Operation Ability Research Articles

Analysis and Compensation of Position Estimation Error for Sensorless Reduced DC-Link Capacitance IPMSM Drives

To extend the lifetime, improve the power density and reduce the system cost, the film capacitor is applied to replace the large-volume electrolytic capacitor in motor drives. As the dc-link voltage fluctuates periodically, the rotor position estimation error and operation stability are necessary to be concerned in the position sensorless control methods. A cross-decoupling complex filtering-based position estimation method is investigated for the reduced capacitance interior permanent magnet synchronous motor drive system. Harmonic components of the extended back electromotive force (EEMF) caused by the dc-link voltage fluctuation are analyzed to evaluate the additional rotor position error. A cross-decoupling complex filter realized by the multiple first-order complex filters with different center frequencies is designed to improve the position estimation precision. Harmonics of the EEMF are suppressed and the position error can be eliminated. The estimation precision and operation ability are improved. Experimental results are performed to verify the effectiveness of the proposed method.

Financial analysis of Bright Dairy based on Harvard Analysis framework

With the continuous improvement of residents' income level, the development potential of dairy products market is huge. Bright Dairy is a dairy company with a century-old operating history. This paper uses the Harvard analysis framework to analyze the strategic choice, accounting quality and financial indicators of Bright Dairy from 2017 to 2021, and forecasts the prospects of Bright Dairy combined with the conclusions of the first three levels. The study found that Bright Dairy has poor performance in terms of debt paying ability, operation ability and profitability, and then proposed development countermeasures such as strengthening market development and asset management.

Open-Circuit Fault-Tolerant Vector Control for Five-Phase SPMSM Based on Five-Phase Six-Leg Inverter

Five-phase permanent-magnet synchronous motor (PMSM) has the ability of fault-tolerant operation, which is beneficial for high reliability occasions. A fault-tolerant current vector control strategy based on five-phase six-leg inverter is proposed for open-circuit fault in this article. It deals with single-, double-, and triple-phase fault conditions. First, the overall control scheme is established based on the mathematical model of five-phase surface-mounted PMSM. To release more control degrees of freedom, the constraint for the sum of fault-tolerant phase currents is removed, and the control variates method is used to calculate the optimal fault-tolerant currents. Furthermore, to achieve the current tracking, the corresponding reduced-order current transformation matrices are derived, and the corresponding main power topology, the five-phase six-leg voltage source inverter (VSI), is established. The unbalanced operation of the topology is investigated, the equivalence to the full-bridge VSI is proved, and the voltage utilization and voltage unbalance of five phase half-bridge, full-bridge, and six-leg inverter are compared. Then, the corresponding carrier-based PWM control strategy based on zero-sequence injection has been proposed, which is equivalent with the three-dimensional space vector PWM algorithm and is computationally efficient. The experimental results confirm the effectiveness of the proposed fault-tolerant control strategy.

The Interaction and Coupling Between Enterprise Value Evaluation and Regional Ecological Environment

Abstract The development of industrial Internet technology enterprises plays an important supporting role in green water and green mountains, as a forestry industry with both economic value and ecological value. at present, it is facing a good opportunity for development. However, industrial Internet technology enterprises are faced with many risks, such as long investment cycle, low comparative income, and their ecological value is easy to be ignored. Based on FCFF model and LINEST function, this paper studies the enterprise value evaluation and ecological development. The main conclusions are as follows: (1) the economic value of industrial Internet technology enterprises is greatly affected by non-financial factors; (2) the excess income of industrial Internet technology enterprises is affected by ecological improvement. (3) under the background of green finance, the comprehensive operation ability of enterprises can be effectively improved through internal control of enterprises, formulation of government laws and supervision of social enterprises. This study has important theoretical and practical significance for China to scientifically and reasonably evaluate the value of industrial Internet technology enterprises.

