A method for extending the measurement range of a spectral light field imaging temperature measurement system and an imaging device

Abstract

The application discloses a kind of spectral light field imaging temperature measurement system measurement range extension method and imaging device, spectral light field imaging temperature measurement system measurement range extension method includes: the response model of temperature measurement system spectral channel is established by blackbody furnace calibration experiment;Establish target function, and the established target function is optimized, and the attenuation piece transmittance of channel center wavelength is obtained. By obtaining the attenuation piece transmittance of center wavelength, the expansion of spectral light field imaging temperature measurement system measurement range is completed. The method of the application can be applicable to different spectral characteristics of temperature measurement object, combined with specified temperature measurement interval, by adjusting attenuation piece transmittance parameter, the consistency of the dynamic response of each channel is guaranteed, and the measurement range of temperature measurement system is widened.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of spectral light field imaging and radiation thermometry, and particularly relates to a measurement range expansion method of a spectral light field imaging thermometry system and an imaging device BACKGROUND

[0002] Incomplete combustion of hydrocarbon fuels not only reduces energy utilization efficiency, but also poses a serious threat to global warming and human health. Accurate temperature measurement not only helps to deepen the mechanism research of soot particle formation, but also provides a measurement basis for pollutant control of industrial combustion devices. The measurement method based on light field imaging technology can obtain the transmission process of light in three-dimensional space, and the distribution of physical parameters is reconstructed by establishing the coupling model between the optical parameters of soot, temperature and detected light intensity. In the actual process, the optical parameters of soot are often unknown. Therefore, this technology needs to couple spectral information to solve the physical parameters and temperature, which generally obtains the spectral information of three fixed wavebands Red (R), Green (G) and Blue (B) in the visible light band by coupling the Bayer filter at the detector pixel. However, in this way, the wide spectral channel is easy to cause the error of the detected light intensity value to increase, thereby affecting the reconstruction result, and the increase of the number of spectral channels of the sensor filter will cause serious aliasing effect, and the current manufacturing cost is high due to the limitation of the processing technology.

[0003] The temperature measurement system based on spectral light field imaging can effectively solve the problems of wide spectral channel and information redundancy in light field imaging. It has the advantages of flexible spectral channel selection, narrow channel range, clear space spectrum modulation relationship and simple reconstruction algorithm. The implementation is to insert a filter array in the main lens aperture plane, and convert the redundant light field information into spectral information. Therefore, the acquisition of spectral light field information can be completed by single exposure. However, in the temperature measurement process, the temperature measurement system has the problem of narrow channel response range. The main reason is that the spectral characteristics of the measured object and the spectral dynamic response of the sensor itself in the system lead to too large dynamic response difference between the radiant energy and the gray scale under different channels. After the gray scale of the high response channel is overexposed, the signal crosstalk produced will affect the channel with low response characteristics, thereby reducing the effective response range of the overall system, so that the spectral light field imaging thermometry system is difficult to cover the target temperature interval of the measured object, and the measurement range is narrowed. SUMMARY

[0004] In view of the narrow measurement range of the current spectral light field imaging thermometry system, the present application provides a measurement range expansion method of a spectral light field imaging thermometry system and an imaging device.

[0005] The solution of the present application to solve the technical problem is:

[0006] The application provides a measurement range expansion method of a spectral light field imaging temperature measurement system, and the method comprises the following steps:

[0007] A fiber spectrometer is used to collect the spectral characteristics of a target object, so that the emission peak wavelength in the combustion process of the target object is obtained.

[0008] In the response wavelength range of the temperature measurement system, the emission peak band generated in the combustion process of the target object is avoided, and the center wavelength λ of each channel is selected randomly under the condition that the center wavelength interval is 20-30 nm, and the number of channels is Channel.

[0009] A channel response model of the spectral light field imaging temperature measurement system is established through a blackbody furnace calibration experiment.

[0010]

[0011] In the formula, h1 and h2 are Planck constants, and h1 is 3.7148*10 -16 / (W·m 2 ), and h2 is 1.4388*10 -2 / (m·K); gray λ is the gray response of the sensor corresponding to the spectral channel; Δt is the exposure time of the imaging device, and the unit is ms; T λ,min is the blackbody furnace temperature corresponding to the gray response value of 2% FR of the channel under the exposure parameter in the shooting process of the target object, and the unit is K; T λ,max is the blackbody furnace temperature corresponding to the gray response value of 90% FR of the current channel, and the unit is K; FR represents full scale; Φ λ is the transmittance of the attenuation sheet with the center wavelength λ; Δλ is the half peak width of the spectral channel, and the unit is nm; E λ is the spectral radiation intensity of the channel with the center wavelength λ, and the unit is W / (m 3 ·sr); is the coefficient of the corresponding relationship formula of the specified channel, and the unit is J·s p-1 / (m 2 ·sr); b λ,Noise is the constant term of the relationship formula, and the unit is W / (m 2 ·sr); q is the highest degree of the relationship formula, and q≤4; M is the number of calibration points in the blackbody furnace experiment.

