889 results about "Recovery effect" patented technology

The invention relates to a method for recovering active carbon fibre organic waste gas by taking nitrogen as desorption medium, belonging to the field of environmental protection. The method for recovering active carbon fibre organic waste gas by taking nitrogen as desorption medium takes the active carbon fibre as a fixed bed adsorber of the adsorbent, adopts thermal nitrogen desorption and can recover and reuse the organic waste gas and nitrogen at the same time. The method of the invention adopts the thermal nitrogen adsorption, generates no secondary contaminant, realizes that the exhaust reaches the standard of the environmental protection, leads the adsorption layer to keep dry at the same time, improves the utilization ratio of the active carbon fibre and prolongs the service life of the active carbon fibre. As vapour is not used for desorption, the equipment has no corrosion problem, thus greatly reducing the manufacture cost of the equipment. The method of the invention has extremely good recovery effects on solvent with large water solubility and easy hydrolysis performance and organic waste gas with high boiling point, has low water content in the recovered products, high quality of the solvent and reduces the running cost.

The present invention discloses a depth image denoising and enhancing method based on deep learning. The method comprises the steps of establishing a depth image denoising and enhancing convolutional neural network, wherein the network is composed of three layers of convolution units which finish the functions of feature extraction, non-linear mapping and image reconstruction of the input images respectively; jointly using the depth and visual images as the input of the convolutional neural network, wherein firstly the visual images are processed into the grayscale images in a grayscale processing manner; and enhancing the edge information and taking out the redundant information by the image preprocessing; segmenting the depth images into the image blocks according to certain intervals, adding the effective data by a rotation and pixel overturning data amplification method, and discarding the interference blocks and the redundant blocks; and improving the learning efficiency of the network adaptively based on a loss training depth image enhancement convolutional neural network of a weight map. According to the method of the present invention, the black spot filling and the denoising operations can be carried out on the depth images with noise real-timely, and the good visual effect and depth value recovery effect can be realized.

The invention discloses a method for regenerating and pre-vulcanizing a hydrogenation catalyst, which comprises the following steps of: after carrying out charcoal burning on the inactivated hydrogenation catalyst, cooling to a certain temperature; and then directly carrying out suitable pre-vulcanizing treatment and passivating treatment outside a device. In the method disclosed by the invention, the regeneration and vulcanization of the inactivated hydrogenation catalyst are organically combined, so that the generated catalyst is directly subjected to pre-vulcanizing and passivating treatment without being cooled, active metal components can be in a certain active state, and at the time, if the pre-vulcanizing is directly carried out, the vulcanizing effect and the utilization rate of a vulcanizer can be improved. A test shows that in the process, the activity recovery effect of the regenerated catalyst can be improved and the service performance of the regenerated catalyst can be improved. Meanwhile, due to the adoption of the method disclosed by the invention, the energy consumption can be reduced, the production cost is reduced and the production period is shortened.

The invention discloses a video image deblurring method based on a neural network, which comprises the following steps: constructing a neural network composed of an encoder, a dynamic fusion network and a decoder; The encoder consists of two layers of convolution, cascaded layers and four single-layer residual structures stacked in turn. The dynamic fusion network is used to weigh and fuse the feature map saved in the last deblurring stage with the feature map obtained by the current stage encoder. The decoder comprises four single-layer residual structures, wherein the four single-layer residual structures are connected with two branches; The final output image of the neural network is the image obtained by adding the intermediate frame image of the input image sequence and the output image of the first branch of the decoder. The loss function is constructed and the neural network is trained. The trained neural network is used to de-blur the video image. The method of the invention has the advantages of fast processing speed and good recovery effect.

The invention relates to an experimental evaluation method of gas-injection displaceable oil of fracture-cave type carbonate reservoir. The method comprises the following steps in sequence: (1) making a fracture-cave type carbonate core model; (2) preparing an in-place oil sample and injected gas, and setting a pressure point p1 for gas injection and a pressure point p2 for gas injection termination; (3) recovering the original state of the core; (4) carrying out an exhaustion experiment from the top end of the core; (5) carrying out the gas-injection displaceable oil experiment for a plurality of times from the top end of the core at the formation temperature; and (6) calculating development indexes (of the gas injection displaceable oil experiment) such as the recovery efficiency of the raw oil, the gas-oil ratio, the gas-water ratio, and the like. By making a physical single fracture plane overall-diameter fracture-cave core model which keeps the completeness of the core, an experimental testing method for physical gas injection displaceable oil simulation is established, and a tool and a means for evaluating the recovery effect of the fracture-cave type carbonate is provided.

