Unpowered dust removal device stereogram. by Yuxuan Liu (349237)

“…Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. …”

Physical model. by Yuxuan Liu (349237)

“…Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. …”

Dust particle flow trace diagram. by Yuxuan Liu (349237)

“…Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. …”

Discrete phase parameter setting. by Yuxuan Liu (349237)

“…Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. …”

Dust deposition, escape data table. by Yuxuan Liu (349237)

“…Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. …”

Generated spline library. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Correlation coefficient matrix. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Actual measurement of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus learning rate. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus training parameters. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Assembly process of machine recognition form. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Unpowered dust removal system field physical map. by Yuxuan Liu (349237)

“…Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. …”

Process of steel truss incremental launching. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

CGAN and AutoML stacking device. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Comprehensive prediction process of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Shape error manual calculation process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

U-wave estimates versus R-matrix noise variance. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Sliding window process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Assembly error angle of a single spline. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Original record form of error matrix. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”