Research on the Cultivation Strategy of Junior Middle School Student's Mathematics Operation Ability in China

Many scholars have carried out research on the cultivation strategy of junior middle school students mathematics operation ability in China, but few scholars have done general research on this topic. We reviewed existing research with the literature analysis method and drew the following conclusions: (1) Most of the researchers are junior middle school teachers, and a small number of researchers are master degree students. Researchers often first analyze the status quo of junior middle school students' mathematics operation ability and its influencing factors. Then, provided some the cultivation strategies; (2) The cultivation strategy of junior middle school student's mathematics operation ability focuses on teachers' perspectives, and mainly concerning on five categories: knowledge, skills, thinking, teaching concepts and teaching methods, and non-intellectual factors. There are few studies on the perspectives of students. (3) The methods used by the researchers are relatively single. The feasibility and the effectiveness of the cultivation strategy are not further followed up and analyzed. In the future, researchers should adopt a variety of research methods from the perspectives of students to explore the cultivation strategies. It is necessary to further follow up and analyze the feasibility and effectiveness of the research strategies.

Features of simulation of operator control of unmanned aerial vehicle and its target load

The article is devoted to the formulation of the problem of synthesis of the control system of an unmanned aerial vehicle (UAV) with the participation of a human operator. An analysis is made of various approaches to the synthesis of systems, models of a human operator as a link in a tracking system, mathematical models and information support for complex human-machine systems, competencies required by UAV operators. The system considers a human operator as a dynamic link that performs compensatory monitoring of the relevant information that is presented on the monitor of the corresponding operator controlling the UAV or its target load in accordance with the task. On the basis of the analysis, a generalized scheme of the UAV control system and its target load is substantiated, a mathematical model of a human operator is studied in the form of a transfer function consisting of five elementary links that take into account the dynamic characteristics of the central nervous system, the delay of the neuromuscular system, the ability of the human operator to smooth random fluctuations of the information presented on the monitor screen received from the telemetry system. As a typical example of a human-machine control system, the ground control point of the multifunctional unmanned aerial complex “Busel” is considered, which includes two workplaces for the UAV control operator and the target load control operator, which is considered equipment designed to monitor objects located on the earth’s surface

An evaluation of case difficulty, operator abilities, when and how to refer

Headlines Endodontically treated tooth needs to last a lifetime and therefore root canal treatment has to be performed with precision the first time around. A good knowledge of case difficulty and operator abilities can help DP decide on whether they want to treat a tooth or refer to a specialist. The Nordic Endodontic Assessment Form places DP and treatment tooth into 4 categories A, B, C and D according to technical skills, theoretical knowledge, and use of tools by DP. To make a referral, good communication with the patient is essential. The referral needs to be done early in the treatment procedure.

High fluorescent nitrogen − doped carbon dots derived from Sanghuangporus lonicericola for detecting tetracyclines in aquaculture water and rat serum samples

Tetracyclines (TCs) are a kind of broad − spectrum and effective antibiotics that have been widely used in veterinary and human medicine, which may pose serious risk to human health if they are accumulated in human body. The fluorescence method using nanomaterials as probes has been gradually used for the detection of TCs because of its simple operation, high sensitivity and recognition ability. Herein, a novel nitrogen doped carbon dots (N − CDs) derived from Sanghuangporus lonicericola was synthesized by hydrothermal method. The N − CDs exhibited bright blue fluorescence, high quantum yield (QY) of 60.99 %, and excellent photostability, which was employed as a fluorescent probe for selective detection of TCs, including oxytetracycline (OXY), doxycycline (DOX), tetracycline (TCY) and minocycline (MNO). The fluorescence intensity of the N − CDs decreased linearly with the increasing concentration of OXY, DOX, TCY and MNO, and their concentrations were in the range of 0.6 – 73.3 μM, 0 – 95.2 μM, 6.5 – 72.3 μM and 10 – 52.6 μM, respectively. As for practical application, the as − prepared N − CDs could not only be effectively applied for determination of TCs in aquaculture water and rat serum samples with low relative standard deviation (RSD) and good recoveries, but also track the concentration change of TCs in rats blood model over time. Towards the fluorescence detection mechanism, the results of UV–vis absorption spectra and fluorescence lifetimes proved that the fluorescent quenching of N − CDs occurred from internal filtration effect (IFE) in the presence of TCs. This work provides guidance for the development of new TCs sensors based on fluorescent nanomaterials, and has a good application prospect in the quality control of agriculture, food and pharmaceutical production processes.

