Radiation measurement precision improvement method based on pyroelectric infrared sensor

Abstract

The invention discloses a radiation measurement precision improvement method based on a pyroelectric infrared sensor, and the method comprises the steps: designing a noise reduction circuit, filtering a voltage signal through a series capacitor, shielding a DC signal, inputting the voltage signal into a comparator, comparing the voltage signal with a set noise threshold value, if the voltage signal value is greater than the noise threshold value, outputting a high level by the comparator, and otherwise, outputting a low level; a single-chip microcomputer rising edge interruption application is triggered through a monostable trigger rising edge, A / D signal collection is carried out, if a voltage signal value is smaller than a noise threshold value, a comparator outputs a low level, no processing is carried out, a differentiating circuit is arranged, and the high level output duration of the monostable trigger is controlled by adjusting the size of a resistor and a capacitor; an A / D sampling algorithm is optimized, decimal numbers are abandoned in a sampling array in a period, large numbers are reserved, and the maximum value in the array is obtained, so that the maximum amplitude of the electric signals is obtained, and errors are reduced; a black body standard source is used for calibration, test data are calibrated, and the linear relation is corrected.

Description

Technical Field

[0001] The invention belongs to the technical field of radiation measurement of pyroelectric infrared sensors, and in particular relates to a method for improving the radiation measurement accuracy based on pyroelectric infrared sensors. Background Art

[0002] In recent years, the demand for infrared sensors has been increasing in countries around the world. The rapid development of the infrared detector manufacturing industry has greatly promoted the application of infrared radiation characteristic measurement technology. Pyroelectric infrared sensors use the temperature change of the component itself caused by the thermal radiation of infrared radiation to detect, and are sensitive to infrared radiation in the range of 8-14μm. However, the precision detection of infrared signals by pyroelectric infrared sensors is easily affected by factors such as circuit noise, optical background noise, and environmental electromagnetic interference, which affects the sensitivity of the entire system and may even cause false signals. It is necessary to reduce noise interference and improve system reliability, and improve the high-precision pyroelectric infrared sensor radiation measurement technology.

[0003] There are many infrared radiation measurement technologies based on pyroelectric sensors at present, but they are still slightly lacking in accuracy requirements. Most of them use hardware circuit filtering, the noise filtering effect is not significant, and the signal-to-noise ratio is not high. The A / D sampling software uses a bubble sort method, which cannot achieve the best effect and affects the accuracy. In addition, the structure of infrared radiation measurement technology is relatively complex and the cost is relatively high. Summary of the invention

[0004] When the pyroelectric infrared sensor is measuring radiation, the weak detection signal is easily disturbed by noise, the measurement signal acquisition value has errors, and the linear relationship of the data curve is poor. These factors will affect the accuracy of radiation measurement. In view of this problem, the present invention provides a method for improving the accuracy of radiation measurement based on a pyroelectric infrared sensor, which reduces noise through hardware circuit design, optimizes the A / D sampling data processing method to reduce the measurement value error, uses a black body standard source to calibrate data and calibrate processing, and improves the accuracy of infrared radiation measurement technology.

[0005] The present invention achieves this object through the following technical solutions:

[0006] A method for improving the radiation measurement accuracy based on a pyroelectric infrared sensor, comprising:

[0007] a) Design a noise reduction circuit, including a series capacitor, a comparator, a monostable trigger and a differential circuit. The series capacitor is connected to the comparator, the comparator is connected to the monostable trigger, the monostable trigger is connected to the differential circuit and the A / D sampling microcontroller respectively, the voltage signal is filtered by the series capacitor to shield the DC signal, and then input into the comparator to compare with the set noise threshold. If the voltage signal value is greater than the noise threshold, the comparator outputs a high level, and the rising edge of the monostable trigger is triggered to trigger the rising edge interrupt application of the microcontroller to collect the A / D signal. If the voltage signal value is less than the noise threshold, the comparator outputs a low level, and no processing will be performed, the invalid signal is filtered out, and only the valid signal is collected; the differential circuit controls the duration of the high level output of the monostable trigger by adjusting the size of the resistor and capacitor;

[0008] b) Optimize the A / D sampling algorithm, discard the small numbers and keep the large numbers in the sampling array within a cycle, obtain the maximum value in the array, and thus obtain the maximum amplitude of the electrical signal to reduce the error;

[0009] c) Use a blackbody standard source to calibrate the test data and correct the linear relationship.

