Multidimensional Coupling Research Articles

Digital twin water conservancy early warning system based on physical level and numerical simulation in intelligent water conservancy construction

Abstract. In 2023, the Central Committee of the Communist Party of China and The State Council issued the Overall Layout Plan for the Construction of Digital China, emphasizing the construction of a smart water conservancy system with digital twin basins as the core. The Guangxi Zhuang Autonomous Region government has clearly proposed to actively build a "digital twin Pinglu Canal", and attaches great importance to the construction of digital twin platform application services during the construction of the Western land-Sea New Passage (Pinglu) canal. Aiming at the problems such as unsatisfactory early warning effect, inaccurate data and imprecise model of existing smart water conservancy technology, this paper proposes a digital twin system for disaster early warning based on physical level and numerical simulation technology, establishes a visual digital water conservancy model and digital twin smart water conservancy cloud platform, and combines multi-physics field and multi-dimensional coupling algorithm to respond to technical pain points. To achieve scientific and accurate monitoring and intelligent management, and contribute to the construction of digitally empowered Pinglu Canal.

Can the resource and environmental dilemma due to water-energy-carbon constraints be solved in the process of new urbanization?

The rapid development of basin resource-based cities (BRCs) in developing countries have led to severe resource and environmental problems centered on the “water-energy-carbon” (WEC) nexus. Based on their spatiotemporal evolution, WEC constraints are evaluated via a multidimensional coupling coordination degree (CCD) mode. Resource-environmental efficiency (REE) under these constraints is measured via the superefficiency SBM model. The path of resource and environmental improvement via new urbanization (NU) is discussed based on the spatial econometric model. Water resource consumption in the BRCs decreased by 12.22 %, but energy consumption and carbon emissions increased by 20.1 % and 70.05 %, respectively, and the CCD of the WEC nexus showed a “highly coordinated - seriously imbalanced” change. Therefore, the REE increase of 44.03 % was unsustainable. NU improved REE and reduced water resource consumption but did not reduce energy consumption or carbon emission, and there is significant regional variability. Scientific and technological innovation, economic agglomeration and land structure diversity contributed to the resource-environmental improvement effects of NU, but optimized industrial structures and environmental governance had masking effects. The policy implication is that during NU, efficiency gains must be combined with policies to promote industrial structure optimization and environmental governance and thus achieve sustainable urban development.

A new highly sensitive flexible SERS substrate: CVD graphene/copper foil decorated by Ag NPs

Graphene-mediated surface-enhanced Raman scattering (SERS) substrates are currently being investigated for their potential in ultrasensitive detection. Graphene (G) combined with plasmonic metal nanostructures is expected to provide an exceptional SERS response. Here, we prepared a flexible multilayer composite structure by directly decorating silver nanoparticles (Ag NPs) on CVD graphene/copper foil under ultrasonic conditions. Due to the multi-dimensional plasmonic coupling of precious metals, extra chemical enhancement and exceptional molecule harvesting capability of G interlayer, the as-prepared Ag/G/Cu multilayer composite structure manifested ultrahigh sensitivity with the detection limit of Rhodamine 6G (R6G) as low as 1.0 × 10-14 M and a high enhancement factor (EF) of 8.86 × 108. The high performance flexible SERS substrate, with its ingenious process and simple structure, demonstrates excellent potential for applications in environmental protection.

Multi-dimensional signals coupling of simultaneous acquisition stripping current with laser-induced breakdown spectroscopy for accurate analysis of Cd(II) in coexisting Cu(II)

