These are the reference conditions for the sensor when it is calibrated, such as 25°C and 50% humidity.

[0063] Correction for temperature effects includes: Identification of temperature changes: The temperature sensor monitors the current ambient temperature in real time and compares it with the reference operating temperature of the UV sensor. Temperature disturbance analysis: Based on the response model of the UV sensor, identify the specific effects of temperature increases or decreases on the sensor output, such as changes in sensor sensitivity or fluctuations in bias current. Correction method: When the ambient temperature deviates from the reference temperature, the temperature response characteristics recorded in the sensor calibration data are used to deduct the measurement deviation caused by temperature changes as a compensation value. In high or low temperature conditions, the gain or reference value of the sensor signal is dynamically adjusted to eliminate nonlinear errors caused by temperature.

[0064] Correction for humidity effects includes: Monitoring humidity levels: The humidity sensor collects ambient humidity data in real time and compares it with the reference operating humidity of the UV sensor. Humidity interference analysis: Humidity changes may affect the optical or electronic properties of the UV sensor through surface adsorption or changes in material properties, such as causing decreased sensitivity or increased noise. Correction method: Based on the real-time change in humidity, refer to the deviation range recorded in the humidity response model to determine the specific impact of humidity on the measured value. Use the preset humidity compensation value to deduct the measurement deviation caused by humidity changes from the raw data, or compensate for the adverse effects of humidity by adjusting the detector's baseline signal level.

[0065] The coordinated correction of temperature and humidity includes: Comprehensive impact analysis: When temperature and humidity change at the same time, coordinated interference may occur, such as an increase in humidity causing an intensified temperature effect. In this case, the system combines the real-time data of the two sensors, evaluates the intensity of the coordinated impact, and searches for corresponding compensation strategies in the model. Dynamic correction: For this coordinated impact, the correction process needs to consider the superposition effect of the two compensation values ​​and dynamically adjust the overall output signal of the sensor.

[0066] The corrected UV measurement results are closer to the actual radiation intensity, eliminating the influence of temperature and humidity interference on the band intensity distinction. This real-time correction mechanism ensures that the device can maintain high measurement accuracy and stability in complex environments (such as high temperature, high humidity or frequently changing scenes).

[0067] S5: Transmitting the processed ultraviolet radiation intensity data to an external device via a low-power wireless communication module, wherein the wireless communication module is a Bluetooth low-power module or a LoRa module to support long-term portable use of the device.

[0068] The UV sensor collects the radiation intensity signals of UVA, UVB and UVC, and after the band processing by the filter, it combines the signal processing algorithm to correct the interference and compensate for environmental factors (such as temperature and humidity) to generate accurate radiation intensity data. The processed UV radiation intensity data (such as radiation value, band category, timestamp, etc.) is packaged into small data packets to adapt to the data transmission requirements of the wireless communication module.

[0069] Bluetooth Low Energy (BLE) module: suitable for short-distance transmission (usually within 10-50 meters), fast transmission speed (up to 1Mbps). It consumes very low power and supports intermittent data transmission, which is particularly suitable for wearable devices or portable sensor applications. Data is sent to mobile phones, tablets or other Bluetooth devices through BLE standard protocols (such as GATT services) for users to view or record in real time.

[0070] LoRa module: suitable for long-distance transmission (up to several kilometers to ten kilometers), especially in outdoor or low-power IoT applications. The data transmission rate is low (usually 0.3-50kbps), but the extremely low power consumption and wide coverage make up for the rate limitation. The radiation intensity data is transmitted to the cloud server or terminal device through the LoRa gateway for centralized management or remote monitoring.

[0071] When the system starts, the low-power communication module is initialized and the wireless network parameters (such as Bluetooth pairing, LoRa channel) are configured. Ensure that the module establishes a stable connection with the target device (such as a mobile phone or gateway). The processed UV radiation intensity data is sent in a timed or event-driven manner. For example: Timed mode: send data every fixed time (such as 1 minute). Event-driven: trigger the transmission immediately when the radiation intensity exceeds the preset threshold. The data is divided into small data packets and transmitted through the wireless protocol to ensure fast and reliable arrival at the target device.

[0072] The wireless module enters low-power mode when inactive and wakes up only for a short time during data transmission to maximize the device's battery life. The communication module dynamically adjusts the transmission power. For example, the Bluetooth low-power module adjusts the transmission power according to the signal strength. The LoRa module selects the appropriate transmission power and data rate according to the distance.

