Xing Jian, Liu Zhijun, Luo Jiashun, Han Bing
College of Information and Computer Engineering, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China.
College of Mechanical and Electrical Engineering, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China.
Rev Sci Instrum. 2020 Oct 1;91(10):104903. doi: 10.1063/5.0016747.
Multiwavelength pyrometry (MWP) is one of the most powerful tools for the precise measurement of high temperatures on the surfaces of non-gray materials. However, the unknown spectral emissivity of target materials is the most difficult obstacle to overcome in processing temperature inversion data using MWP. A direct and fast generalized inverse matrix normalization (GIM-NOR) data processing algorithm based on GIM theory for underdetermined equations is proposed in order to minimize the effects arising from unknown emissivity. The shape of the emissivity distribution is obtained so that the channel with the greatest emissivity can be selected in order to obtain a value close to the real temperature. The final inversion accuracy is then further improved using a NOR compensation method. Six kinds of materials with a distribution of emissivities at 1800 K were used to simulate and verify the proposed algorithm. The results show that the average relative error of temperature inversion was 0.63%, obtained within 8 ms computation time using a standard desktop computer, and the accuracy and efficiency were largely unaffected when 5% random noise was inserted into the simulation data. A set of experimental data for rocket nozzle temperature measurements with MWP were also processed based on the proposed novel algorithm. The results show that the relative error on the temperature was less than 0.50%, for a design temperature of 2490 K, and that the processing efficiency was very high, that is, within 9 ms. Simulation and experiment both proved that the proposed efficient data processing algorithm for MWP based on GIM theory was unaffected by emissivity and achieved good inversion precision and fast data processing. Therefore, the proposed new data processing algorithm for MWP data for measuring transient high temperatures has very broad potential applications, and it also provides a theoretical basis for measuring high-temperature fields using MWP.
多波长高温测定法（MWP）是精确测量非灰色材料表面高温的最强大工具之一。然而，目标材料未知的光谱发射率是使用MWP处理温度反演数据时最难克服的障碍。为了最小化未知发射率产生的影响，提出了一种基于欠定方程广义逆矩阵（GIM）理论的直接快速广义逆矩阵归一化（GIM-NOR）数据处理算法。得到发射率分布的形状，以便选择发射率最大的通道以获得接近真实温度的值。然后使用NOR补偿方法进一步提高最终的反演精度。使用六种在1800 K时具有发射率分布的材料对所提出的算法进行了模拟和验证。结果表明，使用标准台式计算机在8毫秒的计算时间内获得的温度反演平均相对误差为0.63%，并且当在模拟数据中插入5%的随机噪声时，精度和效率基本不受影响。还基于所提出的新算法处理了一组使用MWP测量火箭喷管温度的实验数据。结果表明，对于2490 K的设计温度，温度相对误差小于0.50%，并且处理效率非常高，即在9毫秒内。模拟和实验均证明，所提出的基于GIM理论的MWP高效数据处理算法不受发射率影响，具有良好的反演精度和快速的数据处理能力。因此，所提出的用于测量瞬态高温的MWP数据的新数据处理算法具有非常广泛的潜在应用，并且也为使用MWP测量高温场提供了理论依据。