Dual-layer self-healing strategy for standalone building energy systems: A case study of a tropical island

Due to dynamic building demand and environment, the state of each energy subsystem changes frequently in an integrated energy system (IES), which seriously threatens its operation security. Reliable self-healing operation ability is guarantee of stable energy supply. A dual-layer self-healing strategy considering decision boundaries is proposed to maximize resilience for stand-alone IES. In disturbance identification stage, pressure and release risk model is adopted to detect anomalies and risk state. In scheduling decision stage, decision boundaries of device layer resolve internal strategies conflict within a single device. Decision boundaries of system layer coordinate task and energy allocation among different devices. In scheduling response stage, final scheduling decision is performed to prevent and mitigate impact of potential threats on IES. Results indicate that dual-layer self-healing strategy improves system resilience by 54 % – 163 % in eight fault scenarios compared to fault isolation method. It also has advantages in energy supply reliability, fault absorption and energy storage capacity. Moreover, reduction of decision repetition rate speeds up the real-time scheduling efficiency. The proposed self-healing strategy helps system achieve stronger adaptability and reliability under dynamic conditions. It has a positive effect on practical application of IES for buildings in isolated areas.

Three-dimensional point cloud registration algorithm based on the correlation coefficient

Point cloud registration is an important research problem in machine vision. One of the most widely used methods for point set registration is the iterative closest point (ICP) algorithm. However, ICP is known to be susceptible to local minima because it is based on the local iterative optimization technique and its performance critically relies on the quality of the initialization. To reduce the possibility of the algorithm falling into local minima, we propose an iterative algorithm based on geometric distance and local feature weighting named weighted correlation coefficient iterative closest point algorithm (WCC_ICP). The algorithm first establishes the corresponding relationship of points using linear representation and constructs an optimization model with constraints. Subsequently, the constrained optimization model is converted into an unconstrained optimization model by Lagrangian multiplication. Finally, an iterative technique is used to solve the optimal rigid body transformation of the optimized model. In addition, in each iteration, the identification ability of the local feature operator of points is used to repair the corresponding relation of points, which reduces the risk of the iterative algorithm falling into the local minima. Numerical experiments show that the proposed WCC_ICP algorithm reduces the risk of the iterative algorithm falling into local minima.

Deriving Operating Rules of Hydropower Reservoirs Using Multi-Strategy Ensemble Henry Gas Solubility Optimization-Driven Support Vector Machine

Hydropower is an important clean renewable energy that plays a key role in coping with issues such as global energy security, environmental protection, and climate change. In order to improve the optimal operation ability of hydropower reservoirs in the context of forecast runoff with limited accuracy and prediction period, there has been a growing interest in deriving operating rules of hydropower reservoirs. Reasonable operation decision is very important for safe operation of reservoirs and efficient utilization of water resources. Therefore, a novel method of operation rules derivation is proposed in this study. Optimal operation model of hydropower reservoir is established and support vector machine (SVM) is used to derive operation rules based on the optimal operation results. In order to improve the performance of SVM, the Henry gas solubility optimization (HGSO) is used to optimize its hyperparameters for the first time. Meanwhile, multiple strategies are applied to overcome the drawbacks of HGSO. The multi-verse optimizer (MVO) is used to enhance the exploration capability of basic HGSO. Quadratic interpolation (QI) is used to improve the exploitation ability of HGSO. In this study, the Xiluodu and Xiangjiaba hydropower reservoirs in the upper Yangtze River of China were selected as a case study. First, the improved HGSO called MVQIHGSO was tested on 23 classical benchmark functions. Then, it was employed to optimize hyperparameters of SVM model for deriving operation rules. The results and statistical studies indicate that the improved HGSO outperforms the comparison algorithms in exploration and exploitation. The obtained results imply that the novel method named MVQIHGSO-SVM can provide a new practical tool to deriving operation rules for hydropower reservoirs, which is conducive to the safe and efficient utilization of water resources.

