Fractal Dimension Theory Research Articles

Study on dominant structural factors and laws of combustion performance of acidified coal

The application of acidification technology changes the pore structure and microcrystalline structure of coal, which affects the combustion characteristics of coal products. In this study, three inorganic acids (HF, HCl, and HNO3) were used to treat bituminous coal, and low-temperature nitrogen adsorption tests, X-ray diffraction analysis (XRD), and simultaneous thermal analysis (STA) were carried out. Fractal dimension theory, microcrystalline structure analysis theory, and thermal analysis kinetic theory analyze the pores, crystallites, and combustion characteristics of raw coal and acidified coal, respectively. The correlation between variables can be judged by the Pearson correlation coefficient. The research results show that compared with the microcrystalline structure, the pores determine the acidified coal's synthetical combustion index S, maximum value of differential thermal analysis DTAtop and maximum mass loss rate dW/dtmax to a greater extent. Hydrofluoric acid increased the average pore size of the raw coal by 38.66%, resulting in an 11.60% increase in dW/dtmax. The ignition temperature T5 is the composite performance of the aromatic structure's thermal stability and the microcrystalline structure's ordering. The aromaticity fa determines the reaction in the oxidation weight gain stage to a greater extent and can be used as a new indicator to characterise the spontaneous combustion tendency of coal. The pore and microcrystalline structures jointly determine the activation energy E3 in the combustion stage.

Hypometabolic and hypermetabolic brain regions in patients with ALS-FTD show distinct patterns of grey and white matter degeneration: A pilot multimodal neuroimaging study

BackgroundUp to 50% of amyotrophic lateral sclerosis (ALS) patients develop some degree of cognitive dysfunction and a small proportion of these develop frontotemporal dementia (FTD). Non-invasive techniques of magnetic resonance imaging (MRI) and [18F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomography (PET) have demonstrated structural and metabolic abnormalities, respectively, in the brains of such patients with ALS-FTD. Although initial 18F-FDG PET studies in ALS patients showed only hypometabolism of motor and extramotor brain regions, subsequent studies have demonstrated hypermetabolic changes as well. Such contrasting findings prompted us to hypothesize that hypo- and hypermetabolic brain regions in ALS-FTD patients are associated with divergent degeneration of structural grey matter (GM) and white matter (WM). MethodsCerebral glucose metabolic rate (CMRglc), cortical thickness (CT), fractal dimension (FD), and graph theory WM network analyses were performed on clinical MRI and 18F-FDG PET images from 8 ALS-FTD patients and 14 neurologic controls to explore the relationship between GM-WM degeneration and hypo- and hypermetabolic brain regions. ResultsCMRglc revealed significant hypometabolism in frontal and precentral gyrus brain regions, with hypermetabolism in temporal, occipital and cerebellar regions. Cortical thinning was noted in both hypo- and hypermetabolic brain areas. Unlike CT, FD did not reveal widespread GM degeneration in hypo- and hypermetabolic brain regions of ALS-FTD patients. Graph theory analysis showed severe WM degeneration in hypometabolic but not hypermetabolic areas, especially in the right hemisphere. ConclusionOur multimodal MRI-PET study provides insights into potentially differential pathophysiological mechanisms between hypo- and hypermetabolic brain regions of ALS-FTD patients.

Study on the Slurry Diffusion Law of Fluidized Filling Gangue in the Caving Goaf of Thick Coal Seam Fully Mechanized Caving Mining