[0012] A target function F is established.

[0013]

[0014] In the formula, N is the number of particle dimensions, and the value is the number of channels except the reference channel, that is, N=Channel-1. is the theoretical value of the mth calibration point on the nth channel; is the theoretical value of the mth calibration point on the reference channel with the lowest response characteristic, and the decay rate of the channel with low response characteristic is 100% by default; M is the number of gray scale theoretical calculation points of the channel;

[0015] Optimizing the established objective function to obtain the transmittance Φ of the attenuation sheet with a center wavelength of λ λ .

[0016] Optimizing the established objective function to obtain the transmittance Φ of the attenuation sheet with a center wavelength of λ λ In the step, the particle swarm optimization algorithm is used to optimize the established objective function.

[0017] The method for optimizing the established objective function by using the particle swarm optimization algorithm, comprising:

[0018] setting the number of particle swarms Num, the dimension of particles N, the maximum value of particle position x max =1, the minimum value of particle position x min =0, the maximum value of particle velocity v max =0.005, the minimum value of particle velocity v min =0.0001, the maximum iteration step Loop max =1000, the precision iteration termination threshold ε1=10 -3 and the step iteration termination threshold ε2=10 -4 ;

[0019] randomly initializing the position of particles X=[x 1, ..., x i ..., x Num ], with a dimension of N×Num; x i is the current iteration position of the i th particle swarm, with a dimension of N×1; the velocity V=[v 1, ..., v i ..., v Num ], with a dimension of N×Num; v i is the current velocity of the i th particle swarm, with a dimension of N×1. According to the initialized position of all particles, the individual optimal position of the particle swarm is set; P=[p 1, ..., p i ..., p Num ], with a dimension of N×Num, and the global optimal position G=[g 1, ..., g j ..., g N ] Τ , with a dimension of N×1; p Num is the individual optimal position of the Num th particle swarm, with a dimension of N×1.

[0020] x i = x min · E + (x max - x min ) · r x

[0021] v i = v min · E + (v max - v min ) · r v

[0022] G = p

[0023] wherein r x is a random number for initial assignment of particle position, the element value interval is [0, 1], and the dimension is N x 1; r v is a random number for initial assignment of particle velocity, the element value interval is [0, 1], and the dimension is N x 1; E is an all-1 vector, and the dimension is N x 1;

[0024] The position of the particle is updated, the target function value F corresponding to the particle is calculated, and the individual optimal and global optimal values are updated:

[0025] v i = ω x v i + c1 x r1 x (p i - x i ) + c2 x r2 x (g i - x i )

[0026] x i = x i + v i

[0027] p i = x i if F(x i ) < F(p i )

[0028] G = p i if F(p i ) < F(G)

[0029] wherein ω is an inertia weight, selected as 0.65; c1 and c2 are acceleration constants, set as 1.48, representing the degree of convergence of the particle to the individual optimal and global optimal positions; r1 and r2 are diagonal matrices composed of updated random numbers, the element interval is [0, 1],

[0030] The position of each particle in the updated particle swarm is checked to prevent the position from exceeding the boundary set by the algorithm, and if the position exceeds the boundary, the position of each particle is trimmed within the boundary:

[0031] x i =max(x min ×E,min(x i ,x max ×E))

[0032] It is judged whether the current loop number reaches the maximum iteration number, or the global optimal value is lower than the set threshold value epsilon 1 (i.e., F(G) <= epsilon 1), or the reduction amplitude of the global optimal value is lower than the set threshold value epsilon 2 (i.e., Delta F(G) <= epsilon 2); if one of the three judgment conditions is met, the loop is exited, otherwise the current loop number is increased by one, and the position of each particle is updated, and the next loop is entered;

[0033] The global optimal solution vector G obtained by the algorithm and the corresponding spectral channel transmittance Phi are one-to-one corresponding. The dimension is N*1, wherein the channel center wavelengths are sorted in ascending order, and the transmittances are sequentially corresponding, i.e., lambda 1 <... < lambda j <... < lambda N , and the corresponding formula is:

[0034] The number of particle swarms is set to Num = 300, the particle dimension N = channel-1, the maximum particle position x max = 1, x min = 0, v max = 0.005, v min = 0.0001, the maximum iteration step Loop max = 1000, the iteration termination threshold epsilon 1 = 10 -3 and epsilon 2 = 10 -4 .

