13results about How to "Reduce data storage" patented technology

The application belongs to the technical field of radar signal processing and imaging, and provides a differential coupling single-frequency time-varying low-quantization imaging method, which comprises receiving a SAR echo signal, constructing a single-frequency time-varying threshold signal, single-bit quantization processing of a reference channel, single-bit quantization processing of a phase shift channel, double-channel data fusion and harmonic cancellation, and imaging processing based on a synthesized signal. The application effectively reduces the quantization noise base and improves the detection capability of a SAR system on weak targets under the premise of not significantly increasing the hardware cost.

This invention discloses a planetary landing guidance method based on rapid search for optimal control, belonging to the field of spacecraft guidance and control technology. The implementation method is as follows: The lander's dynamic model is decoupled into a controlled dynamic model and an uncontrolled dynamic model; an optimization model of the reachable region is constructed using thrust amplitude and thrust direction constraints as constraints, solving for the reachable region of controlled motion in a prediction time domain; a fuel consumption optimization model is constructed using different positions within the reachable region as virtual endpoints, and offline optimization is performed to obtain the optimal fuel consumption control for the lander to reach the specified virtual endpoint position. The optimal control is stored as an optimal control database, and the corresponding virtual endpoint state is stored as an endpoint state database; during landing, the uncontrolled motion is superimposed with the endpoint state database to obtain the lander's state prediction space, the optimal terminal state is searched, and the corresponding optimal control command in the optimal control database is obtained. Planetary landing guidance is then implemented based on the optimal control command.

The invention discloses a downsampling wind driven generator transmission chain vibration test analysis method. The method specifically comprises the following steps: collecting vibration data at a selected test point; carrying out downsampling processing on the vibration data of the high-rotating-speed component; according to the VDI3834 standard, carrying out band-pass filtering processing on the vibration data collected by each measuring point; carrying out characteristic index calculation on the filtered vibration signal; and if the calculated numerical value exceeds the VDI3834 standard reference numerical value, carrying out time domain analysis and frequency domain analysis in the next step.

The invention discloses a rail vehicle fault diagnosis information acquisition method. An important information acquisition and storage strategy is adopted. The method comprises the following steps: setting an important information acquisition starting condition of a monitoring point and a single acquisition total duration T0; meanwhile, setting a time-division frequency-division acquisition scheme in the total time period T0; the time-phased frequency-division acquisition scheme comprises the steps that the total acquisition time T0 is divided into T1, T2,..., Ti,... and TN, the sampling frequency corresponding to each time period is F1, F2,..., Fi,... and FN, and T0 is equal to T1 + T2 +... + Ti +... + TN and F1gt; f2gt; gt,... gt; figt; gt,... gt; i is greater than or equal to 1 and less than or equal to N, and N is greater than or equal to 2, namely, the acquisition frequencies in all time periods are different and are sequentially reduced. According to the invention, all effective information of railway vehicle daily fault diagnosis can be collected, invalid information is little or even no information exists, and the problems that the number of monitoring points for railway vehicle fault diagnosis is large, the information collection amount is large, and the calculation processing amount is large can be solved.

The application discloses a multi-path camera image frame extraction method and system, relates to the technical field of data processing, and extracts frames through a two-stage frame extraction strategy combining low-frequency monitoring and high-frequency tracking. When no event occurs, monitoring is performed at a very low first preset data sampling frequency, and subsequent processing is triggered only when a scene change is detected, so that data storage under a static scene is greatly reduced. When a key target is recognized, high-frequency sampling is immediately switched to, so that the integrity of key information is ensured. Compared with fixed-frequency frame extraction, the on-demand resource allocation manner can more effectively save storage and bandwidth.

The application relates to a log storage method and device, computer equipment, a storage medium and a computer program product, and relates to the technical field of storage. The method comprises the following steps: in the case that the used service life of an EMMC is less than a preset service life threshold, storing logs into an intermediate storage space; compressing the logs stored in the intermediate storage space to obtain compressed logs; storing the compressed logs into the EMMC; and in the case that the space occupied by the stored logs in the EMMC is greater than a first preset space threshold, deleting the stored logs in the EMMC. Overall, although the log switch is in an open state, the corresponding preset service life threshold and the first preset space threshold of the EMMC can be used for judgment, and the judgment result is used for determining how to store the logs, so that the loss rate of the remaining service life of the EMMC is reduced. Since the log switch is continuously in the open state, manual temporary adjustment is not needed, and the operation cost is low.

