WO2022082339A1 - 绝缘子雷电流智能监测设备以及绝缘子故障智能判断方法 - Google Patents

绝缘子雷电流智能监测设备以及绝缘子故障智能判断方法 Download PDF

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WO2022082339A1
WO2022082339A1 PCT/CN2020/121784 CN2020121784W WO2022082339A1 WO 2022082339 A1 WO2022082339 A1 WO 2022082339A1 CN 2020121784 W CN2020121784 W CN 2020121784W WO 2022082339 A1 WO2022082339 A1 WO 2022082339A1
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current
lightning
insulator
fault
lightning current
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PCT/CN2020/121784
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English (en)
French (fr)
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黄春光
单林森
丁梁
陈海军
张金鹏
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国网浙江诸暨市供电有限公司
国网浙江省电力有限公司绍兴供电公司
国网浙江省电力有限公司
国家电网有限公司
山东迅实电气有限公司
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Priority to PCT/CN2020/121784 priority Critical patent/WO2022082339A1/zh
Publication of WO2022082339A1 publication Critical patent/WO2022082339A1/zh

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R19/00Arrangements for measuring currents or voltages or for indicating presence or sign thereof
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere

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  • the present application relates to distribution line insulators, for example, to an insulator lightning current intelligent monitoring device and an insulator fault intelligent judgment method.
  • the present application provides an insulator lightning current intelligent monitoring device and an insulator fault intelligent judging method, which can automatically judge whether a fault occurs or is struck by lightning.
  • the application provides an insulator lightning current intelligent monitoring equipment, including:
  • a current acquisition sensor configured to acquire current signals
  • a signal processing module connected to the current acquisition sensor and configured to process the current signal acquired by the current acquisition sensor
  • the fault judgment module is connected with the signal processing module and configured to judge whether the current is lightning current;
  • a window comparator configured to keep the device in a standby state when there is no lightning and no faults in the device, and when a lightning current is generated, wake up the device in the form of an interrupt through the window comparator;
  • a power module configured to supply power to the insulator lightning current intelligent monitoring equipment.
  • the present application provides an intelligent judgment method for insulator faults.
  • the method utilizes the above-mentioned intelligent monitoring equipment for insulator lightning current to perform fault judgment, including the following steps:
  • the MCU stores the collected and processed current signals into the array by DMA;
  • Fig. 1 is the structural block diagram of a kind of insulator lightning current intelligent monitoring equipment provided by the application;
  • Fig. 2 is the fault judgment flowchart provided by this application.
  • FIG. 3 is a schematic diagram of a lightning current impulse test device provided by the application.
  • an insulator lightning current intelligent monitoring device includes:
  • a current acquisition sensor configured to acquire current signals
  • a signal processing module connected to the current acquisition sensor and configured to process the current signal acquired by the current acquisition sensor, includes a filter circuit, an integral amplifier circuit and an analog/digital (AD) conversion circuit connected in sequence, the filter circuit is configured to filter In addition to high-frequency interference signals in the current signal, the integrating and amplifying circuit is configured to integrate and amplify the current signal, and the AD conversion circuit is configured to convert the analog signal into a digital signal;
  • the fault judgment module is connected to the signal processing module and is configured to judge whether the current is lightning current; the window comparator is configured so that when there is no lightning and the equipment is fault-free, the equipment is always in the standby state.
  • the current signal processed by the filter circuit and the integral amplifying circuit first wakes up the device in the form of an interrupt through the window comparator. After the device wakes up, the integrated and amplified signal is collected by AD conversion. When the collected voltage is continuously less than the minimum threshold, the AD conversion is stopped.
  • the collected signals are processed by the multi-point control unit (MCU);
  • a power module configured to power the entire device.
  • the current acquisition sensor may use a Rogowski coil.
  • the current acquisition sensor based on Rogowski coil has the characteristics of real-time current measurement, fast response, no saturation, and almost no phase error.
  • the filter circuit may use a second-order Butterworth filter.
  • the Butterworth filter is characterized by the smoothest frequency response curve in the passband.
  • the acquisition frequency of AD conversion circuit is set to 1us/time.
  • the power module adopts online induction power taking combined with built-in battery to supply power.
