The reasons why thermal imaging systems consume power are analyzed,and a low power consumption design scheme is presented for the thermal imaging systems operating at multiple temperatures. The relation between the re...The reasons why thermal imaging systems consume power are analyzed,and a low power consumption design scheme is presented for the thermal imaging systems operating at multiple temperatures. The relation between the response performance of α-Si microbolometer detector and its operating temperature is studied by means of formulas of microbolometer detector's noise equivalent temperature difference(NETD) and detectivity. Numerical analysis based on true parameters demonstrates that the detectivity decreases slightly and NETD increases slightly when operating temperature rises,which indicates that α-Si microbolometer detector has approximately uniform response in a wide operating temperature range. According to these analyses,a thermal imaging system operating at multiple temperatures is designed. The power of thermoelectric stabilizer(TEC) is less than 350 mW and NETD is less than 120 mK in the ambient temperature range of-40 ℃-60 ℃,which shows that this system not only outputs high-quality images but consumes low power.展开更多
针对当前换流站一次设备温度监测中非接触式红外测温存在成本高、准确率低、时效性差等问题,提出一种面向高压场景的温度监控方案。该方案结合5G无源物联网(Passive Internet of Things,P-IoT)技术与Transformer模型。通过在高压设备关...针对当前换流站一次设备温度监测中非接触式红外测温存在成本高、准确率低、时效性差等问题,提出一种面向高压场景的温度监控方案。该方案结合5G无源物联网(Passive Internet of Things,P-IoT)技术与Transformer模型。通过在高压设备关键部位部署无源温度传感器,利用反向散射通信技术实现低功耗数据传输,并借助5G网络将数据传输至边缘服务器处理。随后,采用基于Transformer的异常检测模型,通过多头注意力机制有效捕捉温度数据中的时序特征,结合最大池化操作实现对异常温度的准确识别与预警。实验结果表明,该方案在高电磁干扰环境下的传输成功率达到99.0%,在温度异常检测任务中的精度、召回率和F1值分别为98.7%、97.5%和96.9%,显著优于LSTM和GRU等传统时序模型。研究成果验证了所提方法在复杂高压场景下的适用性和稳定性,可为后续在更高电压等级的特高压设备中推广应用奠定技术基础。展开更多
文摘The reasons why thermal imaging systems consume power are analyzed,and a low power consumption design scheme is presented for the thermal imaging systems operating at multiple temperatures. The relation between the response performance of α-Si microbolometer detector and its operating temperature is studied by means of formulas of microbolometer detector's noise equivalent temperature difference(NETD) and detectivity. Numerical analysis based on true parameters demonstrates that the detectivity decreases slightly and NETD increases slightly when operating temperature rises,which indicates that α-Si microbolometer detector has approximately uniform response in a wide operating temperature range. According to these analyses,a thermal imaging system operating at multiple temperatures is designed. The power of thermoelectric stabilizer(TEC) is less than 350 mW and NETD is less than 120 mK in the ambient temperature range of-40 ℃-60 ℃,which shows that this system not only outputs high-quality images but consumes low power.
文摘针对当前换流站一次设备温度监测中非接触式红外测温存在成本高、准确率低、时效性差等问题,提出一种面向高压场景的温度监控方案。该方案结合5G无源物联网(Passive Internet of Things,P-IoT)技术与Transformer模型。通过在高压设备关键部位部署无源温度传感器,利用反向散射通信技术实现低功耗数据传输,并借助5G网络将数据传输至边缘服务器处理。随后,采用基于Transformer的异常检测模型,通过多头注意力机制有效捕捉温度数据中的时序特征,结合最大池化操作实现对异常温度的准确识别与预警。实验结果表明,该方案在高电磁干扰环境下的传输成功率达到99.0%,在温度异常检测任务中的精度、召回率和F1值分别为98.7%、97.5%和96.9%,显著优于LSTM和GRU等传统时序模型。研究成果验证了所提方法在复杂高压场景下的适用性和稳定性,可为后续在更高电压等级的特高压设备中推广应用奠定技术基础。