[0073] The responses of external devices include: Bluetooth terminal devices: such as smartphones or tablets, which receive UV data and display real-time band radiation intensity and cumulative dose. Users can set alarm thresholds or analyze historical data through mobile applications. LoRa gateways: collect data from multiple sensor devices and transmit them to cloud servers. Users can remotely monitor and manage UV radiation data through web pages or applications.

[0074] Bluetooth low energy modules enable convenient close-range real-time monitoring, suitable for personal protective equipment such as wristbands or portable UV detectors. They support interconnection with mobile phones without the need for additional hardware gateways. LoRa modules support long-distance, multi-device transmission, suitable for UV data collection in environmental monitoring stations, industrial equipment or agricultural scenarios. The device can run for a long time without frequent battery replacement.

[0075] In this embodiment, by using a photodetector with a wide spectral response range to receive ultraviolet radiation in the environment and generate a corresponding electrical signal, the ultraviolet radiation is subdivided into bands in combination with a multi-band filter, and the radiation intensity of the UVA, UVB and UVC bands is obtained respectively. The spectral resolution deviation value and the signal-to-noise ratio anomaly in the multi-band signal are extracted to evaluate the accuracy of band discrimination under multi-light source interference conditions. When the discrimination accuracy is low, the measurement results are compensated for environmental factors using the established nonlinear model in combination with the real-time data of the temperature and humidity sensors to improve the measurement accuracy. Finally, the processed ultraviolet radiation intensity data is transmitted to an external device through a Bluetooth low energy (BLE) module or a LoRa module, supporting long-term portable use of the device and realizing real-time monitoring and data management.

[0076] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0077] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0078] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the objects associated with each other are in an "or" relationship, but it may also indicate an "and / or" relationship, which can be understood by referring to the context. A person of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this article can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0079] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for measuring ultraviolet radiation, characterized in that: The following steps are involved: S1: Receive ultraviolet radiation in the environment using a photodetector with a wide spectral response range and generate a corresponding electrical signal; S2: subdividing the ultraviolet radiation into bands through a multi-band filter to obtain the radiation intensity of the UVA, UVB and UVC bands respectively; S3: Extract the spectral resolution deviation and signal-to-noise ratio anomaly in the multi-band signal to evaluate the accuracy of UV band radiation intensity distinction under multi-light source interference conditions; S4: When the discrimination accuracy is low, the real-time data of the temperature and humidity sensors are combined, and the established nonlinear model of temperature, humidity and UV sensor response is used to compensate the UV measurement results for environmental factors; S5: Transmitting the processed ultraviolet radiation intensity data to an external device via a low-power wireless communication module, wherein the wireless communication module is a Bluetooth low-power module or a LoRa module to support long-term portable use of the device.

2. A method for measuring ultraviolet radiation according to claim 1, characterized in that: In S3, the spectral resolution deviation value and the signal-to-noise ratio anomaly value in the multi-band signal are extracted. The method for obtaining the spectral resolution deviation value is: Each signal corresponds to the total signal value S of a band clean , including the cumulative signal values ​​within the three bands of UVA, UVB and UVC. In each wide band range, 3 or 5 narrow-band filters are added, each narrow-band filter covers a narrower wavelength range. The signal value transmitted through the narrow-band filter is used to obtain the signal S at multiple subdivided wavelengths in the band. clean (λ); Case of 3 narrow-band filters: Collect the signal values ​​of the central wavelength and the wavelength range on both sides symmetrically, forming 3 sampling points: Indicates the peak wavelength λ peak , the strength value of the net signal; In the case of 5 narrow-band filters: the signal values ​​of the central wavelength and the wavelength range on both sides symmetrically are collected to form 5 sampling points: Based on the multiple signal values ​​obtained by the narrowband filter, the spectral distribution curve within the band is reconstructed, and the actual spectral center wavelength λ is determined by the distribution shape of the curve. actual ; According to the filter design parameters, the ideal spectral center wavelength λ of the recording band ideal , and the actual spectrum center wavelength λ actual Compare with the ideal spectrum center wavelength and calculate the spectral resolution deviation value. The expression is: MK = λ actual -λ ideal ; Where MK is the spectral resolution deviation value.