  • the insulator lightning current intelligent monitoring equipment may also include a narrowband Internet of Things (NB-IOT) connected to the fault judgment module, and the number of lightning strikes and the lightning strike time obtained by the fault judgment module are sent to the server background through the NB-IOT.
  • NB-IOT narrowband Internet of Things
  • the server background saves the received data and sends it to the client for display.
  • the present application also provides an intelligent judgment method for insulator faults.
  • the method utilizes the above-mentioned intelligent monitoring equipment for insulator lightning current to perform fault judgment, and includes the following steps:
  • the MCU stores the conversion result of the AD conversion circuit into the array by means of direct memory access (DMA);
  • DMA direct memory access
  • the data in the array is processed by a limiter and de-jitter algorithm
  • the frequency of the collected current waveform will be calculated to continue to judge whether the current waveform is the power frequency short-circuit current frequency, such as judging the current If the duration is less than the fault current threshold, it will be recorded as an abnormal state and reported.
  • the current waveform is the power frequency short-circuit current frequency. If it is judged that the current waveform is the power frequency short-circuit current frequency, it is judged that the zinc oxide valve is faulty, and the fault occurrence time is recorded. If it is judged that the current waveform is not a power frequency short-circuit current frequency, it will be recorded as an abnormal state and reported.
  • the falling edge of the lightning current waveform Take the falling edge of the lightning current waveform as the judgment standard for lightning occurrence, compare the falling edge of the collected lightning current waveform with the falling edge of the lightning standard current waveform, and judge whether it is within the waveform change range set by the algorithm, such as when the waveform changes. Within the range, continue to judge whether the duration of the collected lightning current waveform falling edge is within the time range of the standard lightning current falling edge, if it is within the time range, continue to judge whether the collected lightning current waveform total time is within the standard Within the time range of the lightning current, if all the above conditions are met, it will be determined as a lightning occurrence, and the lightning occurrence time will be recorded.
  • the lightning current impulse test device for insulator lightning current intelligent monitoring equipment includes TY: voltage regulator, SB: test transformer, D: silicon stack, C: capacitor, R: wave regulating resistance, L: regulating Wave inductor, FL: shunt, CY: measuring instrument and FY: voltage divider.
  • the shunt is connected to the voltage divider with a measuring instrument, and the voltage of the test transformer is boosted by the voltage regulator.
  • the voltage of the secondary side of the test transformer is rectified by the silicon stack and then charged to the capacitor. Discharge the insulator lightning current intelligent monitoring equipment with the wave modulating inductor, measure the actual current value and residual voltage value of the insulator lightning current intelligent monitoring equipment through the measuring instrument, and compare the measured waveform with the waveform monitored by the insulator lightning current intelligent monitoring equipment. .
  • the insulator lightning current intelligent monitoring equipment When the insulator lightning current intelligent monitoring equipment is normal and not damaged, the current passing through the insulator lightning current intelligent monitoring equipment is almost zero. When the zinc oxide resistance sheet fails, if at this time, the wire at the insulator lightning current intelligent monitoring equipment is broken down by lightning , there will be a continuous power frequency current passing through, forming a single-phase grounding fault.
  • the insulator lightning current intelligent monitoring equipment is equipped with a Rogowski coil to monitor the current change through the product to determine whether the zinc oxide of the product here is damaged.
  • the collected waveform should be the normal lightning waveform, and the time is at the us level. If the zinc oxide resistance sheet is damaged, the collected waveform should be within the normal lightning After the wave, there will still be a continuous current passing through.
  • the zinc oxide valve plate is partially short-circuited to simulate the fault state of the zinc oxide valve plate.
  • the current situation of the intelligent insulator is compared to confirm whether the intelligent insulator can receive the fault current and make a fault indication.
  • the present application adopts the above technical solution, and automatically judges whether it is a lightning current and zinc oxide valve failure by analyzing the current signal of the insulator.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Insulators (AREA)
  • Testing Relating To Insulation (AREA)

Abstract

一种绝缘子雷电流智能监测设备以及绝缘子故障智能判断方法,该方法包括,MCU将采集并处理后的电流信号用DMA方式存入数组中,将处理后的数据与雷电标准电流波形比较,如判断为非雷电电流,则继续判断电流持续时间是否大于故障电流阈值,如判断为雷电电流,则判定为一次雷电发生,并记录雷电发生时间。