BackgroundDespite significant advancements in detecting Cd(II) using nanomaterials-modified sensitive interfaces, most detection methods rely solely on a single electrochemical stripping current to indicate concentration. This approach often overlooks potential inaccuracies caused by interference from coexisting ions. Therefore, establishing multi-dimensional signals that accurately reflect Cd(II) concentration in solution is crucial. ResultsIn this study, we developed a system integrating concentration, electrochemical stripping current, and laser-induced breakdown spectroscopy (LIBS) characteristic peak intensity through in-situ laser-induced breakdown spectroscopy and electrochemical integrated devices. By simultaneously acquiring multi-dimensional signals to dynamically track the electrochemical deposition and stripping processes, we observed that replacement reactions occur between Cu(II) and Cd(II) on the surface of Ru-doped MoS2 modified carbon paper electrodes (Ru-MoS2/CP). These reactions facilitate the oxidation of Cd(0) to Cd(II) during the stripping process, significantly increasing the currents of Cd(II). Remarkably, the ingenious design of the Ru-MoS2 sensitive interface allowed for the undisturbed deposition of Cu(II) and Cd(II) during the electrochemical deposition process. Consequently, our in-situ integrated device achieved accurate detection of Cd(II) in complex environments, boasting a detection sensitivity of 8606.5 counts μM⁻1. SignificanceBy coupling multi-dimensional signals from stripping current and LIBS spectra, we revealed the interference process between Cu(II) and Cd(II), providing valuable insights for accurate electrochemical analysis of heavy metal ions in complex water environments.

Multidimensional Engineering Induced Interfacial Polarization by in-Situ Confined Growth of MoS2 Nanosheets for Enhanced Microwave Absorption.

Interface design has enormous potential for the enhancement of interfacial polarization and microwave absorption properties. However, the construction of interfaces is always limited in components of a single dimension. Developing systematic strategies to customize multidimensional interfaces and fully utilize advantages of low-dimensional materials remains challenging. Two-dimensional transition metal dichalcogenides (TMDCs) have garnered significant attention owing to their distinctive electrical conductivity and exceptional interfacial effects. In this study, a series of hollow TMDCs@C fibers are synthesized via sacrificial template of CdS and confined growth of TMDCs embedded in the fibers. The complex permittivity of the hollow TMDCs@C fibers can be adjusted by tuning the content of CdS templates. Importantly, the multidimensional interfaces of the fibers contribute to elevating the microwave absorption performance. Among the hollow TMDCs@C fibers, the minimum reflection loss (RLmin) of the hollow MoS2@C fibers can reach -52.0dB at the thickness of 2.5mm, with a broad effective absorption bandwidth of 4.56GHz at 2.0mm. This work establishes an alternative approach for constructing multidimensional coupling interfaces and optimizing TMDCs as microwave absorption materials.

Multidimensional Fiber‐to‐Chip Optical Processing Using Photonic Integrated Circuits

AbstractMultidimensional multiplexing technologies have been proven to be a promising scheme to meet the demands of high‐capacity optical interconnects and optical processing networks. However, challenges remain to realize multidimensional hybrid multiplexing data transmission and signal processing between few‐mode fiber transmission links and on‐chip optical processing networks, since the optical coupling between fiber and chip is almost exclusively in the single‐mode regime. Here, a multidimensional fiber‐to‐chip optical processing system is proposed and demonstrated for hybrid wavelength‐, mode‐, and polarization‐division multiplexing signals, where multidimensional coupling between few‐mode fiber transmission link and on‐chip multi‐mode processing network is realized by using a 3D photonic integrated (de)multiplexers on a glass chip as well as 2D photonic integrated (de)multiplexers on a silicon chip, and the on‐chip multidimensional optical processing network composed by parallel cascaded micro‐ring resonator array performs a function of reconfigurable optical add/drop multiplexer. By operating wavelength‐division multiplexing in conjunction with mode‐division multiplexing and polarization‐division multiplexing, the communication bandwidth of fiber‐to‐chip optical processing systems can be further scaled.

Photothermal-synergistic peroxymonosulfate activation promoting carbamazepine degradation by Porphyra-derived porous biochar composites: Performance, mechanism, transformation pathway and practical application

Heterogeneous catalysis with peroxymonosulfate (PMS) activation has received increasing attention in recalcitrant contaminants treatment, but multidimensional coupling via engineered biochar materials and photothermal synergy is still rare. Herein, we reported photothermal-synergistic PMS activation by Porphyra-derived porous biochar composites (ZnS/NBC) for carbamazepine (CBZ) degradation. Benefitting from the high specific surface area, highly graphitic structure and strong light-to-heat conversion ability, ZnS/NBC10/PMS/light system showed enhanced degradation performance and nearly complete mineralization of CBZ. Meanwhile, this system maintained high degradation efficiency in real water bodies and natural sunlight condition, respectively. Mechanism analysis confirmed that the predominant role of 1O2 and the auxiliary involvement of SO4−, OH and electron transfer jointly contributed to the CBZ degradation. Finally, the possible degradation pathways of CBZ were elaborated based on the liquid chromatography-mass spectrometry results and Fukui index calculations, and the diminishing ecotoxicity of the accompanying degradation intermediate was evaluated using the toxicity estimation software tool. This study provides a new insight for advancing a comprehensive utilization of photothermal conversion and biochar-based PMS activators to organic wastewater purification.

