CN109800739B - Temperature detection device of electric heating rotary kiln - Google Patents
Temperature detection device of electric heating rotary kiln Download PDFInfo
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Abstract
The invention provides an electric heating rotary kiln temperature detection device of rotary kiln electric heating equipment integrating video detection and temperature induction. The device comprehensively utilizes the advantages of the two, and realizes good automatic temperature control effect through a simpler temperature control mechanism.
Description
Technical Field
The invention belongs to the technical field of temperature control, and particularly relates to a temperature detection device and a control method for an electric heating rotary kiln.
Background
The rotary kiln equipment has high heat transfer capability and good mixing performance, is suitable for the calcining, volatilizing, segregating and other processes of various industrial raw materials, and is widely applied in the industries of metallurgy, chemical industry, cement, paper packaging, environmental protection and the like. As a typical complex industrial plant, rotary kiln control methods are a hotspot and difficulty of research. Because the rotary kiln has the characteristics of multiple variables, nonlinearity, strong coupling and the like, the development of automatic control of the rotary kiln is carried out for a period of quite slow time until the intelligent control theory begins to be integrated into the control of the complex industrial process, the difficult problem of the control of the rotary kiln is successfully solved, and a large amount of theoretical results are generated along with the frequent application of the rotary kiln in production practice. Therefore, the research on the rotary kiln control theory mostly takes intelligent control as a main research direction, and common problems include fuzzy, neural network, expert system, mixed intelligent control and the like.
The control objective of the rotary kiln is to reasonably determine parameters such as wind, coal, material, kiln speed, temperature and pressure of each part of the system of the rotary kiln according to the characteristics of preheating decomposition before raw materials enter the kiln, process the interrelationship between the rotary kiln and the preheater and between the rotary kiln and the cooler, stabilize the thermal system of the whole system, maintain kiln coating, prolong the operation period without accidents and with full efficiency, realize high-quality, stable production and low-consumption production, and simultaneously save energy consumption and reduce the content of harmful gases in waste gas. Wherein temperature is the key to control the rotary kiln. Rotary kilns can generally be divided into three temperature zones: the three temperature zones of the preheating zone, the calcining zone and the thermal insulation zone have different functions. The material is first preheated in a preheating zone and then enters a calcining zone. The calciner zone is the main part of the rotary kiln in which oxidation-reduction reactions take place. The materials that are not fully reacted in the calcining zone are further reacted in the insulating zone. The temperature of the calcining zone directly affects the performance of the rotary kiln and the quality of the product, which is an important process parameter, so that the requirement must be ensured to be within a certain deviation range of the process requirement temperature and to be kept stable as much as possible. The analysis from the control effect requires that the temperature control of the calcining zone has no steady-state error, or has small steady-state error and strong anti-interference capability, and can quickly recover to the original state once being interfered.
However, although there are a great deal of theoretical results, in the actual control site, the environmental conditions are quite complex, so the control effect is still not quite ideal, and the control difficulty of the calcination temperature of the rotary kiln mainly comprises the following points:
(1) The physical and chemical reaction process in the rotary kiln is complex, the heat transfer process is complex, the running conditions and working conditions are greatly changed, such as the thickness of kiln inner lining and kiln skin, the raw slurry flow, moisture, components, fuel coal quality and the like are frequently changed, nonlinearity and large inertia exist, and an accurate mathematical model is difficult to build.
(2) The temperature of the calcining zone is difficult to measure, and the temperature of the material of the calcining zone is measured by an optical fiber colorimetric thermometer arranged in front of the kiln, so that the temperature is delayed in detection and is seriously interfered by dust and smoke.
(3) Because the rotary kiln is large in volume and large in contact area with the surrounding environment, the rotary kiln is easily interfered by the external environment, and more uncertainty factors exist, so that the difficulty of accurately controlling the calcination temperature is increased.
(4) So far, most rotary kilns are mainly controlled by conventional PID, but the rotary kilns have variable working conditions, and the PID controller cannot obtain satisfactory control effect. On one hand, the accuracy of the related sensor at a specific position in the actual use process is difficult to master the aging degree in real time, and is not beneficial to fine processing; on the other hand, in practical application, most of the operators are skilled, and more satisfactory results are obtained by continuously modifying the parameters of the controller. This not only takes a lot of time, but also the parameters must be re-set once the environment, conditions change, otherwise good control results cannot be achieved.