Standard Wave Scatter Table Limitation for Evaluating SGISC Based on Hindcast Data Analysis

The operational measure (OM) of the Second-Generation Intact Stability Criteria (SGISC) is the initial step toward the design of a performance-based dynamic stability assessment of the ship by considering the vessel’s operation, loading condition and weather parameters. The SGISC recommends the standard wave scatter table (WST) for the environmental data, an indefinite requirement for a simplified assessment pathway, which provides the probability of wave occurrence. The existing standard WST was developed based on the North Atlantic Ocean. The study aims to identify the discrepancy in the probability of wave occurrence in the IMO-recommended WST when compared with developed hindcast WST for smaller regions of the North Atlantic Ocean for the application of the SGISC. This study is one of a kind and very significant, given that the assessment using the standard WST provided unrestricted operational ability to ship under the SGISC. The findings of this research provide insights into significant differences in the existing standard WST when compared graphically with hindcast data, especially across different seasons of the North Atlantic Ocean. A case study of OMs on the C11 class post-Panamax container ship for excessive acceleration is provided to better represent the study. In the case study, the operational limitation defined by the hindcast WST for individual sea areas and seasons is compared with the standard WST. This investigation shows that regional and seasonal operational limitations are required for season 4 operation beyond the standard WST safety estimation and that the operational limitation achieved with standard WST is not adequate. The findings suggest that the identified limitations significantly limit the use of a standard WST for unrestricted operational validation in the SGISC. The provided recommendation is very relevant in improving the safety assessment using vulnerability criteria, given that the hindcast data are reliable and available for the season and are also region-specific, and hence the accuracy of the ship stability can be improved while using the SGISC.

Application of self-attention conditional deep convolutional generative adversarial networks in the fault diagnosis of planetary gearboxes

The Generative Adversarial Network (GAN) can generate samples similar to the original data to solve the problem of fault sample imbalance in planetary gearbox fault diagnosis. Most of models rely heavily on convolution to model the dependencies across feature vectors of vibration signals. However, the characterization ability of convolution operator is limited by the size of convolution kernel and it cannot capture the long-distance dependence in the original data. In this paper, self-attention is introduced into Conditional Deep Convolutional Generative Adversarial Networks (C-DCGAN). In the model, vibration features are dynamically weighted and merged, so that it can adaptively focus “attention” on different times to solve the problem of sample differences caused by time-varying vibration signals. Finally, the proposed method is verified on the planetary gearbox experiment and the quality of the generated signal samples is evaluated with Dynamic Time Warping (DTW) algorithm. The visual experimental results indicated that the proposed model performed better than conditional deep convolutional generative adversarial networks (C-DCGAN) and could accurately diagnose various working states of planetary gearboxes.

Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments

Abstract. Operational water-resource forecasters, such as the Colorado Basin River Forecast Center (CBRFC) in the Western United States, currently rely on historical records to calibrate the temperature-index models used for snowmelt runoff predictions. This data dependence is increasingly challenged, with global and regional climatological factors changing the seasonal snowpack dynamics in mountain watersheds. To evaluate and improve the CBRFC modeling options, this work ran the physically based snow energy balance iSnobal model, forced with outputs from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model across 4 years in a Colorado River Basin forecast region. Compared to in situ, remotely sensed, and the current operational CBRFC model data, the HRRR-iSnobal combination showed well-reconstructed snow depth patterns and magnitudes until peak accumulation. Once snowmelt set in, HRRR-iSnobal showed slower simulated snowmelt relative to observations, depleting snow on average up to 34 d later. The melting period is a critical component for water forecasting. Based on the results, there is a need for revised forcing data input preparation (shortwave radiation) required by iSnobal, which is a recommended future improvement to the model. Nevertheless, the presented performance and architecture make HRRR-iSnobal a promising combination for the CBRFC production needs, where there is a demonstrated change to the seasonal snow in the mountain ranges around the Colorado River Basin. The long-term goal is to introduce the HRRR-iSnobal combination in day-to-day CBRFC operations, and this work created the foundation to expand and evaluate larger CBRFC domains.

The Interference of Pre-Processing Software for the Numerical Simulation of Groundwater on the Cognition of Environmental Students: Model Mesh Construction as an Example.

(1) Background: Software for the numerical simulation of groundwater plays an important role in studying environmental problems. However, it is still unclear whether the pre-processing software of the numerical simulation of groundwater has a negative effect on the cognition of undergraduates in the environmental field who only have basic groundwater flow and solute transport knowledge and software operation skills. (2) Methods: To explore this issue, we used software meshing as an example and selected undergraduates in the environmental field to conduct the questionnaire surveys. A total of 345 undergraduate answer sheets were received, and data analysis was carried out. The students were divided into two groups, one with and another without certain basic groundwater flow and solute transport knowledge or software operation skills. (3) Results: For undergraduate students with some basic knowledge or software operation ability, the proportion of students whose cognition was adversely interfered with by the pre-processing software was 64.3%, and the ratio of students not interfered with was 35.7%. For undergraduates without groundwater flow and solute transport knowledge and relevant software operation skills, the ratios were 63.2% and 36.8%, respectively. (4) Conclusions: Pre-processing software numerical simulation of groundwater could negatively interfere with students' cognition. The basic groundwater flow and solute transport knowledge and software operation skills did not observably reduce the interference degree (p = 0.259) but had significant influences on the undergraduates' thinking modes on the numerical simulation problems (p = 0.009). The interference was mainly caused by the significant difference between the level of knowledge possessed by the students and that represented by the pre-processing software. This paper provides basic scientific data for the optimization of students' knowledge structures and the improvement of teaching methods.

Enhanced production of d-pantothenic acid in Corynebacterium glutamicum using an efficient CRISPR–Cpf1 genome editing method

BackgroundCorynebacterium glutamicum has industrial track records for producing a variety of valuable products such as amino acids. Although CRISPR-based genome editing technologies have undergone immense developments in recent years, the suicide-plasmid-based approaches are still predominant for C. glutamicum genome manipulation. It is crucial to develop a simple and efficient CRISPR genome editing method for C. glutamicum.ResultsIn this study, we developed a RecombinAtion Prior to Induced Double-strand-break (RAPID) genome editing technology for C. glutamicum, as Cpf1 cleavage was found to disrupt RecET-mediated homologous recombination (HR) of the donor template into the genome. The RAPID toolbox enabled highly efficient gene deletion and insertion, and notably, a linear DNA template was sufficient for gene deletion. Due to the simplified procedure and iterative operation ability, this methodology could be widely applied in C. glutamicum genetic manipulations. As a proof of concept, a high-yield D-pantothenic acid (vitamin B5)-producing strain was constructed, which, to the best of our knowledge, achieved the highest reported titer of 18.62 g/L from glucose only.ConclusionsWe developed a RecET-assisted CRISPR–Cpf1 genome editing technology for C. glutamicum that harnessed CRISPR-induced DSBs as a counterselection. This method is of great importance to C. glutamicum genome editing in terms of its practical applications, which also guides the development of CRISPR genome editing tools for other microorganisms.

