Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
The need to transport goods across countries and islands has resulted in a high demand for commercial vessels.Owing to such trends,shipyards must efficiently produce ships to reduce production costs.Layout and materia...The need to transport goods across countries and islands has resulted in a high demand for commercial vessels.Owing to such trends,shipyards must efficiently produce ships to reduce production costs.Layout and material flow are among the crucial aspects determining the efficiency of the production at a shipyard.This paper presents the initial design optimization of a shipyard layout using Nondominated Sorting Algorithm-Ⅱ(NSGA-Ⅱ)to find the optimal configuration of workstations in a shipyard layout.The proposed method focuses on simultaneously minimizing two material handling costs,namely work-based material handling and duration-based material handling.NSGA-Ⅱ determines the order of workstations in the shipyard layout.The semiflexible bay structure is then used in the workstation placement process from the sequence formed in NSGA-Ⅱ into a complete design.Considering that this study is a case of multiobjective optimization,the performance for both objectives at each iteration is presented in a 3D graph.Results indicate that after 500 iterations,the optimal configuration yields a work-based MHC of 163670.0 WBM-units and a duration-based MHC of 34750 DBM-units.Starting from a random solution,the efficiency of NSGA-Ⅱ demonstrates significant improvements,achieving a 50.19%reduction in work-based MHC and a 48.58%reduction in duration-based MHC.展开更多
The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design.This complexity arises from the high degrees of fre...The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design.This complexity arises from the high degrees of freedom,diverse operating conditions,and inherent trade-offs between performance metrics in full-car suspension systems.In this paper,a novel switching control strategy is proposed to better balance ride comfort and handling stability for a full-car suspension system.The system integrates a ride comfort controller and an anti-rollover controller,guided by a new rollover risk assessment indicator that requires fewer state variables.First,a vehicle suspension simplification model approach is introduced,reducing the fourteen-degree-of-freedom full-car suspension model to three two-degree-of-freedom models:vertical,pitch and roll.Based on these simplified models,vertical,roll,and pitch controllers are designed,simplifying the controller design process for full-car suspension systems.The ride comfort controller is constructed using the modal energy method in conjunction with the simplified model controllers,while the roll controller functions as the anti-rollover controller.The proposed rollover risk assessment indicator serves as the switching criterion between handling stability and ride comfort control.Experimental results demonstrate that the proposed switching control strategy effectively adapts to various road conditions,enabling the semi-active variable damping suspension system to perform multi-modal switching.Compared to a well-tuned passive suspension,vertical,roll,and pitch accelerations are reduced by 14.13%,13.02%and 13.08%,respectively,significantly improving ride comfort.Additionally,the system effectively mitigates rollover risk,achieving reductions in roll angle,roll speed,and roll acceleration by 19.69%,16.40%,and 29.96%,respectively,thereby greatly enhancing vehicle safety.Overall,the proposed switching control strategy achieves a successful balance between ride comfort and handling stability,enhancing overall driving performance.展开更多
Objective:To evaluate the implementation effectiveness of standardized protective care procedures during hydrofluoric acid procedures in the dental department.Methods:This study was conducted from June 2023 to June 20...Objective:To evaluate the implementation effectiveness of standardized protective care procedures during hydrofluoric acid procedures in the dental department.Methods:This study was conducted from June 2023 to June 2025,selecting 90 patients who underwent hydrofluoric acid-related treatments in the outpatient dental department of this hospital during this period as subjects.Forty-five patients treated between June 2023 and June 2024 received conventional protective care(pre-intervention group),while 45 patients treated between June 2024 and June 2025 underwent the standardized protective care protocol(post-intervention group).Thirteen healthcare personnel participated in both pre-and post-intervention treatment phases.Based on the different nursing models,indicators such as the incidence of adverse events in patients and the exposure rate of healthcare personnel before and after implementation were compared to evaluate the effectiveness of the nursing intervention.Results:The incidence of oral mucosal irritation reactions in patients was lower after implementation,p<0.05.Compared with the pre-implementation period,the incidence of procedure-related adverse events decreased after implementation,p<0.05.There was a significant difference in the occupational exposure rate of healthcare personnel before and after implementation,with a higher rate observed before implementation(p<0.05).Post-implementation,healthcare personnel achieved higher compliance scores for pre-procedure preparation,intra-procedure protection,and post-procedure handling(p<0.05).Patient satisfaction with treatment was lower pre-implementation than post-implementation(p<0.05).Conclusion:Adherence to standardized protective care procedures during hydrofluoric acid operations by dental department staff in outpatient settings standardizes practitioner techniques,effectively prevents oral mucosal irritation in patients,reduces occupational exposure risks for staff,minimizes adverse procedural events,and consequently enhances patient treatment satisfaction.This demonstrates significant practical value.展开更多
Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelli...Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelligent question answering,decision support,and fault diagnosis.As high-speed train systems become increasingly intelligent and interconnected,fault patterns have grown more complex and dynamic.Knowledge graphs offer a promising solution to support the structured management and real-time reasoning of fault knowledge,addressing key requirements such as interpretability,accuracy,and continuous evolution in intelligent diagnostic systems.However,conventional knowledge graph construction relies heavily on domain expertise and specialized tools,resulting in high entry barriers for non-experts and limiting their practical application in frontline maintenance scenarios.To address this limitation,this paper proposes a fault knowledge modeling approach for high-speed trains that integrates structured logic diagrams with knowledge graphs.The method employs a seven-layer logic structure—comprising fault name,applicable vehicles,diagnostic logic,signal parameters,verification conditions,fault causes,and emergency measures—to transform unstructured knowledge into a visual and hierarchical representation.A semantic mapping mechanism is then used to automatically convert logic diagrams into machine-interpretable knowledge graphs,enabling dynamic reasoning and knowledge reuse.Furthermore,the proposed method establishes a three-layer architecture—logic structuring,knowledge graph transformation,and dynamic inference—to bridge human-expert logic with machinebased reasoning.Experimental validation and system implementation demonstrate that this approach not only improves knowledge interpretability and inference precision but also significantly enhances modeling efficiency and system maintainability.It provides a scalable and adaptable solution for intelligent operation and maintenance platforms in the high-speed rail domain.展开更多
A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then ...A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.展开更多
With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally...With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.展开更多
Short suspension system has an indispensable effect on vehicle handling and ride,so,optimization of vehicle suspension system is one of the most effective methods,which could considerably enhance the vehicle stability...Short suspension system has an indispensable effect on vehicle handling and ride,so,optimization of vehicle suspension system is one of the most effective methods,which could considerably enhance the vehicle stability and controllability.Motion control,stability maintenance and ride comfort improvement are fundamental issues in design of suspension system of off-road vehicles.In this work,a dependent suspension system mostly used in off-road vehicles is modeled using Trucksim software.Then,geometric parameters of suspension system are optimized using integrated anti-roll bar and coiling spring in a way that ride comfort,handling and stability of vehicle are improved.The simulation results of suspension system and variations of geometric parameters due to road roughness and different steering angles are presented in Trucksim and effects of optimization of suspension system during various driving maneuvers in both optimized and un-optimized conditions are compared.The simulation results indicate that the type of suspension system and geometric parameters have significant effect on vehicle performance.展开更多
This paper researches how to apply the advanced control technology of model predictive control （MPC） to the design of the dynamic positioning system （DPS） of a semi-submersible platform. First, a linear low-freque...This paper researches how to apply the advanced control technology of model predictive control （MPC） to the design of the dynamic positioning system （DPS） of a semi-submersible platform. First, a linear low-frequency motion model with three degrees of freedom was established in the context of a semi-submersible platform. Second, a model predictive controller was designed based on a model which took the constraints of the system into account. Third, simulation was carried out to demonstrate the feasibility of the controller. The results show that the model predictive controller has good performance and good at dealing with the constraints or the system.展开更多
The Main Optical Telescope (MOT) is an important payload of the Space Solar Telescope (SST) with various instruments and observation modes. Its real-time data handling and management and control tasks are arduous. Bas...The Main Optical Telescope (MOT) is an important payload of the Space Solar Telescope (SST) with various instruments and observation modes. Its real-time data handling and management and control tasks are arduous. Based on the advanced techniques of foreign countries, an improved structure of onboard data handling systems feasible for SST, is proposed. This article concentrated on the development of a Central Management & Control Unit (MCU) based on FPGA and DSP. Through reconfigurating the FPGA and DSP programs, the prototype could perform different tasks. Thus the inheritability of the whole system is improved. The completed dual-channel prototype proves that the system meets all requirements of the MOT. Its high reliability and safety features also meet the requirements under harsh conditions such as mine detection.展开更多
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
基金Supported by Direktorat Riset dan Pengembangan(Directorate of Research and Development)Universitas Indonesia(NKB-690/UN2.RST/HKP.05.00/2022).
