In order to align two probes of dual-probe atomic force microscope (AFM), it is necessary to establish a measuring head to do in-depth research on the probe A scanning the probe B. Firstly, the mechanical characteristics of the probe are obtained by finite element (FE) simulations. Secondly, using the locked-in amplifier to attain the amplitude and frequency signals to analyze the system resolution (better than 1nm), the probe is rotated 90 degrees compared traditional AFM. Lastly, probe B is scanned by probe A in YOZ plane, reducing the scanning range and scanning step gradually. The alignment accuracy is of 5 nm.

A stereo matching algorithm based on deformable convolution is proposed to perform 3D reconstruction of binocular vision.Firstly, the two-dimensional deformable convolution is used to extract the features of the left and right input images.Secondly, the three-dimensional deformable convolution is used to effectively aggregate the relevant features between the two images in the matching cost volume.Finally, a three-stage cascade residual learning method is used to reduce the parameter calculation amount of the matching cost volume, which can meet the real-time requirements of fast matching.According to the principle of the algorithm, the detection of the disparity depth map is completed, and the three-dimensional object is reconstructed through Open3D.The experimental results show that the parameter amount of the algorithm is 0.5×10⁶, the running time is only 0.02s, the generated disparity map has high precision, and the reconstructed 3D effect is good.

Aiming at the difficulties in modeling the element concentration caused by the overlapping peaks of Pb and As in X-ray fluorescence spectroscopy (XRF) and the weak robustness of the crow search algorithm (CSA), the Gaussian mixture model (GMM) is combined with the improved the crow search algorithm (ICSA) to achieve the decomposition of overlapping peaks. Compared with CSA, ICSA has three main improvements: the introduction of the “crow feeding” feature to better connect GMM and ICSA; the fixed probability of awareness is changed to a gradient type to make the population iteration more diverse; appropriate adjustments the global optimization strategy makes the algorithm more stable and converges faster. The comparison experiment between the GMM model and the GMM-ICSA model shows that the decomposition accuracy of the optimized model is increased by 4.93%. At the same time, the mean square error and iteration time are used to measure the quality of the search algorithm, and ICSA is compared with the same type comparative experiments on the four algorithms show that the mean square error and iteration time of ICSA are better than other algorithms, which shows the feasibility of the improved algorithm in dealing with the problem of overlapping peaks.

Motor imagery has been widely used in EEG based brain-computer interface systems. In order to extract feature of the motor imagery EEG accurately and efficiently, the feature of the motor imagery EEG in time, frequency and spatial domain is analysed. Then an approach is put forward that extract feature of the motor imagery EEG from time, frequency and spatial domain, with preprocessing of wavelet transforming and using spatial filter obtained from SOBI and ITFE. Experimental results verify that the proposed method has an obvious improvement in feature extraction compared with the other methods, and the spatial filter obtained from SOBI and ITFE can reflect veridical brains activity.

To capture the characteristics of dynamic temporal-spatial correlation hidden in monitoring data of wind turbine gearbox, a fault prediction method based on long short-term memory (LSTM) network is proposed. The proposed approach mainly consists of two phases: offline training and online detection. First, the oil temperature of the gearbox is taken as the modeling variable and the LSTM-based normal behavior model of wind turbine gearbox oil is built based on historical monitoring data training and learning, which fully takes advantages of the important correlated information between the oil temperature and some relevant input variables. Then, the model residuals are calculated and evaluated to determine the corresponding detection threshold. Furthermore, the well-trained LSTM model is used for online testing.Through model residual analysis and threshold comparison, fault detection and prediction of wind turbine gearbox can be realized.A real motoring data from a wind farm is used to validate the effectiveness of the proposed method. The results show that compared with those traditional methods, the proposed method presents better prediction performance, and can predict the occurrence of gearbox failure earlier.

A new permanent magnet angular acceleration sensor based on the principle of electromagnetic induction is described, and its mechanical structure and principle are introduced.A new method of calibration angular acceleration sensor based on mechanical torsion pendulum institutions is put forward and proved.The experiments show that the calibration method works well and it can objectively reflect the relationship between the un-voltage input and voltage output of the sensor, and can ensure the accuracy of the result. The experiment proves the feasibility of the permanent magnet angular acceleration sensor and its calibration method, and the sensitivity of sensor is about 6.562 μV/(rad·s^-2).