Analysis of power flow transfer characteristics and stability improvement method of DC grid considering converter’s safety boundary

In order to analyze the impact of power flow transfer of the DC grid on safe operation, this paper studies the calculation methods of power flow transfer of the DC grid under master–slave control and droop control, including the calculation of power flow transfer in line disconnection situation and converter power changing situation. Through the proposed calculation methods, by considering the safety boundary constraints of the converter station based on the PQ power domain, the impact on the safe operation of a complex DC grid when power flow transferring is analyzed. Finally, to solve instability caused by the power flow transfer, a virtual impedance-based method is introduced to increase the safety boundary and enhances the stable operation ability of the system. Finally, the simulations of an 11-terminal CIGRE DC system established in PSCAD/EMTDC software verify the correctness of the proposed method. 11This work is supported by Cloud energy storage framework-based AI dispatching strategy of renewable energy integration and contingency response (5100-202199274A-0-0-00).

Research on the Fault-Transient Characteristics of a DC Power System Considering the Cooperative Action of a Flexible Current-Limiting Device and a Circuit Breaker

As an effective carrier of a new energy collection, the DC power grid has low inertia and weak damping characteristics, making it essential to limit fault current and isolate the DC system. To quickly and effectively suppress fault current, a flexible current-limiting device (FCLD) is proposed, which can realize transient fault self-recovery without circuit breaker action and permanent and quick isolation of a fault. It improves the operational ability of the DC system under an asymmetric condition. First, a rectifier provides a set-slope current to each cascade inductor, so the voltage of the inductor can be clamped. Second, a controlled current source (CCS) is applied to generate inverse flux to prevent the inductor from magnetic saturation. The protection action time of the DC circuit breaker is reformulated. Finally, by considering the synergistic action of the current-limiting device, the circuit breaker, and the transient characteristics of the DC grid fault, the protection scheme of the multi-terminal flexible DC system can be formulated. To verify the validity of the proposed flexible current-limiting device, a multi-terminal flexible DC simulation platform is established, and the faults of DC lines are simulated and analyzed.

DEVELOPMENT OF RABBIT GOALS GAME TO INCREASE STUDENT MOTIVATION IN THEMATIC LEARNING AT PRIMARY SCHOOL

Playing is an activity that cannot be separated in children lives. Children preference for playing needs attention so that the games they do support their competence. Especially with the development of technology in the era of the Industrial Revolution 4.0, it has changed the pattern of conventional games into digital-based games. So it is necessary to develop educational games that can meet the needs of children in playing and learning. The purpose of this study was to develop an educational game for thematic subjects called rabbit goals and to find out the impact of using this game on children learning motivation. This research was conducted at MI Barokah At-Tahdzib for 2nd grade students. The results of this development are in the form of a game that contains thematic material and displays for 2nd grade students. The impact of using this educational game includes increasing student motivation, increasing student accuracy, improve students ability in arithmetic operations, and build independent learning in students, because according to students learning by using rabbits is the goal to be more exciting and fun.

Transient Interference Suppression Method Based on an Improved TK Energy Operator and Fuzzy Reasoning

Since sky wave over-the-horizon radar is seriously affected by transient interference, a transient interference suppression method based on an improved Teager-Kaiser energy operator and fuzzy reasoning is proposed. Initially, due to the extraction of the information entropy of slow time samples, the resolution ability of the energy operator to short-term fluctuation characteristics is improved and used to more accurately locate transient interference. Then, four evaluation indexes are constructed to quantify the confidence of the data reconstruction results obtained via the autoregressive, subspace and smoothing methods. Finally, Dempster and Shafer evidence theory is introduced to conduct fuzzy reasoning on the various reconstruction results, and comprehensive results are obtained. The experimental results show that our proposed method has evident advantages in locating weak interference, preventing clutter broadening and maintaining high-speed target energy.