Because of the problem of gangue discharge and surface subsidence during coal mining, the current research on underground filling mainly focuses on the paste filling, solid filling, and grouting filling of the overburden separation layer after scaffolding. We proposed the technology of fluidization gangue grouting for filling the collapse area based on our previous research. The prediction method of residual space in the collapse area and the diffusion law of gangue fluidization filling slurry are two essential points for successfully implementing the technology and maximizing the use of goaf for gangue backfilling and reducing overburden settlement. To further explore the remaining space distribution law of the collapsed goaf in thick seam fully mechanized top coal caving mining and the effect of coal gangue fluidization filling, the caving goaf of the 3307 fully mechanized top coal caving face in Sangshuping No. 2 coal mine in the Weibei mining area was detected by the transient electromagnetic method. We studied the distribution law of the measured abnormal area in the caving goaf, which reflects the distribution law of the remaining space from one aspect. The coefficient of the remaining space was calculated to be 19.5%. Then, we applied COMSOL simulation software. The diffusion law of coal gangue fluidized slurry in the caving goaf was simulated and analyzed. It shows that the most obvious diffusion direction of the coal gangue slurry is the trend of the gradual expansion of the “cavity pore” multi-type residual space, indicating that with the increase in the diffusion distance, the diffusion resistance gradually increases, and the slurry morphology gradually presents the “claw” form. According to the space theory and fractal dimension theory, the prediction method of the remaining space in the caving goaf is given, and the design basis of the filling drilling parameters is determined. Finally, the field-filling test was carried out. The results show that the high- and low-level fluidized filling in the caving goaf can safely and efficiently handle the gangue in the mine, and the residual space characteristics and slurry diffusion law in the caving goaf are consistent with the above. The research results provide theoretical support for the fluidization filling technology of coal gangue in thick seam fully mechanized top coal caving areas.

A comprehensive analysis of pore structures and performances of mineral admixtures modified recycled aggregate concrete based on experiment and theory

Recycled aggregate concrete (RAC) is an important form of construction waste resource utilization, but the existence of multiple interface transition zone (ITZ) leads to complex pore defects in RAC, which seriously weakens its mechanical properties and chloride ion permeability. In this paper, fly ash (FA), silica fume (SF) and mineral powder (SL) admixtures were incorporated into RAC for improving the pore structure of RAC. The effects of admixtures on the pore structure parameters and pore size distribution of RAC were detailly analyzed by means of back scattering electron imaging (BSE), mercury intrusion porosimetry (MIP) and fractal dimension theory (FDT). And the micro characteristics of porosity and pore structure in ITZ were quantitatively described. The results clearly show that the appropriate amount of admixture can reduce the porosity, average pore diameter and the maximum aperture of RAC. Furthermore, the macropores and capillary pores were significantly decreased and gradually changed into transition pores and gel pores. The refinement of pores increases the compactness of RAC, particularly the pozzolanic effect of SF. The newly generated CSH gel and the filling effect of SF greatly decrease the porosity of ITZ. In addition, the fractal dimension (FD) of pore volume exhibits a good positive linear relationship to the compressive strength and chloride ion permeability resistance of RAC.

Dust pollution evaluation based on grayscale average and fractal dimension of digital image

The automatic and effective identification of mine dust draws growing public concern for its universality and being highly hazardous to health and property. Based on improved methods for improved grayscale average (IGSA) and fractal dimension (FD) theory, a vision-based system that employs digital image processing was proposed to recognize dust particles. The proposed approach primarily includes the following procedures: image matrix generation; pixel gradient calculations; image processing for sharpening, gray transformation, and binarization; IGSA and FD calculations, and visualization accomplishments. Image example results show that FD appears to have an exponential relationship with IGSA as well as dust pollution. Then, a dust pollution-level evaluation method based on the pollution-factor Fp was established and contributed to the division of dust pollution regions. During the experiment, wind speed and hole distance were proved to demonstrate a positive and negative correlation with IGSA, respectively, while little impact was observed on the FD and Fp with the factors. A dust pollution monitoring system that is theoretically viable was developed to form an Industrial Internet of Things with a topological structure. The proposed approach provides a digital image-processing method to integrally and automatically characterize the dust morphology. This approach can achieve dust pollution-level and regional divisions.

Pollutant Migration Pattern during Open-Pit Rock Blasting Based on Digital Image Analysis Technology

Previous studies have revealed that toxic gases and dust (smoke dust) are the most common pollutants generated by the blasting operations in open-pit mines, which might lead to a threat to the environment’s condition, health and safety, and properties protection around the blasting site. In order to deal with the problems, a pollution evaluation system was established based on the fractal dimension theory (Dbox(P)) and grayscale average algorithm (Ga) in digital image-processing technology to recognize and analyze the distributions of the smoke-dust cloud, and subsequently determine the pollution degrees. The computation processes of Dbox(P) and Ga indicate three fitted correlations between the parameters and diffusion time of smoke dust. Then, a pollution index (Pi) is put forward to integrate the global and local features of Dbox(P) and Ga, and develop a hazard classification mechanism for the blasting pollutants. Results obviously denote three diffusion stages of the pollutants, mainly including generation stage, cloud-formation stage, and diffusion stage. In addition, it has been validated that the proposed system can also be utilized in single-point areas within a whole digital image. Besides, there are variation trends of the thresholds T1 and T2 in binarization with the diffusion of pollutants. With this identification and evaluation system, the pollution condition of smoke dust can be obviously determined and analyzed.

