67results about How to "Reduce output error" patented technology

The invention discloses a method for quality inspection of active fault and diagnosis of intelligent fault of an engine, which corresponds the symptom of the fault with corresponding frequency for quality inspection of the active fault when the engine is not disassembled. The method specifically comprises the steps of: sequentially loading signals with different frequencies from low frequency to high frequency by a vibrating device to an engine system according to the principle of a relationship between the frequencies and the fault; resonating by the signals with the same frequency; determining the symptom of the fault generated by the signals at the frequency or frequency band; collecting corresponding fault information; extracting the eigenvector of the fault for the collected fault information by a wavelet analysis method as an input eigenvector of inheriting and optimizing wavelet neural network input nodes; and obtaining a network training sample to diagnose on-line measured data. A study sample of the invention has the advantages of easy acquirement, strong pertinence, high accuracy, low cost and the like. An optimized network has the characteristics of good nonlinear mapping and high convergence speed, and can effectively diagnose the fault of the engine.

The invention provides an active power control method in a wind power plant. The active power control method in the wind power plant comprises the steps of computing the active power prediction errors of all predicted points in the wind power plant, establishing a wind power plant active power prediction error distribution function, establishing a wind power plant active power prediction error distribution module, a wind power plant active power prediction confidence degree module and a wind power plant active power control module in sequence, optimizing the wind power plant active power control module, obtaining an optimization confidence weight of all unit sets, and controlling the active power of the wind power plant. The active power control method in the wind power plant is based on historical data analysis. By means of the active power control method in the wind power plant, the power-outputting error of the wind power plant is reduced, the reliability and accuracy of the wind power plant are guaranteed, and a powerful guarantee is supplied to the wind power plant in the grid-connected operation.

An improved system and method of performing capacitance measurements that provides a fast digital response and a reduced output error. The capacitance measurement system includes a circuit configuration that has a variable capacitor and at least one reference capacitor connected to one another at a common node, which in turn is connected to the input of an analog-to-digital converter. The circuit configuration further includes an array of switches coupled between the variable and reference capacitors and the supply voltage, a reference voltage, and ground, respectively, The switched variable and reference capacitors are employed in conjunction with the A-to-D converter to perform, at the common node, a plurality of voltage measurements for use in generating an expression defining the capacitance of the variable capacitor, The generated expression of variable capacitance is independent of a number of specified output error sources including but not limited to a sample-and-hold capacitance, the parasitic capacitance at the input of the A-to-D converter, a sample-and-hold offset voltage, and the leakage current at the input of the A-to-D converter.

The invention relates to the field of GPS signal tracking in a highly dynamic environment and specifically relates to a vector tracking method for performing comprehensive processing on the medium-frequency signals of various channels of a receiver by use of a centralized filter in such a manner of a frequency locked loop assisted phase locked loop instead of a traditional single tracking loop. The vector tracking method comprises (1) frequency mixing, (2) correlator and discriminator outputting, (3) centralized filtering, and (4) vector tracking based on a carrier frequency assisted phase. The FLL assisted PLL manner is adopted in each tracking channel of the receiver to reduce the output error of the discriminator; comprehensive processing is performed on the measured value information in the various tracking channels by use of the centralized filter; the speed error at the moment K+1 is output by the filter and converted to obtain a carrier frequency corrected value and a code frequency corrected value at the moment K+1; next, the carrier frequency corrected value and the code frequency corrected value are fed back to a carrier voltage-controlled oscillator to regulate local multiple carrier signals.

The invention discloses a ship course controller based on a fuzzy PID algorithm. The controller includes: an input unit for obtaining an ideal rudder angle deflection according to the rudder deflection angle required by the ship and the output of a stepping motor drive unit; The digital conversion unit is used for digital-to-analog conversion and analog-to-digital conversion; the fuzzy parameter correction unit is used to perform fuzzy parameter correction according to the output of the stepper motor drive unit and the ideal rudder angle deflection; the PID adjustment unit is used to correct the fuzzy parameter according to the fuzzy parameter correction unit and The output of the stepper motor drive unit is adjusted by PID; the PWM signal output unit is used to output the PWM waveform for controlling the work of the stepper motor according to the output of the PID adjustment unit; the stepper motor drive unit is used to drive the stepper motor to control the course of the ship , and feed back the position, speed and rudder angle of the ship in real time. The invention aims at adopting the fuzzy PID control algorithm to realize the self-adaptive control of the ship steering gear.

