Abstract: The projectile-launcher operation monitoring device includes at least one displacement-sensor and a processor coupled with the displacement-sensor. The displacement-sensor acquires measurements relating to the displacement of the projectile-launcher and to produce a sampled time signal of values relating to the displacement. The processor receives from the displacement-sensor the sampled time signal to determine projectile-launcher operation parameters therefrom, by employing a deep-learning system. The deep-learning system includes an encoder receiving sample-frames from the sampled time signal producing codes relating to the sample-frames. Each of the codes is a vector of values relating to the probabilities of features in the received sample-frames.

Abstract: The projectile-launcher operation monitoring device includes at least one displacement-sensor and a processor coupled with the displacement-sensor. The displacement-sensor acquires measurements relating to the displacement of the projectile-launcher and to produce a sampled time signal of values relating to the displacement. The processor receives from the displacement-sensor the sampled time signal to determine projectile-launcher operation parameters therefrom, by employing a deep-learning system. The deep-learning system includes an encoder receiving sample-frames from the sampled time signal producing codes relating to the sample-frames. Each of the codes is a vector of values relating to the probabilities of features in the received sample-frames.

Abstract: The projectile-launcher operation monitoring device includes at least one displacement-sensor and a processor coupled with the displacement-sensor. The displacement-sensor acquires measurements relating to the displacement of the projectile-launcher and to produce a sampled time signal of values relating to the displacement. The processor receives from the displacement-sensor the sampled time signal to determine projectile-launcher operation parameters therefrom, by employing a deep-learning system. The deep-learning system includes an encoder receiving sample-frames from the sampled time signal producing codes relating to the sample-frames. Each of the codes is a vector of values relating to the probabilities of features in the received sample-frames.