Ultra-short-term multi-energy load forecasting for integrated energy systems based on multi-dimensional coupling characteristic mining and multi-task learning

To address the challenges posed by the randomness and volatility of multi-energy loads in integrated energy systems for ultra-short-term accurate load forecasting, this paper proposes an ultra-short-term multi-energy load forecasting method based on multi-dimensional coupling feature mining and multi-task learning. Firstly, a method for mining multi-dimensional coupling characteristics of multi-energy loads is proposed, integrating multiple correlation analysis methods. By constructing coupling features of multi-energy loads and using them as input features of the model, the complex coupling relationships between multi-energy loads are effectively quantified. Secondly, an ultra-short-term multi-energy load forecasting model based on multi-task learning and a temporal convolutional network is constructed. In the prediction model construction phase, the potential complex coupling characteristics between multiple loads can be fully explored, and the potential temporal associations and long-term dependencies within data can be extracted. Then, the multi-task learning loss function weight optimization method based on homoscedastic uncertainty is used to optimize the forecasting model, realizing automatic tuning of the loss function weight parameters and further improving the prediction performance of the model. Finally, an experimental analysis is conducted using the integrated energy system of Arizona State University in the United States as an example. The results show that the proposed forecasting method has higher prediction accuracy than other prediction methods.

A bicoherence approach to analyze multi-dimensional cross-frequency coupling in EEG/MEG data

We introduce a blockwise generalisation of the Antisymmetric Cross-Bicoherence (ACB), a statistical method based on bispectral analysis. The Multi-dimensional ACB (MACB) is an approach that aims at detecting quadratic lagged phase-interactions between vector time series in the frequency domain. Such a coupling can be empirically observed in functional neuroimaging data, e.g., in electro/magnetoencephalographic signals. MACB is invariant under orthogonal trasformations of the data, which makes it independent, e.g., on the choice of the physical coordinate system in the neuro-electromagnetic inverse procedure. In extensive synthetic experiments, we prove that MACB performance is significantly better than that obtained by ACB. Specifically, the shorter the data length, or the higher the dimension of the single data space, the larger the difference between the two methods.

Large-scale SU-8 Micro-Pole-Arrays decorated with Hierarchical Metal-Dielectric-Metal nanostructures as sensitive 3D SERS substrates

Dielectric layer-mediated surface-enhanced Raman scattering (SERS) substrates are currently explored for ultrasensitive detection and expected to provide uniform SERS response by the virtue of three-dimensional micro-nanostructures, dielectric layer, and plasmonic metal nanostructures. For this purpose, the present work reports on the development of the metal-dielectric-metal (MDM) three-dimensional (3D) micro-pole-arrays structure based on SU-8 colloid lithography. By utilizing the large-scale periodic arrangement characteristics of SU-8 colloidal lithography, along with the hot spot effect created by the nano-gap between MDM, we successfully prepared an array of SERS substrates that exhibit both periodicity and multi-dimensional plasmonic coupling effect. Compared to a single metal nanoparticle substrate, the SERS activity of the substrate is significantly enhanced, and the substrate has trace detection ability (LOD of detection of 10−12 mol/L for R6G). The enhancement factor (EF) is 5.72 × 107. Periodicity ensures that the prepared substrate has good reproducibility (RSD < 8 %) and stability. Furthermore, the substrate modified with HS-β-CD demonstrated potential for rapid trace SERS detection of polychlorinated biphenyls (PCB-77) (LOD of 10−8 mol/L for PCB-77). The results indicate that the proposed substrate has the potential for application in the preparation of SERS sensors with high sensitivity and uniformity.