Disclosure of Invention
In view of the above analysis, the main objective of the present invention is to provide an automatic temperature control device and control method for an electric heating apparatus of a rotary kiln, which overcomes the drawbacks of the prior art, such as poor temperature control effect, or huge structure of a control system, too high cost, and too complex control flow and algorithm, so that the present invention provides an automatic temperature control device and control method for an electric heating apparatus of a rotary kiln, which combines both video detection and temperature sensing, and comprehensively utilizes the advantages of both devices, and realizes a good automatic temperature control effect by a simpler temperature control system architecture and control method.
The aim of the invention is achieved by the following technical scheme.
The technical scheme of the invention relates to an electric heating rotary kiln temperature detection device which comprises a power supply, a processor module, a temperature sensing module, a video detection module and an analog-to-digital conversion module, wherein the temperature sensing module is used for sensing the temperature in a kiln, the signal output is processed by the signal processing module and then is sent to the analog-to-digital conversion module, the signal is processed by the processor module, the video detection module detects the rotary kiln at the same time, the detected image signal is also sent to the processor module for processing, and the processor module corrects the temperature data in the kiln obtained by the temperature sensing module according to the temperature data in the kiln obtained by the temperature sensing module by referring to the temperature data in the kiln obtained by the video detection module.
Further, the temperature sensing module converts a reference voltage of 3.3V into a constant current by using an amplifier, and when the current flows through a thermal resistor (Rt), a voltage drop is generated, and then the weak voltage drop signal is amplified by the amplifier, and the amplified signal is sent to the analog-to-digital conversion module.
Further, the video detection module comprises a video acquisition processing module, wherein the video acquisition processing module comprises a deformation machine learning module, a rotary kiln head image characteristic value solving module and an extended image function building and processing module:
before video acquisition of a kiln head image of a rotary kiln is performed to obtain an image of a heating condition in a kiln cylinder, a plane deformation correction formula from an image center to an image edge direction is firstly established, wherein the image deformation in the non-parallel direction exists due to incomplete parallelism of a lens of the video detection module with an imaging plane, namely, a deformed image is generated:
wherein (x, y) represents the initial position of the image, (x) c ,y c ) Is the corrected position, r represents the deformation distance from the imaging center, k 1 And k 2 For the deformation coefficient in the direction from the center to the edge, ||R area (x, y) is the modulus of the constant integral parameter;
3 scales with the lengths r of 1/8, 1/16 and 1/32 are arranged on the kiln head side of the rotary kiln opposite to the video detection module, one ends of the three scales are arranged on a round surface formed by the kiln head and the kiln cylinder at the tail end of the kiln cylinder at the kiln head side and tangent to the kiln cylinder respectively, the other ends of the three scales are arranged outside the kiln cylinder at the kiln head side and extend outwards along the radial direction of the round surface formed by the kiln head and the kiln cylinder tangent to each other respectively, the three scales are arranged at 120 DEG intervals, the ratio of the length of the scale with the smallest length in the image acquired by the video detection module in the deformed image, namely the ratio of the length in the image deformation to the actual length thereof is an initial value, the ratio of the lengths of the other two scales in the image deformation is iterated respectively in a mode based on a means of a meanshift algorithm, and the iterated result is k respectively 1 And k 2 ；
The rotary kiln head image characteristic value solving module is used for compressing and converting an image to generate a color image I, wherein a corresponding black-and-white image, namely a monochrome image is I', and the gray value g of the monochrome image is expressed by color space linearity as follows:
g＝α r I r +α g I g +α b I b
wherein alpha is r ≥0，α g ≥0，α b ≥0，α r +α g +α b ＝1
Alpha in the formula r ，α g ，α b As optional parameters, I r ，I g ，I b Is the color channel value of image I;
