38results about How to "Method flow is clear" patented technology

The invention relates to a method for transmitting mass data based on a UDP protocol. The method comprises a sending method and a receiving method. As the data transmission of Ethernet is limited by packet size, the situation occurs that a data packet is unsuitable for transmission or even can not be transmitted occurs due to overlarge data size. The method for transmitting mass data based on the UDP protocol effectively combines a compaction algorithm and a data packet splitting method, sends mass data according to a principle of unpacking-compaction-unpacking and receives mass data according to a principle of uniting-decompaction-uniting. The sending end flow and the receiving end flow relate to a private protocol of a compaction / non-compaction data packet. The method has clear flow, concise parameters of a protocol format, strong extendibility and wide application range, can be effectively applied to transmitting mass data based on the UDP protocol and improve the efficiency and reliability of transmission.

The invention discloses a dynamic state estimation method based on self-adaptive volume Kalman filtering, which is used for realizing accurate estimation of a dynamic state variable of an electric power system generator. According to the method, a fading memory index weighted Sage- Husa noise statistical estimator is introduced into volume Kalman filtering; and the mean value and the variance of the time-varying system noise are dynamically estimated and corrected, the influence of system noise matrix mismatching on the state estimation precision is inhibited, and the accurate estimation of the state variable of the generator is improved. The algorithm considers the actual engineering background, is simple and convenient, and has high engineering application value.

The invention provides a g enerating and importing method for communication facility configuration file based on key-value pair format, comprising, s1), filling the configuration information data structure in a communication facility memory into an internal memory dictionary, and then outputting the internal memory dictionary to configuration files of the key-value pair format, 2), establishing the internal memory dictionary, parsing configuration files of the key-value pair format and filling the internal memory dictionary, then disposing the data in the internal memory dictionary to the configuration information data structure in the communication facility internal memory, and configuring the communication facility. The method of the invention can be widely used in communication field and improve the operating efficiency and stability of the communication system.

The invention discloses an on-orbit test method for space-borne sliding spotlight SAR aiming precision. The method comprises the following steps: choosing a ground control point whose absolute position coordinate is Ptarget0; according to the current orbital position of the satellite PSatellite0, forecasting the orbital position PSatellite1 (WGS84 coordinate system) of the control point at the covering time; performing calculations to the SAR imaging related parameters; based on the imaging parameters, calculating the relative position PRelative0 of the control point in an imaging band; covering by the satellite and irradiating to the known control point and downloading data; receiving the data by a ground application system and carrying high precision Doppler center computing and imaging processing; conducting geometrical positioning to the image by the ground application system based on the navigation data and the ephemeris parameters; intercepting the image according to the imaging bandwidth design value; and identifying the already known control point on the image; calculating the relative position coordinate PRelative1 in a scene. The invention can effectively solves the on-orbit test and evaluation on the space-borne sliding spotlight SAR aiming precision and can effectively ensure the accuracy for the user to obtain the SAR image of a required target.

The invention provides an imaging quality improving method of a high-resolution spaceborne SAR. The method comprises the following steps that 1) imaging quality improving demands are analyzed and imaging quality indexes are arranged on the basis of a high-resolution SAR image application; 2) optimized imaging quality indexes are decomposed and distributed; 3) measures for improving the imaging quality are provided; and 4) the imaging quality improving effect is evaluated on the basis of full-link simulation. The method provided by the invention is clear in processes and easy to realize, can guide general design of the spaceborne SAR, is innovative, and is suitable for imaging quality improving researches of other types of SAR satellites.

The invention relates to a method, device and terminal for coordinating LTE (Long Term Evolution) system random access and pilot frequency measurement conflict. The method comprises the following steps: a physical layer MC (Main Control) software module receives and forwards a random access request transmitted by a high layer to a UL-RAPC (Uplink-Random Access Control) module and receives and forwards a pilot frequency measurement request transmitted by the high layer to a CSR-GAPC (Cell Search Pilot Frequency) measuring module; and the UL-RAPC and the CSR-GAPC respectively control an RF (Radio Frequency) module to work respectively according to the random access request and the pilot frequency measurement request by combining with a pilot frequency measurement identification at the reference time provided by a TPU (Time Control Module). The invention realizes the aim that corresponding tasks are carried out according to a certain sequence and priority on the premise of not completely suspending any work, effectively solves the problem of conflict between random access and pilot frequency measurement; and has the advantages of simple device maintenance and clear method flow.

