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In order to seek a better way of control in sewage treatment, a control system which consisted of water unit, sand unit, the oxidation ditch unit, precipitation unit and sludge dewatering unit was designed. The paper investigates various controllable parameters in sewage treatment system and the way of present common automation control. We designed manual control variable aeration program and two automatic control subroutine which included thickness grille and pumping station by using WIN 32 software. The program is designed in Siemens STEP 7 V5.5 software development platform and chose the 10 input contacts which are I0.0~I0.7, I1.0~I1.1 and 10 output contact which are Q1.0~Q1.1, Q0.0~Q0.7.This design achieves automatic control and improves the purifying efficiency on the premise of ensuring water quality.

In order to improve the efficiency of electrostatic precipitators, a control system of constant current source based on Single Chip Microcomputer (SCM) is designed. In the control process, we use the pulse signal from microcontroller P1 port as digital signals of the switch. By changing the number of contact closure control, we achieve steady flow output of different magnitude. By using closed-loop feedback control, we achieve constant monitoring of dust concentration and ensure it compliance with outlet concentration of national requirements. The results show that microcontroller control system has a strong anti-interference, high accuracy, ease of programming, etc. Used in the electrostatic precipitator, collection efficiency can be further improved.

Automatic identification of defects on solar cell modules is the key of improving components efficiency of power generation and achieving the maximum utilization of energy[1]. This paper took the debris defects as an example. Considered the fact that scale factor would have an impact on moment invariants in discrete state, this paper adopted an improved moment invariant for the image feature extraction of debris defects. The scale factor of the new moment invariants is eliminated by transformation. Therefore they have the properties of translation, rotation and scaling simultaneously. Meanwhile, SVM (Support Vector Machine) classifier was used to identify the debris defects. The experimental results show that, compared with the traditional moment invariants, the identification rate of using the improved moment invariants for feature extraction is 96%.

As one of important technologies of IOT (Internet of Things), WSN (Wireless Sensor Networks) has been used in tunnel environmental monitoring. Tunnel environment monitoring has its particularity that WSN nodes show linear topologies. Traditional routing algorithms in WSN do not consider the linear topology of sensor nodes in tunnel and are difficult to realize long-time data transmission in limited battery power. In this paper, we propose Power Control Dynamic Source Routing algorithm (PC-DSR) by the thought of cross-layer design. Routing table is established according to the distance between nodes and the residual energy of nodes and optimum transmission power is calculated in order to save nodes’ power and prolong the life-time of the whole networks. Simulation results show that the novel algorithm can save node's transmission power, which increase the WSN lifetime of 12.3%.