The invention discloses a power system harmonious wave compressed signal reconstruction and detection method based on compressed sensing. The power system harmonious wave compressed signal reconstruction and detection method based on compressed sensing comprises the steps that harmonious wave original signals of a power system and a measurement matrix with a binary sparse random measurement matrix serving as a power system harmonious wave data compressed sample are sent to a frequency mixer for compressed sampling in a simulation domain, then A/D conversion is carried out on the simulation signals, and a compressed sampling value is obtained; it is determined that a compressed sensing sparse base is a discrete Fourier transform base; initialization of fundamental wave filtering is carried out; fundamental wave filtering is carried out; the frequency, amplitude and phase of a fundamental component are detected; the fundamental wave constituent in the compressed sampling value is filtered away; parameter initialization is carried out on a spectrum projection gradient method; a sparse vector estimation value of a harmonious wave component is reconstructed through the spectrum projection gradient method; the frequency, amplitude and phase of the harmonious wave component are detected; reconstruction of the harmonious wave original signals of the power system is finished. The power system harmonious wave compressed signal reconstruction and detection method based on compressed sensing overcomes the defect that all existing recovery algorithms do not take the influence of the fundamental wave component in the harmonious wave signals on signal reconstruction into account, so that the recovery effect is not ideal.

The invention relates to a microscale Al-containing rare earth wrought magnesium alloy and its preparation method and belongs to the scope of industrial magnesium alloy. The magnesium alloy comprises, by weight, 6.5-15.0% of Gd, 3.0-5.5% of Y, 2.0-4.0% of Zn, 0.3-1.5% of Nd, 0.3-0.9% of Zr, 0.4-1.0% of Al and the balance of Mg. The preparation method of the magnesium alloy comprises the steps as follows: raw material preparation, alloy melting, alloy semi-solid extrusion, homogenization treatment, redeformation, cooling and pre-stretching treatment, ageing strengthening treatment and the like. By fully utilizing the defect that Al is preferentially combined with rare earth and Zr in alloy to form a stable phase, Zn element is added to make up insufficiencies and the wrought magnesium alloy with high performance is prepared. The recovery effect of rare earth elements is enhanced, and semi-solid forming and solid plastic forming are combined.

The invention discloses a noise motion blurred picture recovery method based on radial neural net, which comprises the following steps: (1) making the noise motion blurred picture y(m, n) generate the corresponding smoothing picture s(m, n) after low-pass filtering with the two-dimensional median filter; (2) calculating the inaccuracy picture e(m, n)=y(m, n)-s(m, n) between the noise motion blurred picture and the smoothing picture; (3) detecting the edge with Canny operator in order to estimate the gradient f' (m, n) of y(m, n); (4) calculating regular parameter lambda (m, n) of every picture element according to the size of f' (m, n) and generating interpolation picture f lambda (m, n) by radial neural net RBFN according to the inaccuracy picture e(m, n); (5) acquiring the silent motion blurred picture f(m, n) by superimposing the interpolation picture f lambda (m, n) to the smoothing picture s(m, n) after low-pass filtering; (6) acquiring the width HL and the height VL of two-dimensional blurred picture by identifying the motion blurred direction and the motion blurred length of the motion blurred picture automatically and acquiring the recovery picture with the picture recovery method. The invention provides the automatic identification, the low complicated calculation and the good recovery effect.

The invention relates to a foam drainage gas recovery method used for a natural gas horizontal well. The method is capable of injecting a foam scrubbing agent into the bottommost end of a gas well shaft, so that the whole shaft is filled with foam fluid and optimal drainage gas recovery effect is achieved. The technical scheme of the method comprises the following steps: firstly, manufacturing a dynamical underground foam scrubbing bar which consists of a gas nozzle, a tail wing, a boosting agent, a shell and a protection head sleeve, wherein the material for manufacturing the tail wing, the shell and the protection head sleeve is the solid foam scrubbing agent which consists of polyoxyethylene alkyl ethers, polyethylene glycol, urea, imidazoline, sodium dodecyl benzene sulfonate and saturated alcohol sulfate; and the boosting agent is one of dry ice, sodium hydride or potassium oxide; and secondly, throwing the dynamical underground foam scrubbing bar to the bottom of the well, wherein the boosting agent is in contact with water to generate a large amount of gas, so that the foam scrubbing bar is pushed to the bottommost end; and as the foam scrubbing agent is dissolved, a large amount of foam is formed to achieve the optimal effect of drainage gas recovery. The method disclosed by the invention has a wide application range without any wellhead equipment and energy, is simpleand safe in operation, low in cost and has no pollution to the environment.