Study of particle clogging pattern in concrete seepage process based on multi-scale VOF-DEM and experimental comparison

This paper presents an in-depth analysis of the clogging behavior of multi-graded particles within permeable asphalt concrete, and discusses the seepage mechanism. Through the experimental tests and CT scanning reconstruction, the longitudinal pattern of the clogging area within the concrete has been presented. For obtaining a fine-scaling view and exploring the clogging mechanism, a multi-scale VOF-DEM model has been constructed, and the time-averaged displacements/velocities/forces of the particles have been calculated, respectively. It should be noted that the variable water-head structure has been fully considered in our research. Besides the fractal dimension theory has also been introduced for reviewing the reason why some fine-scale particles can still pass through the concrete. The results show that the particle clogging is very serious within 10 mm of concrete surface, and the porosity decreases by about 65.43%. But in the concrete surface 10 mm outside the area of clogging rate decreased relatively small about 16.99%, with the increase of depth clogging gradually weakened. More importantly, the pore size r of channels formed between skeleton particles limits the passing of the particles, and only the particle size is smaller than the pore size can penetrate deeper into the formation of deep clogging.

Research on Rock Damage Evolution Based on Fractal Theory-Improved Dynamic Tensile-Compression Damage Model

According to the characteristics that the dynamic tension of rock material is elastic brittle and the dynamic compression is elastic plastic, based on previous studies, the influence of initial damage is considered in the established compression damage model, and the calculation formula of the damage threshold used to evaluate whether the surrounding rock is affected by blasting is given. According to the classic rock impact dynamic damage model and statistical damage mechanics theory, a rock compressive and tensile statistical damage constitutive model and impact damage model under blasting load is proposed. Based on the proposed damage model and the classic dynamic tensile damage model, the numerical simulation of blasting damage was carried out, and the numerical calculation results were compared with the field measurement results. Based on the established damage model, to further clarify the damage evolution characteristics of rock under blasting load, fractal dimension theory was introduced to analyze the rock damage under blasting loads with different blasting hole network parameters. The results show that compared with the axial direction of the blast hole, the direction of blast hole diameter is the main direction of blasting fracture extension. Tensile fracture mainly occurs along the hole diameter direction, and compression fracture mainly occurs below the hole bottom. Compared with the numerical calculation results based on the classical dynamic tensile damage model, the blasting fracture range obtained according to the damage model, especially the fracture depth below the bottom of the hole, was not much different from the measured value and was closest to the measured value. The crack density of 1 us, 90 aperture, and 130 aperture was larger than that of the other working conditions. Among them, the crack density of 130 aperture was the largest, followed by 90 aperture. At 2~3 us after initiation, cracks between two blast holes, radial cracks and circumferential cracks around two blast holes, and obvious cracks were formed around blastholes; at 4~5 us after initiation, the shock wave front decreased rapidly and propagated outward in the form of the compression wave. The crack propagation velocity was much smaller than that at 1~3 us after initiation. In summary, the proposed damage model is reasonable and has certain engineering practicability.

Experimental analysis of pore structure and fractal characteristics of soft and hard coals with same coalification

Accurate and quantitative investigation of the physical structure and fractal geometry of coal has important theoretical and practical significance for coal bed methane (CBM) development and the prevention of dynamic disasters such as coal and gas outbursts. This study investigates the pore structure and fractal characteristics of soft and hard coals using nitrogen and carbon dioxide (N2/CO2) adsorption. Coal samples from Pingdingshan Mine in Henan province of China were collected and pulverized to the required size (0.20–0.25 mm). N2/CO2 adsorption tests were performed to evaluate the specific surface area (SSA), pore size distribution (PSD), and pore volume (PV) using Braunuer-Emmett-Teller (BET), Barrett-Joyner-Halenda (BJH), and Density Functional Theory (DFT). The pore structure was characterized based on the theory of fractal dimensions. The results unveiled that the strength of coal has a significant influence on pore structure and fractal dimensions. There are significant differences in SSA and PV between both coals. The BJH-PV and BET-SSA obtained by N2-adsorption for soft coal are 0.029–0.032 cm3/g and 3.523–4.783 m2/g. While the values of PV and SSA obtained by CO2-adsorption are 0.037–0.039 cm3/g and 106.016–111.870 m2/g. Soft coal shows greater SSA and PV than hard coal, which is consistent with the adsorption capacity ({V}_{mathrm{L}}). The fractal dimensions of soft and hard coal are respectively different. The Ding coal exhibits larger D1 and smaller D2, and the reverse for the Wu coal seam is observed. The greater the value of D1 (complexity of pore surface) of soft coal is, the larger the pore surface roughness and gas adsorption capacity is. The results enable us to conclude that the characterization of pores and fractal dimensions of soft and hard coals is different, tending to different adsorption/desorption characteristics. In this regard, the results provide a reference for formulating corresponding coal and gas outburst prevention and control measures.

