TW202024586A - Method of monitoring temperature of a target object - Google Patents

Abstract

The present disclosure provides a method of monitoring temperature of a target object which uses a thermal imager to retrieve screen images of the target object, and then performs computation based on pixels reflecting temperature values in the screen images, and then filters off interferences and noises that occasionally occur in the screen images according to surface temperatures of the pixels so as to achieve an objective of stably monitoring the temperature of the target object.

Description

Method of monitoring the surface temperature of the target

The present invention relates to the technical field of temperature measurement, in particular to a method for monitoring the surface temperature of a target.

Generally, a contact sensor is used to measure the surface temperature of an object, but in an environment where the working temperature is extremely high and workers cannot approach, such as steelmaking equipment, it must be carried out in a non-contact measurement method. Infrared thermal image thermometer (thermal imager for short) is currently a fast and accurate measuring instrument. In the above-mentioned high temperature environment, if there are no sparks, splash particles or other interference factors, the staff can directly judge the surface temperature of the target from the picture information captured by the thermal imager.

However, in an environment where interference factors exist, such as a steel mill, directly reading the screen information for temperature interpretation will result in fluctuating temperature values, and the surface temperature of the target cannot be measured stably and accurately.

Therefore, it is necessary to provide a method for monitoring the surface temperature of the target to solve the problems of the conventional technology.

The main purpose of the present invention is to provide a method for monitoring the surface temperature of a target, which can greatly reduce the influence of interference factors on the accuracy of temperature interpretation, and effectively improve the The accuracy of measuring the surface temperature of the target under the harsh environment of flowers, dust, mist or sprayed heat source particles.

In order to achieve the above objective, the present invention provides a method for monitoring the surface temperature of a target, which includes the following steps: S1: continuously obtaining a two-dimensional image frame of the target to be tested; S2: converting the two-dimensional image frame into One-dimensional pixel array data; S3: Calculate the temperature value change of each pixel of N consecutive one-dimensional pixel array data within a period of time; S4: Determine whether the temperature value change of each pixel of the N one-dimensional pixel array data There are noisy pixels; S5: remove the noisy pixels to obtain updated one-dimensional pixel array data; and S6: convert the updated one-dimensional pixel array data into a two-dimensional image frame.

In an embodiment of the present invention, the step S3 includes: calculating the average temperature and variance of each pixel in the N pieces of one-dimensional pixel array data; and calculating each pixel based on the average temperature and variance The discrete degree of each pixel in the one-dimensional pixel array data.

In an embodiment of the present invention, the step S5 includes: removing the temperature value of the pixel whose degree of dispersion is greater than a first threshold value from the one-dimensional pixel array data to which it belongs; recalculating one of the remaining numbers The temperature average value and variance of the same pixel in the three-dimensional pixel array data; and the new temperature average value is backfilled with the data position of the previously removed pixel to obtain an updated one-dimensional pixel array data.

In an embodiment of the present invention, after the step S3, the method further includes: calculating the ratio of the discrete degree of each pixel in the N one-dimensional pixel array data; and if the N one-dimensional pixel array data If the ratio of the discrete degree of one of the pixels in the pixel array data is greater than a predetermined second threshold value, the N pieces of one-dimensional pixel array data are directly removed, and step S1 is returned, otherwise, step S4 is continued.

In an embodiment of the present invention, the step S2 further includes: cumulative transfer Change to the number of frames of the one-dimensional pixel array data; and if the number of frames is lower than a preset value, go back to step S1, otherwise go to step S3.

In an embodiment of the present invention, after step S6, the method further includes: removing the first one of the N pieces of one-dimensional pixel array data, and returning to step S1.

Through the above method of monitoring the surface temperature of the target, the interference noise caused by sparks, splash particles or smoke in the screen can be effectively filtered out, so as to achieve the purpose of stably monitoring the temperature of the target through thermal images.