Embodiments of the invention disclose a memory recovery method and a terminal. The method comprises the steps that the terminal determines a target application from applications running in a background according to a preset rule, wherein the target application is an application needed to be cleared; the terminal freezes the target application and recovers data generated during running of a process of the target application in a memory; and the terminal unfreezes the target application and runs the target application when receiving an input triggering instruction for the target application. By adopting the method and the terminal provided by the embodiments of the invention, the memory recovery effect can be improved.

The invention relates to a real video recovery method based on local strategies and belongs to the field of image processing and pattern recognition. The real video recovery method based on the local strategies is characterized by comprising, firstly, extracting the moving foregrounds of the neighboring two frames of a real video, matching the feature points of the moving foregrounds and accordingly estimating the blurring kernels of every pixel point in the foregrounds; secondly, for eliminating object motion blur of space change inside the video, providing an ADM (adaptive delta modulation) algorithm, namely, recovering all the overlapped local blocks and integrating the local blocks into clear video frames. The real video recovery method based on the local strategies can overcome the deficiencies of amplifying noise and introducing ringing effects in traditional methods and achieve good recovery effects on the edges and the details of the video frames.

The invention discloses a system on chip (SOC) estimation method for a lithium ion battery. The method comprises the following steps: 1, performing SOC real-time update; 2, introducing a dynamic variable; 3, identifying parameters in a battery circuit model; 4, realizing SOC estimation of the lithium ion battery by using an unscented Kalman filter algorithm according to the identified model parameters; 5, implementing the SOC estimation algorithm of the lithium ion battery based on the unscented Kalman filter. The method disclosed by the invention has the following advantages: (1), an improved second order RC equivalent circuit considers the rate capacity effect and recovery effect of the lithium ion battery compared with other circuit models, and compared with the traditional second order equivalent circuit, the dynamic and static characteristics of the battery are well simulated; (2), compared with the other algorithms, the unscented Kalman filter algorithm is low in initial value dependence, accurate in prediction and capable of well solving the nonlinear problem; (3), by utilizing the characteristics of flexibility and convenience of Xilinx FPGA development, the SOC estimation algorithm of the lithium ion battery is implemented on a hardware platform, so that the algorithm is not only theoretical, but also can be applied to portable equipment.

The invention relates to a treatment device of liquid slag. The treatment device comprises a slag pot and a launder and is characterized by further comprising a granulating heat exchange bin, a nozzle, a heat exchanger, a cooling device and an ash conveyor; the slag pot is arranged on the launder; the nozzle and the launder are arranged at the entrance of the granulating heat exchange bin; the nozzle is arranged under the launder; the granulating heat exchange bin is provided with an air inlet and an air outlet; an ash bucket is arranged at the bottom of the granulating heat exchange bin. Perfect function settings enable the afterheat recovery effect of the device to be better.

A robot for the recovery training to combined upper limibs movements of hemiplegia patient is composed of chair, vertical post installed at side of chair, mechanical arm installed to and moving along said vertical post and consisting of mechanical upper and lower arms, bracket for wrist, and elbow joint hanger. Its advantage is high recovery effect.

The invention discloses a regeneration method of a deactivated catalyst and belongs to the field of atmospheric pollution control and environmental protection. The regeneration method comprises the steps of washing the deactivated catalyst with dry compressed air, immersing in deionized water, carrying out ultrasonic treatment, carrying out ultrasonic immersing with cleaning liquid after the treatment, drying to remove water after immersing, putting the catalyst after water removal into an autoclave for immersing with a pore-enlarging agent, sequentially immersing in active replenishing liquid and antitoxic modification liquid after immersion, and carrying out drying and roasting after the immersing. The regeneration method of the catalyst has good active recovery effect, the denitration efficiency reaches about 93%, and the specific surface area and compressive strength are increased.

