SF6 state on-line monitoring method and system for GIL
A state, S16 technology, applied in neural learning methods, measuring devices, character and pattern recognition, etc., can solve problems such as leakage, reduce costs, reduce development cycles and costs, and reduce grid safety accidents
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Embodiment 1
[0077] This embodiment discloses an on-line monitoring system for SF6 state for GIL, such as figure 1 As shown, it includes SF6 status sensor, data relay device, intelligent monitoring device, optical fiber ring network switch and monitoring background. There are multiple SF6 state sensors. Different SF6 state sensors collect state information such as temperature, pressure, density and humidity of SF6 gas in their respective GIL gas chambers; data relay device relays, aggregates and forwards SF6 gas state data; intelligent monitoring The device converts the received SF6 gas state data into IEC61850 protocol, and has the functions of local sound and light alarm and fan linkage control; the monitoring background has the function of displaying the SF6 gas state information of each gas chamber, the function of displaying the alarm information, and the function of querying the historical data curve. and parameter configuration. attached figure 1 This is the network diagram of the...
Embodiment 2
[0086] This embodiment discloses an on-line monitoring system for SF6 state for GIL, such as figure 2 As shown, it includes SF6 status sensor, intelligent monitoring device, optical fiber ring network switch and monitoring background. Different SF6 state sensors collect state information such as temperature, pressure, density and humidity of SF6 gas in their respective GIL chambers; the intelligent monitoring device can convert the received SF6 gas state data into IEC61850 protocol, and has local sound and light alarm and fan Linkage control function; the monitoring background has functions such as the display function of SF6 gas status information in each gas chamber, the display function of alarm information, the function of querying historical data curves and parameter configuration. Different from Embodiment 1, the SF6 state sensor in this embodiment is directly connected to the intelligent monitoring device. The SF6 state sensor is connected with the intelligent monitor...
Embodiment 3
[0090] This embodiment discloses an on-line monitoring method of SF6 state for GIL. This method can be implemented in the monitoring background of Embodiment 1 or Embodiment 2. The Elman algorithm is used to predict the density of SF6 gas one day in advance by using database historical data and genetic particle swarm hybrid optimization. Early maintenance can prevent failures from occurring. Specifically include the following steps:
[0091] S01), using the PSO-GA algorithm to optimize the Elman neural network, the optimization process is:
[0092] S11), determine the Elman network structure, determine the Elman connection weight and threshold;
[0093] S12), initialize the genetic particle swarm population, take the Elman neural network training error as the fitness value, and calculate the population fitness value;
[0094] S13), update the speed and position of the particle, and determine the optimal solution of the population;
[0095] S14), carry out selection, crossov...
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