Abstract: Provided is a method for planning embodied interaction of an intelligent agent based on active perception of environmental information.

Abstract: Provided is an LSTM-based hot-rolling roll-bending force predicting method including the steps of acquiring final rolling data of a stand of a stainless steel rolling mill when performing a hot rolling process, and dividing the data into a training set traindata and a test set testdata; normalizing the traindata; building a matrix P; using a last row of the matrix P as a label of the training set, namely a true value; calculating and updating an output value and the true value of a network; after network training is completed, taking the last m output data of the LSTM network as an input at a next moment, and then obtaining an output of the network at the next moment, wherein the output is a predicted value of the roll-bending force at the next moment; repeating the steps until a sufficient number of prediction data is obtained; and comparing the processed data with the true value in the testdata to check the validity of the network.

Abstract: Provided is a fault signal locating and identifying method of industrial equipment based on a microphone array. The method includes the steps of: acquiring sound signals and dividing the acquired signals into a training set, a verifying set and a test set; performing feature extraction on the sound signals in the training set, and extracting a phase spectrogram and an amplitude spectrogram of a spectrogram; sending an output of a feature extraction module, as an input, to a CNN, and in each layer of the CNN, learning a translation invariance in the spectrogram by using a 2D CNN; in between the layers of the CNN, normalizing the output by using a batch normalization, and reducing a dimension by using a maximum pooling layer along a frequency axis; sending an output from the layers of the CNN to layers of RNN; using a linear activation function; and inputting an output of a full connection layer to two parallel full connection layer branches for fault identification and fault location, respectively.

Abstract: The invention belongs to the technical field of quality control of steel plates and strips products, and relates to a prediction method of crown of steel plates and strips based on data driving and mechanism model fusion. By establishing an outlet crown mechanism model of a hot continuous rolling, the mechanism model and a DNN model are combined to establish a DNN model for predicting crown of steel plates and strips, and the calculated value of the mechanism model is taken as a benchmark value of the outlet crown. The deviation amount between the benchmark value and the actual values of the outlet crown is taken as output of the DNN model for predicting crown of the steel plates and strips, and then sum of the predicted value and the benchmark value based on the DNN model for predicting the crown of the steel plates is taken as the final predicted value of the crown of the steel plates and strips.

Abstract: Provided is a fault signal locating and identifying method of industrial equipment based on a microphone array. The method includes the steps of: acquiring sound signals and dividing the acquired signals into a training set, a verifying set and a test set; performing feature extraction on the sound signals in the training set, and extracting a phase spectrogram and an amplitude spectrogram of a spectrogram; sending an output of a feature extraction module, as an input, to a CNN, and in each layer of the CNN, learning a translation invariance in the spectrogram by using a 2D CNN; in between the layers of the CNN, normalizing the output by using a batch normalization, and reducing a dimension by using a maximum pooling layer along a frequency axis; sending an output from the layers of the CNN to layers of RNN; using a linear activation function; and inputting an output of a full connection layer to two parallel full connection layer branches for fault identification and fault location, respectively.

Abstract: Provided is an LSTM-based hot-rolling roll-bending force predicting method including the steps of acquiring final rolling data of a stand of a stainless steel rolling mill when performing a hot rolling process, and dividing the data into a training set traindata and a test set testdata; normalizing the traindata; building a matrix P; using a last row of the matrix P as a label of the training set, namely a true value; calculating and updating an output value and the true value of a network; after network training is completed, taking the last m output data of the LSTM network as an input at a next moment, and then obtaining an output of the network at the next moment, wherein the output is a predicted value of the roll-bending force at the next moment; repeating the steps until a sufficient number of prediction data is obtained; and comparing the processed data with the true value in the testdata to check the validity of the network.

Abstract: A polyester material including a composite having a carbon nanostructure, which comprises carbon element, from 0.5 to 4 wt % of a first non-carbon non-oxygen element substance, and from 0 to 4 wt %, of a second non-carbon non-oxygen element. The first non-carbon non-oxygen element is selected from the group consisting of P, Si, Ca, Al and Na; the second non-carbon non-oxygen element is any one selected from the group consisting of Fe, Ni, Mn, K, Mg, Cr, S or Co, or a combination of at least two selected therefrom. The G peak and D peak of the carbon element in the Raman spectrum has a peak height ratio of 1-20 in the composite having a carbon nanostructure.

Abstract: A polyester material including a composite having a carbon nanostructure, which comprises carbon element, from 0.5 to 4 wt % of a first non-carbon non-oxygen element substance, and from 0 to 4 wt %, of a second non-carbon non-oxygen element. The first non-carbon non-oxygen element is selected from the group consisting of P, Si, Ca, Al and Na; the second non-carbon non-oxygen element is any one selected from the group consisting of Fe, Ni, Mn, K, Mg, Cr, S or Co, or a combination of at least two selected therefrom. The G peak and D peak of the carbon element in the Raman spectrum has a peak height ratio of 1-20 in the composite having a carbon nanostructure.

Abstract: Various embodiments provide a method of fabricating a fibre, the method comprising translating a fibre having a light transmissive core surrounding by a cladding material; and while translating, non-interferometrically applying energy to alter structure of the light transmissive core and/or the cladding material.

Abstract: A method and apparatus for providing optical supercontinuum. The method comprises creating a spectrally narrow phase feature within a supercontinuum spectrum produced from a laser pulse that has been subjected to supercontinuum generation, thereby producing a modified supercontinuum spectrum, and propagating the modified supercontinuum spectrum through an optical waveguide that is suitable for supercontinuum generation, thereby further modifying the modified supercontinuum spectrum. The method may include modifying the modified supercontinuum spectrum by increasing its energy in a vicinity of the phase feature.

Abstract: A method and apparatus for providing optical supercontinuum. The method comprises creating a spectrally narrow phase feature within a supercontinuum spectrum produced from a laser pulse that has been subjected to supercontinuum generation, thereby producing a modified supercontinuum spectrum, and propagating the modified supercontinuum spectrum through an optical waveguide that is suitable for supercontinuum generation, thereby further modifying the modified supercontinuum spectrum. The method may include modifying the modified supercontinuum spectrum by increasing its energy in a vicinity of the phase feature.