A multi-decade 1000V inductive voltage divider (IVD) was established at the National Institute of Metrology (NIM) in China to function as the 1000V voltage ratio standard at the power frequency. It can provide a wide output ratio ranging from 1×10^-8 to 1. An error compensation method, based on the transformer injection, was introduced to improve the output ratio accuracy. An improved bootstrap calibration method with triaxial shielding was presented, and a multi-ratio reference transformer was designed to calibrate the multi-decade IVD for combinational usage. The accuracy of the mentioned IVD is better than 1×10^-7 and the calibration expanded uncertainty less than 2×10^-8.

For overcoming the limitation of the present water colority measurement method and meeting the requirement of measuring the water colority automatically, a  measuring method of the water colority by color difference value is proposed. The relationship between color difference value and water colority value has been established by experiments, and the water colority value can be obtained based on the color difference value which calculated by measuring the spectral transmittance of water sample. Based on the proposed method, the calibrated system no longer needed the standard solutions during measurement and can be applied to measure any color of water sample. The measurements of natural water show that the measuring results are not only conforming to the measuring results by national standard method, but also higher sensitivity and better repetitiveness.

According to the Non-orthogonal total station system principle, the main sources of the system measurement error are the rotation angle errors of rotary tables and the distance measurement error of the laser range finder. Using GUM algorithm, the uncertainties of these two sources are estimated and the system measurement uncertainty is evaluated. The result is validated by the simulation on MATLAB and the experiment conducted in the laboratory. The results show that when the distance is constant, the measurement uncertainty is almost independent of the horizontal angle, and increases with the absolute value of the vertical angle. When the angle value is constant, the measurement uncertainty increases with the distance from the measured point and the calibration point on the collimated axis.The accuracy of the simulation results is preliminarily verified by experiments.

A geometry dimension measurement method for special-shaped forgings is proposed.The measuring system composed of a green line laser,a CCD camera and a servo system is established.Two dimension information of the laser stripe modulated by the forgings surface profile is extracted from the images.And further the size of the forgings is acquired through the reconstruction of point cloud after coordinate transformation.Aiming at the morphology feature of the special-shaped forgings,a math measuring model based on the CCD scanning is established and a solving method of the optical center motion trail is proposed based on the chessboard reference plane target.The optical center motion trail is solved by using the feature point coordinate of the reference plane on the different frames.The overall profile dimension is achieved according to the optical center motion trail and the math scanning measuring model.The experimental results of the spherical shell cover demonstrate that the measured diameter errors of spherical crown portion are less than 4 mm,meeting the requirement for the accurate measurement of the hot forgings.This method is feasible according to the experimental results.

GUM Sup.1 is concerned with the propagation of distribution through a mathematical model of measurement as a basis for evaluation of uncertainty of measurement. It introduced the principles and the detail processes of Adaptive Monte Carlo method to carry out the propagation of distribution. Then two measurement models were provided, including linear model and non-linear model, to validate the applicative of Adaptive Monte Carlo method. And it proved that both models reached the reasonable evaluation results. At the same time, some problems such as how to choose proper Monte Carlo simulation sample M and numerical tolerance δ were still need to be further researched.

Urbanization has concentrated over 50% of the global population and more than 70% of the carbon emissions. Uncertainties in carbon emissions are very large or unknown at the spatial scale of individual cities, and 50% to 100% errors are not uncommon. The temporal and spatial distribution of greenhouse gas concentration is introduced, and the basic idea of carbon emission inversion model is described. Current NIST funded studies in several cities using top-down approach to estimate carbon emissions. Based on measurement of greenhouse gas concentration and accurate dispersion models that can operate at the city scale, carbon emissions in urban area can be estimated by inversion method. NIST researches are summarized and future works in this field by NIM of China are in plan.