the following function V is constructed:
wherein x and y are pixel points, g x ，g y Single-colour grey value delta of x and y points x，y And (3) performing monochromatic image dimension reduction processing on the function V by using GAUSS moving average to obtain different monochromatic images for European measurement of x and y pixel points when the image I is converted into a color model space:
establishing a function L (x, y, σ, ρ) =ρ·i' (x, y) ·g (x, y, σ)
Wherein, x and y are monochromatic image coordinate values, sigma is a scale factor, rho is a scale factor, and the monochromatic image is I' (x and y);
the extension image function building and processing module is used for building an extension image function f for an extension region of the deformed image extending to the outside of the kiln cylinder body c (L (x, y, sigma, p)), where L (x, y, sigma, p) is normalized to [0,1 ]]The extended image function is:
wherein λ is an extension slope, and an autocorrelation matrix of each pixel point is calculated by using a harris matrix:
wherein x and y are pixel point coordinates, and N is the image size, the characteristic response function of the extended image function is:
R(x，y，c)＝detA(x，y，f c )-k(traceA(x，y，f c )) 2
wherein k is a constant factor and is k 1 And k 2 Arithmetic mean of (2);
the result is obtained by accumulation of fixed integral:
further, the processor module corrects the temperature data in the kiln represented by the kiln head image obtained by the video detection module according to the temperature data obtained by the temperature sensing module, and performs temperature control according to a correction result, and the processor module comprises a heat setting module and a temperature model building module:
a heat setting module for setting the initial temperature and the ambient temperature T of the rotary kiln 1 In the same case, assuming that the temperature of the rotary kiln at time T is T (T) and the heat quantity is Q (T), there are:
Q(t)＝Q 1 (t)+Q 2 (t)
in which Q 1 (t) -heat generated by the rotary kiln itself;
Q 2 (t) -the amount of heat transferred;
wherein C is the heat capacity of the rotary kiln, s is the color difference ratio of the kiln head image obtained by the video detection module after correction and the kiln head image when the temperature is the initial temperature;
the heat of the rotary kiln is expressed as:
the temperature model building module is used for carrying out Laplace transformation on the formula to obtain:
the temperature model of the rotary kiln is established as follows:
let k=ar, t=cr, then there is:
where K is the amplification factor, T is the time constant, and τ is the lag time.
The technical scheme of the invention has the following advantages:
the invention creatively provides a temperature control mode combining video detection and temperature induction, comprehensively utilizes the advantages of the video detection and the temperature induction, and particularly provides a circuit structure of a temperature induction module and a specific mode of image processing in the video detection, based on correcting machine vision information of thermal imaging, a more reliable and accurate temperature control model is provided, and a good automatic temperature control effect is realized through MATLAB simulation test and on-site actual control and verification.
Drawings
FIG. 1 is a schematic diagram of the control device of the present invention;
fig. 2 is a circuit diagram of a temperature sensing module according to the present invention.
Detailed Description
Referring to fig. 1, a schematic diagram of a temperature detection device for an electric heating rotary kiln according to the present invention includes a power supply, a processor module, a temperature sensing module, a video detection module, and an analog-to-digital conversion module, wherein the temperature sensing module is used for sensing the temperature in the kiln, the signal output is processed by the signal processing module and then sent to the analog-to-digital conversion module, the signal is processed by the processor module, the video detection module detects the rotary kiln, the detected image signal is also sent to the processor module for processing, and the processor module corrects the temperature data in the kiln obtained by the video detection module according to the temperature data in the kiln obtained by the temperature sensing module.
Preferably, as shown in the circuit diagram of the temperature sensing module of fig. 2, the temperature sensing module converts a reference voltage of 3.3V into a constant current by using an amplifier, a voltage drop is generated when the current flows through a thermal resistor (Rt), the weak voltage drop signal is amplified by the amplifier, and the amplified signal is sent to the analog-to-digital conversion module.
