γ-radiation noise-filtering algorithm for optical encoder based on improved adaptive line enhancer

Fig. 13. Layout of photoelectric encoder γ-radiation at experimental TID test site (a) Inside the radiation environment, (b) Outside the radiation environment

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Fig. 14. Output waveform of photoelectric encoder when starting work

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Fig. 15. Diagram of filtering effect of improved algorithm

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Fig. 16. Output square wave of photoelectric encoder

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Table 1. Simulation conditions for algorithm parameter analysis

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Table 1. Simulation conditions for algorithm parameter analysis

条件项目 Conditional items	设定值 Setpoint
阶数 Order	20
初始权值 Initial weighting	0
信号频率 Signal frequency	40
信号幅值 Signal amplitude	0.8
信噪比 SNR / dB	8.5
采样点数 Sampling point	1 024

Table 2. Number of iterations at convergence point of algorithm when β/η changes
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Table 2. Number of iterations at convergence point of algorithm when β/η changes
β取值
Value of β
迭代次数
Iteration number
η取值
Value of η
迭代次数
Iteration number
0.1 300 400 300
0.5 150 200 180
0.9 80 100 70
1.3 80 50 100

Table 3. Number of iterations and errors at convergence of each algorithm at normal signal-to-noise ratio
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Table 3. Number of iterations and errors at convergence of each algorithm at normal signal-to-noise ratio
算法类型 Algorithm type LMS NLMS TCLMS ITCLMS IALEM
迭代次数 Iteration number 300 180 280 280 50
稳态误差 Steady state error / % 0.10 0.10 0.15 0.18 0.10

Table 4. Number of iterations and errors at convergence of each algorithm at low signal-to-noise ratio
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Table 4. Number of iterations and errors at convergence of each algorithm at low signal-to-noise ratio
算法类型 Algorithm type LMS NLMS TCLMS ITCLMS IALEM
迭代次数 Iteration number 250 250 300 300 50
稳态误差 Steady state error / % 0.15 0.15 0.25 0.28 0.10

Table 5. Comparison of computational complexity between IALEM and TCLMS algorithms
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Table 5. Comparison of computational complexity between IALEM and TCLMS algorithms
算法
Algorithm
乘法
Multiplication
加法
Addition
TCLMS 4 2
IALEM 4 2

Table 6. Signal-to-noise ratio before and after IALEM filtering
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Table 6. Signal-to-noise ratio before and after IALEM filtering
信号阶段 Signaling phase SNR / dB
滤波前 Pre-filter 10
滤波后 Post-filter 20.73

Table 7. Signal-to-noise ratio before and after filtering during IALEM experimental validation
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Table 7. Signal-to-noise ratio before and after filtering during IALEM experimental validation
信号阶段Signaling phase SNR / dB
滤波前 Pre-filter 6.8
滤波后 Post-filter 15.3

Table 8. Oscilloscope measurement values before and after IALEM filtering
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Table 8. Oscilloscope measurement values before and after IALEM filtering
测量值
Measured value
T₁ / μs T₂ / μs T₃ / μs T₄ / μs
滤波前Pre-filter 608 380 298 190
滤波后Post-filter 560 420 223 296

Table 9. Output errors of photoelectric encoder before and after IALEM filtering
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Table 9. Output errors of photoelectric encoder before and after IALEM filtering
信号阶段
Signaling phase
均匀性误差U_e
Uniformity error / %
正交性误差O_e
Orthogonality error / %
滤波前
Pre-filter
46.2 22.1
滤波后
Post-filter
28.6 14.1

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Wei DONG, Zhonghua WANG, Chao JIANG, Tian QIU. γ-radiation noise-filtering algorithm for optical encoder based on improved adaptive line enhancer[J]. NUCLEAR TECHNIQUES, 2024, 47(8): 080403

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Paper Information

Category: NUCLEAR ELECTRONICS AND INSTRUMENTATION

Received: Nov. 22, 2023

Accepted: --

Published Online: Sep. 23, 2024

The Author Email: WANG Zhonghua (王中华)

DOI:10.11889/j.0253-3219.2024.hjs.47.080403

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Simulation conditions for algorithm parameter analysis

Table 1. Simulation conditions for algorithm parameter analysis

Table 2. Number of iterations at convergence point of algorithm when β/η changes

Table 2. Number of iterations at convergence point of algorithm when β/η changes

Table 3. Number of iterations and errors at convergence of each algorithm at normal signal-to-noise ratio

Table 3. Number of iterations and errors at convergence of each algorithm at normal signal-to-noise ratio

Table 4. Number of iterations and errors at convergence of each algorithm at low signal-to-noise ratio

Table 4. Number of iterations and errors at convergence of each algorithm at low signal-to-noise ratio

Table 5. Comparison of computational complexity between IALEM and TCLMS algorithms

Table 5. Comparison of computational complexity between IALEM and TCLMS algorithms

Table 6. Signal-to-noise ratio before and after IALEM filtering

Table 6. Signal-to-noise ratio before and after IALEM filtering

Table 7. Signal-to-noise ratio before and after filtering during IALEM experimental validation

Table 7. Signal-to-noise ratio before and after filtering during IALEM experimental validation

Table 8. Oscilloscope measurement values before and after IALEM filtering

Table 8. Oscilloscope measurement values before and after IALEM filtering

Table 9. Output errors of photoelectric encoder before and after IALEM filtering

Table 9. Output errors of photoelectric encoder before and after IALEM filtering