Abstract: The disclosure provides an adaptive inversion method of Internet-of-things environmental parameters based on an RFID multi-feature fusion sensing model, including the following steps. Space-medium-interference is proposed as an overall concept, from the multipath propagation mechanism of electromagnetic waves, the electromagnetic wave transmission mechanism is considered. Combining with the joint characteristics of the generalized time domain, frequency domain, energy domain, and spatial domain, a global signal transfer function of RFID sensing is analyzed and derived to complete extraction of RFID sensing main features.

Abstract: A method for correcting a phase jump caused by polarization-induced fading in optical fiber phase demodulation, including the steps of: 1, selecting a demodulated phase in the case of non-depolarization as historical sample data; 2, determining an autoregressive coefficient and a moving average coefficient of the autoregressive moving average model for the demodulated phase; 3, establishing a Kalman prediction model for the demodulated phase, and deriving recursive equations of the Kalman prediction model for the demodulated phase; and 4, judging whether a jump point exists in the actual demodulated phase, determining polarization states of lights if the jump point exists, and correcting the jump point when the polarization states of the lights are in polarization orthogonality by replacing the actual demodulated phase with a predicted phase value. The disclosure ensures the correctness of subsequent vibration-based signal processing.

Abstract: The invention discloses a failure diagnosis method for a power transformer winding based on a GSMallat-NIN-CNN network.

Abstract: The disclosure relates to a phase change thermal storage ceramic having high service temperature and improved utilization rate and utilization efficiency of heat. It is prepared at a low cost with a simple, easy-to-industrially-realized method. A mixture is obtained by mixing and stirring evenly 50-85 wt % of fused mullite powder, 10-45 wt % of pretreated aluminum-silicon alloy powder, and 3-8 wt % of ball clay. A ceramic body is formed by press molding the mixture at 80-150 MPa. The ceramic body is cured at 25-28° C. and a relative humidity of 70-75 RH for 24-36 h, dried at 80-120° C. for 24-36 h, and held at 1,100-1,300° C. for 3-5 h to prepare the phase change thermal storage ceramic. The pretreated aluminum-silicon alloy powder is prepared by holding aluminum-silicon alloy powder in water vapor at 0.02-0.20 MPa for 0.5-3 h to impregnate in an alkaline silica sol and drying the impregnated powder.

Abstract: A method of storing remote sensing big data in a Hbase database. The method includes: obtaining a remote sensing image, and pre-cropping the remote sensing image based on a Google S2 algorithm; selecting a grid level based on a resolution of the remote sensing image; demarcating a coverage scope of the remote sensing image; calculating grids covered within the coverage scope; cropping the remote sensing image according to the grids, to yield a plurality of image blocks, and serializing the plurality of image blocks; establishing an Hbase table; establishing a table storage model containing RowKey, and calculating the RowKey according to attributes of an image block; and integrating data structure of multi-source remote sensing image data according to attribute expression of a zoned remote sensing image in a plurality of dimensions, and storing serialized image blocks in an Hbase database according to the RowKey.

Abstract: A time-frequency block-sparse channel estimation method based on compressed sensing includes the following steps. Step 1: A channel model is established. Step 2: According to the channel model obtained in Step 1, a sparse signal estimation value is solved by a compressed sensing method to further calculate an index set. Step 3: According to the index set obtained in Step 2, a channel matrix estimation value is solved. The method provides a generalized block adaptive gBAMP algorithm, which uses time-frequency joint block sparsity of a massive MIMO system to further optimize selection of an index set in an algorithm iteration process to improve stability of the algorithm. Then, without a specified threshold parameter, based on an F norm, an adaptive iteration stop condition is determined based on a residual, and the validity of the method is proved.

Abstract: A transformer condition evaluation method combining a FAHP-DEMATEL method and a CRITIC method is provided and includes: selecting a plurality sets of condition quantities, building a hierarchical indicator system; calculating a degree of influencing and a degree of being influenced by using the DEMATEL method on a subjective level, calculating a weight of each of a plurality of indicators of an indicator layer through the FAHP-DEMATEL method, calculating the weights of the indicators of the indicator layer through the CRITIC method on an objective level; calculating an optimal weight according to the subjective weights of the indicators and the objective weights of the indicators; and calculating condition scores layer by layer, finally determining an actual health condition of each of a plurality of transformers by combining condition level classification rules. In the disclosure, the weights are calculated based on the subjective level and the objective level.

