52results about How to "The result is accurate and effective" patented technology

The invention discloses an automobile crane hoisting simulation method on the basis of the virtual reality, which is characterized by comprising the following steps of: a first step of newly constructing a project and setting a project name for the new project; a second step of constructing a crane mode; a third step of adding hoisted objects and barriers; a fourth step of setting a hoisting target point; and a fifth step of implementing the hoisting simulation operation by keyboard operation until the hoisted objects reach the hoisting target point, completing hoisting and storing the operation process from a hoisting initial point to the hoisting target point. The construction of the hoisting model adopts a custom configuration mode or a mode of inquiring and adding on the basis of the working condition. The automobile crane hoisting simulation method on the basis of the virtual reality is easy to implement and can accurately simulate the hoisting operation process of a crane.

The invention provides a temperature sensor self-testing device and method. The method comprises the following steps: performing differential processing on a temperature data sequence of a train undernormal conditions to obtain a segmented standard deviation sequence, and performing statistical analysis on the standard deviation sequence to obtain an abnormality detection threshold; performing differential processing on a real-time input temperature data sequence to obtain segmented standard deviation sequence; judging whether the segmented standard deviation sequence is abnormal based on thethreshold and the standard deviation sequence; if a certain segment of segmented standard deviation sequence is greater than or equal to the threshold, judging that the segment of temperature deviation sequence is abnormal, and entering the next step, otherwise, indicating that the sensor is normal; judging the distribution consistency between the abnormal certain segment of temperature deviationsequence, a normal reference sequence and the previous adjacent time period of temperature deviation sequence; if the consistency is present, judging that the sensor is normal, otherwise, judging that the sensor is abnormal. By adoption of the temperature sensor self-testing device and method provided by the invention, the technical problems that fast and effect self-testing cannot be performedon the temperature sensor in the prior art, and the safe and efficient running of the train cannot be guaranteed are solved.

The invention discloses a multi-dimensional force sensor calibration experiment data fitting method based on a genetic algorithm. The method comprises the following steps: (1) carrying out a multi-dimensional force sensor static calibration experiment, and recording each dimension of input force/torque value of a multi-dimensional force sensor and each path of output voltage value under the action of the input force/torque value respectively; (2) deducing a coefficient solution formula of a sensor coupling error theoretical model; and (3) solving the error coefficient solution formula in the step (2) based on the genetic algorithm by using MATLAB (Matrix Laboratory) software, and outputting an undetermined coefficient solution of global optimum. According to the multi-dimensional force sensor calibration experiment data fitting method based on the genetic algorithm, random global search and optimization of the genetic algorithm can be used for data fitting of the multi-dimensional force sensor calibration experiment; the algorithm is simple and reliable and a result is accurate and effective; and a self-adaptive searching process of an optimal fitting curve of the experiment data is finished, so that the precision of a decoupling algorithm is improved.

The invention discloses P2P flow optimization method and system based on a distributed index server architecture. The method comprises the following steps of: on the basis of the P4P concept, partitioning the network into regions and deploying policy servers and positioning servers by an Internet service provider, and deploying index servers in each region by a P2P content provider; positioning the affiliated region and the local index server by a terminal in each region; when possessing new resources, reporting information of the new resources to the local index server by the terminal in each region, and maintaining index information established by the information of the new resources by the index server and acquiring policy matrix information by the aid of the policy server; downloadinga seed file from a seed server by the terminal and transmitting request index information to the local index server according to the hash value in the seed file, and proportionally returning the index information to the terminal by the local index server according to the policy matrix; and getting connection with the corresponding terminal by the terminal according to the returned index information and downloading the resources.

The invention discloses an electroencephalogram and electrocardiogram-based fatigue detection method of an electrocardiogram sensor embedded into a steering wheel. The method performs fatigue detection by constructing a product fuzzy convolutional network. The method specifically comprises the following steps: S1, acquiring electrocardiogram data through an electrocardiogram detection chip, and acquiring electroencephalogram time series data by using an electroencephalograph; S2, processing the electroencephalogram time series data by adopting a fuzzy neural network which contains a laminationand has feedback, and acquiring electroencephalogram characteristic; S3, establishing a depth feature extraction network based on a one-dimensional convolutional neural network framework to extract fatigue features of the electrocardiogram data, and generating an electrocardiogram feature sequence; S4, designing a fusion network, inputting the electrocardiogram characteristic sequence and the electroencephalogram characteristic at the same time, fusing the two signals together, and giving a prediction value; and S5, performing optimizing by using an adaptive moment estimation algorithm, and training a network model. The method can reduce the noise and improve the detection precision, the limitation of the fuzzy neural network on the feature dimension of the input data is reduced by introducing the lamination, and the accuracy of the classification result is improved.

