Limited Conditions Research Articles

Analytic hierarchy process-based optimal load scheduling framework in an islanded distribution network

This paper proposes an analytic hierarchy process (AHP) based optimal load scheduling (AOLS) framework in an islanded distribution network to schedule power among prioritized loads under limited generation conditions. The scheduling problem is solved in two stages: in the first stage, AHP is used to determine the priority ranking of loads by assigning weights that are calculated based on the relative importance of loads and their attributes; in the second stage, optimal load scheduling is implemented by minimizing the total cost of load curtailment, subjected to network constraints and security limits. The scheduling problem is solved in four different cases by varying the total power generation using General Algebraic Modeling System (GAMS) to supply power to the loads in the order of priority. Taking the modified IEEE 34 node distribution network as an example, a simulation study is performed to show that the total cost of load curtailment according to AOLS is 18.51%, 24.86%, 28.65%, and 31.54% less than that of optimal load scheduling framework with equal weightage to all loads (OLSEW) in cases 1, 2, 3 & 4, which verifies the effectiveness of the proposed AOLS framework.

The development of genially-based interactive learning multimedia for elementary school students

This research focuses on producing genially-based interactive multimedia learning for fifth-grade elementary/MI students. This research belongs to the type of research and development research and development (RND). The procedure for developing genially-based interactive learning multimedia uses a development model developed by Sugiyono with ten stages, namely potential and problems, data collection, product design, design validation, product revision, initial trial, product revision, usage trial, product revision, and mass production. However, in the current state of the COVID-19 pandemic and the limited time, conditions, and costs, researchers only carried out these stages, only to stage 9, namely product revision. The results of the validation by media experts with a score of 71 in the good category, material experts with a score of 86.6 in the very good category, and learning experts with a score of 80 in the very good category, so that genially-based interactive learning multimedia is feasible to use. The results of the responses of the SD Muhammadiyah Karangkajen II class teachers in the initial trial, namely by obtaining a score of 82.2 with a very good category, then the results of the responses of the students of SD Muhammadiyah Karangkajen II in the initial trial with the subject of 4 students with a score of 90 in the very good category, while the response of students in the use trial with the subject of 19 students with a score of 95.2 with a very good category. Then, the average value of student responses is 92.6. Based on the results of teacher and student responses, genially based interactive multimedia learning is feasible to use.

Hoping for More: Tocqueville and the Insufficiency of ‘Self-Interest Well Understood’

ABSTRACT Alexis de Tocqueville (1805–1859) was convinced that without a new possibility for transcendence, democracies would be ill-prepared to allow for actual freedom. In Democracy in America, his study of the United States, he explained that when self-interest was enlightened, individuals would tend to identify their personal benefits with the well-being of the community. By transcending their individualistic tendency to self-enclose, they would contribute to forming and maintaining a real sovereignty of the people. However, unless the “doctrine of self-interest well understood” was aided by a higher ideal, by itself it would eventually fall short, thus paving the way for new forms of despotism. Religion, and more specifically, reformed versions of Christianity, seemed to effectively elevate the outlook of the early Americans. As I will argue, however, Tocqueville ultimately held that those versions lacked the profundity and stability required to resist the strong materialistic and individualistic tendencies of people living in a democracy. Tocqueville’s apparent, if anxious-ridden, preference for Catholicism as the more adequate civil religion resonates with important aspects of Augustine’s theory of the Two Cities, the earthly and the heavenly city. For both Tocqueville and Augustine, the Roman Church’s stable doctrine was what could more successfully teach mankind the truth about their limited condition, hence making them more capable of learning the “art of being free.”

Xylem K+ loading modulates K+ and Cs+ absorption and distribution in Arabidopsis under K+-limited conditions.

