At present, the identification of icing status of transmission line conductors is mainly manual. Although the mainstream method based on intelligent vision and UAV can solve the manual problem, the specific situation of conductor icing cannot be further mastered. Based on the information fusion of optical fiber sensor and continuous wavelet decomposition, the online sensing method of transmission line icing is studied. This method uses the transmission line conductor vibration and stress signal acquisition method based on distributed optical sensing technology. After the transmission line conductor vibration and stress signals are collected online by multiple optical fiber sensors, the fusion model based on Elman neural network is used to fuse the multiple optical fiber sensing information, and then the spectrum feature extraction method of optical fiber sensing signal based on continuous wavelet decomposition is used. The spectral characteristics of fused optical fiber sensing signals are extracted as diagnostic samples of the online perception method of conductor icing based on improved logical regression, and the binary classification method is used to identify whether there is icing problem on transmission line conductors online. In the experiment, this method can accurately perceive the online perception results of rime type icing, mixed rime type icing, wet snow type icing, and has the function of accurately sensing the icing status of transmission line conductors.

In order to solve the problem of frequent disconnection of carbon fiber conductors for large-capacity and long-distance transmission due to undetectable hidden defects,a detection method for hidden defects in multi-strand carbon fiber composite core conductors based on optical fiber sensing technology was proposed.The operating environment of the wire was established and the operating conditions were simulated.The time-domain reflection technology based on distributed fiber Brillouin scattering was adopted to detect the temperature and strain distribution of carbon fiber wires,and the optical time-domain reflection technology was combined to detect the loss of optical fibers in carbon fiber wires.Comprehensive comparative analysis was conducted to obtain signal feature quantities such as fiber temperature,strain and loss that could characterize hidden defects in multi-strand carbon fibers,and a neural network model was constructed with each signal feature quantity as input to the model.Through model training,the various weight coefficients within the model were determined,enabling it to effectively detect hidden defects in multi-strand carbon fiber composite core wires.The experimental results show that this method can effectively obtain signal feature quantities of various types of fiber optic and can accurately detect various hidden defects in wires,which has important practical application values.

以某综合管廊为研究背景,利用PyroSim模拟软件建立的仿真计算模型,研究了设立挡烟垂壁、改变防火门开启程度、增设排烟设施等情况下的烟气蔓延规律.研究发现:在烟气未充满管廊时,挡烟垂壁会使烟气蔓延速度降低,烟气蔓延速度与挡烟垂壁高度成反比;防火门打开会使火灾烟气蔓延至相邻防火分区,烟气蔓延速率与防火门开启程度成正相关;机械排烟设施会使烟气蔓延速度显著降低,最高降低约50％,当烟气完全充满整个管廊时,会显著降低综合管廊内烟气浓度,烟气层温度最高降幅32℃,能见度最高增加了66％.通过对综合管廊内烟气蔓延的研究,探寻防治综合管廊烟气蔓延的最佳措施,为综合管廊烟气防治的实际工程应用提供参考.

电缆广泛应用于城市建筑和工业场所,一旦电缆被点燃将会造成严重的后果。而电缆在敷设时并非单根,故本文以水平方向上的平行双电缆为研究对象,通过对其燃烧过程中的3种传热方式进行分析,建立预测火蔓延速度的数学模型。开展水平方向上的平行双电缆火蔓延实验研究,分析电缆间距对火蔓延特性的影响,发现火焰高度、火焰宽度、火蔓延速度随间距的增大而先增大后减小,实验结果和模型预测结果较一致。

理论分析了几何尺寸测量误差和复电容测量误差对接触法和非接触法介电谱测量误差的影响,并对二者的误差进行了比较,然后对电极间隙距离、试样介电常数对介电谱测量误差的影响进行了仿真分析.基于介电谱仪测量得到高温硫化硅橡胶的介电谱,分析了几何尺寸(试样厚度)测量误差对接触法和非接触法测量结果准确性的影响.结果表明:非接触法受几何尺寸和复电容测量准确性的影响比接触法要大,对仪器测量的准确性要求较高,容易产生比接触法更大的误差.非接触法的相对介电常数测量误差随试样相对介电常数的增加先快速增大然后逐渐稳定;试样相对介电常数不大于5时,随着电极间隙距离的增加,相对介电常数的测量误差快速增大.非接触法适用于几何尺寸和介电常数测量准确性足够高的场合.