The invention provides an organic fluorescent small molecule optical property prediction method based on a deep neural network. According to the method, a new organic fluorescent small molecule database is established, molecular descriptors and molecular fingerprints are adopted to extract molecular information, and a multi-layer neural network and a convolutional neural network are input for deep learning training to obtain an organic fluorescent small molecule optical property prediction model; the characteristic information of the to-be-predicted organic fluorescent micromolecules and the experimental solvent thereof are input into the trained organic fluorescent micromolecule optical property prediction model so as to predict the optical property of the to-be-predicted organic fluorescent micromolecule. The method can accurately predict the optical properties (the average relative error is less than 5%) of the organic fluorescent small molecules, so that the development efficiency of the organic fluorescent small molecules is improved.

The invention discloses a target satellite rocket docking ring capture point positioning method based on double-mechanical-arm capture. The method comprises the steps: controlling double mechanical arms of a target satellite to stably capture the captured target satellite; acquiring three capture points of a satellite-rocket docking ring of a capture target satellite by replacing a capture position of a mechanical arm so as to calculate the plane and the circle center of the satellite-rocket docking ring; extracting frame information through image edge detection to obtain a projection line ofa capture target satellite in a satellite-rocket docking ring plane, acquiring position coordinates of capture points in a coordinate system after the coordinate system of the target satellite is established, and completing capture point positioning.

The invention discloses a preparing method for chlorogenic acid and similar compounds thereof. The preparing method comprises the following steps that firstly, reflux extraction is carried out with an extracting agent; secondly, an extracting solution is concentrated into an extract state; thirdly, extract is dissolved and extracted with ethyl acetate; fourthly, the pH value of a concentrated solution obtained after extraction is regulated to be neutral, and filtration with a macroporous resin column is carried out; fifthly, a thin layer preparing plate is used, a spreading agent is selected for spreading, and high-purity chlorogenic acid and similar compounds thereof are obtained through belt scraping, grinding, column filling, washing and concentration drying. The method is clear in flow, simple and low in cost, and the obtained products through purification are good in color and high in yield and purity; besides, the multiple similar compounds of chlorogenic acid are can be obtained at the same time, and a base is provided for wider and more effective application of chlorogenic acid and the similar compounds thereof.

The invention discloses an automatic material connection system and method. The automatic material connection system comprises a sorting machine, a transfer wharf, a connection goods shelf, an AGV trolley and an industrial control platform, wherein the sorting machine is used for sorting materials and stacking the materials into material boxes arranged on the sorting machine one by one; the transfer wharf is used for placing empty material boxes for use; the connection goods shelf is used for placing material boxes fully loaded with materials; the AGV trolley is used for conveying the empty material boxes in the transfer wharf into the sorting machine, taking out the fully loaded material boxes on the sorting machine, conveying the fully loaded material boxes to the connection goods shelf and carrying the connection goods shelf according to processing requirements; and the industrial control platform is used for controlling the whole operation process of the AGV trolley. A whole set of material connection process is completed in an automatic mode, organic combination of a sorting area, the transfer wharf and a goods shelf area in an industrial production enterprise is achieved, and the material turnover efficiency in the industrial production enterprise is remarkably improved.

The invention relates to a loop closing fixed value setting and checking method of an ultra-high voltage alternating-current system. The loop closing fixed value setting and checking method comprises a fixed value setting part and a fixed value checking part, wherein the fixed value setting part comprises loop closing voltage difference fixed value and phase angle difference fixed value setting. According to the loop closing fixed value setting and checking method of the technical scheme provided by the invention, reactive voltage and tidal current distribution of the ultra-high voltage alternating-current system are accurately analyzed, and a loop closing voltage difference fixed value is determined according to a tapping gear of an ultra-high voltage transformer, the operating level of network voltage and the like; a loop closing phase angle difference fixed value is determined according to section power and tidal current distribution before loop closing; whether the fixed values are feasible is checked according to the influence of loop closing impact power on the stability of a power system. The loop closing fixed value setting and checking method is suitable for the ultra-high voltage alternating-current power transmission system.

The invention discloses a fault monitoring method for reciprocating equipment. The method comprises the following steps of S1, collecting a plurality of vibration acceleration signals, selecting one vibration acceleration signal, intercepting a segment of the vibration acceleration signal as a reference signal, and taking the rest as a training data set; S2, selecting a plurality of signal segments from the signals in the training data set, calculating a cross correlation coefficient between each signal segment and the reference signal, taking the signal segment corresponding to the maximum result as a training sample, traversing the training data set and summarizing the reference signals to obtain a training sample; S3, converting the training sample to obtain an upper envelope line and a lower envelope line; S4, collecting a vibration acceleration signal to be monitored, and obtaining a detection sample; and S5, comparing whether the detection sample exceeds the upper envelope line and the lower envelope line, if not, marking as normal, and if yes, marking as abnormal, and giving an alarm. According to the method, the monitoring of the vibration signal is realized in a full-automatic manner, the dependence of the method on human resources is reduced, and the accuracy of the monitoring effect is ensured.