3. A method for measuring ultraviolet radiation according to claim 2, characterized in that: In S3, the spectral resolution deviation value and signal-to-noise ratio anomaly value in the multi-band signal are extracted to evaluate the accuracy of ultraviolet band radiation intensity distinction under multi-light source interference conditions. The signal-to-noise ratio anomaly value is obtained by: Get the original signal S from the detector raw (t), contains the target signal and the noise component, and the net signal is separated by bandpass filtering, and the expression is: S signal (t) = S raw (t)-N(t); where N(t) is the noise signal, and its power P is calculated by sampling the variance of the noise signal N(t) noise , the expression is: Where B is the time period of signal measurement, that is, the total time the signal is collected. The net signal is processed and the signal power P is calculated. signal , the expression is: The signal-to-noise ratio (SNR) is calculated using the power of the signal and the noise, as follows: Compare the actual measured signal-to-noise ratio (SNR) measured and the theoretical expected value SNR expected , calculate the signal-to-noise ratio abnormal value, the expression is: MY = SNR measured -SNR expected ; Where MY is the signal-to-noise ratio outlier.

4. A method for measuring ultraviolet radiation according to claim 3, characterized in that: In S3, the accuracy of distinguishing the radiation intensity of the ultraviolet band under the condition of multiple light source interference is evaluated, specifically: the spectral resolution deviation value and the signal-to-noise ratio anomaly value are normalized, and the accuracy coefficient of distinguishing the radiation intensity of the ultraviolet band under the condition of multiple light source interference is calculated through the normalized spectral resolution deviation value and the signal-to-noise ratio anomaly value.

5. A method for measuring ultraviolet radiation according to claim 4, characterized in that: In S3, the obtained accuracy coefficient of ultraviolet band radiation intensity distinction under multi-light source interference conditions is compared with the accuracy coefficient reference threshold value pre-set according to historical data. If the accuracy coefficient of ultraviolet band radiation intensity distinction under multi-light source interference conditions is greater than or equal to the accuracy coefficient reference threshold value, it means that the accuracy of ultraviolet band radiation intensity distinction under multi-light source interference conditions is high. At this time, no warning signal is generated, and the distinction result of ultraviolet band radiation intensity under multi-light source interference conditions is classified as an accuracy distinction result. If the accuracy coefficient of the ultraviolet band radiation intensity distinction under the condition of multiple light source interference is less than the accuracy coefficient reference threshold, it means that the accuracy of the ultraviolet band radiation intensity distinction under the condition of multiple light source interference is low. At this time, a warning signal is generated, and the distinction result of the ultraviolet band radiation intensity under the condition of multiple light source interference is classified as an inaccurate distinction result.

6. The method for measuring ultraviolet radiation according to claim 1, characterized in that: In S4, when the discrimination accuracy is low, the real-time data of the temperature and humidity sensors are combined, and the established nonlinear model of temperature, humidity and UV sensor response is used to compensate the UV measurement results for environmental factors, specifically: When the accuracy of distinguishing the intensity of UV radiation is low, the changes in ambient temperature and humidity affect the response of the UV sensor, and the measurement results need to be corrected through a compensation model. The initial measurement value S output by the UV sensor measured It is susceptible to the influence of temperature and humidity, and its expression is: S measured =S true +ΔS T +ΔS H ; S measured is the original measurement value of the sensor, S true is the actual intensity of ultraviolet rays in the environment, ΔS T is the effect of temperature on sensor response, ΔS H is the effect of humidity on sensor response; in order to obtain S true , it is necessary to T and ΔS H To compensate, the effect of temperature on sensor output is described using a nonlinear model, expressed as: ΔS T =k T (TT ref )+α T (TT ref ) 2 ; T is the current ambient temperature, T ref is the reference temperature, k T is the linear coefficient of temperature, α T is the nonlinear influence coefficient of temperature; The effect of humidity on the sensor output is described as: ΔS H =k H (HH ref )+α H (HH ref ) 2 ; Where H is the current ambient humidity, H ref is the reference humidity, k H is the linear coefficient of humidity, α H is the nonlinear influence coefficient of humidity.

7. A method for measuring ultraviolet radiation according to claim 6, characterized in that: Combined with nonlinear compensation of temperature and humidity, the actual UV intensity S is calculated. true , the expression is: S true =S measured -(ΔS T +ΔS H ); the effects of temperature and humidity are corrected through each compensation value.

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