1181 results about "Narrowband" patented technology

The invention discloses a wide-narrow integrated ad hoc network method, and belongs to the technical field of network communication. The method comprises the following steps: a network node generates dynamic topology information based on a narrow-band communication module periodic broadcast state beacon; according to the link quality and the node load in the topological information, coordinating the resource allocation of broadband and narrowband channels by adopting a load-aware time slot allocation algorithm; data are classified according to service types, broadband data are modulated and transmitted by adopting orthogonal frequency division multiplexing, and narrowband control instructions are modulated and transmitted by adopting differential phase shift keying; when the link quality is deteriorated, the link is switched, and the transmitting power and the frequency band parameters are dynamically adjusted; and adaptive switching and data distribution of wide and narrow band communication modes are realized. According to the method, the problems of difficulty in topology maintenance and low bandwidth and narrowband resource allocation efficiency in a high-dynamic network scene are solved, the network adaptability, the anti-interference capability and the resource utilization rate are remarkably improved through a dynamic cooperative bandwidth and narrowband communication mode, and meanwhile, the protocol switching overhead and energy consumption are reduced.

The invention provides a digital twin hydrological station system which is characterized in that the system comprises a layered architecture system and a multi-dimensional safety protection mechanism, the layered architecture system is composed of a sensing layer, a transmission layer, a data layer, a model layer, an application layer and a display layer from bottom to top, the sensing layer comprises a heterogeneous hydrological monitoring equipment cluster, and the transmission layer comprises a heterogeneous hydrological monitoring equipment cluster. The equipment cluster is provided with a water level sensor array, a Doppler flowmeter, a spectrum water quality analyzer and an environment monitoring terminal, and total element acquisition of hydrological element data, equipment operation state data and environment data is realized; the transmission layer adopts a hybrid communication protocol stack, integrates an ultra-short wave communication module, an NB-IoT narrowband communication module and an optical fiber communication module, and constructs a multi-path redundant transmission channel, and a key data transmission channel is configured with a dynamic link selection algorithm; the data layer comprises a distributed storage architecture, adopts a mixed storage mode of a relational database cluster and an unstructured database, and is internally provided with a data cleaning engine and a spatio-temporal data fusion module.

The invention belongs to the field of agricultural automation and intelligent equipment, and discloses a portable measuring method and device for pork intramuscular fat content. By screening the characteristic wave bands related to the fat content and selecting the corresponding narrow-band LEDs, the accuracy and effectiveness of the multispectral image are improved. And meanwhile, through multi-modal image fusion analysis, in combination with the RGB image, the black-and-white image and the multi-spectral image, the precision of target segmentation and content prediction is improved. And establishing an end-to-end content prediction model by adopting a mode of combining a CNN and an MLP network. Meanwhile, the FCNN network is used for processing the spectral data, the tedious spectral data preprocessing process is omitted, the advantages of the spectral data and the RGB image are fully played, and a new thought and method are provided for the field of spectral modeling. The technical scheme has the advantages of portability, high efficiency, accuracy and the like, provides powerful support for pork nutrition evaluation, and can provide reference for determination of the fat content of other livestock and poultry meat.

The invention discloses a high-precision three-dimensional first-motion wave travel time chromatography velocity inversion method and device, and relates to the field of seismic exploration. A multi-template windward difference algorithm and an undulating surface narrow-band continuation strategy are adopted to determine three-dimensional global forward first-motion wave propagation travel time; ray tracing is carried out according to the three-dimensional global forward first-motion wave propagation travel time, and a first-motion wave propagation path and a Frechet differential quotient matrix are obtained; establishing a three-dimensional initial inversion velocity field constrained by micro-logging information; constructing a tomographic inversion equation based on the apparent slowness constraint and the regularization constraint according to the travel time residual error and the Frechet differential quotient matrix; and solving the tomographic inversion equation to obtain a tomographic inversion slowness solution, and converting the slowness solution into a velocity solution. The problem of non-uniform travel time delay of seismic wave propagation of a complex near-surface structure can be solved, a more accurate superficial layer velocity structure can be obtained, and the quality of seismic data processing and imaging inversion can be improved.

