Discrimination of Different AE and EMR Signals during Excavation of Coal Roadway Based on Wavelet Transform

During the process of coal road excavation, various interference signals, induced by environmental noise, drilling, and scraper loader, will affect the risk assessment of coal and gas outburst using acoustic emission (AE) and electromagnetic radiation (EMR) monitoring technology. To distinguish between different interference signals and danger signals, discrete wavelet transform (DWT) was used to decompose and reconstruct signals, and continuous wavelet transform (CWT) was used to obtain the time-frequency plane. The research results show that: (1) interference signals generally exhibit fluctuating changes within small ranges; in comparison, the intensity of AE and EMR signals caused by coal and rock fracture is found to continuously rise for a long period (longer than 2 h). (2) Different interference signals and danger signals differ significantly in their time-frequency plane. (3) Through decomposition and reconstruction of original signal, obvious precursor information can be found in the time-frequency plane of reconstructed signals.

A Novel Bimodal Forecasting Model for Solar Cycle 25

In this paper, a novel bimodal model to predict a complete sunspot cycle based on comprehensive precursor information is proposed. We compare the traditional 13 month moving average with the Gaussian filter and find that the latter has less missing information and can better describe the overall trend of the raw data. Unlike the previous models that usually only use one precursor, here we combine the implicit and geometric information of the solar cycle (peak and skewness of the previous cycle and start value of the predicted cycle) with the traditional precursor method based on the geomagnetic index and adopt a multivariate linear approach with a higher goodness of fit (>0.85) in the fitting. Verifications for cycles 22–24 demonstrate that the model has good performance in predicting the peak and peak occurrence time. It also successfully predicts the complete bimodal structure for cycle 22 and cycle 24, showing a certain ability to predict whether the next solar cycle is unimodal or bimodal. It shows that cycle 25 is a single-peak structure and that the peak will come in 2024 October with a peak of 145.3.

Evolution Mechanism, Monitoring, and Early Warning Method of Water Inrush in Deep-Buried Long Tunnel

Water inrush is a serious disaster in tunnel construction. Because the process of water inrush is complicated and there is no effective monitoring and early warning method, the control of water inrush disaster is passive. Firstly, the failure mode and determination method of safety thickness of the antioutburst structure are summarized. The key breakthrough directions and development trends of water inrush mechanism was analyzed. Secondly, the sensitivity ranking and the adjunct characteristics of different types of precursor information are determined by the model test. An improved scheme of microseismic monitoring technology is proposed to locate the spatial position of the water inrush channel, and a multi-information time-space integrated monitoring method for an antioutburst structure is established. By analyzing the evolution law of multi-information in the process of water inrush, the evolution model and its identification method are put forward. Finally, the level of water inrush was determined through the analysis of the dynamic and static reserves of disaster source, and a multilevel and comprehensive warning system of tunnel water inrush is established. Through the remote real-time monitoring and early warning platform and its engineering application, the early warning of water inrush time trend and the early warning of water inrush rupture space position are realized.

Mechanical and Acoustic Responses of Brittle Geomaterials with a Hole under a Compressive Disturbance

The objective of this article was to investigate the acoustic emission (AE) precursor information and crack propagation mechanism of brittle granite specimens containing a hole under uniaxial compression using AE and digital image correlation (DIC) techniques. The results show that the existence of the opening in the specimen leads to the degradation of the mechanical properties, and the stress-strain curve exhibits several stress drops. Each deformation stage of rock had different AE characteristics, so AE signals can be used to characterize the microscopic damage evolution of rock and predict the macroscopic failure process of the surrounding rock of the opening. The deformation field evolution process of the specimen containing an opening gradually develops from a uniform distribution to prominent local deformation, and the deformation of the local area near the opening is greater than that of other areas. The initiation of cracks begins around the opening, and the propagation of tensile cracks around the opening is primarily influenced by the nucleation and propagation in the strain localization area. The crack propagation evolution derived from DIC images can be combined with AE monitoring to accurately reveal the deformation and failure mechanism of the intact specimen containing an opening.

Evolution Pattern and Matching Mode of Precursor Information about Water Inrush in a Karst Tunnel

The water inrush of the Shangjiawan karst tunnel is used to study the evolution pattern of precursor water inrush information in water-filled caves and to further reveal the matching mode of the information. The three-dimensional numerical method FLAC3D was used to simulate the evolution process of water inrush after damage to a water-blocking rock mass structure in a water-filled cave and to obtain the evolution pattern of precursor water-inrush information caused by the damage. The results show that the multifield response to the characteristic precursor information of the water-inrush pattern after the fracture of the water-blocking rock mass follows the order of stress-field displacement-field seepage-field. Further, the matching pattern of the information shows that the stress field increased first and then decreased, the displacement field always increased, and the seepage field increased first and then decreased.

Forecasting Solar Cycle 25 using comprehensive precursor combination and multiple regression technique

In this paper, we propose a new model to predict the complete sunspot cycle based on the comprehensive precursor information (peak, skewness, and maximum geomagnetic index aa of the previous cycle, and start value of predicted cycle). The monthly average sunspot original data are processed by Gaussian smoothing and the new model is validated by the observed sunspots of cycle 24. Compared with the traditional 13-month moving average, the Gaussian filter has less missing information and is better to describe the overall trend of the raw data. Through the permutation and combination of multiple parameters in precursor methods of solar cycle forecasting, the multiple regression technique is used to successfully achieve the peak prediction. The regression coefficient (R) of the empirical model established in this paper can reach 0.95. By adding a new parameter to the original HWR function, we provide a complete solar cycle profile showing unimodal structure. It shows that the peak value of cycle 25 will come in March 2024, with a peak of 140.2.