87results about How to "Overcoming nonlinearity" patented technology

The invention discloses an engine fault prediction method. The method comprises the following steps that effective measurement data of a plurality of sensors of an engine are obtained; the effective measurement data are subjected to normalization processing; the effective measurement data obtained after normalization processing are sliced, and a plurality of slice samples are formed; the multiple slice samples are sent into a deep nerve network to be subjected to feature extraction, and after feature extraction, the slice samples are connected to a fully-connected network; and according to output of the fully-connected network, classification is conducted through a softmax classifier, and the left service life of the engine is determined. According to the provided engine fault prediction method, the process is small, operation is easy, and the engine fault prediction method can be widely applied to various engines of aircraft.

The invention relates to an ultrasonic wave motor transient characteristic testing device and a control system of the device. The device comprises a base and an ultrasonic wave motor arranged on the base, wherein an output shaft on one side of the ultrasonic wave motor is connected with an optical-electricity encoder, an output shaft on the other side of the ultrasonic wave motor is connected with a flywheel inertia load, an output shaft of the flywheel inertia load is connected with a torque sensor through a coupler, the signal output end of the optical-electricity encoder and the signal output end of the torque sensor are respectively connected to the control system, and the control system is composed of an RNNI and an RNNC. The RNNI completes the identification of the input characteristics and the output characteristics of the ultrasonic wave motor under the different control variables and different flywheel inertia loads, and the RNNC achieves the speed/position/torque control output of the ultrasonic wave motor according to the identified result so as to determine the control dynamic characteristic under the different loads and the different control variables. The device and the control system are high in testing accuracy, simple and compact in structure and good in using effect.

The invention discloses an underwater robot depth control device based on linear active disturbance rejection technology and a method thereof. The device includes an underwater robot, a cable, a computer, a control board and a sensor. The lower portion of the underwater robot is equipped with the sensor; the computer is connected with the underwater robot via the cable; the control board is arranged on a control motor; and the depth control method of the linear active disturbance rejection technology is stored in the control board. In the implementation process, information including depth, vertical speed, attitude angle is obtained through the corresponding sensor; a depth controller places a model of a system and external disturbance in the same position; the depth control method based on the linear active disturbance rejection technology is used for controlling resolving and control instructions are outputted; and an actuator of the underwater robot executes the control instructions to complete depth motion control of the underwater robot. According to the invention, the underwater robot depth control device based on the linear active disturbance rejection technology and the method thereof can effectively adapt to strong nonlinear dynamics and external disturbance of the underwater robot and achieve precise depth control.

The invention discloses one low power and anti-high voltage linear motor, which adopts special designed conductive magnetic cover, armature iron and end cover basin shoe parts, wherein, the magnetic conductive cover is orderly set with yoke iron, permanent part, yoke iron with two permanent axis filled with magnetic part; the yoke iron and permanent part, end cover and shell form ring space filled with co-center spiral tube control coil; the permanent magnetic part generates electrode magnetic field and control coil overlap.

The invention discloses a contact type scanning probe for a micro-nano three-coordinate measuring machine. The contact type scanning probe is characterized in that a measuring head and a measuring unit are arranged in a probe housing. The measuring head unit comprises a suspension sheet (5a) and a base (6), wherein the suspension sheet (5a) is arranged inside the inner cavity of the base (6) to form a suspension structure. The central through hole of the suspension sheet is fixedly provided with a probe with a measuring ball. The probe extends out of the bottom port of the base and is free from swinging under the interference of the bottom port of the base. The measuring unit comprises a capacitive sensor arranged on each cantilever of the suspension sheet. According to the technical scheme of the invention, the output signal of the capacitive sensor is adopted as the detection signal of the probe. Therefor, the detection result is ensured to be high in accuracy, high in sensitivity and small in measurement force. Meanwhile, the contact type scanning probe is high in stability and low in cost.

The invention relates to an intelligent configuration system and an intelligent configuration method for a wireless sensor network. The system comprises a sensor network module, a gateway module, an output module, an execution module and an application layer interface module. The system and the method solve problems of poor adaptability, poor reliability and relatively great control cost existing in a device and a method of a traditional sensor network. The system and the method for the wireless sensor network have advantages of intelligent performance, strong robustness, good versatility and small control cost.

The invention provides a bi-axis inertially-stabilized platform high-precision control method based on a self-adaptive backstepping sliding mode, and relates to design of a composite controller for backstepping sliding mode control based on an auxiliary integral sliding mode surface and adaptive neural network construction and optimization. The method is characterized by, to begin with, designing a backstepping sliding mode control method based on the auxiliary integral sliding mode surface according to a bi-axis inertially-stabilized platform dynamical model, and generating a control command according to state error information to realize suppression of indeterminacy and interference of dynamical model parameters; and then, constructing an adaptive neural network, constructing an adaptive neural network weight updating matrix based on the error information to update a weight matrix of the neural network online, estimating upper bound of interference error in real time, and realizing bi-axis inertially-stabilized platform high-precision control under complex environment. The method has the advantages of good real-time performance, fast dynamic parameter response and high multisource interference adaptability and the like, and can used for high-precision control and the like under the complex multisource interference environment.