The invention relates to the technical field of medical instruments, in particular to a limb coordination rehabilitation training device for a neurology department. The limb coordination rehabilitation training device comprises a base, a seat, driving devices and a leg training device. The driving devices are positioned on two sides of the base which is positioned at one end above the base, and the leg training device is positioned at the other end above the base. The driving device comprises a left driving part and a right driving part, the leg training device comprises a left training part and a right training part, the left driving part is used for driving the right training part, and the right driving part is used for driving the left training part. An ultrasonic massaging part is arranged on the seat. By right leg training under left hand drive and left leg training under right hand drive, accordance with human nervous system tissues is realized, and coordination training of upperand lower limbs of patients is benefited; high training pertinence and great recovery effects are achieved; by the ultrasonic massaging part for ultrasonic massaging of thighs and cervical vertebra of the patients, blood circulation is promoted, metabolism rate is increased, and recovery of the patients is benefited.

The invention provides a method for synchronously extracting boron and iron in paigeite. The method comprises the following steps: fully mixing a paigeite powder and an additive composed of sodium carbonate, sodium sulfate, natrium humate, sodium fulvate and sodium oxalate by mixing, agglomerating, performing reduction roasting on dried paigeite agglomerates which take coal as a reducing agent, cooling the roasting agglomerates and placing in a bowl mill, synchronously grinding ore and leaching by water, performing solid-liquid separation on a pulp to obtain a filtrate containing sodium metaborate and filter residues containing metallic iron powder, evaporating and crystallizing a filtrate to obtain the sodium metaborate crystals; employ a wet type weak magnetic separation on the filter residue to obtain the directly reduced metallic iron powder with iron grade greater than 90%, wherein the metallic iron powder is a high-quality furnace material used for making steel of an electric furnace; and treating the magnetic separation nonmagnetic products to recover the valuable components such as magnesium and silicon. The method has the advantages of strong raw material adaptability, simple process flow, high production efficiency, less energy consumption, low cost, good comprehensive recovery effect of ferroboron and high product added value. The method provided by the invention can provide technical support for efficiently using the paigeite with abundant reserve volume for our country, and has wide popularization and application prospects.

A process for all-wet recovery of valuable elements in a complex low-grade sulphide ore comprises the following steps: crushing and grinding a raw material, sieving the crushed and ground raw material, performing size mixing by use of a sodium hydroxide solution, and after that, performing pressurized oxidizing leaching to obtain an alkaline-leached solution and alkaline-leached residues; acidizing the alkaline-leached solution to obtain a lead sulfate product and a heavy lead solution, and performing potential reduction control step by step on the heavy lead solution to obtain crude selenium powder, crude tellurium powder and a post-reduction solution; performing copper-soaking on the alkaline-leached residues by use of a sulfuric acid solution to obtain copper-leached residues and a copper-leached solution; performing antimony and bismuth soaking on the copper-leached residues by use of an acid liquor containing chloride ions to obtain an antimony-leached solution and antimony-leached residues, feeding the antimony-leached slags to noble metals for recovery, and adjusting the pH of the antimony-leached solution step by step to obtain antimony residues and bismuth residues; adjusting the pH of the copper-leached solution to obtain iron residues and an iron-removed solution, wherein the iron residues serve as a waste water treatment additive, and the iron-removed solution is subjected to zinc dust replacement to obtain copper powder and a post-replacement solution; and merging the post-reduction solution and the post-replacement solution, and performing concentration and crystallization to obtain heptahydrate. The process is good in comprehensive recovery effect, strong in adaptation to the raw material, clean and environment-friendly in process, low in demand on equipment, adjustable in implementation scale and high in practicability.

The invention provides a method for comprehensive treatment of household refuses and secondary pollution control. The method comprises the following procedures of: 1) coarse separation of the household refuses; 2) pretreatment of the household refuses; 3) fine separation of the household refuses; 4) aerobic composting of the household refuses; 5) biological organic fertilizer preparation; 6) fabrication of refuse derived fuels; and 7) secondary pollution control. The method employs parallel dual-separation lines which are compact in arrangement; each functional unit device is rational in configuration, easy to operate and mechanically control; the sorting efficiency and the energy source recovery effect are obviously improved; and minimization, harmless treatment, recycling and energy conversion of the household refuses can be realized.