Description

绝缘子雷电流智能监测设备以及绝缘子故障智能判断方法 技术领域
本申请涉及配电线路绝缘子,例如涉及一种绝缘子雷电流智能监测设备以及绝缘子故障智能判断方法。
背景技术
对于配电线路绝缘子,供电部门每年需花费大量的人力、物力和时间进行巡视,以排查绝缘子、避雷器等设施设备的运行情况。有时为排查零值绝缘子还需要增加夜间巡视,通过肉眼观察放电情况、耳听放电声等原始手段作业,这种方式效果极不理想,往往是等到故障发生后才暴露出问题。
目前的防雷绝缘子,其本身是否发生故障损坏,或是否遭受过雷击等状况也仍然需要通过人工巡检进行排查。
发明内容
本申请提供一种绝缘子雷电流智能监测设备以及绝缘子故障智能判断方法,对自身发生故障还是遭受雷击的情况可以自动判断。
本申请提供一种绝缘子雷电流智能监测设备,包括:
电流采集传感器,配置为采集电流信号;
信号处理模块,与电流采集传感器相连且配置为对电流采集传感器采集的电流信号进行处理;
故障判断模块,与信号处理模块相连且配置为判断电流是否为雷电电流;
窗口比较器,配置为当无雷电且设备无故障的情况下,设备一直处于待机 状态,当有雷电流产生时,通过所述窗口比较器以中断的形式唤醒设备;
电源模块,配置为为所述绝缘子雷电流智能监测设备供电。
本申请提供一种绝缘子故障智能判断方法,所述方法利用上述绝缘子雷电流智能监测设备进行故障判断,包括以下步骤:
MCU将采集并处理后的电流信号用DMA方式存入数组中;
将处理后的数据与雷电标准电流波形比较,如判断为非雷电电流,则继续判断电流持续时间是否大于故障电流阈值,如判断为雷电电流,则判定为一次雷电发生,并记录雷电发生时间。
附图说明
图1为本申请提供的一种绝缘子雷电流智能监测设备的结构框图;
图2为本申请提供的故障判断流程图;
图3为本申请提供的雷电流冲击试验装置示意图。
具体实施方式
需要说明的是,在不冲突的情况下,本申请中的实施例及实施例中的特征可以相互组合。下面将参考附图并结合实施例来详细说明本申请。
参考图1和图2所示,一种绝缘子雷电流智能监测设备,包括:
电流采集传感器,配置为采集电流信号;
信号处理模块,与电流采集传感器相连且配置为对电流采集传感器采集的电流信号进行处理,包括依次连接的滤波电路、积分放大电路以及模/数(AD)转换电路,所述滤波电路配置为滤除电流信号中的高频干扰信号,所述积分放大电路配置为对电流信号进行积分并放大,所述AD转换电路配置为将模拟信 号转换为数字信号;
故障判断模块,与信号处理模块相连且配置为判断电流是否为雷电电流;窗口比较器,配置为当无雷电且设备无故障的情况下,设备一直处于待机状态,当有雷电流产生时,经过滤波电路和积分放大电路处理后的电流信号先通过窗口比较器以中断的形式唤醒设备,设备唤醒后对积分放大后的信号进行AD转换采集,当采集电压连续小于最小阈值时,停止AD转换,由多点控制单元(MCU)对采集的信号进行处理;
电源模块,配置为为整个设备供电。
其中,所述电流采集传感器可以采用罗氏线圈。基于罗氏线圈的电流采集传感器具有电流可实时测量、响应速度快、不会饱和、几乎没有相位误差的特点。
所述滤波电路可以采用二阶巴特沃斯滤波器。巴特沃斯滤波器的特点是通频带的频率响应曲线最平滑。AD转换电路采集频率设为1us/次。电源模块采用在线感应取电结合内置电池方式供电。
