32results about How to "Not easily affected by noise" patented technology

The invention discloses an aero-engine rotor-stator rubbing position identification method based on the application of cepstrum and belongs to the technical field of aero-engine fault diagnosis. According to the method, first, aeroengine case vibration acceleration signals of different rubbing positions of an aero-engine are obtained; next, by means of the cepstrum analytical method, Low-dimensional feature parameters are extracted, and training samples are formed; then, training is carried out on a training sample set by means of sorting algorithms, and a rubbing position sorter is obtained; last, rubbing positions are identified with the trained sorter. Only with an acceleration sensor, can rubbing positions of the aero-engine be effectively identified. Compared with the prior art, the method is simple and suitable for real-time diagnosis in the field.

The invention discloses a multi-focus noise image fusion method based on a cycle spinning-Contourlet domain hidden Markov tree model (CS-CHMT) and an improved dual-channel pulse-coupled neural network (IDPCNN). First, two multi-focus images containing a certain level of Gauss white noise are de-noised by use of the CS-CHMT model, and on the basis, a fusion strategy is designed by use of the IDPCNN to obtain a final fused image. According to the invention, by making use of the directional sensitivity of Contourlet transform height and the advantages of anisotropy, performing image de-noising by use of a hidden Markov tree (HMT) model, and introducing a cycle spinning technology to effectively suppress the pseudo Gibbs effect of the images near singular points, the PSNR value of de-noised images is improved. Compared with the traditional multi-focus image fusion method, the improved IDPCNN fusion method can effectively preserve more detailed information characterizing image features, greatly improve the quality of fused images and further improve the visual effect, and has real-time performance.

A power grid peak load clustering extraction method based on Pearson coefficient and MapReduce parallel computing comprises the following steps: 1, conducting data cleaning and abnormal data restoration on a load data set, and then conducting dimensionality reduction on the load data set; 2, storing the data set subjected to dimension reduction in a Hadoop distributed file system line by line, anddividing the data set into slices to form sub-data sets; 3, reading each slice sub-data set in the step 2 by using a MapReduce computing architecture, and selecting an initial clustering center by using a Pearson correlation coefficient as a similarity criterion through a parallel model; and 4, allocating the clustering calculation task to the Map task node in the MapReduce, and combining the initial clustering center in the step 3 to complete parallel clustering of the data set. The method is more suitable for power load big data processing derived from more and more vigorous development information times.

The invention relates to a novel method for identifying overvoltage inside a distribution network. An atomic decomposition algorithm optimized based on an imperial colonial competition algorithm is applied to the analysis of over-voltage signals, and the optimized algorithm can be used to extract the internal characteristics of signals quickly and effectively without being disturbed by noise. A three-phase characteristic atomic spectrum is constructed based on the atomic decomposition algorithm, waveform signals only containing time-domain information are converted into high-dimensional characteristics containing time-frequency information, and the time-frequency characteristics of overvoltage signals are described completely. The three-phase characteristic atomic spectrum is recognized directly by using a convolution neural network, the shortcomings of a shallow learning identification algorithm for the identification of high-dimensional characteristics are overcome, and the subjectivity and complexity in the process of characteristic reduction are avoided. Simulation waveforms and physical models verify that the distribution network overvoltage type identification method of the invention has high identification accuracy and strong adaptability.

The invention discloses a light emitter, which comprises a current mode logic driving module, a modulator and a terminating module, the current mode logic driving module is connected with the input end of the modulator in a direct coupling mode, and the current mode logic driving module is used for generating and outputting a high-speed differential driving signal; the output end of the modulatoris connected with the input end of the terminating module in a direct coupling mode; the modulator is used for modulating an optical signal of the modulator according to the received high-speed differential driving signal to obtain a modulated optical signal and outputting the modulated optical signal; and the terminating module is used for performing far-end impedance matching on the received high-speed differential driving signal. The light emitter has the advantages of saving hardware cost, reducing direct current power consumption, reducing circuit design complexity and facilitating high-density multi-channel integrated design.

The invention discloses a physical layer equipment feature extraction method and device based on sampling rate deviation estimation. The method comprises the following steps: (1) receiving a signal with a repeated signal frame structure sent by target equipment; (2) generating a standard signal according to the received signal, collecting a plurality of sections of signals at different positions from the received signal, and performing unfixed interval correlation operation with the standard signal to obtain a correlation value of each correlation peak and an adjacent point; (3) estimating thetime interval I of the repeated signal frame structure according to the result of the step (3); (4) performing fixed interval correlation operation on the multiple sections of signals at different positions and a standard signal to obtain a correlation value set of each correlation peak and an adjacent point; (5) calculating a change rule of a correlation peak of the received signal according tothe correlation value set obtained in the step (4); and (6) taking the time interval I of the repeated signal frame structure and the change rule of the related peak as the physical layer equipment characteristics of the signal transmitting equipment. According to the invention, equipment feature extraction in a baseband communication system can be realized.