Due to the single feature extraction has not exert information as well as different features have different importance while recognizing UAV composite materials flaws, a method for multi-feature extraction in wavelet packet field and time-field is proposed. The new approach firstly decomposes signal with wavelet packet to get feature, using principal component analysis to decrease the dimension of feature vectors, then, extracts time-field feature considering composite materials characters. at last, the combined feature vectors algorithm is proposed using the matching method. The experimental results indicate the effectiveness of the proposed feature vectors while classifying the bond flaws in composite materials.

Semantic segmentation of indoor scenes has always been an important direction in the field of deep learning semantic segmentation. The main problems of indoor scene segmentation are many semantic categories, many object classes will block each other, and some classes have high similarity. Aiming at these problems, Proposed a method for semantic segmentation of indoor scenes which is based on the BiSeNet (bilateral segmentation network), this method introduces a hollow pyramid pooling layer and a multi-scale feature fusion module. The features are fused to obtain enhanced content features, which improves the models performance for semantic segmentation of indoor scenes. The MIoU performance of this method on the indoor scene dataset in ADE20K increased by 23.5% compared toSegNet and 3.5% compared to before model.

Aiming at the non-uniform sampling series, a four-parameter sine wave curve-fit method is introduced. It is based on the three-parameter sine wave curve-fit method with frequency known. It can attain the four-parameter of sinusoidal curve-fit results with both the uniform sampling series and the non-uniform sampling series. The speciality of the arithmetic is that it turns the optimization of four parameters (amplitude, frequency, phase and offset) into the optimization of one parameter (only frequency) , and without any original parameter estimation. The method has excellent convergence， good robustness, and clearly convergence interval. The validity and feasibility are proved by both simulation and experiments, this method can be applied to the four-parameter sine wave curve-fit with non-uniform sampling series.

In order to research the rule of tissue temperature rise under the action of high-intensity focused ultrasound (HIFU), a finite element simulation model of high-intensity focused acoustic field and tissue temperature field is established, and the simulation model is verified by in vitro irradiation experiments. The focused acoustic field in the water and tissue domain is modeled by simulation, and the absorbed acoustic energy is calculated and used as a heat source to calculate the temperature rise within the tissue. By preparing a biological tissue gel phantom, thermocouples are used to measure the temperature at the focal point of the phantom tissue under the action of HIFU. The results show that the model can effectively predict the temperature rise during HIFU treatment, and the difference between the temperature obtained in the experiment is not more than 3℃; the temperature of the phantom tissue will rise immediately when the phantom tissue is irradiated by ultrasound, and the temperature rise rate is faster at first, as the time increases, the temperature rise rate gradually decreases, and the temperature drops immediately after the irradiation is stopped.

To study the insufficient effect of accelerated life test of ternary lithium battery, an accelerated life model based on Arrhenius model with ambient temperature as a single acceleration factor is established. The accelerated life model is based on the empirical model of battery life decline under the coupling of ambient temperature-discharge rate. The expermental results show that the acceleration effect is limited when the ambient temperature is a single factor. Compared with temperature and discharge rate at 25℃ and 1C, the average number of cycles is shortened by 290 times at 50℃ and 1C, 510 times at 50℃ and 3C, and 710 times at 50℃ and 5C. The coupling of temperature and discharge rate can effectively shorten the times of charge and discharge compared with a single ambient temperature. The coupled accelerated life model is used to infer the battery life characteristics under low or normal level conditions through high-level factors.

A 200kW/180MJ flywheel energy storage system is designed to solve the problem of large load fluctuation of the power grid system. The finite element method is used to model and simulate the flywheel shafting, and the critical speed and vibration mode of the flywheel rotor are calculated, and the modal and harmonic responses of the flywheel rotor supported by mechanical bearings are analyzed. The full cycle detection of the flywheel speed rise and fall is carried out, the amplitude-frequency characteristics of the flywheel running process are recorded, and the amplitude-frequency characteristics of the flywheel are compared and analyzed. The flywheel energy storage system is running well without friction. The oscillation amplitude’s maximum analysis result is 1.6mm less than the designed gap of 3mm.

