Abstract: A high anti-interference microsystem based on System In Package (SIP) for a power grid is provided. The high anti-interference microsystem comprises a ceramic cavity, a ceramic substrate, a magnetic cover plate, a digital signal processing circuit, an analog signal conditioning circuit and a shield, wherein the ceramic cavity supports the ceramic substrate, the magnetic cover plate is in sealed contact with the ceramic cavity, and the ceramic substrate is arranged in a cavity formed by the ceramic cavity and the magnetic cover plate; a sealed shell of the microsystem based on SIP is composed of the magnetic cover plate and the ceramic cavity; the digital signal processing circuit and the analog signal conditioning circuit are arranged on the ceramic substrate and respectively process received signals to be processed; the shield covers an outer side of the sealed shell and is used for shielding external magnetic field interference.

Abstract: A spiking neural network acceleration method includes constructing an approximate computation model according to a spiking neuron model and a spiking coding mode. The approximate computation model utilizes the characteristic that spiking frequency domain coding ignores the time semantics of a spiking sequence, compresses the distribution of spiking signals on a time step, and greatly reduces a spiking routing process and a subsequent neural computation process. The time-driven accelerator replans the computation process of the spiking neural network, sets a deduplication queue and a bitmap to solve the problem of spiking jitter, and realizes efficient support on the inhibitory spiking neural network.

Abstract: Disclosed is an intelligent on-line diagnosis method for winding deformation of power transformer. When a transformer is subjected to short-circuit shock or transportation collision, transformer windings may undergo local twisting, swelling or the like under the action of an electric power or mechanical force, which is called winding deformation and will cause a huge hidden danger to the safe operation of the power network. Commonly used diagnosis methods for winding deformation are all off-line diagnosis methods, which have the disadvantages that transformers need to be shut down and highly skilled operators are required. The present invention provide an intelligent on-line diagnosis method for winding deformation on the basis of combination of information entropy and support vector machine.

Abstract: A method for repairing an organic polluted site includes the following steps: step 1, build a sunlight greenhouse; step 2, carry out pretreatment to the soil of the organic polluted site; step 3, perform a biological heap treatment on the pretreated soil; step 4, implement quality control on the biological heap for soil remediation. By constructing a sunlight greenhouse within the original site of organic pollution sites, placing a biological heap in the sunlight greenhouse for a biological heap treatment, using the heat accumulated in the sunlight greenhouse to promote the volatilization of volatile organic matters in the soil without causing secondary pollution, and meanwhile adding a microbial agent and a nutritional agent to the polluted soil to promote the degradation and conversion of adsorbed organic matters.

Abstract: Disclosed is an intelligent on-line diagnosis method for winding deformation of power transformer. When a transformer is subjected to short-circuit shock or transportation collision, transformer windings may undergo local twisting, swelling or the like under the action of an electric power or mechanical force, which is called winding deformation and will cause a huge hidden danger to the safe operation of the power network. Commonly used diagnosis methods for winding deformation are all off-line diagnosis methods, which have the disadvantages that transformers need to be shut down and highly skilled operators are required. The present invention provide an intelligent on-line diagnosis method for winding deformation on the basis of combination of information entropy and support vector machine.