Abstract 5805: A novel platform of diversified payloads to drive ADC innovation

Abstract First generation of antibody drug conjugates (ADCs) for anticancer therapy has been described more than two decades ago with gemtuzumab-ozogamicin receiving the first approval in 2000. Over the last 4 years, 8 new ADCs got FDA approval essentially due to the innovation on the linker improving the disposition in patients and the manufacturability together with the technical advantages in the engineering of biologics and the introduction of new cytotoxic payloads such as deruxtecan. In the future, next generation ADCs will be developed exploring payloads beyond the currently used cytotoxins to improve safety, efficacy and durability of responses and therefore the short- and long-term therapeutic benefit to patients. Nerviano Medical Sciences (NMS) generated a portfolio of novel and diversified payload linkers leveraging on its proprietary chemical collection that includes cytotoxic and targeted payloads. A rigorous screening funnel has been applied considering diversification in terms of MoAs, pharmacokinetic properties, mechanism of resistance and combinability with other therapies to identify the optimal match with specific tumor types and targets, generating a new class of ADCs with improved selectivity and efficacy for hard-to-treat cancers even in chemoresistant settings. NMS ADC platform incorporates 1) our patent protected payload linker NMS-P945, a duocarmycin like DNA minor groove binder and alkylating agent inducing DNA damage, acting in chemoresistant cells with bystander effect and immunogenic cell death properties and generating ADCs highly efficacious in mouse xenograft models and safe when administered in NHP, 2) novel anthracyclines (PNU-682 derivatives) with an improved stability and safety profile and 3) targeted molecules with different mechanism of action including payloads active in synthetic lethality contexts. Payload linkers with different functionalization generated from each payload have been evaluated for chemical stability, sensitivity to lysosomal protease cleavage, and conjugability to monoclonal antibodies. The ADCs, generated with proof-of-concept antibodies (e.g. Trastuzumab), were characterized in terms of Drug to Antibody Ratio (DAR), aggregation level, plasma stability, antigen binding and differential antiproliferative activity in target positive vs target negative tumor cells. The best products resulting from the screening funnel have been subjected to a multidimensional analysis taking into consideration payload properties, tumor features and antigen expression in selected populations with the aim of identifying tumor types particularly sensitive to the payload. Our multidimensional approach coupling new payload linker with innovative MoA to careful selection of patients will allow to reach unprecedented efficacy and safety profile. Citation Format: Paolo Orsini, Matteo Salsa, Simona Rizzi, Ulisse Cucchi, Daniela Faiardi, Alessia Burocchi, Antonella Ciavolella, Rosita Lupi, Fabio Gasparri, Barbara Valsasina. A novel platform of diversified payloads to drive ADC innovation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5805.

Digital twin-driven assembly accuracy prediction method for high performance precision assembly of complex products

The high performance precision assembly (HPPA) of complex products such as aerospace, aircraft and high-end machine tool has demanding requirements for assembly accuracy. Achieving the accurate prediction of assembly accuracy for these complex products before assembling is the premise of improving the assembly quality and performance, and also has always been a challenge. Existing assembly accuracy prediction methods focus on acquiring the assembly deviation based on CAD model and manufacturing errors of parts, but rarely involve the multidimensional error coupling of parts and the influencing factors in the assembly process, which inevitably cause a certain gap between the prediction result and the actual condition, affecting the reliability of the prediction result. To address the above problems, this paper presents a digital twin (DT)-driven assembly accuracy prediction method for the HPPA of complex products. Firstly, this paper introduces the methodology overview and proposes an overall framework for DT-driven assembly accuracy prediction. Secondly, three key enabling technologies realizing the DT-driven assembly accuracy prediction, including the construction of part digital twin model, the generation of DT-based assembly process model, and assembly deviation propagation and accuracy analysis are introduced in detail. Finally, an application implementation of a prototype system and a case study involving a simplified satellite structure panel assembly process are used to verify the effectiveness and feasibility of the proposed method.