[0035] The inertia weight omega is selected as 0.65.

[0036] The acceleration constants c1 and c2 are set to 1.48.

[0037] The application also provides an imaging device corresponding to the spectral light field imaging temperature measurement system, which comprises a main lens, a microlens array and a sensor, the main lens and the microlens array jointly image an object on the sensor, and an optical filter attenuation sheet array for expanding the temperature measurement range is arranged at the diaphragm of the main lens, and the array element of the optical filter attenuation sheet array has a different center wavelength filter part for transmitting and an attenuation part for attenuating different center wavelengths.

[0038] The transmittance of the filter-attenuation array attenuation part is determined based on the spectral light field imaging temperature measurement system measurement range expansion method of any one of claims 1-6.

[0039] The array element of the filter-attenuation array is a two-layer optical element, and the two-layer optical element is a filter and an attenuation sheet respectively.

[0040] Compared with the prior art, the present application has the following advantages:

[0041] The present application sets different transmittances of the filter-attenuation sheet in different channels, reduces the dynamic response difference between channels, and thus realizes the widening of the temperature measurement range of the system, so that the spectral light field imaging temperature measurement system can cover the target temperature interval of the measurement object.

[0042] The present application proposes a two-layer optical element of the attenuation sheet and the filter, which widens the temperature measurement range of the system. By replacing the attenuation sheet array with different transmittances, the measurement demand of the measurement object in different temperature intervals can be met, and the cost is low and the operation is simple.

[0043] The present application can be applied to target objects with different spectral characteristics, can avoid the emission peak wavelength band of the to-be-measured object, can arbitrarily select the center wavelength of the channel within the response wavelength range of the temperature measurement system, and can obtain high signal-to-noise ratio gray scale information of multiple spectral channels through single exposure.

[0044] The present application proposes to use the particle swarm optimization (PSO) algorithm with strong global search capability to optimize the transmittance parameters of the spectral channel, which can overcome the problem of easily falling into local extreme value in the traditional algorithm. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 It is an imaging device structure diagram of the spectral light field imaging temperature measurement system;

[0046] Figure 2 It is a blackbody furnace temperature measurement device schematic diagram of the spectral light field imaging temperature measurement system;

[0047] Figure 3 It is an algorithm flowchart of the particle swarm optimization (PSO) algorithm for calculating the transmittance parameters;

[0048] Figure 4 It is the iteration result of the particle swarm optimization (PSO) algorithm for the transmittance parameters under different channels;

[0049] Figure 5 It is a filter and filter array gluing schematic diagram;

[0050] Figure 6 It is a comparison of the widening of the front and rear temperature measurement ranges of a four-wavelength temperature measurement system with a blackbody furnace as a temperature measurement object. DETAILED DESCRIPTION

[0051] The present application will be further described below in connection with the accompanying drawings and specific examples. It should be understood that these examples are only used to illustrate the present application and not used to limit the scope of the present application. After reading the present application, those skilled in the art can make various modifications to the present application, and such modifications are within the scope of the present application defined by the appended claims.

[0052] Example 1

[0053] This embodiment takes a blackbody furnace as the temperature measurement object, and takes a four-channel spectral light field imaging temperature measurement system as the target to be widened in dynamic range. The temperature measurement interval is 1583-2300K, and the emissivity is 0.99. The detailed steps are as follows:

[0054] Step one: Since the temperature measurement object is a blackbody furnace, the wavelength range of the tested spectral channel is set within the visible light, and the temperature measurement system only carrying the filter array is subjected to blackbody furnace calibration test. The experiment is shown in Figure 2 During the shooting process, the distance between the system and the blackbody opening of the blackbody furnace is 70cm. The exposure parameters used are 0.1, 0.5, 1, 2, 4ms, respectively. The gray response of the system is recorded ten times every 50K and the average value is taken. The lowest temperature of the blackbody furnace is set to 1583K, and the highest temperature is set to 2300K. The temperature measurement system is set to four different channels (Channel=4), and the center wavelengths are 540, 610, 640, and 660nm, respectively, with corresponding half-peak widths of 40, 35, 25, and 25nm. Through polynomial fitting, the response formula of the system corresponding to the four channels can be obtained, and the results are shown in Table 1.