The invention relates to a giant magnetoresistance current sensor and relates to a device for measuring currents. The giant magnetoresistance current sensor is composed of an electromagnetic conversion module, a signal amplification module and a feedback compensation module, wherein the electromagnetic conversion module comprises a magnetic core of a magnetism accumulation ring, a primary winding and a giant magnetoresistance chip, the signal amplification module comprises an operational amplifier and a push-pull power amplifier, and the feedback compensation module is a feedback winding. The whole measurement circuit forms a closed loop system, and the giant magnetoresistance chip and the magnetic core of the magnetism accumulation ring form a closed structure. The giant magnetoresistance current sensor overcomes the defects that a giant magnetoresistance current sensor in the prior art is very prone to interference of an external stray magnetic field, temperature drift and zero drift cannot be eliminated completely, and the measurement accuracy is affected by intrinsic magnetic hysteresis existing in a magnetic device.

The invention provides a self-adaptive control method for the period of a traffic signal based on an evolutionary game. An evolutionary game theory is applied into the self-adaptive control of a traffic signal, the dynamic characteristics for controlling the traffic flow and the single are sufficiently considered, a signal lamp self-adaptive control model is built, and the problem of the control of the urban traffic signal lamp in the current region can be solved. The method is a completely-distributed control method, so that the characteristics of the traffic system, i.e. the uncertainty, the randomness, the nonlinearity, the locality and the like, can be well solved. Furthermore, relative to the application of other intelligent algorithms, the method is simple in structure, stable in performance, and good in modifiability and expandability.

The invention provides an expansive soil direct shear test device and a shear strength measurement method. The device comprises a strain type direct shear instrument and a loading plate, wherein the loading plate is provided with a limiting structure and a pressure sensor; a larger overlying load is applied before a sample is soaked in water, the limiting structure controls the bottom surface of the loading plate to be contacted with the top surface of porous stone at the upper part of the sample, and the sample is not affected by the overlying load. The measurement method comprises steps as follows: static-pressure sample preparation is carried out according to geotechnical test rules of roads, the sample is soaked in water in constant volume, vertical expansive force is measured, a direct shear test is performed with the vertical expansive force as the overlying load, and effective cohesion and effective internal friction angle of experimental expansive soil are obtained. The test device and the method have the advantages of being simple, convenient to operate, reasonable in structure and economical and guarantee consistent micro-structure before sample shear under the action ofdifferent overlying loads in the direct shear test, so that the problem that shear strength parameters of expansive soil cannot be accurately obtained for a long time in the field is solved, and accurate design parameters are provided for civil engineering structure design of the expansive soil.

The invention relates to a laser scanner used curve rotating mirror which uses gear sharp to displace the regular polyhedron sharp and uses special curve reflector to displace the flat mirror of rotating mirror-oscillating mirror system to achieve the sense scan of the laser beam with even scan speed.

The invention discloses an industrial fault diagnosis method based on an improved KPCA (kernel principal component analysis) and hidden Markov model and belongs to the technical field of industrial process monitoring and diagnosing. Calculation efficiency of KPCA under the condition of large samples is greatly improved by a similarity analysis method, and industrial faults can be classified by means of high dynamic process time sequence modeling capability and time sequence model classifying capability of the hidden Markov model. Accordingly, compared with the existing methods of the prior art, the industrial fault diagnosis method has the advantages that complexity in calculation can be reduced, nonlinear characteristics can be more efficiently processed and nonlinear industrial fault diagnosis is high in accuracy since the nonlinear characteristics and massive data of industrial data are sufficiently considered.

The invention adopts the computer vision technology to recognize characteristics of shapes and nodes of sugarcanes for achieving growth monitoring of the sugarcanes or intelligent segmentation of sugarcane varieties containing sugarcane shoots. Firstly, sugarcane images are obtained through a digital device, S components in a hue saturation value (HSV) color space of the sugarcane images are processed through threshold segmentation and mathematical morphology filter to be used as a template, reserve images of H components are segmented by threshold and calculation to obtain a composite image, the composite image is divided into 64 column areas, characteristic index of mass center ratio, roughness ratio, white spot ratio and the like is extracted, the nodes and internode columns are classified and recognized through a support vector machine so as to obtain the relation of the nodes and positions, and the average recognition rate is 93.71%.