The invention discloses a cGAN algorithm-based super-resolution image recovery technology, and relates to super-resolution recovery for deep convolutional antagonistic neural network images. The existing method needs to carry out a lot of training, the network layers are relatively shallow and the feature weight values included in models obtained through the training are not complete enough, so that the final recovery effect is not ideal. Greyscale maps are used during the training, so that the super-resolution recovery effect for three-channel colored images is not good. Aiming at the defects in the prior art, the invention provides a cGAN algorithm-based super-resolution image recovery method which is capable of training the colored images to achieve better recovery effect. The key points of the method comprises that (1) the training time is short, (2) three-channel colored maps can be directly trained, (3) much image preprocessing is not required, and (4) the models obtained through training can be used once for all.

The invention discloses an image restoration method based on an adaptive residual neural network. The method comprises the steps that an adaptive residual neural network model is built, wherein the adaptive residual neural network comprises a number of adaptive residual units connected in series; training sets for image denoising, image super-resolution and image deblocking effects are respectively selected, and corresponding training parameters are respectively set; according to the adaptive residual neural network model and the training parameters for image denoising, image super-resolution and image deblocking effects, the corresponding target neural network model is trained respectively with the goal of minimizing a loss function; and according to the trained target neural network model for the problem of image denoising, image super-resolution and image deblocking effects, an image to be processed is input to the corresponding target neural network model, and a corresponding high-quality image is output. According to the invention, the PSNR, SSIM and visual effect of the image can be remarkably improved, and the method has the advantages of good recovery effect, high speed and strong robustness.

Belonging to the technical field of wet metallurgy, the invention especially relates to a method for comprehensive recovery of valuable metals from tin anode mud. The method comprises the following technical key points of: mixing the tin anode mud with one or more of an alkali metal hydroxide aqueous solution and an alkali metal sulfide aqueous solution, keeping the pH value of the mixed feed solution greater than 12, placing the feed solution into a sealed reactor, conducting heating to a temperature of 100-300DEG C, carrying out stirring reaction, then performing filtration, recovering valuable metals, mainly tin, from the filtrate, and recovering various valuable metals from the filter residue by means of oxidizing roasting transformation, copper leaching by sulfuric acid, silver leaching by nitric acid, bismuth leaching by hydrochloric acid. The invention is particularly suitable for treatment of tin anode mud with high antimony and low silver, and can achieve a good comprehensive recovery effect for various valuable metals. The leaching rate of tin is greater than 90%, the removal rate of antimony is greater than 85%, and silver, bismuth, copper, as well as lead are enriched over 4 times. And the method generates a relative small amount of ''three wastes'', thus being in favor of environmental protection.

The invention discloses an assessment method of auxiliary CRS-R scale auditory shock based on a brain-computer interface. The assessment method comprises following steps of: 1) selecting simulation, arranging and designing an experimental paradigm; 2), collecting signals; 3) performing data processing; 4) counting inspecting evaluation standards. The assessment method of auxiliary CRS-R scale auditory shock based on the brain-computer interface has following beneficial effects: based on an auditory extraneous experimental paradigm, mismatch negative waves MMN and P300, peculiar to human race, are induced; in combination with an auditory shock assessment method of a coma recovery scale CRS-R, scores of CRS-R auditory shock items are accessed by adoption of the brain-computer interface and a peak detection algorithm; and therefore, the method can not only be effectively used for assessment diagnoses of the coma recovery scale, tracking of recovery effect and selections of a prognosis treatment scheme but also provide scientific and objective detection data to the conventional scale diagnoses in order to ensure authenticity and effectiveness of detection results..

The invention provides a building-out circuit and a testing method for testing the negative bias temperature instability (NBTI). The building-out circuit is respectively connected with a source-measurement unit and a PMOS (P-channel Metal Oxide Semiconductor) to be measured; the building-out circuit comprises an NMOS (N-channel metal oxide semiconductor); a base electrode of the NMOS is electrically connected with a source electrode of the NMOS by a resistor R0; a drain electrode fo the NMOS is electrically connected with a grid electrode of the PMOS to be measured by a resistor R1; a grid electrode fo the NMOS is electrically connected with the grid electrode of the PMOS to be measured by a resistor R2; the potential of the base electrode of the NMOS is set into a value of less than 0V; and the voltage input end of the source-measurement unit is connected with the grid electrode of the NMOS. When an input voltage of the source-measurement unit is changed into 0V, due to the voltage division of the resistor R2, the voltage of the grid electrode of the PMOS to be measured is less than 0V, i.e. when the NBTI recovery effect occurs after the stress voltage is switched off, a partial pressure of the R2 is still applied to the grid electrode of the PMOS to be measured to inhibit the NBTI recovery effect in the PMOS, so that the measurement result is more accurate.