The invention provides a mine dust concentration measuring device which comprises a sensitive element, a control circuit module and an upper computer. The sensitive element comprises inductive type metal electrodes, the control circuit module comprises a measuring circuit, a signal conditioning circuit, an A/D switching circuit and a microprocessor, the sensitive element generates micro electric charge signals on the metal electrodes, the micro electric charge signals are processed through the measuring circuit, the signal conditioning circuit, the A/D switching circuit and the microprocessor in real time and then are transmitted to the upper computer, and the upper computer carries out information preprocessing and feature extraction, sets up a soft measurement model, and then outputs dust concentration measuring signals. The invention further provides a dust concentration measuring method. The mine dust concentration measuring device and the measuring method thereof have the advantages that the defects that measuring errors are large, influences of humidity are obvious, the service life is short and maintenance is inconvenient in an existing mine dust concentration measuring method are overcome effectively, accurate measurement data for coal mine improvement are provided, the borehole operation environment is improved, and the physical health of workers and the safety production of coal mines are protected.

The invention discloses a local voice recognition method based on a BP neural network. The method comprises the following steps that (1) a user inputs voice, command set mapping pairs of operation and voice are set up, and a BP neural network model is obtained; (2) the user inputs voice, forward-propagation is carried out on voice feature parameters input by the user through the BP neural network, an actual output value of a neural network and all expectation values are compared, if one error value is smaller than a preset error value, the step (3) is executed, if all error values are larger than a preset error value X, the step (4) is executed to obtain the name of a neural network output application program, and the application program is started; (4) the error values are subjected to back propagation to be used as input of the BP neural network to correct weights unit one error value is smaller than X; if conditions are stopped, no error value is smaller than X, the training is over. The local voice recognition method has the advantages that the requirement for database memory space is low, the voice recognition speed is high, and accuracy is high.

A four-channel atmospheric polarization information testing sensor signal processing and compensating method, characterized in utilizing a method of step by-step signal processing, comprises: performing step by-step processing to real-time dynamic testing data from the four-channel atmospheric polarization information testing sensor, in the step by-step processing process, through two classifying compensation method of hard compensation and soft compensation, performing signal compensation and matching to error and noise of sensor step by-step signal, so as to obtain effective coherence compensation and suspension to drift error component and amplitude error of each channel signal of the sensor caused by different signal response and transmission characteristics of each channel step by-step physical device, and the random noise caused by the physical noise and environment optical noise of the sensor, therefore effective sensor output is obtained. Through performing atmospheric polarization mode information processing to the obtained digital electric signal, therefore the accurate, reliable atmospheric polarization mode information is obtained.

The invention relates to a low-offset and fast-response voltage-controlled current source. In the voltage-controlled current source which is realized by adopting an operational amplifier, an input offset voltage which is larger relative to an input reference voltage is reduced to an acceptable range through use of an automatic zeroing method, and the output error of the voltage-controlled current source is reduced. The slew rate of the operational amplifier is improved by adding a sampling hold circuit so as to realize the fast response of a circuit. The low-offset and fast-response voltage-controlled current source is especially suitable for applications, such as an LED driving circuit, requiring fast response. In addition, the input offset is reduced by adopting the automatic zeroing method, the low input offset of the voltage-controlled current source can be realized by adopting a standard CMOS (Complementary Metal Oxide Semiconducotr) process, the change of the input offset along with the changes of temperature, time, illumination and irradiation is unnecessarily considered, and the requirement on layout matching is lower, therefore the production cost and time are reduced.

The present invention provides a sample and hold circuit and a serial DAC with high precision output. Even the capacitance value of the capacitor for executing charge allocation is low, the output error caused by the input capacitance (grid capacitance) of an amplifier is lower. The sample and hold circuit comprises the following components: capacitance elements (C11,C12) for allocating charges through a switch (110); a differential circuit; an amplifying grade (16) which is input with the output of the differential circuit and has an output connected with the output terminal (N9); and a sampling voltage supply circuit (17) which provides a sampling voltage to one end of at least one element selected from the capacitance elements (C11,C12). The differential circuit comprises the followingcomponents: a MOS transistor (M1); a MOS transistor (M2); and a load circuit (15) which is connected between the drains of the first and second MOS transistors (M1,M2) and a terminal of a second power supply.