The invention relates to the field of partial discharge source positioning, in particular to a large-scale substation multi-partial discharge source positioning method and system, and the method comprises the steps: forming a sensor array through a movable ultrasonic sensor and an ultrahigh frequency sensor, and collecting ultrasonic signals and ultrahigh frequency signals generated by partial discharge sources respectively; denoising the collected discharge signals, and calculating the distance between the partial discharge source and the sensor array; denoised ultrasonic array signals are divided into a plurality of narrowband signals by discrete Fourier transform, weighted covariance matrixes of all narrowband signals after focusing transformation are subjected to mean value calculation to obtain weighted covariance matrixes of focusing frequency points, and the weighted covariance matrixes of the focusing frequency points are subjected to unitary transformation to obtain a weighted covariance matrix of a plurality of narrowband signals. Estimating the number of partial discharge sources according to a signal source number estimation equation; and carrying out spectrum peak search in a specified space parameter range according to a preset step length to obtain a space parameter corresponding to each partial discharge source, and obtaining a partial discharge source coordinate in a three-dimensional space.

The invention belongs to the technical field of sleep respiratory disease detection, and relates to a sleep apnea identification method based on a hybrid neural network, which comprises the following steps of: sensing human sleep in a bed surrounding environment by using a millimeter wave radar, and positioning a thoracic cavity position by adopting spatial two-dimensional analysis; the problem that interference exists in radar sign signal extraction of different targets at the same distance is solved. And a respiration signal Shannon entropy is constructed as an iterative index of the whale optimization algorithm, and the index is minimized to realize iterative optimization of variational mode extraction parameters, so that different respiration states are matched with different parameters, and thus a dominant frequency narrowband respiration signal is accurately extracted. A breathing time-frequency energy diagram obtained by data processing is used as input, and a CNN network and a bidirectional long-short-term memory module are used together to construct a feature extraction module, so that the method can recognize the change trend of frequency along with time, capture more comprehensive features, and recognize target sleep apnea more accurately. In addition, the hybrid network enables accurate classification of unmanned scenarios, apnea, hypopnea, and normal respiration.

The invention relates to the technical field of pipeline detection, and provides a non-contact pipeline fluid flow velocity measurement method based on a frequency wavenumber domain spatial spectrogram, and the method comprises the steps: collecting a turbulence signal in a pipeline through a piezoelectric film sensor; carrying out snapshot number segmentation on the turbulence signal to obtain a plurality of segmented turbulence time domain signals; fourier transform and narrowband signal processing are carried out on the segmented turbulence time domain signals, and a spatial spectrum corresponding to each narrowband signal component is obtained; constructing a three-dimensional frequency-wave number domain spectrogram according to the spatial spectrum function; and according to the three-dimensional frequency-wavenumber domain spectrogram, calculating the flow velocity of the pipeline fluid. According to the method, a three-dimensional spectrogram characteristic space is constructed through conjoint analysis of the frequency and the wave number, the angle, distance and frequency characteristics of the turbulence signals are decoupled through spatial spectrum estimation methods such as the MUSIC algorithm, multipath interference and noise are effectively restrained, the flow speed of fluid in a pipeline can be accurately estimated, and limitation in a traditional method is overcome.

The invention discloses a reliable data transmission method for a narrowband satellite internet of things. The method comprises the following steps: defining a reverse data frame format; link state monitoring and quantification: continuously or periodically monitoring a quality index representing a link of the satellite Internet of Things terminal; continuously or periodically monitoring the uplink state of the satellite Internet of Things terminal by using a terminal link state evaluation module of the satellite master station baseband system; link state grading: dividing the current link state into a plurality of predefined state grades; identifying the transmission rate of the satellite Internet of Things terminal; constructing a self-adaptive confirmation window strategy: a sending end of the satellite Internet of Things terminal uses a confirmation window with a dynamic window size; the number of data packets confirmed by the transmitted ACK / NACK message, namely the window size, is dynamically adjusted according to the currently sensed link state and the identified terminal transmission rate; the performance of the whole system is improved.

