天然采光与人工照明的智能结合策略

An Intelligent Strategy of Combining DayLighting and Artificial Illumination

以‘绿色照明’为出发点，提出了一个天然采光和人工照明相结合的智能策略。选择一间典型的办公室为试验对象，用BP神经网络建立模型，根据室内天然光的照度水平，自动控制灯具调光输出和遮阳设备状态，从而实现工作区域恒照度的目标。实际应用中，一旦人工照明打开，能检测到的就是天然光和人工光的混合量，很难把天然光分量用设备检测出来，这给控制带来了一定的麻烦。因此提出了一个自适应神经模糊推理系统，用以根据室外的天然光照度来预测室内的天然光照度，作为BP网络的输入。实验数据表明，该方法能有效节约能源，并改善工作环境，提高工作效率。

An intelligent strategy of combining daylight and artificial illumination was presented with the conception of “green lighting”. Using BP neural network to model,and control the adjustable lighting output and shutter automatically based on the interior daylighting level in a typical office room. But there are some problems when put it in use. We could not measure the interior daylight once the artificial lighting is on. So an Adaptive Neural Fuzzy Inference System is proposed. The interior daylighting level is predicted by the measurement of exterior natural lighting, which can be used as input of the BP neural network, Demonstrated by exDerimental data.this method can save energy significantly, and improve working environment and efficiency.