## 5 Conclusions  
Accurately distinguishing and recognizing the working states of HBM is fundamental to ensure the safe and efficient construction of high-rise concrete structures. However, the current research on HBM monitoring mainly focuses on special components or working conditions, and lacks the automatic identification of HBM workflow. In this study, we de veloped an ML-based method for detecting the four working states of an HBM--operating, climbing, pumping, and idling--using triaxial accelerometers and verified it in a super-high-rise building project. The main conclusions are summarized as follows:  
1. The comparison of the vibration signal characteristics for the four states of the HBM was completed and showed that the amplitude and frequency differences between the vibration signals in the idling and pumping states were more pronounced and therefore easier to distinguish. Conversely, the amplitude and frequency of the vibration signals in the operating and climbing states were more similar to each other. As a result, we developed an offset axis crossing count feature tailored to the working characteristics of the HBM. This feature improves our ability to distinguish between the vibration signals occurring during the operating and climbing states;
2. Five typical features such as the mean, root mean square, peak-to-peak, relative power spectral entropy, and the offset axis crossing count values of a single triaxial accelerometer signal were used, which can better recognize the four key states of the HBM. A classification output rule based on the actual workflow of the HBM was established, which can further improve the accuracy of recognizing the working states of the HBM. The number of reporting errors under different states was significantly reduced, and the output results were smoother;
3. The method was practically applied in the SXC super-high-rise construction project, and the overall accuracy rate of the HBM working state recognition reached 97.4%, which shows the strong potential of the method in engineering applications. The method can effectively solve the problem of the lack of real-time monitoring of traditional formwork equipment in the construction process by monitoring and recognizing the four working states of an HBM in real time. This provides a basis for the accurate control and action execution of each HBM component, and for reducing the equipment vacancy rate, ensuring the safe operation of equipment and the quality of concrete structure construction.  
Conceptualization, X.P. and T.Z.; methodology, X.P. and X.L.; software, X.L.; validation, X.P., Z.Z. and T.Z.; formal analysis, X.P. and Z.Z.; investigation, T.Z. and X.L.; resources, G.Z. and L.Z.; data curation, X.P. and L.Z.; writing--original draft preparation, X.P.; writing--review and editing, X.P., Z.Z. and T.Z.; visualization, X.P. and Z.Z.; supervision, T.Z., G.Z. and Z.Z. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Key R&D Program of China (Grant No. 2022 YFC3802200), Shanghai Enterprise Innovation Development and Capacity Enhancement Project (Grant No. 2022007).  
Not applicable.  
The datasets used in this study are available from the authors upon request.  
The authors declare no conflict of interest.