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Work assistance is one of the important means to improve work efficiency. This paper focuses on substation work and proposes a real-time work assistance method based on petri net model. The work assistance includes two aspects, termed as, workflow guidance and operation prompt. Particularly, the workflow constructed by the petri net includes sequence, inhibition, concurrency and conflict structures to declare the correlations between work steps. Further, different forms of operation prompts at each step are designed, considering real-time responses of workers including skip, replay, pause and restart. The effectiveness of the method is well validated by an application of the work assistance on measuring the grounding current of transformer core and clamp. It is demonstrated that the unified assistance method built by the petri net successfully instructs standardized working process, helps avoid potential risks, and provides flexible operation prompts in real time.

The construction of lunar bases is one of the core enabling technologies in current lunar exploration and development plans of various countries. However, to eliminate the constraints of high transportation costs and limited manned space technology, a new research plan is to employ multi robot teams to build lunar bases. The key to this solution is how to achieve path planning for complex tasks for multiple robots. Therefore, this article takes the exploration and collection area, lunar soil collection, and lunar soil transportation in the lunar base construction scene as complex task inputs, and studies a multi robot path planning modeling method based on Petri net model. Firstly, a Petri net model for multi robot motion was constructed. Meanwhile, linear temporal logic(LTL) language was used to describe the related tasks of lunar base construction. Finally, simulation validation was conducted in Matlab software and compared with the modeling method using switching systems. The results show that the total modeling time required for using the Petri net model is reduced by two orders of magnitude compared to the modeling time for a single task switching system model, indicating that the established Petri net multi robot model has advantages such as avoiding dimension explosion and computational efficiency. 月球基地建设是当前各国月球探测与开发计划的核心使能技术之一。然而, 为消除高昂的运输成本和有限载人航天技术的约束, 使用多机器人团队建造月球基地的新研究方案被提出, 该方案的关键是如何实现多机器人针对复杂任务的路径规划。为此, 以月球基地建设场景中的探测采集区域、采集月壤、搬运月壤等作为复杂的任务输入, 研究了一种基于Petri网模型的多机器人路径规划建模方法。构建了多机器人运动的Petri网模型; 使用线性时序逻辑(linear temporal logic, LTL)语言描述月球基地建设的相关任务; 将Petri网模型和LTL公式结合求解得到多机器人路径; 在Matlab软件中进行仿真验证, 并与使用切换系统的建模方法进行对比。结果表明, 使用Petri网模型所需的建模总时间比切换系统模型单个任务的建模时间减少2个数量级, 说明建立的Petri网多机器人模型具有避免维度爆炸、计算高效等优势。

An appearance of radiometers and dosimeters on free sale made it possible to provide better radiation safety for citizens. The effects of radiation may not appear all at once. They can manifest themselves in decades to come in future generations, in the form of cancer, genetic mutations, etc. For this reason, we have developed in this paper a microcontroller-based radiation monitoring system. The system determines an accumulated radiation dose for a certain period, as well as gives alarm signals when the rate of the equivalent dose exceeds. The high reliability of this system is ensured by a rapid response to emergency situations: excess of the allowable power of the equivalent radiation dose and the accumulator charge control. Further, we have composed a microcontroller electronic circuit for the monitoring radiation system. Additionally, an operation algorithm, as well as software for the ATmega328P microcontroller of the Arduino Uno board, have been developed.

The detection and defense of malicious attacks are critical to the proper functioning of network security. Due to the diversity and rapid updates of the attack methods used by attackers, traditional defense mechanisms have been challenged. In this context, a more effective method to predict vulnerabilities in network systems is considered an urgent need to protect network security. In this paper, we propose a formal modeling and analysis approach based on Petri net vulnerability exploitation. We used the Common Vulnerabilities and Exposures (CVE)-2021-3711 vulnerability source code to build a model. A patch model was built to address the problems of this model. Finally, the time injected by the actual attacker and the time simulated by the software were calculated separately. The results showed that the simulation time was shorter than the actual attack time, and ultra-real-time simulation could be achieved. By modeling the network system with this method, the model can be found to arrive at an illegitimate state according to the structure of Petri nets themselves and thus discover unknown vulnerabilities. This method provides a reference method for exploring unknown vulnerabilities.

Alzheimer’s disease is a complex disorder of the nervous system. Diagnosing this disease is a costly process in which numerous laboratory tests and examinations are conducted. Most computational methods for Alzheimer’s disease prediction face low accuracy due to challenges such as a limited number of training samples, noisy/overlapping data, and variability in gene expression. This study presents a reliable computational approach for predicting Alzheimer’s disease through a new method of analyzing gene expression profiles from either brain tissue or blood samples. The proposed Petri net–based approach demonstrates superior diagnostic accuracy compared to existing methods across multiple gene expression datasets derived from both blood and brain tissue. The proposed method runs a Petri net model of the signaling pathways involved in complex nervous system disorders. In addition, the Petri net model provides step-by-step tracking of gene activation until the final diagnosis state is reached. An accurate understanding of the functions of the key genes of the signaling pathways involved in brain cell death will play a significant role in the early diagnosis of this complex disease and hopefully will lead to the identification of suitable preventive treatments or drug targets.