绝缘子雷电流智能监测设备还可以包括与故障判断模块相连的窄带物联网(NB-IOT),故障判断模块得到的雷击次数与雷击时间通过窄带物联网发送到服务器后台。所述服务器后台将接收数据保存,并发送到客户端展示。
如图2所示,本申请还提供一种绝缘子故障智能判断方法,所述方法利用上述绝缘子雷电流智能监测设备进行故障判断,包括如下步骤:
MCU将AD转换电路转换结果用直接存储器访问(DMA)的方式存入数组中;
当AD转换结束后,将所述数组中数据进行限幅消抖算法处理;
将处理后的数据与雷电标准电流波形比较,如判断为非雷电电流,则继续 判断电流持续时间是否大于故障电流阈值,如判断为雷电电流,则判定为一次雷电发生,并记录雷电发生时间。
继续判断电流持续时间是否大于故障电流阈值,如判断电流持续时间大于故障电流阈值,则将采集到的电流波形进行频率计算,以继续判断所述电流波形是否为工频短路电流频率,如判断电流持续时间小于故障电流阈值,则记录为异常状态并上报。
继续判断所述电流波形是否为工频短路电流频率,如判断所述电流波形为工频短路电流频率,则判定为氧化锌阀片故障,并记录故障发生时间,如判断所述电流波形不是工频短路电流频率,则记录为异常状态并上报。
其中,雷电电流的判断方法如下:
取雷电电流波形的下降沿作为雷电发生的判断标准,将采集到的雷电电流波形的下降沿与雷电标准电流波形下降沿进行比较,判断是否在算法设定的波形变化范围内,如在波形变化范围内,则继续判断采集到的雷电电流波形下降沿的持续时间是否在标准雷电流下降沿的时间范围内,如果在时间范围内,则继续判断采集到的雷电电流波形的总时间是否在标准雷电流的时间范围内,若以上条件全满足,则判定为一次雷电发生,并记录雷电发生时间。
为检测绝缘子雷电流智能监测设备在通过雷电流时,能否记录下通过雷电流的波形及时间,通过与实际通过绝缘子雷电流智能监测设备的雷电流波形进行对比,验证绝缘子雷电流智能监测设备的可靠性。因此,如图3所示的绝缘子雷电流智能监测设备雷电流冲击试验装置,包括TY:调压器、SB:试验变压器、D:硅堆、C:电容器、R:调波电阻、L:调波电感、FL:分流器、CY:测量仪器和FY:分压器。所述分流器与分压器连接测量仪器,通过调压器给试验变压器升压,试验变压器二次侧电压通过硅堆整流后给电容器充电,电容器充电完成后,间 隙击穿,通过调波电阻和调波电感对绝缘子雷电流智能监测设备放电,通过测量仪器测量通过绝缘子雷电流智能监测设备的实际电流值和残压值,并将测量波形与绝缘子雷电流智能监测设备监测到的波形进行对比。
当绝缘子雷电流智能监测设备正常未损坏时,通过绝缘子雷电流智能监测设备的电流几乎为零,当氧化锌电阻片故障后,若此时,绝缘子雷电流智能监测设备处的导线被雷电击穿,会有持续的工频电流通过,形成单相接地故障,绝缘子雷电流智能监测设备上装有罗氏线圈,监测通过产品的电流变化,即可判断此处的产品的氧化锌是否损坏。
当绝缘子雷电流智能监测设备正常未损坏时,通过雷电流后,采集到的波形应该为正常的雷电波形,时间在us级上,如果氧化锌电阻片损坏后,采集到的波形在正常的雷电波后,仍然会有持续的电流通过。
将智能绝缘子的高压端接工频6kV电压,低压端接地,将氧化锌阀片部分短接,模拟氧化锌阀片故障状态,对形成短路后的电流情况进行实际测量,并与智能绝缘子采集到的电流情况进行对比,确认智能绝缘子能否接收到故障电流并做出故障指示。
本申请采用上述技术方案,通过对绝缘子的电流信号的分析,自动判断是否为雷电电流以及氧化锌阀片故障。

