# Long-Lifetime Event-Driven Wireless Monitoring System for Pole-Mounted Transformers
## 3 Proposed Event-Driven Monitoring System  
To extract a physical quantity of an abnormal input in conventional wireless monitoring systems, an ADC and TX need to make multiple samplings and data transmissions for each intermittent abnormal input. This results in high energy consumption because all the components are turned on all the time. As suggested by (3) and (5), energy consumption can be reduced by using the proposed EC, as shown in Figure 5a. The EC minimizes the turn-on time of each block while continuously monitoring the input. In addition, it employs event-driven data sampling and transmission that allows only one sample for each intermittent abnormal period, as depicted in Figure 5b, and makes the power consumption of the ADC and TX independent of sampling frequency. When an \(i\)th abnormal input is sensed at \(t=t_{\text{L}i}\), the BPF and RMS converter generate the signal \(v_{\text{RMS}}\) based on \(v_{\text{IN}}\) until \(v_{\text{RMS}}\) becomes zero at \(t=t_{\text{UI}}\). After a time delay \(t_{\text{D}}\), the ADC and TX are enabled by the EC for their normal operating times \(t_{\text{ADC}}\) and \(t_{\text{TX}}\), respectively. Then, each block falls into sleep mode when disabled; the power consumption in sleep mode is negligible compared to that in normal mode. The energy consumption for a conventional wireless monitoring system with an RMS converter and EC, \(E_{\text{ECi}}\), can be approximated as  
\[E_{\text{ECi}}\approx P(\text{EC})\Big{(}t_{\text{L}(i+1)}-t_{\text{L}i}\Big{)} +[P(\text{BPF})+P(\text{RMS})]\cdot(t_{\text{UI}}-t_{\text{L}i})+P_{\text{ADC }}t_{\text{ADC}}+P_{\text{TX}}t_{\text{TX}}. \tag{6}\]  
In the conventional monitoring system shown in Figure 4a, the BPF and RMS converter are always-on blocks. However, the proposed EC reduces the normal operation time for each block, with \(t_{\text{UI}}-t_{\text{L}i}\), \(t_{\text{ADC}}\), and \(t_{\text{TX}}\) being much smaller than \(t_{\text{L}(i+1)}-t_{\text{L}i}\) for the \(i\)th intermittent abnormal input. Therefore, the energy consumption of the BPF, RMS converter, ADC, and TX can be greatly reduced. As long as \(P(\text{EC})(t_{\text{L}(i+1)}-t_{\text{L}i})\) is small enough to be neglected, \(E_{\text{ECi}}\) can be lower than \(E_{\text{RMSi}}(f_{\text{L}})\) in (5). However, the uncertainty of whether the maximum value of \(v_{\text{RMS}}\) occurs at time \(t_{\text{D}}\) reduces the signal-to-noise ratio (SNR) of the  
Figure 5: Conventional monitoring system with proposed event controller (EC). (**a**) Block and (**b**) timing diagrams, with sampling time delay \(t_{\text{D}}\). overall monitoring system. The SNR of the conventional monitoring system with EC in Figure 5a, for the \(i\)th intermittent abnormal input, \(SNR_{\text{ECI}}\), can be expressed as  
\[SNR_{\text{ECI}}=\frac{P(RMS(v_{\text{S}}(t_{\text{Li}}+t_{\text{D}})))}{P(RMS(v _{\text{NF}}(t_{\text{Li}}+t_{\text{D}})))}, \tag{7}\]  
where \(RMS(x(t))\) is the RMS value of \(x\) from the lower time bound \(t_{\text{Li}}\) to \(t\), with \(t_{\text{Li}}\leq t\)\(\leq t_{\text{Ui}}\). As \(v_{\text{NF}}(t)\) is Gaussian noise with a mean of zero and is not correlated with \(v_{\text{S}}(t)\), \(RMS(v_{\text{NF}}(t_{\text{Li}}+t_{\text{D}}))\) can be assumed to be constant regardless of \(t_{\text{D}}\), leading to  
\[SNR_{\text{ECI}}\approx\alpha[RMS(v_{S}(t_{\text{Li}}+t_{\text{D}}))]^{2}, \tag{8}\]  
where \(1/\alpha\) is the noise power. As \(RMS(v_{\text{S}}(t_{\text{Li}}+t_{\text{D}}))\) varies with \(v_{\text{S}}\) and \(t_{\text{D}}\), \(SNR_{\text{ECI}}\) cannot be guaranteed to have its maximum value at the time of sampling. To guarantee that the maximum RMS value is transmitted, a peak detector is attached after the RMS converter in the proposed monitoring system shown in Figure 6a. Unlike the previous conventional system with proposed EC in Figure 5a, this system samples the maximum RMS value using the peak detector and holds its value until \(v_{\text{RMS}}\) becomes zero at \(t=t_{\text{Ui}}\) as shown in Figure 6b.