FMS reliability cannot be accurately evaluated without considering coupling relations between system elements. This paper presented a hierarchical and quantitative evaluation index system for FMS based on Petri net models and judgment matrix construction. In the proposed system, influencing factors and their coupling relations related to system elements including human, control systems, and mechanical equipment are analyzed. Based on the above analysis, FMS is described as a hierarchical system composed of the whole-level system, processing system, and transfer system. Petri net for the running process of each system is modelled for reliability simulation analysis. And judgment matrices of indexes are constructed and combined with simulation of Petri net models to determine weighted values for influencing factors. Finally, an application example is completed to verify the effectiveness of the proposed system. Results indicate that the system can help to quantitatively evaluate the reliability of FMS based on availability indexes of elements and clearly show weaknesses of the system from element level, which is a significant basis for the FMS reliability improvement during the design stage.

The thermal coal supply chain serves as core infrastructure for ensuring the safe and stable supply of electricity in China. Effective risk management and control of this supply chain are therefore critical to national energy security and socio-economic development. However, the thermal coal supply chain involves multiple complex risk dimensions, including cross-regional multi-entity coordination, a complex network structure, and a dynamic policy environment. Traditional risk analysis methods often fall short in depicting the concurrent events and dynamic propagation characteristics inherent to such a system. This necessitates systematically investigating the thermal coal supply chain within the Coal–Electricity Joint Venture (CEJV) operational framework, which primarily involves equity-based consolidation and long-term contractual coordination between coal producers and power generators, to comprehensively analyze its critical risk factors and transmission mechanisms. Initially, based on the integration of coal-fired power joint operation policy evolution and industry characteristics, 28 risk factors were identified across three dimensions: internal enterprise, external environment, and overall structure. These encompassed production fluctuation risks, thermal coal transport process risks, and insufficient supply chain flexibility. A dynamic behavior model for the thermal coal supply chain was constructed by analyzing the causal relationships among these risk factors, based on the operational processes of each link. Utilizing Petri net simulation technology enables a quantitative analysis of supply chain risks, facilitating the identification of bottleneck links and potential risk points. Through model simulation, 18 key risk factors were determined, providing a theoretical basis for optimizing supply chain resilience within CEJV enterprises. The limitations of traditional methods in dynamic process modeling and industrial applicability were addressed through a Petri net-based methodology, thereby establishing a novel analytical paradigm for risk management in complex energy supply chains.

One barrier to persistent operations in systems of unmanned aerial vehicles (UAVs) served by logistics support stations is the need for methods to manage and efficiently schedule system resources. This paper presents a scheduling framework for UAV systems served by battery charging and battery replacement stations. We extend existing Petri net models for these systems to prevent unwanted resource overlap and impose a resource pairing rule to facilitate cyclic operation. Based on this rule, an extended Petri net that explicitly models the interactions of specific resources is derived. The detailed nature of the extended Petri net allows for the creation of linear programs that capture the structure of the net and generate optimal cyclic resource schedules. These cyclic schedules enable the persistent orchestration of tasks for UAV and logistics support stations. Computational complexity of the linear programs is explored.

Current testing methods for autonomous driving systems primarily focus on simple traffic scenarios, generating test cases based on traffic accidents, while research on generating edge test cases for complex driving environments by traffic regulations is not adequately comprehensive. Therefore, we propose a method for scenario modeling and violation testing using an autonomous driving system based on traffic regulations named TraModeAVTest. Initially, TraModeAVTest constructs a Petri net model for complex scenarios based on the combination relationships of basic traffic regulation scenarios and verifies the consistency of the model’s design with traffic regulation requirements using formal methods, to provide a representation of traffic regulation scenario models for the violation testing of autonomous driving systems. Subsequently, based on the coverage criteria of the Petri net model, it utilizes a search strategy to generate model paths that represent traffic regulations, and employs a parameter combination method to generate test cases that cover the model paths, to test the violation behaviors of autonomous driving systems. Finally, simulation experiment results on the Baidu Apollo demonstrate that the test cases representing traffic regulations generated by TraModeAVTest can effectively identify the behaviors of autonomous vehicles violating traffic regulations, and TraModeAVTest can effectively improve the efficiency of generating different types of violation scenarios.

Aiming at the operation conflict problem of multi-objective, multi-path and multi-vehicle relay during mine locomotive operation under complex geological conditions, a mine operation of locomotive modeling method based on an object-oriented stratified timed Petri net is proposed. In order to load and transport materials as object oriented, which are combined with the mine operation of locomotive rules and time constraints, stratified modeling of an underground roadway route is carried out. In addition, given token time parameters to describe the dynamic behavior of the locomotive, through the model to analyze the operation of a mine transport locomotive, the correlation matrix and accessibility tree analysis are used to study the conflict. Taking the actual operation of a locomotive in a complex mine in Guizhou as an example, the operation of locomotive behavior model was established to detect the interval and time of operation conflicts. The experimental results show that the proposed operation of locomotive modeling and conflict analysis method are effective and feasible, and have important application value to the safe operation of a mine production system.