Temperature field testing system based on multi-sensor image fusion

The engine temperature field test refers to the measurement of the wall temperature and the hot end components of the high-temperature gas turbine engine combustion chamber. The service life of the engine hot end components is closely related to whether the distribution of the hot end component temperature field is uniform, so the engine temperature field must be accurately tested.

1 Research status

At present, domestic engine production and repair enterprises mainly use direct contact method and manual interpretation method to test the temperature field of certain engine parts. The direct contact method uses thermocouples to directly test the temperature of engine parts, as shown in Figure 1(a). However, this method has a large measurement error and can only measure the temperature of certain points, and cannot measure the entire temperature field. The manual interpretation method refers to the engine production and repair enterprises using the color temperature characteristics of temperature-indicating paint to indirectly interpret the temperature of engine parts, as shown in Figure 1(b). At present, most engine manufacturers use temperature-indicating paint to indirectly measure the temperature field of engine parts. Temperature-indicating paint is a temperature sensor that can show different colors in different temperature ranges. It is applied to the surface of the engine test piece and its temperature is judged according to the color of the temperature-indicating paint on the surface of the test piece.

Using temperature-indicating paint to measure the temperature field of the hot end parts of the engine has the advantages of large measurement area, wide temperature measurement range, convenient use, simple operation, and no damage to the surface shape of the object. Therefore, it can be widely used. However, this method is easily affected by ambient light and has disadvantages such as large errors and low efficiency. In order to improve the test accuracy, test efficiency and robustness of the engine temperature field, this paper proposes an engine temperature field test system based on multi-sensor image fusion for the first time.

2 Overall system design

2.1 Working Principle

The entire engine temperature field test system is composed of five major parts: light source, engine temperature field test parts, lens, CCD image sensor, image acquisition card, image fusion processing and temperature recognition computer. The role of the light source is to provide enough light to achieve image acquisition in a dim environment or under special illumination that requires separate light; the role of the lens is to ensure that the image sensor can collect target images of appropriate size and high clarity through its own adjustment; the image sensor converts the image into a signal for acquisition through a CCD or CMOS photosensitive element; the image acquisition card is mainly used to collect the target image obtained by the image sensor and transmit it to the computer image processing system, and the computer performs image fusion, processing and temperature recognition on the collected image. The overall block diagram of the entire engine temperature field test system is shown in Figure 2.

The working process of the whole system is as follows: first, when the test target approaches the center of the CCD image sensor's viewing angle, the image acquisition card sends a start pulse to the CCD image sensor and the lighting equipment respectively to start the image sensor and the lighting equipment, and the CCD image sensor scans and outputs a frame of image; then the image acquisition card converts the analog signal collected from the CCD image sensor into a digital signal through A/D conversion; the image acquisition card sends the image signal to the image processing and temperature recognition computer for image fusion and temperature recognition, and finally the computer displays the results of image processing, analysis, and target temperature recognition.

2.2 Light Source

In the process of testing the system, the purpose of light source selection is to obtain a target image with high contrast between target information and background information, so as to highlight the target features of interest and suppress the background features of no interest, thereby greatly reducing the difficulty of target image processing and improving the robustness and measurement accuracy of the system. Therefore, the selection of light source should follow the principles of high contrast, moderate brightness, uniform light source, high robustness, etc., while also taking into account factors such as service life, temperature influence, price cost, and design difficulty. Commonly used light sources include LED lamps, halogen lamps, fluorescent lamps, and laser light sources. LED lamps are selected here because they have the advantages of stability, energy saving, adjustable brightness, and long service life.

2.3 Image Sensor

The image sensor is a key component of the test system for acquiring images. It converts the test target optical signal into an electrical signal and then converts it into a digital image signal through A/D conversion. The digital image processing can then be performed in the computer. Currently, there are two main types of image sensors: CCD and CMOS. The CCD image sensor [1] is a new type of semiconductor solid-state image sensor. It is made of CCD charge-coupled devices. It has the advantages of high integration, low power consumption, simple structure, impact resistance, long life, stable performance, and high imaging quality. Therefore, it is widely used. The CMOS image sensor is made of CMOS photoelectric conversion devices. This sensor is cheap but the imaging quality is not high. Considering that the test system has high requirements for image quality, the CCD image sensor is selected here. This system installs multiple CCD image sensors to obtain images of the test target from different angles. The use of a multi-sensor redundant structure also improves the robustness of the system.