[0010] Furthermore, the specific contents of optimizing the A / D sampling algorithm are as follows:

[0011] The array collected in one cycle is a i1 ~a in , the first element a i1 Assigned initial values ​​and perform the first round of comparison:

[0012] If a i1 >a i2 , then discard a i2 , compare a i1 with a i3 ;

[0013] If a i1 i2 , then let a i1 =a i2 , and then compare a i1 with a i3 ;

[0014] Until the n-1th round of comparison:

[0015] If a i1 >a in , then discard a in ;

[0016] If a i1 in , then let a i1 =a in ;

[0017] ​​The final output value of ai1 is the maximum value in the collected array.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The present invention can firstly effectively reduce noise interference through the hardware design of the noise reduction circuit; secondly, optimize the sampling data software processing algorithm to effectively reduce the data error; finally, use the black body standard source for calibration to effectively correct the linear relationship; the present invention can improve the infrared radiation measurement accuracy through the above technical scheme. In addition, the technical scheme of the present invention also has the advantages of simple structure, easy assembly and low cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0021] Figure 1 Schematic diagram of the noise reduction circuit structure according to an embodiment of the present invention;

[0022] Figure 2 This is a simulation signal input result diagram of the circuit simulation software of the embodiment of the present invention;

[0023] Figure 3 This is a diagram of simulation signal output results of the circuit simulation software according to an embodiment of the present invention;

[0024] Figure 4 The oscilloscope is a waveform diagram of a signal collected by an embodiment of the present invention;

[0025] Figure 5 This is a flow chart of the A / D sampling algorithm of the present invention;

[0026] Figure 6 The upper computer displays the data curve graph for sampling and taking values ​​using the bubble sort method;

[0027] Figure 7 The host computer displays a data curve graph using the A / D sampling value algorithm of the present invention;

[0028] Figure 8 This is the result diagram of fitting the non-standard heat source curve;

[0029] Fig. 9 This is the result of fitting the blackbody standard heat source curve. DETAILED DESCRIPTION

[0030] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to be able to fully convey the scope of the present invention to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0031] This patent aims to improve the accuracy of pyroelectric infrared sensor radiation measurement technology. The main measures include noise reduction circuit hardware design, A / D sampling algorithm optimization design, and data calibration.

[0032] 1. Noise reduction circuit hardware design

[0033] When the pyroelectric infrared sensor measures radiation, it outputs a weak electrical signal according to the change in temperature. If the signal is unstable due to noise interference, or even the valid signal is submerged in the noise, the poor signal-to-noise ratio will affect the signal quality and the measurement accuracy. It is necessary to suppress the noise and filter out the invalid signal.

[0034] The hardware circuit uses the invalid signal judgment method + rising edge differentiation method to filter out noise. The combination of the two filters out noise and retains valid signals. The noise reduction circuit structure is as follows Figure 1 shown.

[0035] The premise of the invalid signal judgment method is to set the noise threshold and compare the actual signal value with it. The threshold value can be set by adjusting the potentiometer according to the actual environment requirements. When the output voltage signal of the pyroelectric infrared sensor passes through the comparator MAX913, it is compared with the threshold to determine whether the signal is invalid. Before comparison, the voltage signal is filtered by the series capacitor, mainly filtering out the DC signal and eliminating the DC signal from entering.

[0036] The rising edge differential method mainly uses the rising edge to trigger the microcontroller to perform A / D sampling. If the voltage signal value is greater than the noise threshold, the comparator will output a high level, and through the rising edge trigger of the monostable trigger SN74LV221APW, the rising edge interrupt application of the microcontroller is triggered to start A / D signal collection. If the voltage signal value is less than the noise threshold, the comparator will output a low level and will not be processed. Invalid signals are filtered out and only valid signals are collected. The differential duration is t = RC. The duration can be changed by adjusting the resistance and capacitance. It must be controlled within a cycle time and must not exceed one cycle time.

[0037] The simulation signal input results using LTspice circuit simulation software are as follows Figure 2 The output is as shown in Figure 3As shown in the above simulation results, it can be seen that, assuming the noise threshold is 100mV, the potentiometer is adjusted to a voltage of 100mV; when U IN When >100mV, the comparator outputs a high level, and the rising edge triggers the microcontroller interrupt request to perform A / D sampling; when U IN When <100mV, the comparator outputs a low level, the microcontroller is not triggered, and A / D sampling is not performed, thus filtering out the noise interference signal.

[0038] 2. Optimization of A / D sampling algorithm

[0039] Infrared target radiation measurement can provide important characteristic information for target identification, including important characteristics such as target radiation illumination and radiation intensity. The radiation illumination measurement is obtained by collecting heat source signals through pyroelectric infrared sensors, and the radiation intensity is obtained based on the radiation illumination measurement value. The pyroelectric infrared sensor outputs a sine wave analog signal, and the oscilloscope collects the signal waveform. Figure 4 As shown:

[0040] For sine wave signals, the maximum amplitude is the value required to obtain the radiant illumination. How to obtain the maximum amplitude in one cycle of A / D sampling is crucial. If the obtained value deviation is large, it will affect the measurement accuracy. The software uses the traditional bubble sort method. If the cycle is 1ms, A / D sampling is obtained once every 10us, and a total of 100 times are obtained in one cycle. The 100 values ​​are an array. The 100 numbers in the array are compared and judged, and the maximum value is retained. However, the data curve using this method is not smooth and fluctuates.

[0041] Since the bubble sort compares the 100 numbers in the array one by one, starting from the first number in the array, the two adjacent numbers are compared in turn. If the first number is greater than the second number, their positions are swapped, otherwise the positions remain unchanged, and the second number is compared with the third number, and so on, until the last number. This will take a certain amount of time for the entire sorting process, which will affect the software processing timing and make the obtained values ​​unstable. The data curve displayed by the host computer of the bubble sort method is as follows Figure 6 Shown by the light blue line.