1‧‧‧Infrared Thermal Image Thermometer

2‧‧‧Thermal image analysis module

3‧‧‧Target to be tested

Data _src ‧‧‧Full thermal image screen

Data _tar ‧‧‧Specific area

Noise _pixel ‧‧‧Noise pixel

P(x,y), P ₁ , P _m×n ‧‧‧ pixels

10‧‧‧Two-dimensional image screen

20‧‧‧One-dimensional pixel array data

S1, S11, S2, S21~S24, S3, S31~S35, S4, S5, S51, S6, S7‧‧‧Step

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‧‧‧像素集

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‧‧‧Pixel Set

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‧‧‧像素

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‧‧‧Pixel

f ¹ , f ² , f ³ , f ^T , f ^T+1 ‧‧‧One-dimensional pixel array data

F ^T 、F ^T+1 ‧‧‧Data collection

FIG. 1 is a schematic diagram of a device for implementing a preferred embodiment of the method for monitoring the surface temperature of a target object of the present invention.

Figure 2 is a main flow chart of a preferred embodiment of the method for monitoring the surface temperature of a target object of the present invention.

FIG. 3 is a detailed flowchart of a preferred embodiment of the method for monitoring the surface temperature of the target object of the present invention.

Figure 4 is a schematic diagram of converting a two-dimensional image frame into a one-dimensional pixel array data in the method for monitoring the surface temperature of a target of the present invention.

FIG. 5 is a schematic diagram of a collection of N pieces of one-dimensional pixel array data accumulated in the method for monitoring the surface temperature of the target object of the present invention.

In order to make the above and other objectives, features, and advantages of the present invention more obvious and understandable, the following will specifically cite the preferred embodiments of the present invention, together with the accompanying drawings, and describe in detail as follows.

Please refer to FIG. 1, which is a schematic diagram of a device that implements a preferred embodiment of the method for monitoring the surface temperature of a target of the present invention. Used to implement the present invention to monitor the surface temperature of the target The device of the method mainly includes an infrared thermal image thermometer 1 and a thermal image analysis module 2.

The infrared thermal image thermometer 1 is used for capturing a thermal image of a target 3 with a specific temperature to continuously generate a two-dimensional image frame of the thermal image. The target 3 to be tested may be a steel drum used for steelmaking operations, and may contain high-heat molten steel. In one embodiment, the infrared thermal image thermometer 1 performs a thermal image capturing action on the outer surface of the ladle.

The thermal image analysis module 2 is wired or wirelessly connected to the infrared thermal image thermometer 1 to receive two-dimensional image frames continuously generated by the infrared thermal image thermometer 1. The thermal image analysis module 2 is used to execute the method of monitoring the surface temperature of the target object according to the received two-dimensional image frame.

Please further refer to FIG. 2 and FIG. 3, which are the main flowchart and detailed flowchart of a preferred embodiment of the method for monitoring the surface temperature of the target object of the present invention. The method for monitoring the surface temperature of a target object mainly includes steps S1 to S6, as follows: Step S1: Continuously obtain a two-dimensional image frame of the target to be measured; Step S2: Convert the two-dimensional image frame into a one-dimensional Pixel array data; Step S3: Calculate the temperature value change of each pixel of N consecutive one-dimensional pixel array data within a period of time; Step S4: Determine whether the temperature value change of each pixel of the N one-dimensional pixel array data There are noisy pixels; step S5: remove the noisy pixels to obtain updated one-dimensional pixel array data; step S6: convert the updated one-dimensional pixel array data into a two-dimensional image frame.

Please refer to FIG. 3 and FIG. 4, which are schematic diagrams of converting a two-dimensional image frame into a one-dimensional pixel array data in the method for monitoring the surface temperature of a target of the present invention. In step S1, the two-dimensional image frame 10 may be a partial image (ie, Data _tar ) captured for a specific area in a complete thermal image frame (ie, Data _src ) (as shown in step S11 in FIG. 3). In an embodiment, as shown in FIG. 4, the two-dimensional image frame 10 may include m×n pixels, where P(x,y) is represented as the pixel in the xth row and the yth column.

As shown in Figures 3 and 4, when step S2 is performed, the two-dimensional image frame 10 is converted into one-dimensional pixel array data 20, that is, a data set of m×n pixels is arranged in order into one A three-dimensional array, namely P ₁ , P ₂ , ..., P _m×n (as in step S21 in Fig. 3). In an embodiment, the order may be from left to right, top to bottom, that is, according to P(0,0), P(1,0), P(2,0), P(3 ,0),...,P(m,0), P(0,1), P(1,1), P(2,1),...P(m,1), P(0, 2),...P(m,n-1), P(0,n), P(1,n), P(2,n),..., P(m-1,n) , P(m,n) are arranged in the order of the one-dimensional array data 20.