Potassium (K+) is an essential macronutrient for plant growth. The transcriptional regulation of K+ transporter genes is one of the key mechanisms by which plants respond to K+ deficiency. Among the HAK/KUP/KT transporter family, HAK5, a high-affinity K+ transporter, is essential for root K+ uptake under low external K+ conditions. HAK5 expression in the root is highly induced by low external K+ concentration. While the molecular mechanisms of HAK5 regulation have been extensively studied, it remains unclear how plants sense and coordinates K+ uptake and translocation in response to changing environmental conditions. Using skor mutants, which have a defect in root-to-shoot K+ translocation, we have been able to determine how the internal K+ status affects the expression of HAK5. In skor mutant roots, under K+ deficiency, HAK5 expression was lower than in wild-type although the K+ concentration in roots was not significantly different. These results reveal that HAK5 is not only regulated by external K+ conditions but it is also regulated by internal K+ levels, which is in agreement with recent findings. Additionally, HAK5 plays a major role in the uptake of Cs+ in roots. Therefore, studying Cs+ in roots and having more detailed information about its uptake and translocation in the plant would be valuable. Radioactive tracing experiments revealed not only a reduction in the uptake of 137Cs+ and 42K+in skor mutants compared to wild-type but also a different distribution of 137Cs+ and 42K+ in tissues. In order to gain insight into the translocation, accumulation, and repartitioning of both K+ and Cs+ in plants, long-term treatment and split root experiments were conducted with the stable isotopes 133Cs+ and 85Rb+. Finally, our findings show that the K+ distribution in plant tissues regulates root uptake of K+ and Cs+ similarly, depending on HAK5; however, the translocation and accumulation of the two elements are different.

Using a fast hybrid pixel detector for dose-efficient diffraction imaging beam-sensitive organic molecular thin films

We discuss the benefits and showcase the applications of using a fast, hybrid-pixel detector (HPD) for 4D-STEM experiments and emphasize that in diffraction imaging the structure of molecular nano-crystallites in organic solar cell thin films with a dose-efficient modality 4D-scanning confocal electron diffraction (4D-SCED). With 4D-SCED, spot diffraction patterns form from an interaction area of a few nm while the electron beam rasters over the sample, resulting in high dose effectiveness yet highly demanding on the detector in frame speed, sensitivity, and single-pixel count rate. We compare the datasets acquired with 4D-SCED using a fast HPD with those using state-of-the-art complementary metal-oxide-semiconductor (CMOS) cameras to map the in-plane orientation of π-stacking nano-crystallites of small molecule DRCN5T in a blend of DRCN5T: PC71BM after solvent vapor annealing. The high-speed CMOS camera, using a scintillator optimized for low doses, showed impressive results for electron sensitivity and low noise. However, the limited speed restricted practical experimental conditions and caused unintended damage to small and weak nano-crystallites. The fast HPD, with a speed three orders of magnitude higher, allows a much higher probe current yet a lower total dose on the sample, and more scan points cover a large field of view in less time. A lot more faint diffraction signals that correspond to just a few electron events are detected. The improved performance of direct electron detectors opens more possibilities to enhance the characterization of beam-sensitive materials using 4D-STEM techniques.

Can a single ammonia and water molecule enhance the formation of methanimine under tropospheric conditions?: kinetics of •CH2NH2 + O2 (+NH3/H2O).

The aminomethyl (•CH2NH2) radical is generated from the photo-oxidation of methylamine in the troposphere and is an important precursor for new particle formation. The effect of ammonia and water on the gas-phase formation of methanimine (CH2NH) from the •CH2NH2 + O2 reaction is not known. Therefore, in this study, the potential energy surfaces for •CH2NH2 + O2 (+NH3/H2O) were constructed using ab initio//DFT, i.e., coupled-cluster theory (CCSD(T))//hybrid-density functional theory, i.e., M06-2X with the 6-311++G (3df, 3pd) basis set. The Rice-Ramsperger-Kassel-Marcus (RRKM)/master equation (ME) simulation with Eckart's asymmetric tunneling was used to calculate the rate coefficients and branching fractions relevant to the troposphere. The results show 40% formation of CH2NH at the low-pressure (<1 bar) and 100% formation of CH2NH2OO• at the high-pressure limit (HPL) condition. When an ammonia molecule is introduced into the reaction, there is a slight increase in the formation of CH2NH; however, when a water molecule is introduced into the reaction, the increase in the formation of CH2NH was from 40% to ∼80%. The calculated rate coefficient for •CH2NH2 + O2 (+NH3) [1.9 × 10-23cm3 molecule-1 s-1] and for CH2NH2 + O2 (+H2O) [3.3 × 10-17cm3 molecule-1 s-1] is at least twelve and six order magnitudes smaller than those for free •CH2NH2 + O2 (2 × 10-11cm3 molecule-1 s-1 at 298K) reactions, respectively. Our result is consistent with that of previous experimental and theoretical analysis and in good agreement with its isoelectronic analogous reaction. The work also provides a clear understanding of the formation of tropospheric carcinogenic compounds, i.e., hydrogen cyanide (HCN).