[0042] In the present invention, the first number a from the array i1 After assigning the initial value, it is compared with the following n numbers. If the following number is smaller than it, there is no need to exchange positions and the following decimal is discarded. Otherwise, the following large number is reassigned to it and it is finally assigned the maximum value.

[0043] Collection array a i1 ~a in The comparison process is as follows:

[0044] The first element a i1 Assigned initial values ​​and perform the first round of comparison:

[0045] If a i1 >a i2 , then discard a i2 , compare a i1 with a i3 ;

[0046] If a i1 i2 , then let a i1 =a i2 , and then compare a i1 with a i3 ;

[0047] Until the n-1th round of comparison:

[0048] If a i1 >a in , then discard a in ;

[0049] If a i1 in , then let a i1 =a in ;

[0050] The final output value of ai1 is the maximum value in the collected array.

[0051] When n is 100, the 100 numbers take the maximum value, array a i1 ~a i100 There are 100 elements in total, a i1 The first element is assigned an initial value, compared with the following numbers, the smaller one is discarded and the larger one is retained, and so on. The flow chart of the sampling algorithm of the present invention is as follows Figure 5 shown.

[0052] This comparison method reduces complexity, saves time, and improves efficiency. The obtained values ​​are more stable and accurate, and the accuracy of infrared radiation measurement is improved. The host computer displays the radiance data curve as a smooth straight line, which solves the problem of unstable data fluctuations. Figure 7 Shown by the light blue line.

[0053] 3. Data calibration

[0054] When measuring infrared target radiation in the field, the environment is uncontrolled and greatly affected by the external environment. Therefore, in order to improve the accuracy of radiation measurement, a blackbody standard heat source is used for calibration. Use a non-standard heat source and a blackbody standard heat source to perform tests, set different temperature levels, and record the collected data, as shown in the following table.

[0055] Table 1 Data record table of different heat sources

[0056] ​​

[0057] The non-standard heat source curve fitting results are as follows Figure 8 As shown, the fitting results of the blackbody standard heat source curve are as follows Fig. 9 shown.

[0058] The above test results show that the linear relationship of the non-standard heat source test data is slightly worse than that of the blackbody standard heat source test. Based on the blackbody standard heat source data curve, the software uses the calibration formula to correct the linear relationship so that the linear relationship of the test data reaches the blackbody source standard, thereby improving the accuracy of infrared radiation measurement.

[0059] The present invention has been described in detail above through embodiments, but the contents described are only exemplary embodiments of the present invention and cannot be considered to limit the scope of implementation of the present invention. The protection scope of the present invention is defined by the claims. Anyone who utilizes the technical solution described in the present invention, or a technician in the field, inspired by the technical solution of the present invention, designs a similar technical solution within the essence and protection scope of the present invention to achieve the above technical effects, or makes equal changes and improvements to the scope of application, shall still belong to the scope of protection covered by the patent of the present invention. It should be noted that in order to make a clear statement, the description of some components and processes that have no direct and obvious connection with the scope of protection of the present invention but are known to those skilled in the art are omitted in the description of the present invention.

Claims

1. A method for improving the radiation measurement accuracy based on pyroelectric infrared sensor, characterized in that: include: a) Design a noise reduction circuit, which includes a series capacitor, a comparator, a monostable trigger and a differential circuit. The series capacitor is connected to the comparator, the comparator is connected to the monostable trigger, the monostable trigger is connected to the differential circuit and the A / D sampling microcontroller respectively, the voltage signal is filtered by the series capacitor to shield the DC signal, and then input into the comparator to compare with the set noise threshold. If the voltage signal value is greater than the noise threshold, the comparator outputs a high level, and the rising edge of the monostable trigger is triggered to trigger the rising edge interrupt application of the microcontroller to collect the A / D signal. If the voltage signal value is less than the noise threshold, the comparator outputs a low level, and no processing will be performed, the invalid signal is filtered out, and only the valid signal is collected; the differential circuit controls the duration of the high level output of the monostable trigger by adjusting the size of the resistor and capacitor; b) Optimize the A / D sampling algorithm, discard the small numbers and keep the large numbers in the sampling array within a cycle, obtain the maximum value in the array, and thus obtain the maximum amplitude of the electrical signal to reduce the error; c) Use a blackbody standard source to calibrate the test data and correct the linear relationship.

2. The method for improving the radiation measurement accuracy based on a pyroelectric infrared sensor according to claim 1, characterized in that: The specific contents of optimizing the A / D sampling algorithm are as follows: The array collected in one cycle is a i1 ~a in , the first element a i1 Assigned initial values ​​and perform the first round of comparison: If a i1 >a i2 , then discard a i2 , compare a i1 with a i3 ; If a i1 i2 , then let a i1 =a i2 , and then compare a i1 with a i3 ;​ Until the n-1th round of comparison: If a i1 >a in , then discard a in ; If a i1 in , then let a i1 =a in ;​ The final output value of ai1 is the maximum value in the collected array.

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