[0055] Table 1. Fitting results of four spectral channels of the blackbody furnace calibration system

[0056]

[0057] Step two: Since the temperature measurement object is set to a blackbody furnace, the corresponding lowest calibration temperature and highest calibration temperature are the same for the four different channels. The center wavelength of the low response channel is 540nm, and the corresponding transmittance is 100%, and Φ 540nm = 100%. That is:

[0058] T 540,min = T 610,min = T 640,min = T 660,min = 1583K

[0059] T 540,max = T 610,max = T 640,max = T 660,max = 2300K

[0060] Step three: Referring toFigure 3 The algorithm flow chart of the present application is shown in Figure 2. The particle swarm optimization (PSO) algorithm is used to determine the appropriate transmittance parameters for different channels. For the temperature interval in step two, a verification point is selected every 25 K, for a total of 14 verification points (M = 14). The theoretical calculation value of the 540 nm channel is used as the reference value and a target function F is established, as shown in equation (1). The particle swarm quantity is set to Num = 300, the particle dimension N = 3, the maximum particle position x max = 1, x min = 0, v max = 0.005, v min = 0.0001, the maximum iteration step Loop max = 1000, and the iteration termination threshold is ε1 = 10 -3 and ε2 = 10 -4 . The particle position X = [x 1, …, x i ,..., x 300 ] is randomly initialized according to equation (2), with a dimension of 3 × 300, and the velocity V = [v 1, …, v i ,..., v 300 ] is randomly initialized, with a dimension of 3 × 300. The particle individual optimal position P = [p 1, …, p i ,..., p 300 ] is set, with a dimension of 3 × 300, and the global optimal position G = [g 1, …, g j ,..., g3] is set, with a dimension of 3 × 1.

[0061]

[0062]

[0063] In equation (3), x i is the current iteration position of the i-th particle swarm, with a dimension of 3 × 1; v i is the current velocity of the i-th particle swarm, with a dimension of 3 × 1; r x is a random number for initial assignment of the particle position, with a value range of [0, 1] for each element, and a dimension of 3 × 1; r v is a random number for initial assignment of the particle velocity, with a value range of [0, 1] for each element, and a dimension of 3 × 1; E is a full 1 vector, with a dimension of 3 × 1.

[0064] Step four: The particle position is updated according to equation (3), the target function value F corresponding to the particle is calculated according to equation (1) and the response model relationship in the disclosure, and the individual optimal and global optimal values are updated according to equation (4).

[0065]

[0066]

[0067] where ω is the inertia weight selected as 0.65. c1 and c2 are acceleration constants set as 1.48, representing the degree of convergence of particles to the individual and global optimal positions; r1 and r2 are diagonal matrices consisting of the updated random number, with elements in the interval [0, 1],

[0068] Boundary check is performed on the position of each particle in the updated particle swarm to prevent the position from exceeding the boundary set by the algorithm. If it exceeds, it is trimmed to within the boundary:

[0069] x i =max(x min ×E,min(x i ,x max ×E)) (5)

[0070] It is determined whether the current loop number reaches the maximum iteration number, or the global optimal value is lower than the set threshold ε1 (i.e. F(G)≤ε1), or the reduction amplitude of the global optimal value is lower than the set threshold ε2 (i.e. ΔF(G)|≤ε2). If one of the three conditions is met, the loop is exited, otherwise the current loop number is increased by one (i.e. Loop=Loop+1), and step four is entered to update the position of each particle and enter the next loop.

[0071] Step five: the global optimal solution vector G obtained by the algorithm and the corresponding spectral channel transmittance Φ are one-to-one corresponding. The dimension is N×1, where the channel center wavelength is sorted in ascending order, corresponding to the transmittance in turn, i.e. λ1<...<λ j <...<λ3, λ1=610nm, λ2=640nm, λ3=660nm, and the corresponding formula is: The transmittance solution varies with the iteration step length as Figure 4 shown.