GlMPC activated by GCN4 regulates secondary metabolism under nitrogen limitation conditions in Ganoderma lucidum.

Mitochondrial pyruvate carrier (MPC) is a pyruvate transporter that plays a crucial role in regulating the carbon metabolic flow and is considered an essential mechanism for microorganisms to adapt to environmental changes. However, it remains unclear how MPC responds to environmental stress in organisms. General control non-derepressible 4 (GCN4), a key regulator of nitrogen metabolism, plays a pivotal role in the growth and development of fungi. In this study, we report that GCN4 can directly bind to the promoter region and activate the expression of GlMPC, thereby regulating the tricarboxylic acid cycle and secondary metabolism under nitrogen limitation conditions in Ganoderma lucidum. These findings provide significant insights into the regulation of carbon and nitrogen metabolism in fungi, highlighting the critical role of GCN4 in coordinating metabolic adaptation to environmental stresses.

Using the Life Cycle Approach for Multiobjective Optimization in the Context of the Green Supply Chain: A Case Study of Brazilian Coffee

This study proposes a multiobjective optimization model (MOO) based on a green supply chain so that coffee produced in Brazil could supply the North American market with lower environmental impacts and costs. Production and distribution arrangements were established considering four coffee-producing regions, three ports of origin in Brazil, four destination ports, seven roasting plants, and fifteen consumption centers, all distributed throughout the American territory. Environmental and economic performances regarding global warming potential (GWP) and costs were determined for a life cycle approach. The results indicate that coffee cultivation has the most significant contributions to the GWP of the arrangements. The transport of the product by road also plays an essential role, especially if extensive distances are covered during the port–roaster–consumer center journey in the United States. The analysis showed differences of 2.0 kg CO2eq and US$8.00 per ton of coffee between the best and worst arrangements, which can be considered significant when projected to the Brazilian annual coffee export scale. In the environmental limit condition, the optimization can lead to non-trivial results compared to the real market. The model conceived for the MOO can be improved to reproduce more realistic conditions by incorporating producer and consumer markets, inserting uncertainties.

Controlling Salmonella: strategies for feed, the farm, and the processing plant

Controlling Salmonella in poultry is an ongoing food safety measure and while significant progress has been made, there is a need to continue to evaluate different strategies that include understanding Salmonella-poultry interaction, Salmonella-microbiota interactions, Salmonella genetics and response to adverse conditions, and preharvest and postharvest parameters that enable persistence. The purpose of this symposium is to discuss different strategies to consider from feed milling to the farm to the processing environment. This Poultry Science Association symposium paper is divided into 5 different sections that covers 1) immunological aspects of Salmonella control, 2) application of Salmonella genetics for targeted control strategies in poultry production, 3) improving poultry feed hygienics: utilizing feed manufacture techniques and equipment to improve feed hygienics, 4) practical on farm interventions for controlling Salmonella-what works and what may not work, and 5) monitoring and mitigating Salmonella in poultry. These topics elucidate the critical need to establish control strategies that will improve poultry gut health and limit conditions that exposes Salmonella to stress causing alterations to virulence and pathogenicity both at preharvest and postharvest poultry production. This information is relevant to the poultry industry's continued efforts to ensure food safety poultry production.

Rheological and microstructural properties of heteroprotein complex coacervates formed by lactoferrin and osteopontin

Lactoferrin (LF) and osteopontin (OPN) form heteroprotein complex coacervates (HPCCs) within limited conditions of pH, ionic strength, total protein concentration (TPC), and protein stoichiometry. In this study, it was determined using dynamic oscillatory rheology, that the coacervates exhibit frequency-dependent, viscoelastic behaviour whereby the storage modulus (G′) was less than the loss modulus (G″) for all frequencies studied (≤100 rad/s). By reducing the TPC and/or ionic strength of the system, an increase in the protein concentration and strength of the coacervate was achieved. The G′ and G″ of the coacervates were largely independent of temperature <50 °C, but above this temperature, significant changes occurred due to protein denaturation. Using microscopic techniques, it was also determined that both proteins co-localise throughout the coacervate phase in a highly ordered, structural network of protein and water. The resulting freeze-dried coacervate powder particles had a honeycomb-like appearance due to an intricate network of porous channels formed during the drying process. This physicochemical characterisation of LF-OPN HPCCs has increased scientific understanding of their rheological and microstructural properties which can now be understood, predicted, and controlled for subsequent biochemical analysis.

