基于MEC-BP高海拔隧道供氧浓度与劳动强度规律

陈政; 郭春; 谌桂舟; 张佳鹏; 许昱旻

doi:10.3969/j.issn.0258-2724.20210669

基于MEC-BP高海拔隧道供氧浓度与劳动强度规律

doi: 10.3969/j.issn.0258-2724.20210669

西南交通大学土木工程学院，四川成都 610031

基金项目: “十三五”国家重点研发计划（2019YFC0605104）；教育部科技产学合作协同育人项目（201801221005）；四川省教育科研资助（2020597）

详细信息

作者简介:
陈政（1992—），男，博士研究生，研究方向为隧道及地下工程，E-mail：1847485788@qq.com

中图分类号: U25
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- 文章访问数: 237
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- 被引次数: 0
出版历程
- 收稿日期: 2021-08-16
- 修回日期: 2021-12-16
- 网络出版日期: 2023-04-13
- 刊出日期: 2022-12-01

Oxygen Supply Concentration and Labor Intensity of High Altitude Tunnel Based on MEC-BP

School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China

摘要

摘要:
为解决高海拔隧道施工供氧关键技术，开展高海拔隧道供氧浓度及劳动功率对劳动强度的影响研究. 通过在西藏拉萨达孜区的圭嘎拉隧道进行现场实测，以平均能量代谢率作为衡量劳动强度指标，采用肺通气量仪搜集6名测试人员在不同劳动强度（50、75 W和100 W劳动功率）和供氧浓度（20.9%、25.0%和29.0%）下的肺通量数据，并转化为劳动强度指标，运用基于思维进化算法的前馈神经网络（mind evolutionary computation back-propagation, MEC-BP）对劳动强度指标进行拟合. 研究结果表明：MEC-BP神经网络拟合数据的拟合优度略高于GA-BP 和BP 神经网络的拟合优度；50 W低劳动功率下，施工人员平均能量代谢率对氧浓度的变化较小，最大约0.1 kJ/(min•m²)；在100 W较高劳动功率下，25%供氧浓度可作为4 200 m高原供氧浓度参考值.
- 隧道 /
- 供氧 /
- 神经网络 /
- 拟合 /
- 平均能量代谢率
Abstract:
In order to solve the key technology of oxygen supply in high-altitude tunnel construction, the influence of oxygen supply concentration and labor power on labor intensity in a high-altitude tunnel is studied. Through field measurement in Guigala Tunnel in Dazi District, Lhasa, Tibet, the average energy metabolic rate is used as the indicator to measure labor intensity. The lung flux data of six testers under different labor intensities (labor power of 50, 75, and 100 W) and oxygen supply concentrations (20.9%, 25.0%, and 29.0%) are collected by using the lung ventilation meter, and the data are then converted into the indicator of labor intensity. The mind evolutionary computation back-propagation (MEC-BP) neural network is used to fit the labor intensity indicator. The results show that the goodness of fit of the MEC-BP neural network is slightly higher than that of GA-BP and BP neural networks. Experimental tests and MEC-BP neural network fitting data show that under low labor power of 50 W, the average energy metabolic rate of construction personnel changes slightly with oxygen concentration, with a maximum value of about 0.1 kJ/(min•m²). Under high labor power of 100 W, an oxygen supply concentration of 25% can be used as the reference value of oxygen supply concentration at the plateau of 4 200 m.
- tunnel /
- oxygen supply /
- neural networks /
- fitting /
- average energy metabolic rate