[0072] The transmittance parameters of the four channels obtained by the algorithm are Φ 540nm =100%, Φ 610nm =22.38%, Φ 640nm =24.38%, and Φ 660nm =10.53%. Considering the cost, the transmittance parameters of the attenuation sheet array are selected as the type close to the four theoretical values, so the actual transmittance of the four-wavelength attenuation sheet array is: Φ 540nm =100%, Φ 610nm =20%, and Φ640nm = 25%, Φ 660nm = 10%. The imaging device structure corresponding to the system is shown in Figure 1 , the attenuation sheet array and the filter array are glued in a manner Figure 5 , and are installed at the main lens stop. The corrected spectral light field imaging temperature measurement system is built, and the blackbody furnace experiment is performed again to calibrate the channel dynamic response curve. The temperature measurement exposure time is 0.4 ms, and the corrected dynamic response curve is shown in Figure 6 . The maximum gray scale deviation of the method proposed in the application at four channels 540 nm, 610 nm, 640 nm, and 660 nm is 3.4, the minimum deviation is 0.8, and the average deviation is 1.9. The correlation coefficient R 2 of the curve fitting of the data points is 0.999, and it can be considered that all points are on the same line, that is, the dynamic responses of the channels are basically the same. In addition, the temperature measurement interval length is increased from 228 K to 612 K, which is improved by 2.7 times, verifying the feasibility of the method in widening the measurement range of the spectral light field imaging temperature measurement system in practical application.

[0073] Embodiment 2

[0074] The embodiment is an imaging device of a spectral light field imaging temperature measurement system, referring to Figure 1 . The imaging device of the spectral light field temperature measurement system includes a main lens, a filter attenuation sheet array, a microlens array, and a sensor. The main lens and the microlens array jointly image an object on the sensor. The filter attenuation sheet array is arranged at the main lens stop and is used to expand the temperature measurement range. The array element of the filter attenuation sheet array has a filter portion for transmitting different center wavelengths and an attenuation portion for attenuating different center wavelengths.

[0075] The transmittance of the attenuation portion of the filter attenuation sheet array is determined based on the measurement range expansion method of the spectral light field imaging temperature measurement system provided in embodiment 1.

[0076] In one embodiment, the array element of the filter attenuation sheet array is one layer of optical element, which is made of a material with a specific transmittance and center wavelength.

[0077] In one embodiment, the array element of the filter attenuation sheet array is two layers of optical elements, which are a filter and an attenuation sheet respectively. The filter is used to select the center wavelength, and the attenuation sheet has a specific transmittance.

Claims

1. A method for extending the measurement range of a spectral light field imaging temperature measurement system, comprising: The optical fiber spectrometer is used to collect the spectral characteristics of the target object to be measured, and the emission peak band of the combustion process of the target object to be measured is obtained; Within the response wavelength range of the temperature measurement system, avoid the emission peak wavelength of the combustion process of the target object to be measured, and under the condition that the channel wavelength spacing is 20-30nm, arbitrarily select the central wavelength λ under the channel to determine the number of channels Channel; The channel response model of the spectral light field imaging temperature measurement system is established through the blackbody furnace calibration experiment: Where h1 and h2 are Planck constants, which are 3.7148×10 -16 / (W·m 2 ),1.4388×10 -2 / (m·K); gray λ is the grayscale response of the sensor under the corresponding spectral channel; Δt is the exposure time of the imaging device; T λ,min T is the blackbody furnace temperature corresponding to the grayscale response value of 2% FR under the exposure parameters during the shooting of the object to be measured; λ,max It is the temperature of the blackbody furnace when the grayscale response value of the current channel is 90% FR; FR represents full scale; Φ λ is the transmittance of the attenuator of the channel with the central wavelength λ; Δλ is the half-peak width of the spectral channel; E λ is the spectral radiation intensity of the channel with a central wavelength of λ; is the coefficient of the corresponding relationship under the specified channel; b λ,Noise is the constant term of the relation; q is the highest degree of the relation, and q≤4; Establish the objective function F: Where N is the number of particle dimensions, N = Channel-1, and Channel is the number of channels; is the theoretical value of the mth calibration point under the nth channel; It is the theoretical value of the mth calibration point under the reference channel with the lowest response characteristic, and the attenuation rate of the channel with low response characteristic defaults to 100%; M is the number of grayscale theoretical calculation points of the channel; Optimize the established objective function to obtain the transmittance Φ of the attenuator with a central wavelength of λ λ .

2. The method for expanding the measurement range of the spectral light field imaging temperature measurement system according to claim 1, characterized in that: Optimize the established objective function to obtain the transmittance Φ of the attenuator with a central wavelength of λ λ In the step, the particle swarm optimization algorithm is used to optimize the established objective function.