The present application relates to the technical field of fabric detection, and particularly relates to a fabric flaw intelligent detection method and system based on machine vision, which comprises the following steps: performing gray-scale processing, geometric correction and denoising, illumination compensation and texture enhancement processing on the fabric image collected under controlled illumination, extracting edges and tracking contour point sequences; calculating outer angles, directionality and signed curvatures based on local point sets, combining concave-convex discrimination, key point reservation, thinning and anti-aliasing smoothing, and reconstructing continuous defect boundary trajectories; and then matching with a defect feature interval library to output defect types and boundary positioning information. Through the present application, the problems of missing detection / mis-detection and unstable positioning of defect boundaries under complex texture and illumination fluctuation conditions in the prior art are solved.

This invention discloses a method and system for epilepsy monitoring and early warning, relating to the field of medical signal processing. It solves the problems of high false alarms and false negatives, and low energy efficiency in existing monitoring technologies due to physiological artifact interference, individual differences, and continuous high power consumption. The key technical points are: first, achieving deep artifact removal of the signal through multi-angle collaborative filtering; second, constructing a personalized lightweight prediction model based on historical data similarity matching and transfer learning; and finally, employing a dynamic signal filtering and graded power adjustment mechanism. This achieves the technical effect of significantly improving the accuracy of early warning for patients with specific lesions while greatly reducing system redundancy and energy consumption.

Embodiments of the present application provide a picture search method, an electronic device, a storage medium and a program product, comprising: in response to receiving a picture search request, obtaining a text semantic feature and a keyword of a search text, the search text being carried in the picture search request; in the case of obtaining the keyword, searching a picture information set respectively matched with the text semantic feature and at least one keyword from a picture information library to obtain a candidate picture information set; and selecting a candidate picture information satisfying a preset condition from the candidate picture information set as a picture search result according to a similarity corresponding to each candidate picture information in the candidate picture information set, the similarity being a similarity between a picture global feature of the corresponding candidate picture information and the text semantic feature. The scheme can improve the picture search efficiency, reduce the calculation overhead, and also take into account the recall rate and accuracy of the picture search, and reduce the index persistence cost of the semantic vector.

The application discloses an MES-based production data management system and method, relates to the technical field of data calculation, and comprises the following steps: obtaining production data of each production manufacturing stage in a manufacturing execution system; calculating data values of the production data based on the outlying characteristics of each production data; when the data values meet preset conditions, screening first storage data which needs full storage and second storage data which needs partial storage from the production data; matching each first storage data and second storage data with a storage server based on the data values and the storage cost of the storage server, determining the corresponding relationship between the production data and the storage server, and storing the production data in each storage server based on the corresponding relationship. The application achieves the technical effects of reducing the difficulty and cost of local maintenance of a super large data table in the later stage.

The invention discloses a column bulk sample modeling method based on clear rules and concepts, which comprises the following steps: step 1, before modeling a column bulk sample, clearing the rules and concepts of reinforcing steel bars, and arranging the reinforcing steel bars for modeling the column bulk sample; and step 2, displaying the reinforcing steel bars during modeling of the column bulk sample. The invention relates to the technical field of building design, and can solve the problem that there is no steel bar clear concept and rule during column bulk sample modeling in the prior art.

The invention belongs to the field of super capacitor management, and particularly relates to a nonlinear error calibration method and system for voltage sampling of an energy storage battery cluster. The method comprises the following steps: inputting an energy storage battery cluster sampling voltage value needing to be corrected into a constructed cubic polynomial model, and calculating to obtain a corrected voltage value; the cubic polynomial model takes a sampling voltage value as an independent variable and takes a corrected voltage value as a dependent variable; the initial value of the model constant term coefficient is determined according to a sampling voltage value obtained under the condition that the real voltage value of the energy storage battery cluster is equal to 0; an initial value of a model monomial coefficient is determined through linear fitting by taking the sampling voltage values as independent variables and taking the corrected voltage values as dependent variables according to each group of obtained sampling voltage values and corresponding real voltage values; initial values of a quadratic term coefficient and a cubic term coefficient of the model are determined through three-order polynomial fitting according to the acquired sampling voltage values of each group, the corresponding real voltage values and initial values of a monomial term coefficient and a constant term coefficient of the model.

The invention discloses a real-time simplified multi-task recording and playback method and system for an unmanned surface vehicle based on double constraints, and belongs to the technical field of fishery breeding equipment control. Aiming at the problems of complicated operation and easy loss of key nodes in the prior art, a demonstration recording scheme based on double-constraint real-time simplification is provided, and a complete task including a space trajectory and an operation equipment state is synchronously constructed; and during playback, automatically sailing along the recording track and reproducing the state of the operation equipment, and supporting a single boat to store a plurality of reusable tasks. The method is suitable for automatic operation scenes of unmanned surface vessels.