HTML全文

图 1 MEC-BP神经网络框架

Figure 1. MEC-BP neural network framework

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图 2 现场测试及实验仪器

Figure 2. Field test and experimental instrument diagram

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图 3 BP神经网络结构

Figure 3. Structure diagram of BP neural network

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图 4 MEC-BP迭代收敛及拟合优度

Figure 4. MEC-BP iterative convergence and goodness of fit

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图 5 GA-BP拟合优度

Figure 5. GA-BP goodness of fit

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图 6 BP拟合优度

Figure 6. BP goodness of fit

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图 7 MEC-BP拟合平均能量代谢率变化

Figure 7. MEC-BP fitting average energy metabolic rate change chart

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表 1 现场测试及计算数据

Table 1. Field test and calculation data

测试人员编号	氧浓度/%	功率/W	肺通量/(L·min⁻¹)	A/m²	测试环境温度/K	标准肺通气量/ (L·min⁻¹)	平均能量代谢率/ (kJ·(min·m²)⁻¹)
1 号	20.9	50	10.52	1.86	298.15	5.78	0.57
	25.0	50	7.88	1.86	286.15	4.51	0.50
	29.0	50	7.29	1.86	284.15	4.20	0.48
	20.9	75	20.03	1.86	296.15	11.08	0.96
	25.0	75	17.07	1.86	288.15	9.71	0.69
	29.0	75	17.02	1.86	290.15	9.61	0.67
	20.9	100	32.75	1.86	298.15	18.00	2.21
	25.0	100	27.88	1.86	292.15	15.64	1.80
	29.0	100	27.94	1.86	292.15	15.67	1.80
2 号	20.9	50	9.75	1.80	299.15	5.34	0.56
	25.0	50	7.52	1.80	292.15	4.22	0.49
	29.0	50	6.73	1.80	284.15	3.88	0.47
	20.9	75	20.45	1.80	298.15	11.24	1.06
	25.0	75	18.12	1.80	298.15	9.96	0.81
	29.0	75	16.41	1.80	284.15	9.46	0.71
	20.9	100	27.54	1.80	298.15	15.13	1.80
	25.0	100	23.89	1.80	290.15	13.49	1.50
	29.0	100	22.87	1.80	289.15	12.96	1.39
3 号	20.9	50	8.64	1.72	298.15	4.75	0.53
	25.0	50	7.39	1.72	291.15	4.16	0.50
	29.0	50	6.91	1.72	283.15	4.00	0.49
	20.9	75	23.56	1.72	297.15	12.99	1.52
	25.0	75	20.45	1.72	298.15	11.24	1.17
	29.0	75	19.31	1.72	285.15	11.10	1.14
	20.9	100	29.44	1.72	298.15	16.18	2.14
	25.0	100	26.56	1.72	289.15	15.05	1.92
	29.0	100	25.44	1.72	285.15	14.62	1.84
4 号	20.9	50	10.74	1.85	298.15	5.90	0.59
	25.0	50	7.86	1.85	291.15	4.42	0.49
	29.0	50	6.66	1.85	282.15	3.87	0.46
	20.9	75	18.64	1.85	295.15	10.35	0.83
	25.0	75	16.24	1.85	292.15	9.11	0.59
	29.0	75	13.52	1.85	284.15	7.80	0.53
	20.9	100	25.79	1.85	298.15	14.17	1.55
	25.0	100	22.17	1.85	300.15	12.10	1.17
	29.0	100	21.25	1.85	283.15	12.30	1.20
5 号	20.9	50	10.22	1.99	298.15	5.62	0.54
	25.0	50	8.54	1.99	292.15	4.79	0.49
	29.0	50	7.47	1.99	282.15	4.34	0.47
	20.9	75	19.39	1.99	298.15	10.66	0.74
	25.0	75	18.72	1.99	292.15	10.50	0.71
	29.0	75	18.35	1.99	283.15	10.62	0.73
	20.9	100	28.27	1.99	298.15	15.54	1.60
	25.0	100	25.88	1.99	299.15	14.17	1.37
	29.0	100	24.33	1.99	285.15	13.98	1.33
6 号	20.9	50	9.99	1.85	298.15	5.49	0.56
	25.0	50	7.35	1.85	291.15	4.14	0.48
	29.0	50	6.19	1.85	282.15	3.59	0.45
	20.9	75	19.31	1.85	298.15	10.61	0.88
	25.0	75	19.17	1.85	294.15	10.68	0.89
	29.0	75	18.84	1.85	292.15	10.57	0.87
	20.9	100	27.5	1.85	300.15	15.01	1.70
	25.0	100	26.09	1.85	299.15	14.29	1.57
	29.0	100	25.13	1.85	289.15	14.24	1.56

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参考文献(16)

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基于MEC-BP高海拔隧道供氧浓度与劳动强度规律

doi: 10.3969/j.issn.0258-2724.20210669

作者简介: 陈政（1992—），男，博士研究生，研究方向为隧道及地下工程，E-mail：1847485788@qq.com

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Oxygen Supply Concentration and Labor Intensity of High Altitude Tunnel Based on MEC-BP

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作者简介:
陈政（1992—），男，博士研究生，研究方向为隧道及地下工程，E-mail：1847485788@qq.com