The invention discloses a control method for a hysteresis nonlinear robot system, and belongs to the field of robot system control. A hysteresis nonlinear robot with P-I (Prandtl-Ishlinskii) is selected as a research object to measure system parameters of the robot and joint position information and joint velocity information of the robot, a performance function is introduced to convert a constraint tracking control problem of an original robot to an unconstrained stabilization problem, and unknown parameters in the hysteresis nonlinearity are regulated by employing adaptive control to designan adaptive predetermined performance backstepping control strategy. The control method for the hysteresis nonlinear robot system optimizes the transient performance of the system, improves the convergence rate, ensures the steady state performance of the system, and improves the control precision; and moreover, the adaptive parameter regulation law is employed to estimate the unknown parameters in the hysteresis nonlinearity so as to effectively solve the problems of the system oscillating and system instability caused by hysteresis nonlinearity and improve the working performances of the system.

The invention discloses an intelligent programmable-control microcurrent measurement display system, which is characterized by comprising a computer control module, a display module, a communication module, an A/D (analog/digital) conversion module, a microcurrent measurement system programmable control module, a programmable-control current signal amplifying module and a programmable-control filter module. Microcurrent signals to be measured are input to the programmable-control current signal amplifying module, are amplified and then converted into voltage signals, the voltage signals are input to the programmable-control filter module so as to be filtered, the filtered signals are input to the display module through the A/D conversion module and the communication module so as to be displayed, the programmable-control current signal amplifying module, the programmable-control filter module and the A/D conversion module are controlled by the microcurrent measurement system programmable control module, and the computer control module controls the microcurrent measurement system programmable control module through the communication module. The intelligent programmable microcurrent measurement display system is low in manufacturing cost, higher in adaptability and lowered in price resistance to scientific research.

The invention relates to a decoupling control method of an airborne LiDAR attitude angle compensation device. In order to compensate effects on airborne laser radar measurement point cloud imposed byhelicopter-borne platform attitude angle change, an attitude angle compensation device is designed. The device is a tri-axle turntable, and there is control coupling, so a decoupling control method isprovided. The method comprises steps of firstly, establishing a mathematical model of an attitude angle compensation device dynamic system and proving the reversibility of the attitude angle compensation device dynamic system; then, establishing a neural network inverse system model of the attitude angle compensation device dynamic system, acquiring neural network learning data and carrying out offline training on the neural network; then, comparing output of the neural network inverse system with an expected input value, and sending the differential value into a feedforward controller to beused for correcting a control voltage signal of the attitude angle compensation device dynamic system; and finally, by combining a fuzzy-PID controller of a closed-loop feedback loop, forming a feedforward-feedback composite controller. Thus, real-time decoupling of the attitude angle compensation device dynamic system is achieved, control precision and anti-interference are improved and dynamic control performance is improved.

The invention discloses a phase angle amplitude PID adaptive method based on three-dimensional magnetic characteristic measurement of BP neural network. In the process of signal processing, adopting afrequency domain approach, compared with the time domain method, the harmonics are decomposed into frequency domain, the amplitude and phase angles are independently closed-loop controlled, as the amplitude is traversed to minimize the error between the output voltage and the desired voltage, then the phase angle is found to minimize the output error, PID can quickly find the appropriate amplitude and phase angle, so that the output waveform vector in three directions is a standard spherical or ellipsoidal after synthesis, so that the actual waveform can quickly and accurately approximate thedesired waveform. When the excitation frequency and amplitude change, the weights of the hidden layer and the output layer of the neural network change correspondingly, so that the PID parameters canbe adaptively changed with the feedback adjustment process of the waveform, so that the rapidity and accuracy of the magnetic measurement process are greatly improved, and the response time is greatly reduced.

The invention discloses a satellite communication in motion attitude detection device and method. The device comprises satellite communication in motion, a microprocessor, an attitude detection moduleand a complementary filter, the attitude detection module comprises an X-axis attitude detection module, a Y-axis attitude detection module and a Z-axis attitude detection module; the method comprises the following steps of three-axis coordinate system building and attitude detection module layout, real-time information collection and uploading, satellite communication in motion three-axis weighted fusion angular velocity value obtaining, satellite communication in motion attitude angle obtaining and satellite communication in motion attitude angle correction. Accordingly, design is reasonable, by means of fusion of multiple micromechanical gyroscope homologous sensors and fusion of micromechanical gyroscope and accelerometer heterogenous sensors, the satellite communication in motion attitude can be accurately obtained, the cost is low, the reliability is high, the precision is high, and the practicability is high.

The invention discloses a radar pitching motion control method based on prediction RBF feedforward compensation type fuzzy PID, and aims at a two-dimensional laser radar to three-dimensional laser scanning system to control the swinging or pitching motion of a two-dimensional laser radar. Firstly, a PID algorithm with feedforward compensation is adopted to eliminate nonlinear factors in a radar pitching motion system; PID parameters are set in a fuzzy self-adaptive mode, then for unknown parts in nonlinear factors, the unknown parts are fitted through the universal approximation characteristicof a radial basis function neural network (RBF), and on the basis, generalized predictive control based on a state equation is adopted to optimize the control system in a rolling mode so as to further reduce the output error of the system. According to the control method provided by the invention, the steady-state error, the response time and the adjustment time of the system can be reduced, so that the control method can effectively control the pitching motion of the two-dimensional laser radar.