A circular path is produced by measuring stylus rotating with the lever axle, and the horizontal deviation affects the accuracy of surface profile measurements. Based on the improvement of traditional measuring rod, the mathematical model of non-linear measurement error and the compensation algorithm of polynomial fitting error are derived. The method of calculating error compensation parameters by fitting a standard ball is proposed. For a spherical cap of 79.505 3 mm radius, experimental results shown that the size of the radius error is less than 1 μm, the effect of the compensation is better.

To reduce the microwave leakage-induced uncertainty, a Mach-Zehnder interferometric switch was applied in the interrogation microwave synthesizer of NIM5 Cesium fountain clock. The interferometric switch may introduce the phase transient. Meanwhile, other microwave and electronic parts in fountain clock may also introduce phase transient. The phase transient induces frequency shift and uncertainty. To evaluate the frequency shift and uncertainty, the phase transient Realtime measurement was taken on interrogation microwave synthesizer by home made triggered phase transient analyzer. The seven days continuous measurement result shows that the frequency shift and uncertainty are in 10^-16 level, and 100Hz periodic phase transient are found. The periodic phase transient may come from the interrogation microwave synthesizer, which need be researched and improved further.

The primary heat capacity standard for medium temperature is employed for the traceability of the specific heat capacity, phase transition temperature and enthalpy. The device mainly adopts the adiabatic calorimetric method, which makes the calorific value traceable to SI units. Firstly, the research significance and the principle of primary heat capacity standard is introduced, and then the progress on the research in the field is demonstrated. Finally new design and scheme of primary heat capacity standard based on this work are put forward.

In order to better serve environmental radiation monitoring, the planer HPGe spectrometer is calibrated by standard radioactive point sources 241Am, 133Ba, 60Co, 137Cs, 152Eu. And the detection efficiency, half height full width, channel address and other data under different energy are obtained respectively. After data processing, the function of energy-channel, function of FWHM-energy scale, relationship of energy and detection efficiency are obtained. At the same time, the energy resolution is 1.58keV (60Co, 1.33Mev). It is found that the MC model established by CT technology is more reliable and efficient. At the same time, the detection efficiency of the model is corrected by the upper dead layer and the bottom dead layer thickness in turn, and the relative error of the overall detection efficiency is within 5%, which is in good agreement with the actual experimental results.

A jellyfish detection algorithm based on improved Faster R-CNN is proposed. Firstly, a data set containing 7 species of jellyfishes is established. Secondly, on the premise of ensuring the accuracy, the number of branches C is set to 8 to solve the problem that ResNeXt (C=32) has a high amount of calculation for target detection. Finally, to solve the problems of low detection accuracy and small individuals unable to be recognized, expansion convolution is introduced into the residual network. The experimental results shown that compared with VGG16, ResNet101, ResNeXt (C=32) and ResNeXt (C=8), the mAP value of the proposed algorithm increase by 3.15%, 2.09%, 3.01% and 2.36%. F1-score increase by 2.53%, 1.99%, 2.01% and 2.31%. Loss function convergence value of the proposed algorithm approach to 0. Results of P-R curve, visual analysis and video detection show that the accuracy and detection number of jellyfish by the proposed algorithm is the best, the proposed algorithm has high detection accuracy and can meet the requirements of real-time monitoring.

To accurately measure large size poses, a large size pose measurement device consisting of 7 laser tracking interferometers is established. According to the difference in the number of laser tracking interferometers measuring each mirror, the effects of two tracking methods, 322 and 331, on the accuracy of pose measurement are simulated. Therefore, it is found that the position of the measured point is related to the distance of the base station plane. The error model between the relative position between the measured point coordinate value and the measurement base station and the measurement error is derived from the coordinate solution formula. By analyzing the sensitivity of errors in the directions of x, y, and z to distance changes, it is found that errors caused by distance changes in the z direction are the most sensitive. When the distance between the measured point and the measurement base station is reduced from 1300.8mm to 0mm, the measurement error increases from 2.2μm to 2626.1μm. The actual attitude measurement experiment results show when a tracking method is adopted, the measured point can be avoided from being too close to the plane of the station, which is helpful to improve the measurement accuracy of the system.

