# Pull-Out Test and Mechanical Properties Analysis Based on Intelligent Bolt and Internet of Things
## 6 Conclusions  
The intelligent bolt pull-out test system based on the Internet of Things proposed in this paper can play a role in comprehensive monitoring of the bolt pull-out test process, and can provide more basis for deformation analysis and safety state evaluation of supporting rock and soil masses. 1. The stress process of bolt rod end tension-rod end displacement is divided into three stages, namely quasi-elastic stage, strengthening stage and failure stage. The stress history of bolts with different anchorage lengths is the same, but the curve shape changes from steep to slow with the increase in anchorage length. Under normal working conditions, increasing the length of the bolt can reduce the deformation of the bolt to a certain extent and effectively exert the passive anchoring effect of the bolt. 2. By increasing the length of the anchor rod, the ultimate uplift bearing capacity of the anchor rod can be improved, but the improvement is very limited. The anchorage length of the anchor rod in the loess layer selected in this experiment is suggested to be 10-16 m, which can not only meet the requirements of engineering safety and quality, but also avoid waste and save cost. 3. The axial force of the bolt gradually decays along the length direction of the anchorage section, and the axial force decays the most in the first half of the rod body. Compared with the high anchorage length bolt, the axial force of the low anchorage length bolt is relatively uniform, and the range of axial force is increased. The frictional resistance of the bolt is unevenly distributed along the length direction of the anchorage body, reaching a peak at the front end of the anchorage body, and gradually decreasing with the increase in the anchorage length, showing a single peak curve. When the tension at the end of the rod reaches the ultimate pull-out bearing capacity, the peak friction resistance is basically unchanged with the increase in the anchorage length, while the average friction resistance in the middle of the rod body is significantly reduced. Intelligent bolts can monitor key information in real time and have great application value in many fields. Its further research direction mainly has two aspects:  
1. Data processing and analysis: With the help of big data and cloud computing, the massive monitoring data generated by the increase in applications are efficiently stored, managed and analyzed, and the rules are mined to accurately predict the performance and safety status ; intelligent algorithms such as machine learning and deep learning are studied, and prediction models are established through historical data training to achieve fault diagnosis and early warning, such as using neural networks to evaluate forces. 2. Material and structure design: Explore new materials (such as high-strength alloy steel, composite materials) to manufacture bolt anchors, improve mechanical properties and durability, and ensure the compatibility of materials and sensors; the structure design is optimized to make the installation, maintenance and replacement more convenient, improve the anti-interference ability and reduce the maintenance cost. **Author Contributions:** Study conception and design: [PERSON] and [PERSON]; data collection: [PERSON]; analysis and interpretation of results: [PERSON] and [PERSON]; draft manuscript preparation: [PERSON] and X.L. All authors have read and agreed to the published version of the manuscript. **Funding:** The authors received no specific funding for this study. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request. **Conflicts of Interest:** Author [PERSON] was employed by the company The-First-Company of China Construction Sixth Engineering Bureau Corp., Ltd.