Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers(LVCBs).A fault diagnosis algorithm based on an improved Sparrow Search Algorithm(ISSA)optimized Ba...Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers(LVCBs).A fault diagnosis algorithm based on an improved Sparrow Search Algorithm(ISSA)optimized Backpropagation Neural Network(BPNN)is proposed to improve the operational safety of LVCB.Taking the 1.5kV/4000A/75kA LVCB as an example.According to the current operating characteristics of the energy storage motor,fault characteristics are extracted based on Empirical Wavelet Transform(EWT).Traditional BPNN has problems such as difficulty adjusting network weights and thresholds,being sensitive to initial weights,and quickly falling into local optimal solutions.The Sparrow Search Algorithm(SSA)with self-adjusting weight factors combined with bidirectional mutations is added to optimize the selection of BPNN hyperparameters.The results show that the ISSA-BPNN can accurately and quickly distinguish six conditions of motor voltage reduction:motor voltage increase,motor voltage decrease,energy storage spring stuck,transmission gear stuck,regular state and energy storage spring not locked.It is suitable for fault diagnosis and detection of the energy storage part of LVCB.展开更多
电力线通信检测装置是低碳楼宇能源互联网的核心设备,其采用的电力线载波通信(power line communication,PLC)的传输速度虽快,但路径搜索信令的通信可靠性较低,严重制约了中继对通信性能的提升效果;双向工频自动通信系统(two way automa...电力线通信检测装置是低碳楼宇能源互联网的核心设备,其采用的电力线载波通信(power line communication,PLC)的传输速度虽快,但路径搜索信令的通信可靠性较低,严重制约了中继对通信性能的提升效果;双向工频自动通信系统(two way automatic communication system,TWACS)的可靠性虽然很高,但路径搜索速度较慢,严重影响了通信时效性。为提高电力线通信检测装置在能源互联网信息感知中的性能,提出一种基于PLC与TWACS的多模式融合通信路径搜索算法。为保证电力线通信的覆盖范围,在改进算法中由PLC负责主要数据信息的传输;而下行通信搜索信令则由鲁棒性较强的TWACS替代,以保证广播信息与路径中继指令传输的可靠性。仿真结果表明,所提算法能够有效提高能源互联网的通信质量和通信效率,更好地满足低碳楼宇电力线通信检测装置的性能需求。展开更多
基金This research was funded by Sichuan Science and Technology Program(2023YFSY0013).
文摘Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers(LVCBs).A fault diagnosis algorithm based on an improved Sparrow Search Algorithm(ISSA)optimized Backpropagation Neural Network(BPNN)is proposed to improve the operational safety of LVCB.Taking the 1.5kV/4000A/75kA LVCB as an example.According to the current operating characteristics of the energy storage motor,fault characteristics are extracted based on Empirical Wavelet Transform(EWT).Traditional BPNN has problems such as difficulty adjusting network weights and thresholds,being sensitive to initial weights,and quickly falling into local optimal solutions.The Sparrow Search Algorithm(SSA)with self-adjusting weight factors combined with bidirectional mutations is added to optimize the selection of BPNN hyperparameters.The results show that the ISSA-BPNN can accurately and quickly distinguish six conditions of motor voltage reduction:motor voltage increase,motor voltage decrease,energy storage spring stuck,transmission gear stuck,regular state and energy storage spring not locked.It is suitable for fault diagnosis and detection of the energy storage part of LVCB.
文摘电力线通信检测装置是低碳楼宇能源互联网的核心设备,其采用的电力线载波通信(power line communication,PLC)的传输速度虽快,但路径搜索信令的通信可靠性较低,严重制约了中继对通信性能的提升效果;双向工频自动通信系统(two way automatic communication system,TWACS)的可靠性虽然很高,但路径搜索速度较慢,严重影响了通信时效性。为提高电力线通信检测装置在能源互联网信息感知中的性能,提出一种基于PLC与TWACS的多模式融合通信路径搜索算法。为保证电力线通信的覆盖范围,在改进算法中由PLC负责主要数据信息的传输;而下行通信搜索信令则由鲁棒性较强的TWACS替代,以保证广播信息与路径中继指令传输的可靠性。仿真结果表明,所提算法能够有效提高能源互联网的通信质量和通信效率,更好地满足低碳楼宇电力线通信检测装置的性能需求。