In order to improve the segmentation accuracy of the 3D point cloud model in the feature fuzzy region, a segmentation method based on multi-view region growing was proposed.Based on the principle of direction difference of normal vectors of grids, the model was divided into different categories of sub-regions.Then the one-to-one mapping relationships between point cloud and multi-view distance images were established in the corresponding regions.The sensitivity of Canny operator for gray level was used to obtain independent connected domains and their barycentric coordinates were calculated. The corresponding points were extracted as seed points in 3D point cloud.To separate the adjacent surfaces, the offset angle of normal vectors of grids was introduced.At the same time, the remaining independent surfaces were extracted according to the principle of iterative nearest points.To achieve segmentation optimization, KNN algorithm was used to remove the off-group points.Experiments were carried out on the selected model data set.The results showed that the complicated point cloud model could be divided reasonably by the proposed method, and the segmentation accuracy was not less than 80%.

In order to solve the problem that SO₂ fluorescence signals was faint and always cannot be distinguished with noises, a novel method based on wavelet optimization ensemble empirical mode decomposition (EEMD) was proposed. The SO2 detection system had been built. Using the SO₂ detection system, SO₂ concentration can be detected. The average error of detection was 0.0011, and the correlation coefficients between SO₂ concentration and the fluorescence intensity was 0.9787. Wavelet optimization EEMD denoising method were applied to SO₂ detection system, the results showed that the signal noise ratio(SNR) was 224.7958, the mean squared error(MSE) was 1.01×10^-7, and the normalized correlation coefficient(NCC) was 0.9973. The correlation coefficients between SO2 concentration and fluorescence intensity was 0.9936. Compared with the wavelet denoising method and EEMD denoising method, the wavelet optimization EEMD method has the best denoising effect. The proposed method is superior to wavelet denoising method and EEMD denoising method.

Gradient method, surface fitting and N-R method are 3 main sub-pixel displacement algorithms of digital speckle correlation method to improve the precision of the measuring system. The principles of three kinds of algorithm were studied and numerical simulation was carried out. To compare the different precision from 3 methods under noise, the computer models generate a series of speckle gram whose displacement is 0.01 pixels and different Gaussian noise was added in generated graphics.  The results showed that in the precision requirement in 0.01 pixels, the upper bounds on noise variance of gradient method and N-R method are respectively 0.006 and 0.000 5, and the calculation precision of surface fitting method has huge uncertainty, gradient method is more suitable for engineering application.

The positive conductive slurries prepared by different types of conductive particles for lithium batteries are studied by using nuclear magnetic resonance (NMR) technology. By measuring the relaxation time and spectrum of the slurries, it is found that the relaxation time of carbon black slurry is negatively correlated with the BET value under the same grinding dispersion condition, and the relaxation spectrum of carbon black slurry is single-peak structure, indicating that carbon black is more easily dispersed. The relaxation spectra of carbon nanotube (CNT) slurry are all multi-modal, which indicates that the dispersion of CNT is poor. Further research results show that the larger the solid content of CNT slurry, the larger the specific surface area of the particles, the larger the relaxation time of the main peak of the relaxation spectrum, the lower the proportion of the main peak signal, indicating that the CNT is more prone to entanglement and aggregation in the solvent.

A novel modeling method based on multi-branch BP neural network is proposed to describe the displacement/pressure hysteresis of pneumatic muscle. Firstly, the displacement/pressure hysteresis characteristic test system was built to obtain the displacement/pressure hysteresis loops of pneumatic muscle. Then, the classical BP neural network, multi-branch BP neural network and Prandtl-Ishlinskii model are used to fit the hysteresis loop of pneumatic muscle, respectively. Finally, the comparative study found that the multi-branch BP neural network can effectively avoid the over-fitting phenomenon in the fitting process of classical BP neural network, and the modeling capacity is obviously better than the traditional Prandtl-Ishlinskii model. Compared with Prandtl-Ishlinskii model, the mean average, mean square and maximum errors of multi-branch BP neural network are reduced by 87.45%, 86.68% and 74.73%.