Claims (14)

  1. 一种绝缘子雷电流智能监测设备,包括:
    电流采集传感器,配置为采集电流信号;
    信号处理模块,与所述电流采集传感器相连且配置为对电流采集传感器采集的所述电流信号进行处理;
    故障判断模块,与所述信号处理模块相连且配置为判断电流是否为雷电电流;
    窗口比较器,配置为当无雷电且设备无故障的情况下,设备一直处于待机状态,当有雷电流产生时,通过所述窗口比较器以中断的形式唤醒设备;
    电源模块,配置为为所述绝缘子雷电流智能监测设备供电。
  2. 根据权利要求1所述的绝缘子雷电流智能监测设备,其中,所述信号处理模块包括滤波电路、积分放大电路以及AD转换电路,所述滤波电路配置为滤除所述电流信号中的高频干扰信号,所述积分放大电路配置为对所述电流信号进行积分并放大,所述AD转换电路配置为将模拟信号转换为数字信号。
  3. 根据权利要求2所述的绝缘子雷电流智能监测设备,其中,所述窗口比较器是配置为:
    当有雷电电流产生时,经过所述滤波电路和所述积分放大电路处理后的电流信号先通过所述窗口比较器以中断的形式唤醒设备,设备唤醒后对积分放大后的信号通过AD转换电路进行AD转换采集,当采集电压连续小于最小阈值时,停止AD转换,由MCU对采集的信号进行处理。
  4. 根据权利要求1所述的绝缘子雷电流智能监测设备,其中,所述电流采集传感器采用罗氏线圈。
  5. 根据权利要求2所述的绝缘子雷电流智能监测设备,其中,所述滤波电路采用二阶巴特沃斯滤波器。
  6. 根据权利要求2所述的绝缘子雷电流智能监测设备,其中,所述AD转换电路的采集频率设为1us/次。
  7. 根据权利要求1所述的绝缘子雷电流智能监测设备,其中,所述电源模块采用在线感应取电结合内置电池方式供电。
  8. 根据权利要求1所述的绝缘子雷电流智能监测设备,还包括:与故障判断模块相连的窄带物联网,故障判断模块得到的雷击次数与雷击时间通过所述窄带物联网发送到服务器后台。
  9. 一种绝缘子故障智能判断方法,所述方法利用如权利要求1至8任一项所述的绝缘子雷电流智能监测设备进行故障判断,包括以下步骤:
    MCU将采集并处理后的电流信号用DMA方式存入数组中;
    将处理后的数据与雷电标准电流波形比较,如判断为非雷电电流,则继续判断电流持续时间是否大于故障电流阈值,如判断为雷电电流,则判定为一次雷电发生,并记录雷电发生时间。
  10. 根据权利要求9所述的绝缘子故障智能判断方法,其中,所述继续判断电流持续时间是否大于故障电流阈值,包括,如判断电流持续时间大于故障电流阈值,则将采集到的电流波形进行频率计算,以继续判断所述电流波形是否为工频短路电流频率,如判断电流持续时间小于故障电流阈值,则记录为异常状态并上报。
  11. 根据权利要求10所述的绝缘子故障智能判断方法,其中,所述继续判断所述电流波形是否为工频短路电流频率,包括,如判断所述电流波形为工频短路电流频率,则判定为氧化锌阀片故障,并记录故障发生时间,如判断所述电流波形不是工频短路电流频率,则记录为异常状态并上报。
  12. 根据权利要求11所述的绝缘子故障智能判断方法,其中,所述雷电电 流的判断方法如下:
    取雷电电流波形的下降沿作为雷电发生的判断标准,将采集到的雷电电流波形的下降沿与雷电标准电流波形下降沿进行比较,判断是否在算法设定的波形变化范围内,如在波形变化范围内,则继续判断采集到的雷电电流波形下降沿的持续时间是否在标准雷电流下降沿的时间范围内,如果在时间范围内,则继续判断采集到的雷电电流波形的总时间是否在标准雷电流的时间范围内,若以上条件全满足,则判定为一次雷电发生,并记录雷电发生时间。
  13. 根据权利要求12所述的绝缘子故障智能判断方法,还包括:判定为一次雷电发生后,通过窄带物联网将雷击次数与雷击时间发送到服务器后台。
  14. 根据权利要求13所述的绝缘子故障智能判断方法,还包括:所述服务器后台将接收数据保存,并发送到客户端展示。
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114724042A (zh) * 2022-06-09 2022-07-08 国网江西省电力有限公司电力科学研究院 一种输电线路中零值绝缘子自动检测方法
CN115077836A (zh) * 2022-06-02 2022-09-20 中国人民解放军国防科技大学 一种复现电连接器间歇故障的冲击试验方法
CN115498509A (zh) * 2022-10-12 2022-12-20 南京尚志电子科技有限公司 一种阻雷避雷装置
CN115862981A (zh) * 2022-12-27 2023-03-28 南京尚志电子科技有限公司 一种无线监测阻雷装置
CN118193959A (zh) * 2024-05-14 2024-06-14 深圳普泰电气有限公司 一种电涌能量的监测方法及系统