A spatial elliptic arc interpolation method comprises the following six major steps: step 1, a spatial elliptic arc interpolation code format is defined; step 2, decoding is carried out to acquire spatial elliptic arc interpolation data information; step 3, an interpolation central angle is calculated; step 4, interpolation parameter increment is calculated; step 5, interpolation point calculation is carried out; and step 6, the interpolation ending point is judged. The spatial elliptic arc interpolation method of the invention is applicable to interpolation of elliptic arcs with any starting and ending points and in any spatial planes. The spatial position and the interpolation direction of an elliptic arc are determined by the long-axis direction vector and the short-axis direction vector of the elliptic arc, and regulate interpolation in the counterclockwise direction of the vector product of the two direction vectors. The spatial elliptic arc interpolation method of the invention requires no interpolation quadrant judgment, has a clear and simple process, and is easy to implement.

The invention discloses an asymmetric catalytic reaction enantioselectivity prediction method based on deep learning. The method comprises the following steps: firstly, acquiring and sorting asymmetric catalytic reaction data in which isocyano acetate participates, and designing a model training set and a sample external test set; calculating and processing molecular descriptors of reaction related compounds, summarizing the molecular descriptors and reaction conditions into a group of feature vectors, and inputting the feature vectors into a model; respectively constructing a deep neural network regression model and a convolutional neural network regression model based on the training set, and optimizing hyper-parameters of the deep neural network regression model and the convolutional neural network regression model, so as to obtain a model capable of accurately predicting the reaction enantioselectivity of the training set; and utilizing the optimal neural network model to predict the enantioselectivity of the in-vitro reaction of the sample, and checking the mobility of the model. The result shows that the model can accurately predict the enantioselectivity of the in-vitro reaction of the sample, and the robustness and mobility of the model are further verified.

The invention belongs to the technical field of gene engineering and relates to a method for predicting RNA binding protein based on circRNA position information. The method comprises the following steps of: based on circRNA chromosome position information, obtaining chromosome position information of first 100 basic groups at a starting position in the same direction of circRNA, then obtaining a front side position sequence in the same direction of the circRNA on a Linux system by utilizing bioinformatics software bedtools, and further obtaining motif of the front side position sequence in the same direction of the circRNA; downloading a meme format file of the motif of a known protein from a known database, and comparing and matching the meme format file of the motif with the motif of the front position sequence in the same direction of the circRNA to obtain the RNA binding protein of the circRNA. According to the method, the RBP of circRNA can be predicted in batches, and the method is not limited by the number and species.

The invention relates to a system health state prediction method based on a Bayesian neural network. The method comprises the steps: dividing each node of a system structure to obtain a first integrated node and a second integrated node; establishing an original multi-level system Bayesian network model based on the first integration node to obtain a state distribution prediction result of the first integration node, and establishing a deep learning model and a Bayesian network model based on the second integration node to obtain a state distribution prediction result of the second integration node; and integrating the state distribution prediction result of the first integration node and the state distribution prediction result of the second integration node to realize health state prediction of the whole system. According to the method, health state monitoring data is effectively utilized, and the conditions of data overlapping and coupling are avoided; and the Bayesian neural network is used to divide and predict the system state, and the operation and maintenance of the subsequent system are effectively guided.

The invention provides a method for tenderizing a low-temperature meat product by using a polymer biological enzyme. The method for tenderizing the low-temperature meat product by utilizing the polymer biological enzyme comprises the following steps: S1, preparing raw materials, namely selecting Jinhua pigs or Ningxiang pigs which are good in growth condition, healthy and disease-free, then fixingthe pigs according to pig slaughtering management regulations specified in China, inspecting the pigs and then slaughtering the pigs; S2, carrying out pig carcass treatment: slaughtering pigs, performing bloodletting, viscera removing, tongue-free, unhairing, hoof removing and reproductive organ removing, but reserving leaf fat, kidney and diaphragm, then segmenting the obtained pig trunks segmented along the center line, keeping the temperature of the pig carcass at 0-4 DEG C during segmentation, and keeping the segmented pork blocks complete. According to the method, three modes of physicaltenderizing, chemical tenderizing and polymer biological enzyme tenderizing in pork tenderizing treatment are effectively combined, so that the tenderness of the dried meat slices can be remarkably improved, the texture of the dried meat slices can be improved, the tenderizing degree of the dried meat slices can be controlled, and the nutritional value can be increased.