Preferably, the video detection module comprises a video acquisition processing module, wherein the video acquisition processing module comprises a deformation machine learning module, a rotary kiln head image characteristic value solving module and an extended image function building and processing module:
before video acquisition of a kiln head image of a rotary kiln is performed to obtain an image of a heating condition in a kiln cylinder, a plane deformation correction formula from an image center to an image edge direction is firstly established, wherein the image deformation in the non-parallel direction exists due to incomplete parallelism of a lens of the video detection module with an imaging plane, namely, a deformed image is generated:
wherein (x, y) represents the initial position of the image, (x) c Yc) is the corrected position, r represents the deformation distance from the imaging center, k 1 And k 2 For the deformation coefficient in the direction from the center to the edge, ||R area (x, y) is the modulus of the constant integral parameter;
3 scales with the lengths r of 1/8, 1/16 and 1/32 are arranged on the kiln head side of the rotary kiln opposite to the video detection module, one ends of the three scales are arranged on a round surface formed by the kiln head and the kiln cylinder at the tail end of the kiln cylinder at the kiln head side and tangent to the kiln cylinder respectively, the other ends of the three scales are arranged outside the kiln cylinder at the kiln head side and extend outwards along the radial direction of the round surface formed by the kiln head and the kiln cylinder tangent to each other respectively, the three scales are arranged at 120 DEG intervals, the ratio of the length of the scale with the smallest length in the image acquired by the video detection module in the deformed image, namely the ratio of the length in the image deformation to the actual length thereof is an initial value, the ratio of the lengths of the other two scales in the image deformation is iterated respectively in a mode based on a means of a meanshift algorithm, and the iterated result is k respectively 1 And k 2 ；
The rotary kiln head image characteristic value solving module is used for compressing and converting an image to generate a color image I, wherein a corresponding black-and-white image, namely a monochrome image is I', and the gray value g of the monochrome image is expressed by color space linearity as follows:
g＝α r I r +α g I g +α b I b
wherein alpha is r ≥0，α g ≥0，α b ≥0，α r +α g +α b ＝1
Alpha in the formula r ，α g ，α b As optional parameters, I r ，I g ，I b Is the color channel value of image I;
the following function V is constructed:
wherein x and y are pixel points, g x ，g y Single-colour grey value delta of x and y points x，y And (3) performing monochromatic image dimension reduction processing on the function V by using GAUSS moving average to obtain different monochromatic images for European measurement of x and y pixel points when the image I is converted into a color model space:
establishing a function L (x, y, σ, ρ) =ρ·i' (x, y) ·g (x, y, σ)
Wherein, x and y are monochromatic image coordinate values, sigma is a scale factor, rho is a scale factor, and the monochromatic image is I' (x and y);
the extension image function building and processing module is used for building an extension image function f for an extension region of the deformed image extending to the outside of the kiln cylinder body c (L (x, y, sigma, p)), where L (x, y, sigma, p) is normalized to [0,1 ]]The extended image function is:
wherein λ is an extension slope, and an autocorrelation matrix of each pixel point is calculated by using a harris matrix:
wherein x and y are pixel point coordinates, and N is the image size, the characteristic response function of the extended image function is:
R(x，y，c)＝detA(x，y，f c )-k(traceA(x，y，f c )) 2
wherein k is a constant factor and is k 1 And k 2 Arithmetic mean of (2);
the result is obtained by accumulation of fixed integral:
preferably, the processor module corrects the temperature data in the kiln represented by the kiln head image obtained by the video detection module according to the temperature data obtained by the temperature sensing module, and performs temperature control according to a correction result, and the processor module comprises a heat setting module and a temperature model building module:
a heat setting module for setting the initial temperature and the ambient temperature T of the rotary kiln 1 In the same case, assuming that the temperature of the rotary kiln at time T is T (T) and the heat quantity is Q (T), there are:
Q(t)＝Q 1 (t)+Q 2 (t)
in which Q 1 (t) -heat generated by the rotary kiln itself;
Q 2 (t) -the amount of heat transferred;
wherein C is the heat capacity of the rotary kiln, s is the color difference ratio of the kiln head image obtained by the video detection module after correction and the kiln head image when the temperature is the initial temperature;
the heat of the rotary kiln is expressed as:
the temperature model building module is used for carrying out Laplace transformation on the formula to obtain:
the temperature model of the rotary kiln is established as follows:
let k=ar, t=cr, then there is:
where K is the amplification factor, T is the time constant, and τ is the lag time.