Conserved copper regulation of the antimicrobial isocyanide brassicicolin A in Alternaria brassicicola

Phytopathogenic Alternaria species are renown for production of toxins that contribute to virulence on host plants. Typically, these toxins belong to well-known secondary metabolite chemical classes including polyketides, non-ribosomal peptides and terpenes. However, the purported host toxin brassicicolin A produced by A. brassicicola is an isocyanide, a chemical class whose genetics and encoding gene structure is largely unknown. The chemical structure of brassicicolin A shows it to have similarity to the recently characterized fumicicolins derived from the Aspergillus fumigatus isocyanide synthase CrmA. Examination of the A. brassicicola genome identified AbcrmA, a putative homolog with 64% identity to A. fumigatus CrmA. Deletion of AbcrmA resulted in loss of production of brassicicolin A. Contrary to reports that brassicicolin A is a host-specific toxin, the ΔAbcrmA mutants were equally virulent as the wildtype on Brassica hosts. However, in line with results of A. fumigatus CrmA generated metabolites, we find that brassicicolin A increased 360-fold under copper limited conditions. Also, like A. fumigatus CrmA derived metabolites, we find brassicicolin A to be a broad-spectrum antimicrobial. We speculate that CrmA-like isocyanide synthase products provide the producing fungi a fitness advantage in copper depleted environments.

Natural and anthropogenic carbon input affect microbial activity in salt marsh sediment.

Salt marshes are dynamic, highly productive ecosystems positioned at the interface between terrestrial and marine systems. They are exposed to large quantities of both natural and anthropogenic carbon input, and their diverse sediment-hosted microbial communities play key roles in carbon cycling and remineralization. To better understand the effects of natural and anthropogenic carbon on sediment microbial ecology, several sediment cores were collected from Little Sippewissett Salt Marsh (LSSM) on Cape Cod, MA, USA and incubated with either Spartina alterniflora cordgrass or diesel fuel. Resulting shifts in microbial diversity and activity were assessed via bioorthogonal non-canonical amino acid tagging (BONCAT) combined with fluorescence-activated cell sorting (FACS) and 16S rRNA gene amplicon sequencing. Both Spartina and diesel amendments resulted in initial decreases of microbial diversity as well as clear, community-wide shifts in metabolic activity. Multi-stage degradative frameworks shaped by fermentation were inferred based on anabolically active lineages. In particular, the metabolically versatile Marinifilaceae were prominent under both treatments, as were the sulfate-reducing Desulfovibrionaceae, which may be attributable to their ability to utilize diverse forms of carbon under nutrient limited conditions. By identifying lineages most directly involved in the early stages of carbon processing, we offer potential targets for indicator species to assess ecosystem health and highlight key players for selective promotion of bioremediation or carbon sequestration pathways.

The influence of penetration angle on anti-penetration performance and reverse penetration ricochet phenomenon of UHMWPE laminates

Penetration angle refers to the angle between the normal of laminates and the projectile trajectory. In actual battlefield conditions, projectiles may hit Ultra-High Molecular Weight Polyethylene fiber (referred to as UHMWPE) laminates from various angles, resulting in ricochet phenomena and secondary injuries. Currently, research on bullets hitting penetrating laminates at a perpendicular angle is relatively well-developed, while research on the penetration of laminates by bullets at other angles is limited. Therefore, this study combined experiments and numerical calculations to investigate the penetration of 7.62 mm steel core projectiles at different angles on UHMWPE laminates. The study found that UHMWPE laminates enhanced bullet resistance through yawing and bending the penetrating projectiles at different angles. The influence of penetration angle on the impact area of the projectile-facing surface, the height of the bulge on the backside, and the penetration depth, as well as the trajectory and morphology of the projectile, were mastered in this study. Notably, a penetration angle of 50° was the limit condition for projectile to produce reverse penetration ricochet phenomenon of projectiles in UHMWPE laminates with a thickness of 30 mm. These research findings provide a theoretical basis and technical support for the bulletproof design of UHMWPE laminates.

AI for PET image reconstruction.