Effect of Fragmentation on Pore Structures and Fractal Characteristics of Intact Coal and Deformed Coal Based on Experiments

Coal mining has to develop to deeper strata with the increasing demand for coal, which leads to frequent coal and gas outburst disasters. Especially, when there is a deformed coal in the coal seam, the outburst disasters are easier and more intense. Coal and gas outburst disasters can be promoted by the fragmentation. In order to clearly explain the reasons for the impact of fragmentation on deformed coal and gas outburst, mercury intrusion porosimetry, low-temperature liquid N2 adsorption test, and scanning electron microscope were carried out in this paper. The differences in pore characteristics of intact coal and deformed coal under different particle size conditions were analyzed from pore shapes, pore size distributions, and fractal dimensions. The damage paths of fragmentation on various kinds of pores in intact coal are as follows: macropores, mesopores, minipores, and micropores, and those on various kinds of pores in deformed coal are as follows: macropores, micropores, mesopores, and minipores. According to the fractal dimension theory and experimental results, the calculative results of fractal dimensions show that the fragmentation and tectonism reduce the surface roughness and structural complexity of macropores and mesopores and increase those of minipores and micropores in deformed coal. Finally, combined with the coupling effect of fragmentation and tectonism on pores, the reason of deformed coal with high crushing degree in fields of outburst was explained. The research provides the basis for the prevention of coal and gas outburst.

Simulation and Experiment Research on the Surface Deformation and Residual Stress of Fractal Rough Surface Single-Shot Peening

In order to study the influence of workpiece surface topography on deformation and residual stress during shot peening, the paper built a rough surface single-shot peening simulation model and designed a rough surface workpieces shot peening experiment to verify the correctness of the built simulation model, which differed from the smooth surface simulation model and was closer to the actual processing situation. Based on the W-M fractal dimension theory, the shot peening model of the target with a rough surface is established, and the simulation analysis is carried out by finite element software. The effect of different impact positions of the pellet on surface residual stress and surface displacement were also simulated. The simulation found that with the increase of surface complexity, the surface deformation and residual stress would both increase after shot peening. Through shot peening tests on workpieces with different surface roughness, it is found that the error between simulation and experiment results on surface deformation and residual stress are both less than 20%, which verifies the validity of the rough surface single-shot peening model and that the established model could provide a new method on shot peening simulation analysis.

Experimental and Numerical Simulation of Water Adsorption and Diffusion in Coals with Inorganic Minerals

The study on the adsorption and micropore filling of water vapor in coal is significant for predicting coalbed methane content in coal seams. The primary purpose of this study is to explain the effects of coal pore structure and its surface chemistry on water vapor monolayer adsorption, micropore filling, and diffusion coefficient. First, X-ray diffraction (XRD) and mercury intrusion porosimetry (MIP) analyzed inorganic mineral components of two kinds of coal samples and pore fissures structures. Then, we divide pores and fissures according to the theory of fractal dimensions. Furthermore, we carried out the water vapor adsorption and desorption experiments on two kinds of coal; in particular, we set 14 points of relative pressure between 0 and 0.2. Guggenheim–Anderson–de Boer (GAB), Frenkel–Halsey–Hill (FHH), and Freundlich models were used to analyze the data of water vapor adsorption to obtain the boundary pressure points of the monolayer, multilayer adsorption, and capillary condensation. Finally, the parameters of the models were obtained by fitting the adsorption data of water vapor according to the combined GAB, Freundlich, DA, and bidisperse adsorption (BDA) models to analyze the interaction mechanism between coal and water. We explain why the strongly adsorbed water minerals, such as pyrite, illite, and nacrite coal, can improve water vapor’s adsorption and diffusion capacity in coal pore fissures.

