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基于表面测温的管内流量及温度识别问题在红外无损检测领域还处于起步阶段,是目前红外无损检测技术从定性向定量发展的关键理论基础.针对目前流量识别结果较温度识别结果差和基于最小二乘拟合的识别方法精度有限的问题,使用Gnielinski关联式建立管道充分发展段的一维传热模型,并采用Levenberg-Marquardt(L-M)算法根据表面检测温度进行管内流体流量及温度的识别.通过理论推导和具体算例得,待识别参数的相对识别误差值与参数灵敏度最大值和参数真实值乘积的绝对值成反比关系,含测温误差的温度分布与基于最小二乘拟合得到的温度分布之间的方差不等于测温误差标准偏差的平方与测温点个数的乘积,同时提出了基于表面测温等方差拟合的管内流量及温度的识别方法.数值实验证明该方法在存在测温误差时仍可以精确识别出管内流量及温度.“,”Identification of flow rate and temperature in a heat supply pipeline based on surface temperature measurement is still at the initial stage in the field of infrared nondestructive testing, which is the key theory for the development of infrared nondestructive testing. In order to solve the problem that the flow rate identification result was less accurate than the temperature identification result and the accuracy of the identification method based on least square fitting was limited, a heat transfer model of the fully developed region of the pipeline had been built based on Gnielinski correlation equation, and the identification problem had been solved by Levenberg-Marquardt (L-M) algorithm based on surface temperature measurement. Through theoretical derivation and numerical examples, it has been found that the parameter relative identification error is inversely proportional to the absolute value of the product of the sensitivity maximum and the true value of the parameter, and the variance between the measurement temperature distribution with measurement error and the temperature distribution based on least square fitting is not equal to the product of the standard deviation of the measurement error and the number of measurement points. The identification method based on equal variance fitting of surface temperature measurement was proposed. Numerical experiments have proved that the method can accurately identify the flow rate and temperature in the pipeline with measurement error.