2.4 Lens

The lens is an important component of the test system. It images the test target on the light-sensitive surface of the CCD image sensor. Its quality is directly related to the acquisition quality of the temperature field image of the engine components, and also directly affects the performance of the overall system. In this test system, the selection of the lens in this test system follows the following three principles:

(1) Follow high resolution;

(2) The imaging size should not be smaller than the target surface size of the CCD image sensor;

(3) Select the focal length of the lens according to the distance between the CCD image sensor and the target to be tested. Here, multiple lenses are used, each lens is aimed at a CCD image sensor.

2.5 Image acquisition card

The image acquisition card converts the target analog image signal obtained by the CCD image sensor into a digital image signal. The image acquisition card has an external signal interface connected to the CCD image sensor, and the image acquisition card is installed in a bus slot of the computer. When working, the image acquisition card first acquires the analog image signal output by the CCD image sensor, and then converts the analog image into a digital image through A/D conversion and stores it in the memory. The computer performs digital image fusion and processing on the collected multi-source images. At present, there are two main types of image acquisition cards: PCI and PXI. The image acquisition card based on the PCI bus has the extreme conditions of vibration, impact, temperature and humidity in the industrial environment. Considering the high vibration and high temperature when the engine is working, the image acquisition card based on the PCI bus is selected here.

2.6 Image Fusion Processing Computer

In order to reduce manual interpretation errors, image fusion and image processing must be performed before using the temperature-indicating paint image for temperature field recognition. The image fusion processing computer collects and stores the target image obtained from the CCD image sensor into the computer memory, and performs digital fusion and temperature recognition processing on the target image to obtain the temperature field distribution of the test target.

3 System Software Design

The software design process of the engine temperature field test system based on image fusion is shown in Figure 3.

The entire software design mainly includes the following three parts: image fusion preprocessing and image fusion, fusion image postprocessing, and color temperature recognition of the test target temperature-indicating paint image. Image fusion preprocessing refers to performing image correction, image enhancement, and image registration preprocessing on N target images obtained by N sensors at different angles before image fusion. The purpose of image fusion is to expand the system's operating range, improve system reliability and image spatial resolution, improve image accuracy, enhance feature display capabilities, provide change test capabilities, and replace or repair defects in image data.

Commonly used image fusion algorithms include space-based image fusion and transform-domain-based image fusion. This project uses the wavelet fusion algorithm in the transform-domain image fusion algorithm to fuse the target images. This algorithm has the advantages of removing feature correlation, providing multi-scale information, and enhancing the features and details of interest.

The result of image fusion based on wavelet transform algorithm is shown in Figure 4. Image C is the fusion image of image A and image B. Here, the wavelet basis coefficient is sym6, the number of decomposition layers is 3, the low frequency is averaged, and the high frequency is weighted by the window coefficient.

Three evaluation indicators of image fusion are calculated: information entropy, spatial frequency and average gradient. By comparing the numerical results, the three indicators of the fused image are significantly improved, which means that the quality and clarity of the fused image are significantly improved.

After image fusion, image post-processing is performed: including feature selection, spatial transformation, color quantization, and image segmentation. Finally, the temperature of the target image is identified according to the color temperature characteristics of the temperature-indicating paint. The method for determining the temperature value of the temperature-indicating paint color image is as follows: To determine the temperature value of point A, it is necessary to find the point B on the curve that is closest to point A. The distance between point A and point B can be expressed by the Euclidean distance. If AB is the minimum distance, it is considered that the temperature value corresponding to point B is the temperature of point A.

4 Conclusion

In this test system, image fusion is the key to image processing, which directly determines the quality and clarity of the processed image. Experiments have shown that this system significantly improves the test efficiency and test accuracy of the engine temperature field, and has very good application and promotion value.