After the model is built, the processor realizes the automatic temperature control of the rotary kiln according to the model.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (1)
1. The device is characterized by comprising a power supply, a processor module, a temperature sensing module, a video detection module and an analog-to-digital conversion module, wherein the temperature sensing module is used for sensing the temperature in the kiln, the signal output is processed by the signal processing module and then is sent to the analog-to-digital conversion module, the signal is processed by the processor module, the video detection module also detects the rotary kiln and the detected image signal is also sent to the processor module for processing, and the processor module corrects the temperature data in the kiln obtained by the temperature sensing module according to the temperature data in the kiln obtained by the video detection module;
the temperature sensing module converts a reference voltage of 3.3V into constant current by using an amplifier, voltage drop is generated when the current flows through a thermal resistor (Rt), the voltage drop signal is amplified by the amplifier, and the amplified signal is sent to the analog-to-digital conversion module;
the video detection module comprises a video acquisition processing module, wherein the module comprises a deformation machine learning module, a rotary kiln head image characteristic value solving module and an extended image function building and processing module:
before video acquisition of a kiln head image of a rotary kiln is performed to obtain an image of a heating condition in a kiln cylinder, a plane deformation correction formula from an image center to an image edge direction is firstly established, wherein the image deformation in the non-parallel direction exists due to incomplete parallelism of a lens of the video detection module with an imaging plane, namely, a deformed image is generated:
wherein (x, y) represents the initial position of the image, (x) c ,y c ) Is the corrected position, r represents the deformation distance from the imaging center, k 1 And k 2 For the deformation coefficient in the direction from the center to the edge, ||R area (x, y) is the modulus of the constant integral parameter;
3 scales with the lengths r of 1/8, 1/16 and 1/32 are arranged on the kiln head side of the rotary kiln opposite to the video detection module, one ends of the three scales are arranged on a round surface formed by the kiln head and the kiln cylinder at the tail end of the kiln cylinder at the kiln head side and tangent to the kiln cylinder respectively, the other ends of the three scales are arranged outside the kiln cylinder at the kiln head side and extend outwards along the radial direction of the round surface formed by the kiln head and the kiln cylinder tangent to each other respectively, the three scales are arranged at 120 DEG intervals, the ratio of the length of the scale with the smallest length in the image acquired by the video detection module in the deformed image, namely the ratio of the length in the image deformation to the actual length thereof is an initial value, the ratio of the lengths of the other two scales in the image deformation is iterated respectively in a mode based on a means of a meanshift algorithm, and the iterated result is k respectively 1 And k 2 ；
The rotary kiln head image characteristic value solving module is used for compressing and converting an image to generate a color image I, wherein a corresponding black-and-white image, namely a monochrome image is I', and the gray value g of the monochrome image is expressed by color space linearity as follows:
g＝α r I r +α g I g +α b I b
wherein alpha is r ≥0，α g ≥0，α b ≥0，α r +α g +α b ＝1
Alpha in the formula r ，α g ，α b As optional parameters, I r ，I g ，I b Is the color channel value of image I;
the following function V is constructed:
wherein x and y are pixel points, g x ，g y Single-colour grey value delta of x and y points x，y And (3) performing monochromatic image dimension reduction processing on the function V by using GAUSS moving average to obtain different monochromatic images for European measurement of x and y pixel points when the image I is converted into a color model space:
establishing a function L (x, y, σ, ρ) =ρ·i' (x, y) ·g (x, y, σ)
Wherein, x and y are monochromatic image coordinate values, sigma is a scale factor, rho is a scale factor, and the monochromatic image is I' (x and y);
the extension image function building and processing module is used for building an extension image function f for an extension region of the deformed image extending to the outside of the kiln cylinder body c (L (x, y, sigma, p)), where L (x, y, sigma, p) is normalized to [0,1 ]]The extended image function is:
wherein λ is an extension slope, and an autocorrelation matrix of each pixel point is calculated by using a harris matrix:
wherein x and y are pixel point coordinates, and N is the image size, the characteristic response function of the extended image function is:
R(x，y，c)＝detA(x，y，f c )-k(traceA(x，y，f c )) 2
wherein k is a constant factor and is k 1 And k 2 Arithmetic mean of (2);
the result is obtained by accumulation of fixed integral:
the processor module corrects the temperature data in the kiln represented by the kiln head image and obtained by the video detection module according to the temperature data obtained by the temperature sensing module, and performs temperature control according to a correction result, and the processor module comprises a heat setting module and a temperature model building module:
a heat setting module for setting the initial temperature and the ambient temperature T of the rotary kiln 1 In the same case, assuming that the temperature of the rotary kiln at time T is T (T) and the heat quantity is Q (T), there are:
Q(t)＝Q 1 (t)+Q 2 (t)
in which Q 1 (t) -heat generated by the rotary kiln itself;
Q 2 (t) -the amount of heat transferred;
wherein C is the heat capacity of the rotary kiln, s is the color difference ratio of the kiln head image obtained by the video detection module after correction and the kiln head image when the temperature is the initial temperature;
the heat of the rotary kiln is expressed as:
the temperature model building module is used for carrying out Laplace transformation on the formula to obtain:
the temperature model of the rotary kiln is established as follows:
let k=ar, t=cr, then there is:
where K is the amplification factor, T is the time constant, and τ is the lag time.
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