Thermal Image Data Processing Technology of Pseudo Soldering Based on Trend Analyzing
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摘要: 针对现有检测手段难以解决的外观正常、又有电气连接的电子产品虚焊类缺陷的问题，本文采用脉冲红外热像检测方法获取温度数据，引入趋势分析法建立了虚焊类缺陷热像数据拟合曲线特征参量与不同虚焊程度缺陷之间的对应关系，成功解决了过余温度信号中难以辨识背景噪声和焊点缺陷信号的问题，提高了热像信号的分辨率和信噪比。Abstract: Pseudo soldering with a normal appearance and electrical connections cannot be effectively detected by the existing detection technology. Pulse infrared detection technology was applied, and the trend that analyzes processes was adopted to establish the relationship between the degree of pseudo soldering and characteristic parameters of the infrared fitting curve. It is difficult to distinguish the background noise, and the signal of the pseudo soldering from excess temperature was successfully resolved. Results show that the resolution and signal-to-noise ratio were improved.
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Key words:
- pulse infrared thermal /
- pseudo soldering /
- trend analyzing
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图 3 焊点模型示意图
Figure 3. Schematic diagram of solder joint model
1− electron components(SMT); 2− Solder joint; 3− Pseudo soldering(Air void); 4−copper layer(pad & wire); 5− Circuit board(PCB)
图 5 同一批次试验数据焊点温度随时间变化曲线
Figure 5. Time dependence curve of solder joint temperature of the same batch of experimental data
图 7 仿真数据降温段3阶至8阶多项式拟合结果
Figure 7. Third to eighth order polynomial fitting results of cooling section of simulation data
图 9 拟合降温速率最大值与虚焊程度散点图
Figure 9. Scatter diagram of fitting the maximum cooling rate and the degree of false welding
图 11 不同时间点的虚焊焊点原始热像图
Figure 11. Original thermal image of pseudo solder joint at different time
图 12 试验数据降温段3阶~8阶多项式拟合结果
Figure 12. Third to eighth order polynomial fitting results for cooling section of experimental data
图 14 拟合结果导数绝对值最大值与虚焊程度散点图
Figure 14. Scatter diagram of maximum absolute value of derivative of fitting results and false soldering degree
表 1 仿真数据降温段3阶至8阶多项式拟合评价指标
Table 1. Evaluation index of third to eighth order polynomial fitting in cooling section of simulation data
Fitting Order Sum of Squares of Errors（SSE） R-Square Root Mean Square（RMSE） 3 1407.1 0.7753 2.6136 4 1012.9 0.8375 2.2228 5 762.77 0.8770 1.9337 6 592.89 0.9039 1.7090 7 470.74 0.9234 1.5266 8 378.84 0.9380 1.3729 
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表 2 试验数据降温段3阶~8阶多项式拟合评价指标
Table 2. Evaluation index of third to eighth order polynomial fitting in cooling section of experimental data
Fitting Order SSE R-Square RMSE 3 1.5125 0.9897 0.1091 4 0.4450 0.9970 0.0594 5 0.1359 0.9991 0.0330 6 0.0583 0.9996 0.0217 7 0.0324 0.9998 0.0162 8 0.0272 0.9998 0.0149
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