The invention discloses a self-disturbance rejection controller designing method capable of overcoming a gap nonlinearity. The method comprises the following steps: determining an order of which the valence needs to be reduced according to the number of pure integrators in series in an open-loop transfer function of a system control loop; and designing a corresponding order-reducing expansion state observer of which the reduced order equals the number of the pure integrators in series to cancel the effect of the backlash nonlinear element. According to the self-disturbance rejection controllerdesigning method capable of overcoming the gap nonlinearity, the control performance is greatly improved, so that the output of the system can perfectly track an expected input; no steady state errorexists, and finally, the adverse effect of an extreme ring oscillation is eliminated; the method needs no precise system model and gap model, and is not sensitive to the amplitude of the backlash nonlinearity; and with the exception of the backlash, the method can effectively compensate other nonlinear effects with similar characteristics such as a hysteresis nonlinearity characteristic caused byfrictions to eliminate a limiting ring oscillation associated therewith.

The invention adopts the computer vision technology to recognize characteristics of shapes and nodes of sugarcanes for achieving growth monitoring of the sugarcanes or intelligent segmentation of sugarcane varieties containing sugarcane shoots. Firstly, sugarcane images are obtained through a digital device, hue saturation intensity (HSI) color space conversion is performed on the sugarcane images, color characteristics and threshold segmentation of an H component and an S component are combined, reverse images are segmented by threshold and calculation to obtain a composite image, the composite image is divided into 64 column areas, finally characteristic index of H parameters, S parameters, roughness ratio, white spot ratio and the like is extracted, the nodes and internode columns are classified and recognized through a support vector machine so as to complete recognition of the nodes and positions, and average recognition rate is 94.2%.

The invention provides a self-calibration method and system of IC lock frequency, and relates to the technical field of electronics. The method comprises the following steps: periodically receiving test pulse input signals with a rated time length input by a test circuit, and counting the test pulse input signals by using a to-be-tested clock as the working clock; comparing a current counting value with a pre-stored rated counting value to calculate a frequency deviation of the to-be-tested clock; judging whether the frequency deviation is greater than a preset frequency error threshold; and selecting a corresponding frequency adjustment mode according to a judgment result to calibrate the clock frequency of the IC, wherein the frequency adjustment mode comprises fine frequency tuning and coarse frequency tuning. By adoption of the self-calibration method and system provided by the invention, the self-calibration of the IC lock frequency can be realized without requiring an external test device to carry an accurate frequency indicator or write the frequency deviation in the IC through a test communication pin, moreover, the test time can be shortened, the test efficiency and the calibration accuracy are improved, and the test cost is lowered.

The invention discloses an omnidirectional positioning buoy control method based on a fuzzy algorithm. The method comprises the following steps: acquiring position information of a buoy; calculating aflight path deviation value and generating a course instruction for eliminating the flight path deviation value by comparing the position information with planned flight path information, wherein thecourse instruction comprises a command course and a set speed obtained by taking the track deviation value as an input value and calculating through a fuzzy algorithm; acquiring the actual heading and the actual running speed of the buoy; according to the actual course, the command course, the actual running speed and the set speed, calculating a control quantity by utilizing a PID algorithm; anddriving the buoy to move to a specified position of a planned route according to the control quantity. The invention provides an omnidirectional positioning buoy control method, system and equipmentbased on the fuzzy algorithm, which can improve the correction performance of self-tuning control and improve the control precision, so an ocean buoy can quickly correct track deviation and realize accurate positioning.

The invention discloses a KPCA and thinking optimization BP neural network-fused total water consumption prediction method. The method comprises the following steps of determining a prediction factorby using a correlation coefficient method; using the kernel principal component analysis (KPCA) for carrying out dimension reduction processing on prediction factors, and solving nonlinear characteristics among data; establishing a total water consumption prediction model by using the BP neural network; and predicting the total water consumption by using the model. The first two steps of the method are data preprocessing, and the method aims to extract the useful information in the water data and eliminate the interference of the redundant information on prediction, the third step is to put the BP neural network into the prediction of the total water consumption, and optimize the weight and the threshold value of the BP neural network by adopting a thinking evolution learning algorithm atthe same time; and the last step is used for checking the model effect. According to the method, experiments are carried out in the annual open statistical water consumption data of the national statistical bureau, and results show that the water consumption total amount prediction model based on the KPCA and thinking optimization BP neural network can well predict the future water consumption total amount.

The invention provides a sterilization and disinfection solution preparing device and a mixed liquor PH value regulating and controlling method and belongs to the field of disinfection methods or devices for objects. The method comprises the steps of: firstly obtaining a pH measurement value of a hypochlorous acid solution; calculating an input signal of a fuzzy controller by using the PH measurement value; inputting the obtained input signal into the fuzzy controller; generating a dosing pump frequency signal via the fuzzy controller and controlling the pump output of a hydrochloric acid solution to keep the PH value of the hypochlorous acid solution stable within a certain range. The method uses the fuzzy controller to control the whole production process, enables the output change curve of the pH value of the hypochlorous acid solution to approach the ideal level, overcomes the defects of nonlinearity and big time delay of conventional control methods and has favorable effectiveness and robustness. With the system and the method, the workload of managing staff is reduced, the working efficiency is increased and the objectives of unattended operation, safety and reliability are truly achieved.