In a preferred embodiment, with reference to FIGS. 3 and 5, the step S2 may further include: accumulating the number of frames i converted into the one-dimensional pixel array data 20 (as shown in step S22 in FIG. 3 ); and if the screen number i is lower than a preset value T, go back to step S1, otherwise, go to step S3 (such as step S23 in Figure 3). In other words, in this step, the cumulatively obtained N two-dimensional image frames must be at least equal to T and converted into T one-dimensional pixel array data before the N one-dimensional pixel array data is regarded as a data set F _T (Such as step S24 in Figure 3), then step S3 is continued. In a preferred embodiment, the preset value T may be 10, but it is not limited thereto.

的溫度平均值及變異數，例如第1筆一維像素陣列資料f¹中的第一個像素

、第2筆一維像素陣列資料f²中的第一個像素

、....以及第N筆一維像素陣列資料f^T中的第一個像素

即是所述N筆一維像素陣列資料中的位於第一個位置的像素集，其中N等於前述的預設值T。所述步驟S32即是將所述N筆一維像素陣列資料中的位於同一位置的像素的溫度值配合所計算出的溫度平均值及變異數計算出所述N筆一維像素陣列資料中的位於同一位置的像素各自的離散程度。 With reference to Figure 3, the step S3 may include: calculating the average temperature and variance of each pixel in the N pieces of one-dimensional pixel array data (such as step S31 in Figure 3); and The temperature average value and variation number are used to calculate the degree of dispersion of each pixel in each one-dimensional pixel array data (such as step S32 in Figure 3). In other words, in Fig. 5, the step S31 is to calculate the pixel set at the same position in the N one-dimensional pixel array data.

The average temperature and variance of the temperature, such as the first pixel in the first one-dimensional pixel array data f ¹

, The first pixel in the second one-dimensional pixel array data f ²

,... and the first pixel in the Nth one-dimensional pixel array data f ^T

That is, the pixel set at the first position in the N pieces of one-dimensional pixel array data, where N is equal to the aforementioned preset value T. The step S32 is to calculate the temperature values of the pixels located at the same position in the N pieces of one-dimensional pixel array data with the calculated temperature average value and variation number to calculate the value of the N pieces of one-dimensional pixel array data The degree of dispersion of pixels located at the same position.

With reference to Fig. 2, the step S5 includes: removing the temperature value of the pixel whose degree of dispersion is greater than a first threshold value from the one-dimensional pixel array data to which it belongs; recalculating the remaining one-dimensional The temperature average value and variance of the same pixel in the pixel array data; and backfill the data position of the previously removed pixel with the new temperature average value to obtain an updated one-dimensional pixel array data (as shown in the step in Figure 3) S51). Step S51 is to treat pixels with a degree of dispersion greater than a first threshold as noise pixels with unusual temperature and remove them. For example, the sparks in the ladle or the slag on the surface of the molten steel has a high temperature. When it is splashed, it will become a noise pixel with an unusual temperature value in the two-dimensional image shown in Figure 4. Noise _pixel . When these pixel Noise _pixel noise is removed, i.e., step S51 and recalculates the average temperature variation of the same pixel number of one-dimensional array of pixel data in the remaining items, for temperature compensation of the pixel value is removed, the The new temperature average value backfills the data positions of the previously removed pixels to obtain an updated one-dimensional pixel array data. At this time, the pixels originally regarded as noise have become normal pixels, and the degree of dispersion has become smaller than the first threshold value.

With reference to Figure 2, after the step S3, the method further Including: calculating the ratio of the degree of dispersion of each pixel in the N pieces of one-dimensional pixel array data (such as step S33 in Figure 3); and if the degree of dispersion of one of the pixels in the N pieces of one-dimensional pixel array data If the ratio of is greater than a predetermined second threshold value, the N one-dimensional pixel array data are directly removed (such as steps S34 and S35 in Figure 3), and step S1 is returned to obtain N one-dimensional pixel arrays again Data, otherwise proceed to step S4. Steps S33 to S35 are the elimination steps performed to avoid too many noise pixels in the acquired continuous two-dimensional image frames when the state of the target to be measured is unstable. In other words, among the N pixels located at the same position in the N pieces of one-dimensional pixel array data, if the number of pixels with excessive dispersion in the N pixels accounts for the total number of N pixels located at the same position (ie N pixels ) Is greater than the second threshold, it means that there are too many noise pixels in the N pieces of one-dimensional pixel array data, and the N pieces of one-dimensional pixel array data need to be directly removed, and step S1 is returned to Re-acquire N one-dimensional pixel array data. In an embodiment, the second threshold value may be 0.5. When the discrete degree ratio of one of the pixels in the N one-dimensional pixel array data is greater than 0.5, it means that more than half of the N pixels are discrete Excessive pixels.