The invention relates to power load data processing, in particular to a power load data dimension reduction reconstruction processing method based on VMD and OMP. The method comprises the following steps: acquiring power load data; carrying out data decomposition filtering and dimension reduction processing on the acquired power load data through a variational mode decomposition method; and then,after obtaining intrinsic mode components of which the frequencies are from low to high, performing reconstruction optimization processing on the decomposed and filtered data by using an orthogonal matching tracking algorithm. According to the method, a VMD operation method and an OMP operation method are combined for the first time, the dimension reduction reconstruction processing method which is high in operation efficiency and universality is obtained, and the method is suitable for a data set of an existing dimension, not prone to being affected by noise, high in stability and more suitable for power load big data processing derived in the increasingly flourishing development information age.

The invention provides a rapid wakeup method and system in the technical field of wireless communication. The method comprises the following steps: a transmitting end and a receiving end appoint a wakeup frequency f0; when awakening is carried out, the sending end generates an awakening signal at an awakening frequency agreed with the receiving end, and the awakening signal is composed of two sections of signals which are respectively an upper frequency sweep signal or a lower frequency sweep signal with the signal frequency linearly rising or falling for T milliseconds from the awakening frequency f0 at the slope u0, the signal frequency linearly drops or rises for T milliseconds from the slope u0 to a lower or upper sweep frequency signal of wake-up frequency f0; sending a wake-up signal in an agreed time slot; and in the dormant state, the receiving end is temporarily awakened in an appointed time slot, two receiving windows with the duration of L milliseconds are opened, receiving signals in the two windows are processed, and if an awakening condition is met, the receiving end enters a continuous awakening state. According to the method, the chirp signal not only can be used for awakening, but also can be used for synchronization, so that the system reliability is improved.

A method is described for setting an optimum write power for recording information on an optical recording medium. First a series of test patterns is written on the medium, each test pattern being written with a different write power. On reading the test patterns, the modulation of each read signal is determined. The modulations as a function of write power are curve-fitted to an analytic function. The normalised derivative of this function is determined analytically and is used to determine the value of the optimum write power for the medium.

According to one embodiment, a semiconductor integrated circuit has a transconductance circuit, a first load circuit, and a second load circuit. At least one of the above transconductance circuit, the first load circuit and the second load circuit has an impedance adjusting module to adjust impedance in the following way of deceasing a parameter P: P=Z01*Z04-Z02*Z03, wherein Z01 stands for impedance of the transconductance circuit from the view of a first output terminal, Z02 stands for impedance of the transconductance circuit from the view of a second output terminal, Z03 stands for impedance of the first load circuit, and Z04 stands for impedance of the second load circuit.

A controller for a switched mode power converter (SMPC) module for use in a multiphase SCMP is disclosed, comprising: a signal generator, configured to generate a periodic signal and a clock, both having a frequency and a signal phase, and for controlling the switched mode power converter module; a first-clock and second-clock inputs configured to receive respective first-clock and second-clock signal having the frequency and respective first and second phases from neighbouring controllers; and wherein the signal generator comprises a phase adjustment circuit configured to adjust the phase of the periodic signal so as to be equidistant from the first and second phase, wherein the phase adjustment circuit determines an error signal in dependence on an offset between the phase and a mid-point between the first phase and the second phase, and a feedback circuit configured to adjust the phase in dependence on the error signal.

The invention discloses a distributed optical fiber sensing system based on delay reservoir calculation and a signal identification and positioning method thereof. The system is composed of an input layer, a storage pool and an output layer. The input layer is provided with two nodes, one node is used for inputting a non-necessary reservoir excitation signal, and the other node is used for inputting an external vibration signal; the storage pool is composed of a delay nonlinear system, and a delay optical fiber of the delay nonlinear system is a sensing optical fiber; the output layer is provided with two nodes, one node outputs a vibration type, and the other node outputs a vibration position. The signal identification and positioning method comprises the following steps of: before a system is started, carrying out network training, and determining an output connection right according to a virtual node state of target output and training signals; and after the system is started, the output connection weight and the virtual node state of the to-be-detected vibration signal are utilized to obtain the output calculated by the reserve pool, namely the type and the position of the vibration signal. According to the invention, the light reserve pool is utilized to calculate strong learning ability, modeling ability and rapid processing ability, and accurate and real-time identification and positioning of external vibration are realized.