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

A motor generator main body 100 includes: field winding 8 whose energization is controlled by a semiconductor control device 30 that is supplied with power through a brush 14 and whose energization is controlled by a control circuit unit 22A; and armature winding 10A whose energization is controlled by an inverter power circuit unit 20 controlled by the control circuit unit 22A. The motor generator device is constructed by mounting the inverter power circuit unit 20 and the control circuit unit 22A in the motor generator main body. The brush is provided between the field winding 8 and the armature winding 10A, and the control circuit unit 22A, and the semiconductor control device 30 is mounted in the control circuit mounted portion 22 mounted with the control circuit unit 22A. The motor generator unit tries for integrating the motor generator with the inverter to make the wiring of the energization circuit unit for providing the current to the rotor coil reasonable.

The invention discloses a method and device for feature extraction of physical layer equipment based on sampling rate deviation estimation. The method includes (1) receiving a signal with a repeated signal frame structure sent by a target equipment; (2) generating a standard signal according to the received signal, from Collect multiple signals at different positions in the received signal, and perform correlation calculations with the standard signal at irregular intervals to obtain the correlation value of each correlation peak and adjacent points; (3) Estimate the time of repeating the frame structure of the signal according to the results of step (3) Interval 1; (4) carry out the fixed-interval correlation operation with the signal of many different positions with the standard signal, obtain the correlation value set of each correlation peak and adjacent point; (5) the correlation value set calculation that step (4) obtains receives The change rule of the signal correlation peak; (6) the time interval I of the repeated signal frame structure and the change rule of the correlation peak are used as the physical layer device characteristics of the signal transmitting device. The invention can realize equipment feature extraction in a baseband communication system.

The invention discloses a method for enhancing the contrast between a target and a background based on a multi-channel polarization distance model. The steps include: 1. obtaining polarization images under different polarization angles; The G channel image in the RGB image; 4. Calculate the activity value of the simulated photoreceptor R; 5. Use the multi-channel polarization distance model to calculate the polarization distance image. The present invention can well enhance the contrast between the target and the background in the low contrast scene, thereby improving the visibility and conspicuousness of the target.

The invention discloses a finger vein recognition method and device based on an improved local binary model, which can overcome the influence of noise, improve the recognition accuracy and be easy to achieve in parallel. S1, acquire the finger vein image to be identified, locate the finger vein feature point position, and calculate the LmTP feature of each feature point based on the improved local binary model; S2, compare the finger vein by means of the fusion distance and the similarity of the LmTP feature Match the feature points with the finger vein feature points of the preset template image; S3, calculate the global similarity of the matching point pair according to the matching result; S4, perform finger vein recognition on the finger vein image according to the global similarity .

A constant on-time controlled switching converter, a controller and a control method thereof are disclosed, wherein the switching converter includes a main transistor and an inductor coupled to the main transistor. The control method includes: generating a conduction time control signal; generating a ramp signal, and adjusting the ramp signal to be equal to the common-mode voltage when the main transistor is turned from off to on; based on the ramp signal, the common-mode voltage, the reference signal and A feedback signal representative of the output voltage of the open converter generates a comparison signal; and a control signal is generated based on the on-time control signal and the comparison signal to control the main transistor.

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.

Provided is a meditation training HRV signal analysis method based on an extremum energy decomposition method, the HRV signal analysis method comprising: acquiring an ECG signal in meditation training at a given time and a given sampling frequency, and obtaining an RRI signal after denoising; taking the RRI signal x(t) as an original signal, and decomposing the original signal x(t) into n extremum mode function components and a margin; using the n extremum mode function components obtained by decomposing the original signal x(t) to represent components of the original signal at different frequency bands; and determining, according to the n extremum mode function components, whether the RRI signal enters a meditation state. According to the method, an RRI signal is analyzed by using the extremum energy decomposition method, wherein an original signal is decomposed into a plurality of components, namely, extremum component functions; and the energy of each component is calculated, and the energy distribution of the original signal is obtained.