Search

We herein describe the synthesis of a new class of axially chiral aza/boracyclophanes (BDN1, BXN1, BDB1 and BXB1) using binaphthyls as chiral building blocks and the main-group (B/N) chemistry with tunable electronic effects. All macrocycles substituted with triarylamine donors or triarylborane acceptors are strongly luminescent. These macrocycles showed two distinct meta and para π-conjugation pathways, leading to the formation of quasi figure-of-eight and square-shaped conformations. Interestingly, comparison of such structural models revealed that the former type of macrocycles BXN1 and BXB1 gave higher racemization barriers relative to the other ones. The results reported here may provide a new approach to engineer the optical stability of π-conjugated chiral macrocycles by controlling π-substitution patterns. The ring constraints induced by macrocyclization were also demonstrated to contribute to the configurational persistence as compared with the open-chain analogues p-BTT and m-BTT.

The shield type temporary support robot is an important component of the intelligent excavation robot system for large section roadways that adapts to the coexistence of dirt and debris. Its main function is to provide a safe and reliable workspace for achieving 'parallel excavation and support' operations. In order to enhance the safe and stable support of the shield type temporary support robot for surrounding rock during its pushing and driving process, based on the structure, working environment, and operational requirements of the shield type temporary support robot, a mathematical model of its pushing amount and support force during pressurized driving, as well as a dynamic model of pressurized driving, are established. A hydraulic control system for the shield type temporary support robot driving under pressure is designed. The system mainly consists of a support hydraulic system and a driving hydraulic system. During static support, the support hydraulic system needs to constantly output a support force greater than the weight of the upper shield body itself, and the driving hydraulic system is in standby mode. When driving under pressure, the support hydraulic system and the driving hydraulic system work simultaneously, ensuring that the temporary support robot 'reducing stress without leaving the roof' while steadily moving forward with the roof under pressure at all times. A precise control method for shield type temporary support robot driving under pressure based on fuzzy PID is proposed. The pressure and displacement signals of the temporary support robot are collected in real time by displacement sensors integrated on the displacement cylinder and pressure sensors in the hydraulic circuit. The signals are used to reflect the changes in support force and driving displacement during the temporary support robot's driving under pressure. Based on the error and error rate of the support force and displacement, the fuzzy PID algorithm is used to modify the control parameters of the support force and displacement, achieving reliable control of driving under pressure based on the fuzzy PID algorithm. Both simulation and experimental results show that the effect of fuzzy PID control is superior to traditional PID control. Under fuzzy PID control, the relative error of support force during the pushing and driving process of the shield type temporary support robot is less than 1%, and the driving displacement error is less than 2 mm. Moreover, the response speed of support force and pushing amount control is fast, ensuring the safe and stable support of the surrounding rock during the pushing and driving process.

The adaptive cutting technology of the shearer is a key technology for achieving intelligent mining in fully mechanized working faces. In order to solve the problem of low automatic cutting precision of the shearer in complex coal seams, a prediction method for the height adjustment of shearer drum based on improved gated recurrent neural network (GRU) is proposed. Considering the correlation between adjacent data in the longitudinal and transverse directions of the cutting trajectory, the fixed length sliding time window method is used to obtain the height data of the shearer drum. The input data is divided into continuous and adjustable subsequences, while processing the feature information in the transverse and longitudinal directions. To improve the prediction efficiency of the model and meet the real-time requirements of cyclic cutting, causal convolution gated recurrent unit(CC-GRU) is proposed to perform dual feature extraction and dual data filtering on input data. CC-GRU utilizes causal convolution to focus on the local temporal features in the longitudinal direction of the sequence in advance, in order to reduce computational costs and improve computational speed. CC-GRU uses gating mechanism to serialize and model the features obtained from convolution to capture long-term dependencies between elements. The experimental results show that using the CC-GRU model to predict the height adjustment of the shearer drum, the MAE is 43.80 mm, MAPE is 1.90%, RMSE is 50.35 mm, the determination coefficient is 0.65, and the prediction time is only 0.17 seconds. Compared to long short term memory (LSTM) neural networks, GRU, and temporal convolutional network (TCN), the CC-GRU model has a faster prediction speed and higher prediction precision. It can more accurately predict the height adjustment trajectory of the shearer in real time. This provides a basis for the establishment of coal seam models in the working face and the prediction of the height adjustment trajectory of the shearer.

The advantages and disadvantages of five commonly used mining monorail cranes, namely explosion-proof diesel engine monorail crane, explosion-proof battery monorail crane, pneumatic monorail crane, rope traction monorail crane, and cable dragging monorail crane, are analyzed. It is pointed out that explosion-proof diesel engine monorail crane and explosion-proof battery monorail crane have been widely used for underground equipment and material transportation in coal mines due to their strong transportation capacity. The explosion-proof battery monorail crane has green and clean features. It has gradually become a key research and development equipment for underground auxiliary transportation in coal mines. This paper analyzes the research status of the mining monorail crane system from four aspects of battery drive, positioning, measurement and control, and information transmission. It is pointed out that the current mining monorail crane system has low automation and intelligence levels. To achieve intelligent transportation of the monorail crane, it is necessary to study the key technologies such as lithium battery explosion-proof and battery management of the monorail crane, global and local fusion precise positioning, multi-sensor information fusion intelligent measurement and control, edge computing information transmission, etc. For the explosion-proof and battery management technology of lithium battery, a topology optimization design method of explosion-proof large capacity lithium battery structure based on variable density method, and a balanced management scheme based on improved sparrow search algorithm/genetic algorithm are proposed. For precise positioning technology, a global positioning method based on inertial navigation and odometer fusion, and a local positioning method based on visual+UWB combination are proposed. For intelligent measurement and control technology, an intelligent detection method based on recursive least squares algorithm/second-order approximate extended Kalman filter , the real-time construction method for follow-up electronic fences, and vector control method based on fuzzy rules are proposed. For the information transmission technology, the 'local-short range-ground' communication system architecture based on the fusion of 5G network and the distributed data calculation and transmission method based on edge computing are proposed. The proposal of key technical issues and solutions for intelligent monorail cranes in coal mines provides a new approach to accelerate the development of intelligent monorail cranes in coal mines.