A method of modeling seismic wave-field data in order to suppress near-surface and sub-surface related multiple reflection signals is provided. The reflection signals include main primary reflection signals, main random noise signals, main multiple reflection signals, residual primary reflection signals, residual random noise signals, and residual multiple reflection signals. Main random noise signals are separated from the reflection signals using a frequency-wavenumber domain method to provide data having suppressed main random noise. Main primary reflection signals are separated from the data having suppressed main random noise using frequency-wavenumber filtering and weighted median filtering to provide data having suppressed main random noise and main primary reflections. Multiple reflection signals are modeled using parabolic path summation on the data having suppressed main random noise and main primary reflections.

The invention discloses a remote self-powered pipe fluid parameter monitoring terminal, and the terminal comprises a fluid power generation device and an energy storage monitoring device. The energy storage monitoring device comprises an intelligent control panel and a rechargeable battery. The intelligent control panel comprises a microcontroller, a wireless communication module, and a composite sensor. The terminal converts fluid energy into electric energy through the fluid power generation device, stores the electric energy in the rechargeable battery, and achieves the technical effects of self-power and energy storage. Through a WIFI module or a GPRS module, the terminal achieves a technical effect of wireless remote transmission. The terminal analyzes the flowing speed of fluid through the microcontroller, collects the temperature and pressure information of the fluid through the composite sensor, achieves a technical effect of monitoring the parameters of pipe fluid, saves a fluid monitoring module, enables the structure to be more simple, is low in cost, and is smaller in size.

The invention relates to a highly-maneuvering target micro cycle calculation method and a highly-maneuvering target micro cycle calculation system. The method comprises the following steps: step 1, acquiring an echo signal x of a target, wherein x={x1, x2,..., xi,..., xN}, i=1, 2,..., N, N is the number of pulses accumulated, and xi is the value of the echo signal at the ith point; step 2, calculating the overall translation estimated value of the target according to the echo signal of the target; step 3, using the overall translation estimated value of the target to compensate overall translation to obtain a micro signal after compensation; and step 4, estimating the cycle of the target according to the micro signal after compensation. According to the method of the invention, by processing Doppler ambiguity of the target and compensating the overall translation of the target, the estimated micro cycle of the target is more accurate and effective.

The invention provides an optimal scheduling method for a power system to which renewable energy is accessed. Power data of the power system in a research area are acquired, and optimal power flow calculation is carried out; power supply flexibility evaluation time scale parameters are selected; a power supply flexibility optimal model is built; and according to the result of the optimal power flow calculation and the power supply flexibility optimal model, the power supply-side flexibility optimal result is acquired and outputted. According to the method of the invention, acquisition of the optimal combination of the power system power supply flexibility and the operation cost in various conditions is realized, the optimal process is simple and reliable, the optimal result is accurate and effective, an effective theoretical basis is provided for power system operation and scheduling, and the operation stability of the power system is thus improved.

The embodiment of the invention provides a genome sequencing data sequence assembling method. By means of the method, the advantages of denovo sequencing and the advantages of re-sequencing can be integrated, and genome sequencing data sequences are effectively assembled. A drafted sequence traversal path of the genome sequencing sequences obtained based on a reference sequence and generated after sequencing data are mapped to the reference sequence in a comparing mode and an overlapping relation set of the genome sequencing data are known. The set comprises a determined relation subset and an undetermined relation subset. The method includes the steps that after the sequencing data sequences are mapped to an affinis reference genome in a comparing mode, the drafted data traversal path of the genome sequencing sequences is obtained based on the reference sequence, all nodes in the drafted sequence traversal path are checked one by one; iterated revision is conducted on the drafted sequence traversal path according to the connection relation of the determined relation subset and/or the undetermined relation subset in the overlapping relation set, and the overlapping relation set is updated; the next node is checked based on the updated drafted sequence traversal path and the updated overlapping relation set till the last node is checked.