3. The method for extending the measurement range of the spectral light field imaging temperature measurement system according to claim 2, characterized in that: The method of optimizing the established objective function using the particle swarm optimization algorithm includes: Set the number of particle swarm Num, particle dimension N, and maximum particle position x max =1, minimum value of particle position x min =0, maximum particle velocity v max =0.005, minimum particle velocity v min =0.0001, maximum iteration step length Loop max =1000, precision iteration termination threshold ε1 = 10 -3 and step size iteration termination threshold ε2=10 -4 ; Randomly initialize the positions of all particles X=[x1,K,x i ,...,x Num ], the dimension is N×Num; x i is the current iteration position of the particle in the i-th particle group, with a dimension of N×1; the velocity V=[v1,K,v i ,...,v Num ], dimension is N×Num; v i is the current velocity of the particle in the i-th particle group, with dimension N×1; According to the initialization positions of all particles, the optimal position of the particle swarm is set as P = [p1, K, p i ,...,p Num ], with dimensions of N×Num and global optimal position G=[g1,K,g j ,...,g N ] Τ , dimension is N×1; p Num is the individual optimal position of the Num-th particle group, with a dimension of N×1; x i =x min ·E+(x max -x min )·r x v i =v min ·E+(v max -v min )·r v G=p1 Where r x It is a random number for initial assignment of particle position, the value range of the element is [0,1], and the dimension is N×1; r v It is a random number that is initially assigned to the particle velocity. The value range of the element is [0,1] and the dimension is N×1. E is an all-1 vector with a dimension of N×1. Update the position of the particle, calculate the objective function value F corresponding to the particle, and update the individual optimal and global optimal values: v i =ω×v i +c1×r1×(p i -x i )+c2×r2×(g i -x i ) x i =x i +v i p i =x i if F(x i )<F(p i ) G=p i if F(p i )<F(G) Where ω is the inertia weight; c1 and c2 are acceleration constants; r1 and r2 are diagonal matrices composed of updated random numbers, with the interval of elements being [0,1], r1=diag([r1 1 ,...,r1 N ]), The position of each particle in the updated particle swarm is checked to prevent it from exceeding the boundary set by the algorithm; if it exceeds the boundary, the position of each particle is trimmed to within the boundary: x i =max(x min ×E,min(x i ,x max ×E)) Determine whether the current number of loops has reached the maximum number of iterations, or whether the global optimal value is lower than the set threshold ε1, F(G)≤ε1, or whether the reduction in the global optimal value is lower than the set threshold ε2, |ΔF(G)|≤ε2; if one of these three judgment conditions is met, then jump out of the loop; otherwise, increase the current number of loops by one, re-update the positions of each particle, and enter the next loop; The global optimal solution vector G obtained by the algorithm is matched one-to-one with the transmittance Φ of the corresponding spectral channel; The dimension is N×1, where the channel center wavelength is sorted from small to large, corresponding to the transmittance, that is, λ1<...<λ j <...<λ N , and the corresponding formula is:

4. The method for expanding the measurement range of a spectral light field temperature measurement system according to claim 3, characterized in that: Set the number of particle swarms Num = 300, particle dimension N = Channel-1; the maximum particle position x max =1,x min =0,v max =0.005,v min =0.0001, maximum iteration step length Loop max =1000, iteration termination threshold ε1 = 10 -3 and ε2=10 -4 .

5. The method for extending the measurement range of the spectral light field imaging temperature measurement system according to claim 3, characterized in that: The inertia weight ω is selected as 0.

65.

6. The method for extending the measurement range of the spectral light field imaging temperature measurement system according to claim 3, characterized in that: The acceleration constants c1 and c2 were set to 1.

48.

7. An imaging device for a spectral light field imaging temperature measurement system, comprising a main lens, a microlens array, and a sensor, wherein the main lens and the microlens array together form an image of an object on the sensor, characterized in that: A filter attenuation plate array for expanding the temperature measurement range is provided at the aperture of the main lens, and an array element of the filter attenuation plate array has a filtering portion for transmitting different central wavelengths and an attenuation portion for attenuating different central wavelengths; In the imaging device of the system, the transmittance of the attenuation part of the filter attenuation plate array is determined based on the measurement range expansion method of the spectral light field imaging temperature measurement system according to any one of claims 1 to 6.

8. The imaging device according to claim 7, wherein The array element of the filter attenuation plate array is a layer of optical elements.

9. The imaging device according to claim 8, wherein The array elements of the filter attenuation plate array are two layers of optical elements, which are respectively a filter and an attenuation plate.

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