The invention belongs to the technical field of intelligent engineering management, and discloses an automatic monitoring and control method of an engineering management system based on the Internet of Things. According to the method, a four-layer Internet of Things architecture comprising a sensing layer, a network layer, a platform layer and an application layer is constructed, and the four-layer Internet of Things architecture is uploaded to a cloud platform through a 5G / narrowband Internet of Things dual-mode transmission channel. A digital twinborn technology is innovatively adopted to construct a three-dimensional visual engineering model, intelligent identification and prediction of abnormal working conditions are realized through a machine learning algorithm, and a multi-stage linkage control mechanism is established. And when construction deviation or equipment failure is detected, the system automatically generates an optimization control strategy and issues the optimization control strategy to the execution terminal, so that accurate regulation and control of the construction machinery and intelligent pushing of early warning information are realized. According to the method, a manual inspection mode of traditional engineering management is broken through, full-process automatic supervision is realized through data fusion analysis and closed-loop control, the construction quality supervision precision is effectively improved by more than 30%, the safety accident rate is reduced by 50%, and the engineering management efficiency is remarkably improved.

The invention relates to the technical field of image focus detection, in particular to a fiber endoscope image focus detection method and system, and the method comprises the following steps: providing a data quality guide interface; capturing narrow-band light images of the endoscope away from a first preset position and a second preset position of the intestinal wall in the axial movement process, calculating brightness gain values of a blue light channel and a green light channel, calculating an asymmetric scattering correction coefficient, and updating indication of color information calibration integrity; tracking the pixel moving speed of the interferent in the view in the propulsion operation process, calculating the relative depth of the interferent, and updating the indication of the validity of the depth data of the interference layer; identifying the image area which is not shielded by the interferent, and updating the indication of the information coverage degree of the background area; triggering an image synthesis operation; performing color compensation on the image information of the image area which is stored in the background canvas and is not shielded by the interferent; reconstructing a clear image; and performing focus detection on the clear image. The method improves the accuracy of focus detection.

The invention provides a power grid frequency detection method, system and device and a medium, and the method comprises the steps: carrying out the narrowband signal decomposition of an obtained input voltage signal of a power grid through a null-space tracking algorithm, and obtaining a fundamental main mode component of the input voltage signal; performing low-pass processing on the fundamental wave main mode component to obtain a fundamental wave signal of the fundamental wave main mode component; performing discrete Fourier transform on the fundamental wave signal to obtain phase information of the fundamental wave signal; according to the phase information of the fundamental wave signal, calculating phase deviation information of the fundamental wave signal in pre-selected adjacent cyclic waves to obtain frequency estimation information of the power grid; according to the invention, narrow-band decomposition is carried out on an input voltage signal through a null-space tracking algorithm, so that a fundamental main mode can be accurately extracted; and phase deviation information can be determined based on discrete Fourier transform, so that when the interference frequency of the power grid is close to the fundamental frequency, high separation precision can be kept, and the accuracy of power grid frequency estimation can be improved.

The invention discloses a rail transit multi-network integration method based on a digital trunking technology, relates to the technical field of communication, and aims to solve the problem that a traditional narrowband trunking system cannot meet the requirements of voice and data comprehensive bearing and vehicle-ground large-bandwidth service real-time transmission. The method comprises the following steps: constructing a time division duplex long-term evolution broadband digital trunking unified bearing platform; an intermediate media access control layer fusion architecture is deployed, and seamless mobility management of the heterogeneous network is realized through unified authentication and multi-link aggregation; an intelligent vertical switching algorithm based on prediction and multi-criterion decision is introduced, a bidirectional long-short-term memory network model is utilized to predict a network state trend, and an improved entropy weight method and an analytic hierarchy process are combined to dynamically select an optimal access network according to service requirements. According to the invention, the network operation efficiency and the user experience can be obviously improved, and high reliability and high service quality of the rail transit communication system are ensured.