The invention discloses a ship host active-disturbance-rejection controller which is characterized in that a system is composed of the active-disturbance-rejection controller, an accelerator servo mechanism, a ship host mathematic model and a wind wave flow interference signal. The input end of the active-disturbance-rejection controller receives a speed setting signal which is compared with an actual speed signal, and after the signal is processed by the active-disturbance-rejection controller, the output end of the active-disturbance-rejection controller is connected with the input end of the accelerator servo mechanism and transmits an output control signal. The output end of the accelerator servo mechanism is connected with the input end of the ship host mathematic model. The output end actual speed is connected with the input end of the active-disturbance-rejection controller. The ship host active-disturbance-rejection controller overcomes the defect that the rotational speed control process of a ship host has uncertainty caused by nonlinearity, time variation and disturbance of the environment, the speed switching control process of the ship host is rapid and smooth, adjustment of an accelerator is small, and the high-precision speed can be achieved.

The invention provides a sliding mode control method and control device for the tension of a tension roll strip steel, and belongs to the field of the industrial automation. The method comprises the following steps of: step 1: modeling the tension of the tension roll strip steel; step 2: designing the sliding mode control method of the tension roll strip steel. Compared with a traditional PID control method, the sliding mode control method of the invention can effectively overcome control difficulties such as the non-linear of the tension of the tension roll strip steel, and the unknown external disturbance. The invention relates to a sliding mode control device for the tension of a tension roll strip steel. The control device selects a Siemens S7-300 series PLC (CPU model 315-2DP) as a master station, and selects a distributed I/O ET200S (CPU model IM151-7) with own CPU as a slave station. The master and slave stations communicate via the Profibus-DP fieldbus. The hardware design andthe software design of the control device are completed.

The invention provides a high-linearity and low-voltage phase interpolating circuit. The high-linearity and low-voltage phase interpolating circuit comprises a state machine, a biasing generation unit, a current-steering digital to analog converter, a voltage-current conversion module, a main multiplexer, a secondary current-steering digital to analog converter, a secondary voltage-current conversion module, a secondary multiplexer and a multiplier. The state machine is used for outputting a control code for controlling the current-steering digital to analog converter and the secondary current-steering digital to analog converter to output differential control current; the biasing generation unit is used for providing biasing current to the current-steering digital to analog converter, thesecondary current-steering digital to analog converter and the multiplier; the voltage-current conversion module and the secondary voltage-current conversion module are used for converting the differential control current to control voltage; the main multiplexer and the secondary multiplexer are controlled by the control code respectively and the control voltage is selected; the multiplier is used for outputting a phase interpolating circuit clock signal according to the control voltage and a clock signal output by a phase-locked loop. According to the high-linearity and low-voltage phase interpolating circuit provided by the invention, the linearity of the phase interpolating circuit can be improved and the non-linearity introduced by high-order harmonic waves is eliminated.

The embodiment of the invention provides a tobacco leaf shredding charging precision control method and system. The method comprises the following steps of S1, inputting a charging precision error parameter and a charging precision error change rate parameter in a tobacco leaf shredding charging process into a preset fuzzy controller, and outputting a proportional coefficient of a PID controller by the preset fuzzy controller; and S2, based on the proportional coefficient, constructing the PID controller so as to control the charging accuracy during a tobacco leaf shredding charging process. By using the tobacco leaf shredding charging precision control method and system, the method of combining the PID controller and fuzzy control is used to control a charging accuracy error, and a proportional value Kp of the PID controller is dynamically adjusted through the fuzzy control so that for the different charging accuracy errors, different charging additional speeds are obtained. And thenthe charging precision error is reasonably improved so that a charging amount accords with a requirement in a tobacco leaf shredding process.

The invention provides a near-infrared model online update method based on local weighted Lasso, which belongs to the field of near-infrared on-line detection. The method is divided into four parts: historical data acquisition and preprocessing, acquisition of similarity measurement matrix, establishing of a local Lasso model and acquisition of a query sample prediction value. The method proposesthe update method based on local weighted Lasso, and a JITL method can overcome the nonlinearity of an industrial process, the generalization performance of the algorithm can be enhanced, variable selection and regression can be simultaneously carried out, the amount of calculation is reduced, the accuracy and predictability of the model can be improved, and promotion of a near-infrared on-line analysis and detection technology can be realized.