Abstract: A time-frequency block-sparse channel estimation method based on compressed sensing includes the following steps. Step 1: A channel model is established. Step 2: According to the channel model obtained in Step 1, a sparse signal estimation value is solved by a compressed sensing method to further calculate an index set. Step 3: According to the index set obtained in Step 2, a channel matrix estimation value is solved. The method provides a generalized block adaptive gBAMP algorithm, which uses time-frequency joint block sparsity of a massive MIMO system to further optimize selection of an index set in an algorithm iteration process to improve stability of the algorithm. Then, without a specified threshold parameter, based on an F norm, an adaptive iteration stop condition is determined based on a residual, and the validity of the method is proved.

Abstract: A method and a system for power equipment diagnosis based on windowed feature and Hilbert visualization are provided, which belong to the field of power equipment fault diagnosis. The method includes: obtaining an original data set of monitoring data containing power equipment fault features; introducing windowed feature calculation considering logarithmic constraints to process data to obtain a feature sequence; using Hilbert visualization method for further processing to obtain a Hilbert image data set used to train and verify a convolutional neural network; and finally directly inputting newly obtained test sample data after windowed feature calculation and Hilbert visualization processing into the trained network for fault diagnosis and location.

Abstract: A thermoplastic polymer-based composite material and a preparation method thereof are provided. The thermoplastic polymer-based composite material is obtained by impregnating a reinforcing material with a mixture or an oligomer of an epoxy resin, a bisphenol A/F, and a catalyst and then performing an in-situ polymerization. The thermoplastic polymer-based composite material is less expensive to produce, has an optimal impregnation effect, excellent secondary processing performance, high heat resistance, desirable mechanical properties and excellent overall performance.

Abstract: The present disclosure provides a lignite char supported nano-cobalt composite catalyst and a preparation method thereof. In the method, lignite is used as a raw material, and a lignite char supported high dispersion nano-cobalt composite catalyst is obtained by a modified impregnation method followed by a high temperature pyrolysis process. The composite catalyst prepared by the present disclosure has a hierarchical pore structure, a high specific surface area, and uniformly dispersing nano-sized cobalts on the lignite char with controllable particle size, so that the obtained catalyst has an excellent catalytic activity for low-temperature CO2 methanation; moreover, the preparation process is simple and feasible, the raw materials used are cheap and easily available. Therefore, the composite catalyst is very suitable for industrial production and application.

Abstract: A multi-police-officer collaborative round-up task allocation and path planning method under the constraint of a road network, including: acquiring a road topological map G of the road network; acquiring police officer distribution information and information of a task target location in the G of the road network; according to the position where the task target appears, a set of nodes that the task target is next likely to reach are determined; acquiring the movement speed of police officers and the task target; confirming a set of police officers to be assigned according to an interception point set and the movement speed of the police officers and the task target; calculating the congestion degree of each intersection in the interception point set; building a multi-police-officer collaborative round-up task allocation and path planning optimization model; solving the optimization model to obtain a multi-police-officer collaborative round-up task allocation and path planning scheme.

Abstract: A method and a system for predicting a gas content in transformer oil based on a joint model are provided and belong a field of transformer failure prediction. The method includes the following: determining a type and a time series of gas to be predicted related to a failure, processing an original series by adopting empirical mode decomposition (EMD) and local mean decomposition (LMD) for a non-stationarity characteristic of a dissolved gas concentration series in oil; performing normalization on each sub-series component, dividing a training sample and a test sample; and establishing a deep belief network (DBN) prediction model for each of the sub-series components for training, performing superposition and reconstruction on the established DBN prediction model to perform characteristic extraction and classification on multi-dimensional data of the failure, evaluating prediction performance of the prediction model through calculating an error index.

Abstract: A method and a system for identifying third-order model parameters of a lithium battery based on a likelihood function are provided, which relates to a method for estimating battery model parameters of a lithium battery under different temperatures, different system-on-chips (SOCs), and charge-discharge currents. The method includes the following steps. A third-order battery model of the lithium battery is established. A battery model output voltage Ud and a total battery current I under different temperatures, different SOCs, and charge-discharge currents are collected. The likelihood function is adopted to construct an identification model, and the collected data is substituted into the identification model to calculate the battery model parameters. Identified parameters are substituted into the third-order battery model to obtain a battery terminal voltage to be compared with a measured terminal voltage.