文摘The need to transport goods across countries and islands has resulted in a high demand for commercial vessels.Owing to such trends,shipyards must efficiently produce ships to reduce production costs.Layout and material flow are among the crucial aspects determining the efficiency of the production at a shipyard.This paper presents the initial design optimization of a shipyard layout using Nondominated Sorting Algorithm-Ⅱ(NSGA-Ⅱ)to find the optimal configuration of workstations in a shipyard layout.The proposed method focuses on simultaneously minimizing two material handling costs,namely work-based material handling and duration-based material handling.NSGA-Ⅱ determines the order of workstations in the shipyard layout.The semiflexible bay structure is then used in the workstation placement process from the sequence formed in NSGA-Ⅱ into a complete design.Considering that this study is a case of multiobjective optimization,the performance for both objectives at each iteration is presented in a 3D graph.Results indicate that after 500 iterations,the optimal configuration yields a work-based MHC of 163670.0 WBM-units and a duration-based MHC of 34750 DBM-units.Starting from a random solution,the efficiency of NSGA-Ⅱ demonstrates significant improvements,achieving a 50.19%reduction in work-based MHC and a 48.58%reduction in duration-based MHC.
基金Supported by the Australian Research Council’s Discovery Project(Grant No.DP200100149)Taishan Scholars Program of Shandong Province(Grant No.tsqn202211062)Chinses Scholarship Council(Grant No.202006690005).
文摘The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design.This complexity arises from the high degrees of freedom,diverse operating conditions,and inherent trade-offs between performance metrics in full-car suspension systems.In this paper,a novel switching control strategy is proposed to better balance ride comfort and handling stability for a full-car suspension system.The system integrates a ride comfort controller and an anti-rollover controller,guided by a new rollover risk assessment indicator that requires fewer state variables.First,a vehicle suspension simplification model approach is introduced,reducing the fourteen-degree-of-freedom full-car suspension model to three two-degree-of-freedom models:vertical,pitch and roll.Based on these simplified models,vertical,roll,and pitch controllers are designed,simplifying the controller design process for full-car suspension systems.The ride comfort controller is constructed using the modal energy method in conjunction with the simplified model controllers,while the roll controller functions as the anti-rollover controller.The proposed rollover risk assessment indicator serves as the switching criterion between handling stability and ride comfort control.Experimental results demonstrate that the proposed switching control strategy effectively adapts to various road conditions,enabling the semi-active variable damping suspension system to perform multi-modal switching.Compared to a well-tuned passive suspension,vertical,roll,and pitch accelerations are reduced by 14.13%,13.02%and 13.08%,respectively,significantly improving ride comfort.Additionally,the system effectively mitigates rollover risk,achieving reductions in roll angle,roll speed,and roll acceleration by 19.69%,16.40%,and 29.96%,respectively,thereby greatly enhancing vehicle safety.Overall,the proposed switching control strategy achieves a successful balance between ride comfort and handling stability,enhancing overall driving performance.
基金Construction of Standardized Protective Nursing Plan for Hydrofluoric Acid Operation in Stomatology and Re search on Injury Prevention Effect(Project No.:FZ2025101)。
文摘Objective:To evaluate the implementation effectiveness of standardized protective care procedures during hydrofluoric acid procedures in the dental department.Methods:This study was conducted from June 2023 to June 2025,selecting 90 patients who underwent hydrofluoric acid-related treatments in the outpatient dental department of this hospital during this period as subjects.Forty-five patients treated between June 2023 and June 2024 received conventional protective care(pre-intervention group),while 45 patients treated between June 2024 and June 2025 underwent the standardized protective care protocol(post-intervention group).Thirteen healthcare personnel participated in both pre-and post-intervention treatment phases.Based on the different nursing models,indicators such as the incidence of adverse events in patients and the exposure rate of healthcare personnel before and after implementation were compared to evaluate the effectiveness of the nursing intervention.Results:The incidence of oral mucosal irritation reactions in patients was lower after implementation,p<0.05.Compared with the pre-implementation period,the incidence of procedure-related adverse events decreased after implementation,p<0.05.There was a significant difference in the occupational exposure rate of healthcare personnel before and after implementation,with a higher rate observed before implementation(p<0.05).Post-implementation,healthcare personnel achieved higher compliance scores for pre-procedure preparation,intra-procedure protection,and post-procedure handling(p<0.05).Patient satisfaction with treatment was lower pre-implementation than post-implementation(p<0.05).Conclusion:Adherence to standardized protective care procedures during hydrofluoric acid operations by dental department staff in outpatient settings standardizes practitioner techniques,effectively prevents oral mucosal irritation in patients,reduces occupational exposure risks for staff,minimizes adverse procedural events,and consequently enhances patient treatment satisfaction.This demonstrates significant practical value.