Application of the Material Balance Equation Based on the BET Multimolecular Fractal Theory in a Shale Gas Reservoir

During shale gas reservoir development, obtaining actual formation pressure is challenging; therefore, it is challenging to obtain a single well production allocation using the current formation pressure based on a productivity equation. Different shale gas reservoirs with different rock adsorption properties and the traditional Langmuir isotherm adsorption equations are not accurate in describing the adsorption properties of shale gas reservoirs, causing significant errors. BET multimolecular adsorption, considering the shale gas surface fractal dimension theory to describe the adsorption properties, can describe the adsorption surface as a multimolecular layer and regard adsorption using a fractal dimension, describing the adsorption property of shale gas more accurately. According to the core adsorption test data and theory, the actual BET multimolecular adsorption is established by considering the shale gas surface fractal dimension. Therefore, the actual material balance equation was obtained using the theory, establishing the relationship between the formation pressure and cumulative shale gas production. A time-independent distribution and cumulative gas production chart were formed using the productivity equation. Consequently, the material balance equation, which takes advantage of the BET multimolecular fractal theory, was conducted. This allocation production method obtained from the material balance equation has significant importance in shale gas development.

Experimental study of fracture evolution in enhanced geothermal systems based on fractal theory

Long-term seepage under high temperature and high pressure affects fracture morphology, ultimately impacting the development efficiency of Enhanced Geothermal Systems (EGS). In this study, rock samples with different morphologies were produced and their morphologies were described quantitatively using fractal dimension theory. Experimentally, distilled water and simulated geothermal fluid were injected into fractures at a constant flow rate for 360 h. The behaviors of different fluid components during the fracture evolution process under high temperature and high pressure were observed. Results show that apertures and permeability decreased by 7.1% and 19.5% when distilled water was used, while they decreased by 0.6% and 1.8% respectively when simulated geothermal fluid was injected. The fracture apertures first decreased and then gradually increased. The more complex the fracture shape, the faster the mineral dissolution rate. With fractal dimensions of 1.007, 1.027 and 1.056, the dissolution rates of rock-like minerals in deionized water were 9.43×10−2, 1.33×10−1 and 1.51×10−1 mg/L per 12 hours, respectively. This study lays a foundation for further research on fracture network evolution and provides a basis for the long-term efficient and stable operation of EGS.

Prediction method of permeability of textile-reinforced concrete based on fractal dimension theory

Water in the external environment of textile-reinforced concrete (TRC) migrates along the direction of internal directional fiber bundles, thereby damaging the TRC and thus increasing the permeability of the internal matrix. This paper studies the effects of concrete water–cement ratios of concrete, grid sizes and fiber bundle Tex content on the permeability of TRC on the macro and micro scales, and the roughness of concrete was evaluated by fractal dimension through a nuclear magnetic resonance test. Results show that the permeability of TRC increases with the decrease in the grid size of the textile, the increase in the Tex content and the increase in the water–cement ratio of concrete. In this paper, a TRC seepage prediction model is established based on the dimensional analysis method and permeability test. The increase of permeability will seriously affect the durability of building materials and will be unsuitable for strengthening and repairing buildings. Therefore, studying the increase of the permeability of TRC under the action of external pressure water is important.

Fractal Dimension Analysis Based Aging State Assessment of Insulating Paper with Surface Microscopic Images

The insulating paper of the transformer is affected by many factors during the operation, meanwhile, the surface texture of the paper is easy to change. To explore the relationship between the aging state and surface texture change of insulating paper, firstly, the thermal aging experiment of insulating paper is carried out, and the insulating paper samples with different aging times are obtained. After then, the images of the aged insulating paper samples are collected and pre-processed. The pre-processing effect is verified by constructing and calculating the gray surface of the sample. Secondly, the texture features of the insulating paper image are extracted by box dimension and multifractal spectrum. Based on that, the extreme learning machine (ELM) is taken as the classification tool with texture features and aging time as the input and output, to train the algorithm and construct the corresponding relationship between the texture feature and the aging time. After then, the insulating paper with unknown aging time is predicted with a trained ELM algorithm. The numerical test results show that the texture features extracted from the fractal dimension of the micro image can effectively characterize the aging state of insulating paper, the average accuracy can reach 91.6%. It proves that the fractal dimension theory can be utilized for assessing the aging state of insulating paper for onsite applications.

