To improve the transmission rate and communication quality of indoor visible light communication(VLC), a VLC channel estimation and equalization method based on orthogonal time-frequency space(OTFS) modulation and residual convolutional neural network(ResCNN) is proposed. First, an indoor VLC system based on OTFS modulation is constructed, and a time-frequency domain channel estimation model based on training sequences is proposed. Then, ResCNN learns the mapping relationship between the least squares(LS) channel estimation and the optimized channel to solve the inter-symbol interference problem and improve the accuracy of channel estimation. Finally, the visible light channel is estimated and equalized using ResCNN. The experimental results show that when the signal transmission distance is 1 m and the transmission rate is 512 Mb/s to 1.5 Gb/s, the bit error rate estimated by the proposed method is lower than 3.8×10^-3, effectively improving the transmission rate and communication quality of indoor short-distance VLC.