Assessment of reclaimed water utilization in water-scarce regions of China: A multi-dimensional–multi-agent coupling and nesting perspective

Reclaimed water utilization is a vital strategy for combatting global water scarcity. In China, diverse degrees and types of water scarcity have led to insufficient and unbalanced reclaimed water utilization. To address this problem, this study introduces a novel perspective that considers multi-dimensional (reclaimed water quantity–quality–price) and multi-agent (reclaimed water producers–consumers–government) coupling and nesting to establish a comprehensive framework for evaluating the reclaimed water utilization level (RWUL) in water-scarce regions. This comprehensive framework, comprising theoretical research, model construction, and region selection, is applied to water-scarce regions of China. The findings reveal that the RWUL grades in these regions are generally modest—Grades I to III (lower-level to high-level reclaimed water utilization). The RWUL grades vary based on regional water scarcity combinations. RWUL grades in water-scarce regions characterized by low water quality scarcity (Type C) are lower than those in regions with high water quantity and high water quality scarcity (Type H), low water quantity and high water quality scarcity (Type G), and low water quantity and low water quality (Type D). However, none of these regions achieved Grade IV (higher-level reclaimed water utilization). Consequently, based on the identified main influencing factors of RWUL, this study proposes five region-tailored measures for each water scarcity combination of regions to enhance their RWUL. By offering a comprehensive framework for assessing RWUL in water-scarce regions of China, this study not only identifies the existing shortcomings in reclaimed water utilization but also provides tailored measures for improvement. These insights are essential for policymakers seeking to implement targeted measures that promote reclaimed water utilization in water-scarce regions.

Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders.

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density-phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4-/CD8- double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.

Enhancing solid-state photochromic performance of Stenhouse Adducts doped in bulk polymers by C3-Symmetric multipolar design

Here, we introduce a C3-symmetric molecular design strategy to develop a brand-new visible-light organic photoswitch, named tri-branched multipolar Stenhouse Adduct (TMSA). After doping TMSA into low glass transition polymers (i.e. thermoplastic urethane, TPU) via simple blending and solution casting, the resultant composite films exploit unique geometric and electronic effects of TMSA to afford markedly-improved photoswitching performance compared to those doped with dipolar donor-acceptor Stenhouse Adduct (DASA) counterparts with suppressed solid state photochromism. Importantly, they display good fatigue resistance over 50 photo-discoloration/thermal-recovery cycles with slow degradation, surpassing those literature-reported composites involving various DASAs (<30 cycles). As revealed by combined experiment and computation studies, the multi-dimensional electronic coupling in multipolar TMSA facilitates the thermal cyclization and non-planar branched structures of TMSA afford large free space in polymers for efficient molecular isomerization, while the promoting effect on TMSA isomerization induced by ester-rich polymer micro-environments is more pronounced relative to DASA counterpart.

Digital economy and carbon emission: The coupling effects of the economy in Qinghai region of China

This study provides an in-depth analysis of the complex relationship between the digital economy and carbon emissions, fully drawing on essential principles of environmental economics, coupled economics, and sustainable development theory. Focusing on the Qinghai region in the western province of China, the study employs highly sophisticated methods such as multiple regression analysis and system dynamics modeling to reveal the multidimensional coupling effects between digital economy development and carbon emission dynamics. The study's results clearly show that in the Qinghai region of China, the booming growth of the digital economy is related to carbon emissions. Of particular interest, the study finds that this relationship exhibits a high degree of complexity and non-linearity and evolves gradually over time. Initially, the rapid expansion of the digital economy, accompanied by high energy consumption and increased carbon emissions, posed a significant challenge to environmental protection. However, a clear inverted “U"-shaped relationship has emerged as the digital economy evolves. This key inflection point signals a shift in the landscape as the digital economy begins to deliver some ecological benefits, potentially reducing the trend of carbon emissions in the future. The findings of this study go beyond simple causality and reveal a complex and evolving dynamic relationship between the digital economy and carbon emissions. Through such insights, this study provides a solid academic foundation and carefully constructs actionable policy recommendations to drive sustainable development. These insights apply to the Qinghai region of China and provide valuable references and lessons for other areas facing similar challenges.

Leverage rule-based Bayesian network on assessing straits/canals resilience performance on a risk coupling analysis perspective

ABSTRACT The maritime transportation system is comprised of several crucial nodes, including straits and canals, which are becoming increasingly susceptible to external emergencies and disturbances. The intricate interactive relationships and non-linear influences among the risk factors pose significant challenges in assessing the resilience performance of these straits and canals. To address these challenges, a four-stage resilience assessment framework was developed to analyze the resilience performance of the straits and canals under uncertain risk coupling scenarios. The framework leverages the advantages of fuzzy logic and Bayesian network, enabling the construction of conditional probability tables and reducing expert judgement inconsistencies. The findings indicate that the Strait of Malacca exhibits higher resilience performance under multi-dimensional risk coupling scenarios. This framework has significant potential in providing valuable insights for risk and resilience management and can be extended to similar industries.