基金support from the Scientific Funding for the Center of National Railway Intelligent Transportation System Engineering and Technology,China Academy of Railway Sciences Corporation Limited(Grant No.2023YJ354)。
文摘Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelligent question answering,decision support,and fault diagnosis.As high-speed train systems become increasingly intelligent and interconnected,fault patterns have grown more complex and dynamic.Knowledge graphs offer a promising solution to support the structured management and real-time reasoning of fault knowledge,addressing key requirements such as interpretability,accuracy,and continuous evolution in intelligent diagnostic systems.However,conventional knowledge graph construction relies heavily on domain expertise and specialized tools,resulting in high entry barriers for non-experts and limiting their practical application in frontline maintenance scenarios.To address this limitation,this paper proposes a fault knowledge modeling approach for high-speed trains that integrates structured logic diagrams with knowledge graphs.The method employs a seven-layer logic structure—comprising fault name,applicable vehicles,diagnostic logic,signal parameters,verification conditions,fault causes,and emergency measures—to transform unstructured knowledge into a visual and hierarchical representation.A semantic mapping mechanism is then used to automatically convert logic diagrams into machine-interpretable knowledge graphs,enabling dynamic reasoning and knowledge reuse.Furthermore,the proposed method establishes a three-layer architecture—logic structuring,knowledge graph transformation,and dynamic inference—to bridge human-expert logic with machinebased reasoning.Experimental validation and system implementation demonstrate that this approach not only improves knowledge interpretability and inference precision but also significantly enhances modeling efficiency and system maintainability.It provides a scalable and adaptable solution for intelligent operation and maintenance platforms in the high-speed rail domain.
基金supported by National Basic Research Program of China(973Program)(2012CB720000)National Natural Science Foundation of China(61225015,61273128)+2 种基金Foundation for Innovative Research Groups of the National Natural Science Foundation of China(61321002)the Ph.D.Programs Foundation of Ministry of Education of China(20111101110012)CAST Foundation(CAST201210)
文摘A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.
基金supported by the National Outstanding Youth Science Foundation (60925011)the National Natural Science Foundation of China (61203181)
文摘With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.
文摘Short suspension system has an indispensable effect on vehicle handling and ride,so,optimization of vehicle suspension system is one of the most effective methods,which could considerably enhance the vehicle stability and controllability.Motion control,stability maintenance and ride comfort improvement are fundamental issues in design of suspension system of off-road vehicles.In this work,a dependent suspension system mostly used in off-road vehicles is modeled using Trucksim software.Then,geometric parameters of suspension system are optimized using integrated anti-roll bar and coiling spring in a way that ride comfort,handling and stability of vehicle are improved.The simulation results of suspension system and variations of geometric parameters due to road roughness and different steering angles are presented in Trucksim and effects of optimization of suspension system during various driving maneuvers in both optimized and un-optimized conditions are compared.The simulation results indicate that the type of suspension system and geometric parameters have significant effect on vehicle performance.
基金Supported by the Basic Research Foundation of Central University(HEUCFZ1003)
文摘This paper researches how to apply the advanced control technology of model predictive control （MPC） to the design of the dynamic positioning system （DPS） of a semi-submersible platform. First, a linear low-frequency motion model with three degrees of freedom was established in the context of a semi-submersible platform. Second, a model predictive controller was designed based on a model which took the constraints of the system into account. Third, simulation was carried out to demonstrate the feasibility of the controller. The results show that the model predictive controller has good performance and good at dealing with the constraints or the system.
基金Project 863-2.5.2.25 supported by the National High Technology Research & Development (863) Program of China
文摘The Main Optical Telescope (MOT) is an important payload of the Space Solar Telescope (SST) with various instruments and observation modes. Its real-time data handling and management and control tasks are arduous. Based on the advanced techniques of foreign countries, an improved structure of onboard data handling systems feasible for SST, is proposed. This article concentrated on the development of a Central Management & Control Unit (MCU) based on FPGA and DSP. Through reconfigurating the FPGA and DSP programs, the prototype could perform different tasks. Thus the inheritability of the whole system is improved. The completed dual-channel prototype proves that the system meets all requirements of the MOT. Its high reliability and safety features also meet the requirements under harsh conditions such as mine detection.