Image reconstruction for positron emission tomography (PET) has been developed over many decades, with advances coming from improved modelling of the data statistics and improved modelling of the imaging physics. However, high noise and limited spatial resolution have remained issues in PET imaging, and state-of-the-art PET reconstruction has started to exploit other medical imaging modalities (such as MRI) to assist in noise reduction and enhancement of PET's spatial resolution. Nonetheless, there is an ongoing drive towards not only improving image quality, but also reducing the injected radiation dose and reducing scanning times. While the arrival of new PET scanners (such as total body PET) is helping, there is always a need to improve reconstructed image quality due to the time and count limited imaging conditions. Artificial intelligence (AI) methods are now at the frontier of research for PET image reconstruction. While AI can learn the imaging physics as well as the noise in the data (when given sufficient examples), one of the most common uses of AI arises from exploiting databases of high-quality reference examples, to provide advanced noise compensation and resolution recovery. There are three main AI reconstruction approaches: (i) direct data-driven AI methods which rely on supervised learning from reference data, (ii) iterative (unrolled) methods which combine our physics and statistical models with AI learning from data, and (iii) methods which exploit AI with our known models, but crucially can offer benefits even in the absence of any example training data whatsoever. This article reviews these methods, considering opportunities and challenges of AI for PET reconstruction.

Chaos Synchronization of InGaAsP Lasers

The optical output of a semiconductor laser can fluctuate chaotically by modulating its direct current in limited conditions of the modulated current signal parameters in terms of modulation frequency and modulation index. In this work, single, double, and chaotic pulses of an InGaAsP laser with direct current modulation, are numerically presented through a bifurcation diagram. Numerically, the unidirectional optical coupling system realizes chaotic synchronization between two identical InGaAsP lasers with direct current modulation, as the transmitter/receiver configuration. The transmission time for transmitting light from the transmitted laser to the received laser is essential for controlling the quality of chaos synchronization. The transmission time applies on the order of nanoseconds. Chaos synchronization quality is estimated by a correlation plot and calculated by the cross-correlation coefficient. This study observed the best synchronization quality (complete chaos synchronization) when the two lasers are identical. On the other hand, the chaotic synchronization between two non-identical InGaAsP lasers was investigated. In this case, complete chaos synchronization is not found, and the quality of chaotic synchronization was observed to decrease as the mismatch between the parameters of the two lasers increased.

Multi-objective optimization of two-echelon vehicle routing problem: Vaccines distribution as a case study

During pandemics, the efficiency of the vaccine supply chain may be compromised, especially the last-mile distribution, due to poor infrastructure that is unable to support the urgent need for vaccination. In developing countries, this becomes even more challenging due to limited vehicles, road conditions, and inadequate cold storage. Since it is impractical to construct permanent warehouses when pandemics occur, vaccine distribution would be extravagant both environmentally and financially. In this study, a new multi-objective MILP model combining two-echelon vehicle routing problem (2E-VRP) and vaccine supply chain (VSC) is presented to minimize the number of unsatisfied doses undelivered to customers. A heuristic solution based on the greedy random search is proposed to solve the model, as it is classified as NP-hard model. The model is solved using the commercial solver CPLEX for different datasets. Then the heuristic is used to solve the same datasets, and the results are compared based on the solution’s quality and computation efforts. Moreover, Pareto fronts were constructed to demonstrate the trade-offs between the conflicting objective functions. Finally, a real case study is solved using the proposed model to demonstrate its effectiveness compared to the original VRP, and the results showed an improvement of average 11.97% in the number of doses delivered.

IoT and Ensemble Long-Short-Term-Memory-Based Evapotranspiration Forecasting for Riyadh.

Evapotranspiration (ET) is the fundamental component of efficient water resource management. Accurate forecasting of ET is essential for efficient water utilization in agriculture. ET forecasting is a complex process due to the requirements of large meteorological variables. The recommended approach is based on the Internet of Things (IoT) and an ensemble-learning-based approach for meteorological data collection and ET forecasting with limited meteorological conditions. IoT is part of the recommended approach to collect real-time data on meteorological variables. The daily maximum temperature (T), mean humidity (Hm), and maximum wind speed (Ws) are used to forecast evapotranspiration (ET). Long short-term memory (LSTM) and ensemble LSTM with bagged and boosted approaches are implemented and evaluated for their accuracy in forecasting ET values using meteorological data from 2001 to 2023. The results demonstrate that the bagged LSTM approach accurately forecasts ET with limited meteorological conditions in Riyadh, Saudi Arabia, with the coefficient of determination (R2) of 0.94 compared to the boosted LSTM and off-the-shelf LSTM with R2 of 0.91 and 0.77, respectively. The bagged LSTM model is also more efficient with small values of root mean squared error (RMSE) and mean squared error (MSE) of 0.42 and 0.53 compared to the boosted LSTM and off-the-shelf LSTM models.