A method for data analysis for thermal conductivity measurement using transient hot-wire method is present. Numerical simulation is introduced in data processing. Finite volume method is used to solve the control equations. The finial result is obtained by comparison of the simulated temperature curve with the experimental temperature curve. The presented method is very effective for experimental data analysis. The correct result could be gotten with much less data points, which is very helpful for the design of experimental system.

In order to solve the difficulty in extracting nonlinear fault features, a new feature extraction method based on multiscale entropy and distance evaluation technique is proposed.First, multiscale entropy analysis is performed to extract and characterize detail features over different scales from bearing vibration signals.Second, distance evaluation approach is employed to evaluate the extracted features and select some sensitive features as subsets.The subsets are input into support vector machines for further condition classification and fault identification.Bearing fault diagnosis experiments validate the effectiveness of the proposed method.The experimental results demonstrate that the optimal sensitive feature subsets outperformed the single scale feature, the original feature sets and other random feature subsets in diagnosis accuracy.

Aiming at the problem of fault diagnosis for rotating machinery with very low signal-to-noise ratio under strong noise background, a fault diagnosis method for rotating machinery based on AMD and stochastic resonance is proposed. If the frequency components of the signal are known, signal with different frequency components can be decomposed into single frequency signal using the AMD method, especially to decompose a signal with closely spaced frequency components. For the fault feature frequency can be predicted in rotating machinery fault diagnosis, AMD method is used to extract fault feature frequency signal in mechanical vibration signal and add low intensity noise to the signal firstly. Then, the signal with noise is put into the optimal stochastic resonance system and denoising and enhancing the signal. Finally the spectrum of the signal is obtained, if the frequency spectrum contains the fault feature frequency, it shows that the faults exist in mechanical vibration signal. Through the extraction of the rolling bearing fault signal feature proved that the method has a good effect.

Distortion can reflect the deviation between the actual image and the ideal image of a metallographic microscope, and is an important technical indicator for accurate and reliable performance of metallographic microscopes. According to the calibration standard "Evaluation and Representation of Measurement Uncertainty", the distortion measurement process of the metallographic microscope was studied, the mathematical model for the uncertainty evaluation of the distortion measurement results was established, the sources of uncertainty were comprehensively analyzed, and the uncertainty of the distortion measurement results of the metallographic microscope was evaluated.The results show that when the coverage factor k=2, the confidence level is 95%, under the condition of the total magnifications is 50×, 100×, 200×, 500× and 1000×, the relative distortion measurement results of the metallographic microscope is (0.5±0.4)%, (0.3±0.6)%, (1.3±0.4)%, (0.4±0.4)%, (0.9±0.1)%, respectively. The uncertainty of the measurement results mainly comes from the distortion measurement system and repeatability test.

To study the traceability technology of the number concentration of airborne particles in micrometer range, an inkjet aerosol generator (NIM-IJAG) is developed and its performance is verified. The particle size and number concentration of obtained solid particles by NIM-IJAG are closely related to the nozzle aperture, solute density, solution mass concentration, output parameters of electrical controller, clean air flow volume and other parameters. On the basis of accurately obtaining the droplet size, the effective control of the particle size of solid particles can be achieved by changing the solution concentration, the number concentration of solid particles could be effectively controlled by adjusting the voltage frequency applied on the nozzle. Through experimental verification, NIM-IJAG can produce 1~20μm monodisperse solid particle samples with number concentration in 0~30/cm³, which can trace to the national metrology standard.

When using the interferometer to measure the straightness of the ultra-long rail, the stitching may introduce a large error due to the length of the rail exceeding the measurement range of the interferometer, since the straightness of the whole long guide rail needs to be divided into multiple sections and then each straightness is measured separately.By analyzing the influencing factors in the splicing process, and combined with the structural characteristics of long guide rails, a new straightness splicing method for long guide rails is proposed.This method uses common points distributed on two adjacent sub-guide rails for splicing, and uses the stable characteristic of the angle between two adjacent sub-guide rails to realize straightness splicing .Through simulation and experiment, the measurement results of the direct measurement method and the coordinate transformation splicing method in the range of 30m are compared, and the difference of straightness results between the two methods is less than 10μm, which shows that the proposed method can effectively reduce the stitching error.Finally, this method is applied to the straightness measurement of 72m rail, and compared with the electronic level measurement method, the difference of the two results methods is 10μm, which indicated that the proposed method can achieve high-precision straightness stitching.