The invention discloses a preparation method of a spicy garlic-flavor dried pork, which comprises the following steps: taking pure lean pork as a raw material, trimming the pure lean pork, cutting the trimmed lean pork into diced meat with the size of 3*3cm, sprinkling edible salt, pickling for 30 minutes, sprinkling corn starch, and uniformly stirring; putting the prepared diced pork into a pot, frying with oil, putting the fried diced pork in a steamer, steaming for 50 minutes, adding monopotassium glycyrrhizinate, uniformly stirring, repeatedly frying and steaming for 8 times, uniformly mixing the obtained product with a mixture of fresh minced red pepper, mashed garlic and Chinese prickly ash, canning, and storing for one week to obtain the spicy garlic-flavor dried pork. The obtained dried pork has rich taste, the taste is spicy and refreshing, the method has clear process, simple technology, low cost and high yield, and a more efficient way is provided for preparing the spicy garlic-flavor dried pork.

The invention relates to a preparation method of unsaturated fatty acid in macadamia nut oil, and belongs to the technical field of pharmaceutical chemicals. The method comprises the following steps of: carrying out ester exchange; carrying out urea inclusion; recovering unsaturated fatty acid ester; carrying out secondary inclusion and secondary recovery of unsaturated fatty acid ester; separating urea from a filter cake; and hydrolyzing to obtain the unsaturated fatty acid. Compared with the prior art, the method is clear in process, simple and low in cost, the purified product is good in color and high in yield, and unsaturated fatty acid ester and fatty acid can be extracted to the maximum extent.

The invention discloses a method for extracting licoflavone by using R19. The preparation method comprises the following steps of: taking R19 as a raw material, dissolving the R19 in water to obtain a sample loading solution, then treating macroporous resin, soaking the macroporous resin with an ethanol-water solution, packing the macroporous resin, and washing the macroporous resin with pure water until no alcohol smell exists; eluting by using water as an eluent, and detecting through TLC to obtain a flavonoid compound; and then purifying the flavonoid compound by using a polyamide column to finally obtain the high-content flavonoid compound. The method for extracting licoflavone by using R19 is clear in process, simple in process, low in cost and high in yield, and provides a more efficient way for preparing licoflavone.

The invention discloses a terminal firmware over-the-air upgrading system and an over-the-air upgrading method. The system comprises at least one far-end server and a plurality of terminals, wherein each terminal carries out autonomous networking according to a networking limiting condition of the terminal. Meanwhile, multiple terminals meeting respective networking limiting conditions jointly form a terminal cluster in an autonomous networking mode; firmware upgrading data used for achieving terminal firmware over-the-air upgrading is stored in the far-end server and the terminal cluster; andwhen a terminal needing firmware upgrading exists in the system, the terminal can obtain the firmware upgrading data from the far-end server and the terminal cluster. According to the invention, theInternet of Things is combined with the block chain, and the terminal can acquire the data required for upgrading from multiple sources when executing the upgrading operation, so that the data acquisition efficiency can be greatly improved.

A shock absorber matching method of an inertial navigation assembly can enable a shock absorption system to meet use requirements through performance parameter matching of a single shock absorber, provides a specific height difference measurement method for an installation mode of a current shock absorber, and meanwhile determines a static deformation amount and static rigidity determination method. On the basis of the current method, a shock absorber size matching height size requirement range and a shock absorber rigidity matching requirement range can be provided, the method is not limited to an eight-point installation matching mode, and the method is clear in process and flexible in selection and matching.

The invention discloses a residual gray field calculation method of a local digital image correlation method. The residual gray field calculation method comprises the steps of calculation point grid construction, displacement field interpolation and gray interpolation, residual gray field calculation, and residual gray field after-processing. According to the method, on the basis of traditional residual gray field analysis, aliasing and other factors which are not beneficial to feature extraction in a traditional method are eliminated; compared with a traditional discrimination method using correlation coefficients of DIC, the method can provide more accurate positioning for features, can quantitatively and visually display matching results, and can prompt newly appearing image features, such as cracks, defects and the like; according to the method, on the basis of grid construction, displacement fields of discrete calculation points in the sub-region DIC can be organized, continuous interpolation of the displacement fields is achieved, continuity of the displacement fields is guaranteed, and ambiguity is avoided; the method is clear in process and easy to implement, not only can be implemented by using a CPU, but also can be implemented by using a shader of a GPU, and has extremely high calculation efficiency.