With reference to Figures 2 and 3, the method further includes step S7 after step S6: removing the first entry (f ₁ ) in the N entries of one-dimensional pixel array data, and returning to step S1 (as in step S7 in Figure 3). That is, in order, the first two-dimensional image frame obtained first is removed, the N+1-th two-dimensional image frame is converted into one-dimensional pixel array data, and the remaining one-dimensional pixel array data is assembled to Continuous monitoring of the surface temperature of the target to be measured.

In summary, compared with the prior art, the present invention converts two-dimensional picture data into one-dimensional data, and identifies pixels that should belong to noise in the picture based on the one-dimensional data of the successive pictures before and after, and through the same picture in the continuous picture The temperature values of other pixels located at the same position are averaged as the compensation value to fill in the removed pixel (that is, to replace the original unusual temperature value of the pixel), to To eliminate image noise. Therefore, the present invention can effectively filter out the interference noise caused by sparks, splash particles or smoke in the picture, and achieve the purpose of stably monitoring the temperature of the target through thermal images.

Although the present invention has been disclosed in the preferred embodiments, it is not intended to limit the present invention. Anyone familiar with the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the present invention The scope of protection shall be subject to the scope of the attached patent application.

S1, S2, S3, S4, S5, S6, S7‧‧‧Step

Claims (7)

A method for monitoring the surface temperature of a target includes the following steps: S1: continuously obtaining a two-dimensional image frame of a target to be measured; S2: converting the two-dimensional image frame into one-dimensional pixel array data; S3: calculating The temperature value change of each pixel of the continuous N pieces of one-dimensional pixel array data; S4: Determine whether there is a noise pixel according to the temperature value change of each pixel of the N pieces of one-dimensional pixel array data; S5: Remove the noise pixel Obtain updated one-dimensional pixel array data; and S6: Convert the updated one-dimensional pixel array data into a two-dimensional image frame. According to the method for monitoring the surface temperature of a target object as described in the first item of the scope of patent application, the step S3 includes: calculating the average temperature and variance of each pixel in the N pieces of one-dimensional pixel array data; and according to The temperature average value and variation number are used to calculate the degree of dispersion of each pixel in each one-dimensional pixel array data. According to the method for monitoring the surface temperature of a target object as described in item 2 of the scope of patent application, the step S4 includes: treating pixels with a dispersion degree greater than a predetermined first threshold as noise pixels. The method for monitoring the surface temperature of a target object as described in item 3 of the scope of patent application, wherein the step S5 includes: dividing the temperature value of the pixel whose degree of dispersion is greater than a first threshold value from the one-dimensional pixel array data to which it belongs Remove Recalculate the temperature average and variance of the same pixel in the remaining one-dimensional pixel array data; and backfill the new temperature average to the data position of the previously removed pixel to obtain an updated one-dimensional pixel array data. The method for monitoring the surface temperature of a target object as described in item 2 of the scope of patent application, wherein after the step S3, the method further comprises: calculating the degree of dispersion of each pixel in the N pieces of one-dimensional pixel array data And if the ratio of the discrete degree of one of the pixels in the N pieces of one-dimensional pixel array data is greater than a predetermined second threshold value, then the N pieces of one-dimensional pixel array data are directly removed, and the step is returned S1, otherwise proceed to step S4. The method for monitoring the surface temperature of a target object as described in item 1 of the scope of patent application, wherein the step S2 includes: accumulating the number of screens converted into one-dimensional pixel array data; and if the number of screens is lower than a preset value, Go back to step S1, otherwise go to step S3. The method for monitoring the surface temperature of a target object as described in item 6 of the scope of patent application, wherein after step S6, the method further includes: removing the first one of the N one-dimensional pixel array data, and returning Step S1.

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