The invention discloses a radar speed measurement AI algorithm. The radar speed measurement AI algorithm comprises six steps, namely, data acquisition, feature data extraction, data preprocessing, flow model establishment, flow model optimization and flow data output. The flow data output after the liquid level speed actually measured by the radar is optimized and calculated through the flow model, errors caused by liquid level fluctuation and signal strength influences are reduced, and the accuracy of the flow data output by a radar tachymeter is improved. Meanwhile, the established evaluation model can further evaluate the accuracy of the output flow data, in the process of repeatedly resolving and evaluating the flow data, the accuracy of the flow data of the radar tachymeter can be gradually improved, and flow metering data with small errors can be output.

The invention discloses an intelligent granary management and control method based on machine learning and a terminal. The method comprises steps of obtaining a to-be-predicted input factor of the intelligent granary, sending the to-be-predicted input factor to a granary analysis decision model to obtain a personnel scheduling strategy, the granary analysis decision model comprising a feedforwardmodel established by using a multi-layer feedforward neural network trained by an error back propagation algorithm, and the personnel scheduling strategy comprising sampling inspection personnel, sampling inspection objects and sampling inspection time. According to the invention, the historical data is learned to obtain the granary analysis decision model, and the output error of the network is continuously reduced by adopting the feedforward model established by the multi-layer feedforward neural network trained by the error back propagation algorithm, so that a finer prediction and traceability result is presented; the optimal manual scheduling strategy is found on the basis of the model, so that an intuitive, clear and effective means is provided for personnel allocation for grain management of government grain departments and storage enterprises, and optimal manual scheduling is realized.

The invention relates to a method and a device for controlling pulse width modulation (PWM) duty cycle. The method comprises the following steps that (1) a data separator automatically separates input data into an integral part and a decimal part according to the judging result that the input data is a floating-point number or a fixed-point decimal; (2) a numerical integrator accumulates and integrates the decimal part separated by the data separator, wherein after being spilled, the integral part which is greater than 1 is input into an adder and is added to the integral part output by the data separator, and the remainder part is continuously left in an integral accumulator for accumulation in the next period; (3) in the current period, the adder outputs the accumulated integral part into a PWM duty cycle generator, and the PWM duty cycle generator adjusts the duty cycle of a PWM waveform according to the data. Compared with the prior art, the method and the device have the advantages that the output precision of a PWM executer can be improved, the cost is reduced, the stability of a control system can be more quickly realized, fluctuation is reduced, steady-state errors are reduced, the quality of the control system is improved, and the like.

The invention discloses a rolling mill main transmission system output feedback control method considering input limitation. The method comprises the following steps that S1, establishing a kinetic model of a rolling mill main transmission system; S2, designing a high-gain extended state observer, and obtaining estimated values of a system state and total disturbance; S3, introducing a performancefunction, and constraining transient and steady-state performances of a rolling mill rotating speed tracking error; and S4, according to the estimated values of the system state and the total disturbance obtained in the step S2, formulating an output feedback control strategy for the rolling mill main transmission system constrained by the performance function, and under the condition that inputis limited, converging the roller rotating speed tracking error into a preset area. According to the method, the transient performance of the system can be optimized, the convergence rate can be increased, the steady-state performance of the system can be guaranteed, the control precision can be improved, through the design of an observer, interference accurate estimation and compensation under the output feedback meaning are achieved, and the robustness of the whole system is improved.

An apparatus includes a sensor body (206), a sensor (204) configured to measure differential pressure, and first and second pressure inputs in or on the sensor body. The pressure inputs are configuredto provide multiple input pressures to the sensor. Each pressure input includes a barrier diaphragm (208, 210) configured to move in response to pressure and an overload diaphragm (216, 218) configured to limit movement of the barrier diaphragm. The overload diaphragm is also configured to exert a preload force against the sensor body. The overload diaphragm of each pressure input may include multiple convolutions. Bases (502) of the convolutions may be configured to provide the preload force, and tops of the convolutions may be separated from the sensor body by gaps (504). Tops (602) of theconvolutions that are non-adjacent may be configured to provide the preload force, and tops of the convolutions between the non-adjacent convolutions may be separated from the sensor body by gaps (604).