Illuminance uniformity refers to the ratio of minimum illuminance to average illuminance on a specific surface. The more uniform the light distribution, the better the illuminance, the more comfortable the visual experience, and the closer the illuminance uniformity is to 1, the better. On the contrary, the smaller, the more visual fatigue.

Evaluation technology of illuminance uniformity

The problem of illumination uniformity is of great significance in the field of precision machining, so the accurate evaluation of illumination uniformity is of great significance. Because of the nonlinearity of illumination uniformity itself, it is difficult to realize minimum area evaluation directly according to the definition. The least square method, which has been used all the time, often leads to inaccurate judgment of the evaluation object. A quasi-sinusoidal particle swarm optimization algorithm is proposed.

That is, according to the designed method of changing the population size and diversity function, the particle swarm automatically adjusts its size at the peak and trough of each sine wave segment according to the quasi-sine law, and then updates the position and speed of the particle according to the basic particle swarm optimization algorithm. In the updating process, not only can each particle be fully evolved, but also the continuity between particles is ensured and the diversity of particle swarm is maintained.

This algorithm solves the problem of illuminance uniformity evaluation well. Examples show that QSPSO can exert its advantages for nonlinear optimization problems such as illuminance uniformity evaluation, or problems with many optimization parameters, or problems with inconvenient expression of objective optimization function.