General-purpose measuring instruments such as polar coordinate measuring instrument and coordinate measuring machine can carry out coordinate measurement on the eccentric wheel shaft, they are mainly equipped with spherical probes, which cannot directly measure the lift and lift error corresponding to the eccentric wheel shaft follower.To solve this problem, a measurement method of eccentric wheel shaft based on coordinate inversion method is proposed.The structure of eccentric wheel shaft and the calculation method of theoretical lift for different probes are introduced in detail.The lift model formulas of the plane probe, roller probe and knife-edge probe are deduced by the coordinates of the surface contour point of the eccentric wheel shaft.The center of the circle of least squares and the center of rotation are used to determine the position of the "peach tip" of the eccenter.An eccentric wheel shaft measurement experiment is carried out on a polar coordinate measuring instrument.The experimental results show that the lift measurement method based on the coordinate inversion method is effective, the difference between the coordinate inverse lift and theoretical lift corresponding to the three kinds of probes is 0.87, 0.90 and 0.90μm, the lift based on coordinate inversion can more accurately reflect the actual motion law of the follower.

By means of high-temperature reduction method, the oxidized mercury will be reduced to elemental mercury without any catalyst, which is convenient for the monitoring of mercury in flue gas. Using differential optical absorption spectroscopy (DOAS) to inversion the concentrations of mercury, and then comparing that with the outcome resulted from experiment without the high-temperature device to verify the applicability of high temperature equipment, and to carry out experiments mixed with different concentrations of the elemental mercury and mercury oxidation. By probing into the impact of genetic algorithm, FFT and the integral area method on the concentration of mercury in flue gas based on the traditional DOAS algorithm, it’s turned out that the traditional algorithm is of contingency with a comparatively large overall error, while the Fourier transform inversion error is too large, the algorithm of integral area inversion has a lower error and a stable volatility than genetic algorithm and integral area inversion error minimum of 0.55%. The volatility of genetic algorithm is also not as stable as that of integral area inversion, which demonstrates that the integral area inversion is the most applicable for the inversion of low concentration of mercury.

In order to reduce the influence of target deformation and complex background changes on the tracking effect during target tracking, a target tracking algorithm based on hybrid correlation filtering information fusion redetection is proposed.Firstly, the correlation filtering algorithm is used to extract the HoG feature of the target gradient histogram, the color template is used to obtain the color feature of the target, and the sampling score of the two templates are calculated.Secondly, the two feature information is combined in a linear combination to determine the target position, during the tracking process, two templates are selected to sample a larger score according to the set threshold condition and then redetect the position of the target.Finally, it outputs results for all the frame target positions.Compared with other excellent algorithms, the algorithm has better tracking effect on dealing with target deformation and background clutter.

The perpendicularity error is one of an important error sources of micro-nano coordinate measuring machines (CMMs). This error should be measured with high accuracy and compensated by an effective model. The measurement setup based on PSD was used to measure the straightness errors which can be transformed into the perpendicularity errors of the micro-nano CMM. A model for perpendicularity errors of the micro-nano CMM was built and used to compensate the errors. Several 0-class gauge blocks were measured and the measuring errors in X and Y directions of the blocks were reduced by 11μm and 5μm respectively after the compensation. The correctness of the perpendicularity error measuring method and the effectiveness of the compensation model were validated.

It's difficult to detect the starting point of signal during measuring time-of-flight of sound propagation, caused by which measurement error should be eliminate. A comprehensive measurement algorithm based on time-frequency analysis is proposed to obtain high-precision ultrasonic velocity. Firstly, cross-correlation method within time domain is used to measure the whole cycle time of sound wave traveled; then, phase difference in the signal frequency domain is used to obtain the ultrasonic propagation group delay information; finally, the high-precision time-of-flight measurement is obtained by combining time and frequency domain information, so as to improve the measurement accuracy of sound velocity. By building the sound velocity measurement platform employed “FPGA + microprocessor” architecture, results show that the algorithm is effective and instructive to practice.