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS63201569A (ja) * 1987-02-18 1988-08-19 Furukawa Electric Co Ltd:The 雷撃電流測定装置
CN2854618Y (zh) * 2005-12-15 2007-01-03 马海明 高压输电线路雷击遥测设备
CN103558448A (zh) * 2013-10-11 2014-02-05 国家电网公司 一种输电线路多通道雷电流监测装置
CN103592506A (zh) * 2013-11-30 2014-02-19 国家电网公司 一种架空输电线路雷电流在线监测装置
CN107064599A (zh) * 2016-12-26 2017-08-18 华北电力大学 一种氧化锌避雷器分布式测量系统
CN207051425U (zh) * 2017-06-29 2018-02-27 西安交通大学 一种输电线路雷电流在线监测装置
CN107831354A (zh) * 2017-12-10 2018-03-23 南京宁普防雷设备制造有限公司 低功耗雷电流峰值采集系统
CN109375073A (zh) * 2018-11-15 2019-02-22 国网浙江省电力有限公司绍兴供电公司 防雷绝缘子动作电流和故障电流捕捉及识别模块
CN109585101A (zh) * 2018-11-15 2019-04-05 国网浙江省电力有限公司绍兴供电公司 基于物联网技术的配电网一体式防雷绝缘子
CN109765441A (zh) * 2018-12-27 2019-05-17 国网浙江诸暨市供电有限公司 智能绝缘子故障判断方法
CN109765440A (zh) * 2018-12-27 2019-05-17 国网浙江诸暨市供电有限公司 智能绝缘子雷电流监测设备
CN109839579A (zh) * 2018-12-27 2019-06-04 国网浙江诸暨市供电有限公司 智能限压器雷电流冲击试验装置

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS63201569A (ja) * 1987-02-18 1988-08-19 Furukawa Electric Co Ltd:The 雷撃電流測定装置
CN2854618Y (zh) * 2005-12-15 2007-01-03 马海明 高压输电线路雷击遥测设备
CN103558448A (zh) * 2013-10-11 2014-02-05 国家电网公司 一种输电线路多通道雷电流监测装置
CN103592506A (zh) * 2013-11-30 2014-02-19 国家电网公司 一种架空输电线路雷电流在线监测装置
CN107064599A (zh) * 2016-12-26 2017-08-18 华北电力大学 一种氧化锌避雷器分布式测量系统
CN207051425U (zh) * 2017-06-29 2018-02-27 西安交通大学 一种输电线路雷电流在线监测装置
CN107831354A (zh) * 2017-12-10 2018-03-23 南京宁普防雷设备制造有限公司 低功耗雷电流峰值采集系统
CN109375073A (zh) * 2018-11-15 2019-02-22 国网浙江省电力有限公司绍兴供电公司 防雷绝缘子动作电流和故障电流捕捉及识别模块
CN109585101A (zh) * 2018-11-15 2019-04-05 国网浙江省电力有限公司绍兴供电公司 基于物联网技术的配电网一体式防雷绝缘子
CN109765441A (zh) * 2018-12-27 2019-05-17 国网浙江诸暨市供电有限公司 智能绝缘子故障判断方法
CN109765440A (zh) * 2018-12-27 2019-05-17 国网浙江诸暨市供电有限公司 智能绝缘子雷电流监测设备
CN109839579A (zh) * 2018-12-27 2019-06-04 国网浙江诸暨市供电有限公司 智能限压器雷电流冲击试验装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SHAN, LINSEN: "Development of an Intelligent Lightning Protection Insulator for Distribution Network", ZHEJIANG ELECTRIC POWER, vol. 38, no. 4, 1 January 2019 (2019-01-01), pages 69 - 74, XP055924187, ISSN: 1007-1881, DOI: 10.19585/j.zjdl.201904012 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115077836A (zh) * 2022-06-02 2022-09-20 中国人民解放军国防科技大学 一种复现电连接器间歇故障的冲击试验方法
CN115077836B (zh) * 2022-06-02 2024-06-07 中国人民解放军国防科技大学 一种复现电连接器间歇故障的冲击试验方法
CN114724042A (zh) * 2022-06-09 2022-07-08 国网江西省电力有限公司电力科学研究院 一种输电线路中零值绝缘子自动检测方法
CN115498509A (zh) * 2022-10-12 2022-12-20 南京尚志电子科技有限公司 一种阻雷避雷装置
CN115862981A (zh) * 2022-12-27 2023-03-28 南京尚志电子科技有限公司 一种无线监测阻雷装置
CN118193959A (zh) * 2024-05-14 2024-06-14 深圳普泰电气有限公司 一种电涌能量的监测方法及系统

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