The invention discloses a method for testing the content of glycol phenylate. The method comprises the following steps: preparing glycol phenylate standard solutions of different concentrations, with water as blank control, testing the absorbance values of the standard solutions at the wavelength of 270nm, establishing a coordinate system with the absorbance values and standard concentration as coordinates, drawing a standard curve, testing the absorbance values of the glycol phenylate standard solutions at the wavelength of 270nm, and performing linear regression on the absorbance values by virtue of the standard curve so as to obtain the concentration of the solution to be tested. In such a mode, the method for testing the content of glycol phenylate is to rapidly test the content of glycol phenylate in a solution by an ultraviolet spectrophotometry method. The method is short in testing time, accurate and effective in result, easy to perform, free of expensive experiment instruments or reagents, relatively low in cost and easy to popularize and used in middle and small laboratories.

The invention discloses a method for mining a friend relationship network of a customer in an E-commerce website. Offline friend relationships of the customer are speculated according to historical sales records of commodities. According to the method for mining the friend relationship network of the customer in the E-commerce website, the offline friend relationship network is mined according to online consumption records of a user, the customer does not need to actively manage friend relationships, and the offline friend relationships are obtained in a mining mode through a system.

In various examples, a virtualized computing platform for advanced computing operations including image reconstruction, segmentation, processing, analysis, visualization, and deep learning may be provided. The platform may allow for inference pipeline customization by selecting, organizing, and adapting constructs of task containers for local, on-premises implementation. Within the task containers, machine learning models generated off-premises may be leveraged and updated for location specific implementation to perform image processing operations. As a result, and by using the virtualized computing platform, facilities such as hospitals and clinics may more seamlessly train, deploy, and integrate machine learning models within a production environment for providing informative and actionable medical information to practitioners.

The invention relates to a non-contact medical partition access control system, which comprises a temporary storage channel, wherein a first identification module is arranged at the inlet position ofthe temporary storage channel, a second identification module is arranged in the temporary storage channel, a third identification module is arranged at the outlet position of the temporary storage channel, and the first identification module, the second identification module and the third identification module are respectively connected with a main controller. The invention provides a non-contactmedical partition access control system and method, wherein on the premise that no physical contact with a user exists, identity recognition and confirmation are conducted on the user, the user is disinfected after air showering, and then the user is allowed to enter, so that in a non-contact environment, even if the user wears the protective clothing, identity recognition and people number confirmation and disinfection can be realized, the infection possibility is effectively reduced, the use safety of the user is ensured, and recognition is convenient and accurate.

The invention discloses a method for quantifying the new-old asphalt interface fusion degree based on the performance of an asphalt mixture. The method comprises the steps of pretreating RAP, and determining synthesis design gradation and the optimal asphalt consumption; screening conventional performance indexes capable of being used for quantitatively calculating the new-old asphalt interface fusion degree DOB, and determining the change relationship of the performance indexes along with the asphalt consumption; determining performance index test results P1, P2 and P3 of the concrete sampleand effective asphalt contents x1, x2 and x3 in a black stone state, an actual regeneration state and a 100% complete fusion state of a new-old asphalt interface; and calculating to obtain the new-oldasphalt interface fusion degree in the actual regeneration state according to the effective asphalt content proportion relationship in different states. According to the method, high-end instrumentsand equipment are not needed, the new-old asphalt interface fusion degree DOB of the recycled mixture can be obtained through a mix proportion design process in a simple and crude engineering field laboratory, and engineering field construction personnel can conveniently judge the RAP regeneration performance in time.

The invention relates to a cluster type electrical potential safety hazard pre-judgment method based on an artificial neural network. The method comprises steps of collecting monitoring data of the electrical safety monitoring points as training data; preprocessing to obtain sample training data, using electrical safety monitoring points as neurons of the artificial neural network; inputting the preprocessed sample training data into an artificial neural network to obtain an expected output vector and the actual output of the current artificial neural network, calculating the partial derivative of an error function to each neuron of an output layer, correcting a connection weight and a threshold value by using the partial derivative and the output of the neuron of an input layer, and judging whether to continue iteration or not by using a global error; and after training is completed, judging whether electrical potential safety hazards exist or not according to real-time acquired data.On the basis of relevance of an existing power grid, the electrical safety early warning effect under a cluster type monitoring mode is achieved, along with increase of the sample size and the self-learning time, the pre-judgment result and early warning are more accurate and effective, electrical safety hidden dangers are found out as soon as possible, and the life and property safety of peopleis effectively protected.