A Streptomyces species from the ginseng rhizosphere exhibits biocontrol potential.

Plants and their associated microbes live in complicated, changeable, and unpredictable environments. They usually interact with each other in many ways through multidimensional, multiscale, and multilevel coupling manners, leading to challenges in the coexistence of randomness and determinism or continuity and discreteness. Gaining a deeper understanding of these diverse interaction mechanisms can facilitate the development of data-mining theories and methods for complex systems, coupled modeling for systems with different spatiotemporal scales and functional properties, or even a universal theory of information and information interactions. In this study, we use a "closed-loop" model to present a plant-microbe interaction system and describe the probable functions of microbial natural products. Specifically, we report a rhizosphere species, Streptomyces ginsengnesis G7, which produces polyketide lydicamycins and other active metabolites. Interestingly, these distinct molecules have the potential to function both as antibiotics and as herbicides for crop protection. Detailed laboratory experiments conducted in Arabidopsis (Arabidopsis thaliana), combined with a comprehensive bioinformatics analysis, allow us to rationalize a model for this specific plant-microbe interaction process. Our work reveals the benefits of exploring otherwise neglected resources for the identification of potential functional molecules and provides a reference to better understand the system biology of complex ecosystems.

Advancing coupling coordination simulation in the social-human-ecological system of the Three Gorges Reservoir Area: A multi-scenario system dynamics approach

Due to the lack of scientific and systematic thinking in the early stages of high-quality urbanisation, the interaction and stress between the social-human-ecological (SHE)11SHE social-human-ecological. system intensified, resulting in a series of problems related to the low level of ecological environment and the imbalanced socio-economic development. It is crucial to enhance the safety, health, and well-being of city dwellers, as well as to promote the sustainable development of the region. Based on complex systems science, using the Three Gorges Reservoir Area (TGRA)22TGRA Three Gorges Reservoir Area. as an instance, this study develops a multidimensional coupling conceptual model of the SHE system, employs the system dynamics (SD)33SD system dynamics. method to clarify the SHE system’s causal feedback mechanism, and simulates the coupling coordination degree (CCD)44CCD coupling coordination degree. from 2010 to 2030. Simultaneously, eight scenarios are created to improve the system’s CCD by modifying factors. According to historical and sensitivity test findings, the SD model used in this work can effectively represent the SHE system’s dynamic coupling and interaction connection. Furthermore, under the comprehensive development scenario that takes into account the protection of the ecological environment, human intelligent regulation, and socio-economic development, the TGRA has the biggest growth in CCD. As a result, raising the policy intensity of a single subsystem is insufficient. Balancing policy implementation for each subsystem is advantageous to improving the coupling coordination of the SHE system in the TGRA. The study is of significant importance for achieving high-quality socio-economic development and sustainable ecological management in the TGRA region.

Multi-dimensional hybrid potential stochastic resonance and application of bearing fault diagnosis

Stochastic resonance is a method to enhance weak signal by using noise, which has a wide range of applications in weak signal detection. In order to further investigate the application of multi-dimensional coupling stochastic resonance in practical engineering, a Multi-dimensional Double connection coupling Hybrid Potential Stochastic Resonance (MDHPSR) system is proposed in this paper. Firstly, the potential functions of bi-stable and tri-stable are briefly described, and the tri-stable system having a higher output amplitude. Secondly, the effect of different coupling methods on the output of the central and adjacent coupling ends are studied, and the output amplitude of double connection coupling is higher. Then, the double connection coupling of different potential functions is studied, and MDHPSR system effect is the best. Compared with Multi-dimensional Double connection Classical Bi-stable Stochastic Resonance (MDCBSR) system, MDHPSR system has better anti-noise performance. Finally, applying the two multi-dimensional coupling systems to bearing fault diagnosis, MDHPSR system output amplitude is higher and the Signal-to-Noise Ratio (SNR) is improved by more than 3 dB. This demonstrates the superior performance of MDHPSR system for weak signal detection and the value of the multi-dimensional coupling system for practical engineering applications.