Fast and robust for texture-less feature registration via adaptive heterogeneous kernels

Feature registration is a core problem in computer vision and machine learning techniques. In recent years, significant progress has been made in learning-based feature registration algorithms. However, such methods usually capture image-level features and strive to capture contour information, inadvertently neglecting the exploration of low-texture regions, while the complex model structure brings more parameters. Therefore, it remains a challenging task to effectively address low-texture feature registration under limited sample conditions. In this paper, we propose a fast and robust feature registration algorithm to achieve fast feature registration in the low-texture case. Specifically, we first construct a two-step learning framework and use a faster adaptive heterogeneous filter (AdaH-Filter) to guide coarse-grained and fine-grained feature extraction. Then, we propose registration feature refiners (ReFR) to achieve the fusion of two-stage features in a low-texture environment while guaranteeing the speed of the detector. Finally, to further improve the network performance, a Warp Extractor is proposed to improve the speed and portability of model inference. This strategy allows the network to perform different levels of fine extraction adaptively according to the registration requirements. Moreover, the proposed method is trained in an end-to-end manner, guided by cosine loss, without any additional supervision. Extensive experimental results on several challenging and representative feature registration datasets in the industry show that the proposed method outperforms the existing state-of-the-art methods. More importantly, it has a faster inference speed under different sensor modalities.

Strategies for low limit maintenance thresholds and condition states for bridge structures

AbstractThe objectives of asset management are to ensure secure service of the objects and/or network, to preserve the infrastructure capital and to maintain the function through their life cycle. Maintenance activities should preserve the performance and future serviceability in such way that an adequate level of reliability with respect to performance requirements applicable to the structure under consideration is preserved. Hence adequate and low limit maintenance should guarantee reliability, safety functionality, availability, maintainability, health and security, as well as environmental and economic performance at the politically agreed level of service. In order to arrange resources, the concept of condition‐states and minimum maintenance thresholds are widely used in context of maintenance planning in many European countries. However, there is no uniform approach defining and rating the condition‐states and setting the low limit maintenance thresholds. In general, national authorities or individual operators are using their own developments which consequently lead to different levels of service. In many cases, the models and criteria used are based on country‐specific experience with implementation of condition‐based maintenance strategies. Moreover, in some European countries, preventive maintenance uses both condition‐based and scheduled maintenance strategy, with certain maintenance measures carried out in a condition‐based manner and some other measures are planned/fixed at certain intervals. In this contribution based on the outcomes of IM‐SAFE project, maintenance concepts, condition‐state definitions and low limit thresholds of maintenance strategies of European countries will be presented, discussed and compared. In addition, a special focus is given to apply sustainable measures and to develop maintenance strategies respecting the European green deal scopes.

Chaotic Effect-Based Array Duffing Systems with Improved Nonlinear Restoring Force for Weak Signal Detection in Dynamic MWD.

In the process of dynamic Measurement While Drilling (MWD), the strong vibration and rapid rotation of the Bottom Hole Assembly (BHA) lead to multi-frequency and high-amplitude noise interference in the attitude measurement signal. The weak original signal and extremely low signal-to-noise ratio (SNR) are always the technical difficulties of dynamic MWD. To solve this problem, this paper uses the chaotic effect of the Duffing system, which takes the expression (-x3 + x5) as a nonlinear restoring force to detect the weak characteristic signal of downhole dynamic MWD. First of all, in order to meet the limit condition of the chaotic phase transition of the system output, the frequency value of the characteristic signal is reconstructed and transformed based on the variable scale theory. Then, in order to solve the influence of the initial phase of the characteristic signal on the detection accuracy, a detection model based on the array Duffing system is presented, and a frequency-detection scheme with all-phase coverage is given. Finally, another array Duffing system is designed for the parameter estimation of the characteristic signal. The critical value of chaotic phase transition is determined by adjusting the amplitude of the driving signal of the array Duffing system, and then the amplitude and phase parameters of the characteristic signal are synchronously estimated. The experimental results show that the proposed method can effectively extract the weak characteristic signal within the strong noise, and the SNR of the characteristic signal can be as low as -21 dB. Through the attitude calculation for the extracted characteristic signal, it can be seen that the proposed method can improve the accuracy of the inclination of the drilling tool significantly, which proves the feasibility and effectiveness of the method proposed in this paper.