Ground Moving Target Detection With Seismic Fractal Features

Due to the strong nonstationary characteristics of seismic signals, energy criteria-based methods are not robust for detecting moving targets, especially in data with low SNRs. To address this problem, we propose a new method for detecting ground moving target based on fractal dimension (FD) theory named FD-based support vector machine (FD-SVM). In this method, seismic signals are first measured by fractals, which can effectively extract seismic nonlinear features. These fractal features are then fed into an SVM to distinguish moving targets from noise. Two data sets are used to evaluate the proposed method. One is a set of seismic signals induced by wheeled and tracked vehicles. The other is a set of seismic signals generated by human footsteps. Experimental results demonstrate that the proposed FD-SVM algorithm achieves promising results on both data sets. Compared with the benchmark methods, the FD-SVM algorithm achieves a better precision rate, recall rate, and F1 score.

Experimental study of convective heat transfer characteristics of fractures with different morphologies based on fractal theory

In the Enhanced Geothermal System (EGS), the flow state of the fracture of the thermal reservoir (granite) is important for heat transfer. In this paper, the effects of reservoir temperature, flow rate and fracture shape on the thermal convection that occurs in the fracture of rough granite are studied based on the fractal dimension theory. The rough fracture is manufactured regularly by carving technology. The shear flow experiments were carried out at confining pressures of 10, 15 and 20 MPa to analyze the flow state. The convective heat transfer experiments were conducted at 60 and 70 °C to simulate different heat reservoir conditions. The results indicated that the outlet temperature and overall heat transfer coefficient (OHTC) increased with the increase in the rock temperature. A higher flow rate can enhance the thermal performance. The complexity of the fracture surface is also an important factor that affects the convective heat transfer process. The larger fractal dimension of the fracture surface can more easily excite turbulence, affecting the thickness of the boundary layer. The OHTC will increase as the fractal dimension increases.

An improved extreme learning machine algorithm for transient electromagnetic nonlinear inversion

Transient electromagnetic method (TEM) inversion is significantly nonlinear. To eliminate the multicollinearity problem faced by the extreme learning machine (ELM) algorithm for TEM inversion, an improved ELM algorithm (F-ELM) based on fractal dimension technology is proposed. By reducing the dimension of the hidden layer output matrix (H) based on fractal dimension theory without losing the main statistical information, the proposed algorithm can not only guarantee the full column rank of the newly produced hidden layer output matrix (H′) but also enhance the training speed of the overall process. To prove the effectiveness of the F-ELM algorithm, a synthetic example and a field example using TEM inversion are established in this study. The experimental results illustrate that compared with the ordinary ELM algorithm and its variants, the proposed algorithm greatly reduces the computing time, improves the inversion accuracy and stability of the algorithm. Furthermore, it is also proven that the F-ELM algorithm is a very effective technique for TEM inversion.

English spoken stress recognition based on natural language processing and endpoint detection algorithm

Nowadays, there are more and more researches on the application of natural language processing technology in computer-aided language system, which can provide a good assistant role for foreign language learners. However, in the research of computer-aided language system, there are still some deficiencies in the recognition of English spoken stress nodes, which cannot be well recognized. Based on this, this paper proposes a method of English spoken accent recognition based on natural language processing and endpoint detection algorithm, which aims to promote the accuracy of accent recognition in the computer-aided language system and improve the performance of the computer-aided language system. In order to avoid the interference of background noise, this paper proposes a short-term time-frequency endpoint detection algorithm which can accurately judge the beginning and end of speech in complex environment. Then, on the basis of traditional speech feature extraction and fractal dimension theory, a nonlinear fractal dimension speech feature is extracted. Finally, RankNet is used to process the extracted features to realize the recognition of English spoken stress nodes. In the simulation analysis, the application effect of the short-term time-frequency endpoint detection algorithm proposed in this paper in the complex background noise and the effect of non-linear fractal dimension speech features on the recognition of English spoken stress nodes are verified. Finally, the performance and good application effect of the method designed in this paper are illustrated.