Abstract: A method and a system for online monitoring of a health status of an insulated-gate bipolar transistor (IGBT) module are provided, which belong to the field of IGBT status monitoring. In order to overcome the inability to real-time monitor health statuses of existing IGBT modules, the method of the disclosure includes the following steps. A current sensor is used to measure a collector current of each IGBT module. A collected current value is substituted into a simulation model to obtain a current imbalance rate. A failure module is located according to the current imbalance rate and temperature to achieve the objective of monitoring an IGBT health status.

Abstract: A method and a system for fault diagnosis with small samples of power equipment based on virtual and real twin spaces are disclosed, which belong to the field of fault diagnosis of power equipment. The method includes: test samples containing different locations, types and severity levels of fault of power equipment are acquired to form a real physical space; a virtual mirror space is acquired by simulation according to a simulation model of the equipment to be diagnosed; the training set in the real physical space is spatially integrated with the sample set in the virtual mirror space to obtain a training sample set in the twin spaces; the training sample set in the twin spaces serves as the supplement to the training set in the real physical space, and the fault type and fault location serve as diagnostic labels to be input to the deep neural network for training.

Abstract: Provided are a time domain channel prediction method and a time domain channel prediction system for an OFDM wireless communication system, which relate to the technical field of adaptive transmission in wireless communication. Frequency domain channel information is converted into time domain tap information by inverse Fourier transform. With respect to each time domain tap information, tap information prediction based on an extreme learning machine is realized, and finally predicted tap information is converted into frequency domain channel information by Fourier transform. To improve a generalization ability of a channel predictor, an output weight of the extreme learning machine is punished by a combination of l2 regularization and l1/2 regularization. The disclosure may provide satisfactory prediction performance and may output a sparse output weight, which reduces the requirement for memory storage. The disclosure ensures adaptive transmission and adaptive coding of wireless communication.

Abstract: A method and a system for selecting important delay taps of channel impulse response are provided, which belong to the field of adaptive transmission technology of wireless communication. The method performs local predictability estimation on all delay taps in the channel impulse response in wireless communication, thereby selecting the important delay taps in the channel impulse response. The disclosure uses recurrence rates of the delay taps to estimate local predictability of the delay taps. Noise delay taps are distinguished from the important delay taps through the local predictability of the delay taps, which improves the identification rate of the important delay taps of the channel impulse response in wireless communication. The disclosure may implement the selection of the important delay taps of the channel impulse response, which provides guarantee for implementing adaptive transmission and adaptive coding of wireless communication.

Abstract: A method for blockchain payment channel network multi-path routing based on a genetic algorithm includes: S1, constructing a directed graph according to a structure of a payment channel network; S2, based on the payment channel network, generating an initial population; S3, taking a total fee charge of the k payment paths corresponding to the each individual as an adaptability, and selecting a parent based on the adaptability; S4, based on the adaptability, performing a cross operation and a mutation operation on the parent; S5, when a population converges or a number of iterations reaches a preset threshold, determining the total fee charge for the each individual in a last-generation population, and selecting an individual with the smallest total fee charge as an optimal solution under a current k value; and, S6, selecting a target payment path from a plurality of selected payment paths.

Abstract: A titanium-containing calcium hexaaluminate material and preparation method thereof is disclosed. The technical solution is: using 60˜80 wt % alumina micro powder, 5˜20 wt % calcium-containing micro powder, 10˜20 wt % titania micro powder and 1˜10 wt % manganese oxide micro powder as raw materials, blending the raw materials evenly in a planetary ball mill to obtain a blend, machine pressing the blend at 100˜200 MPa to obtain a green body, drying the green body at 110˜200° C. for 12˜36 h, and incubating the dried green body at 1500˜1800° C. for 1˜8 h to obtain the titanium-containing calcium hexaaluminate material. The present disclosure has low cost and simple process, and the prepared titanium-containing calcium hexaaluminate material has the characteristics of good chemical stability, high thermal shock resistance and strong melt resistance to titanium-aluminum alloy.