The invention discloses a space-air-ground integrated broadband narrowband adaptive emergency communication system, and relates to the technical field of space-air-ground integrated communication, and the system comprises a communication management center, a spectrum environment sensing module which is used for monitoring the use condition of each spectrum bandwidth through spectrum monitoring equipment disposed at each layer of space, air and ground, and sending the use condition of each spectrum bandwidth to the communication management center; comprising spectrum utilization rates of broadband and narrowband services, and constructing a dynamic spectrum map; and the demand prediction module is used for predicting spectrum demands of future broadband and narrowband services in combination with the historical communication data and the current network state. Through the dynamic spectrum allocation technology and in combination with 5G waveforms, spectrum resource allocation can be adjusted in real time according to actual service requirements and network conditions, resource waste or insufficiency in a traditional fixed spectrum allocation mode is avoided, the utilization rate of spectrum resources is remarkably improved through intelligent spectrum management, and the spectrum allocation efficiency is improved. The efficient cooperative work of broadband and narrowband services is ensured, and reliable spectrum guarantee is provided for emergency communication.

The invention discloses a polymorphic sleep data fusion self-attention sleep system and method. The system comprises a data acquisition module which is responsible for acquiring environmental data and physiological data of a user; the signal preprocessing module is used for performing segmentation, normalization and de-noising processing on the collected EEG and EOG signals; the frequency division multiplexing module is used for decomposing the preprocessed signal frame into a plurality of narrowband signals by using a frequency division multiplexing technology; the feature extraction module is used for extracting features from the decomposed narrowband signals; the model training module is used for training a model by utilizing the feature set; the sleep staging module is used for performing real-time or offline sleep staging through the trained model; the sleep quality evaluation module is used for calculating a sleep quality index based on a sleep staging result; the correlation analysis module is used for performing correlation analysis on the relationship between different sleep stages and the sleep quality indexes to generate a quality evaluation model; and the early warning system module is used for setting an early warning threshold value according to the sleep quality evaluation result and the quality evaluation model.

A feature extraction and simulation method for sound signals of an autonomous navigation ship tunnel thruster. A digital filter is used to process measured signals to remove spike signals, and the characteristics of residual wideband floor noise signals are analyzed. A finite impulse response filter is designed, and the impulse response of the finite impulse response filter is convolved with white Gaussian noise, so that simulated noise is matched with frequency-domain characteristics of floor noise signals. A spike signal amplitude is calculated, and a group of sine wave signals having a corresponding frequency are generated as spike signals. Narrowband spike signals and wideband floor signals are superposed and synthesized into simulated tunnel thruster noise. A feasible solution is provided for research and analysis of sound signals of a tunnel thruster. The sound characteristics of the tunnel thruster are accurately extracted, a predicted sound level is improved, and a tunnel thruster sound source database is established, thus providing valuable data support for signal quality analysis of a ship autonomous navigation system, fault diagnosis and improvement of a control strategy for the tunnel thruster.

The invention discloses an ultra-high-speed imaging device based on acousto-optic filtering modulation. The ultra-high-speed imaging device comprises a spectrum modulation system, a spectrum imaging system and a data processing system. The spectrum modulation system utilizes an acousto-optic tunable filter (AOTF) to dynamically modulate broadband continuous spectrum light, narrow-band illumination light which rapidly changes along with time is generated, and time information of a dynamic scene is effectively mapped to a spectrum dimension. And the spectral imaging system images the spectral coded dynamic scene to the hyperspectral camera to realize acquisition of spectral space-time information. The data processing system performs spectral crosstalk correction, channel separation and demosaicing reconstruction on the acquired original mosaic image, and recovers a time sequence image according to a spectrum-time mapping relation, thereby realizing single-shot superspeed imaging in a dynamic process. The device has the advantages of being simple and compact in structure, flexible in time window, high in imaging fidelity and the like, and has wide application prospects in the fields of rapid dynamics such as microfluidics, laser processing and ultrafast physics.

The invention discloses an all-dielectric structure type broadband wave-absorbing metamaterial and a design method thereof. The all-dielectric structure type broadband wave-absorbing metamaterial comprises a substrate and a plurality of resonators, the plurality of resonators are periodically and uniformly arrayed on the surface of the substrate, the adjacent resonators are connected with each other, each resonator comprises a pyramid structure unit and a grid structure unit, the pyramid structure units are nested in the grid structure units to form a pyramid-grid composite resonator, and the substrate and the resonators are both made of a high dielectric loss composite material. Based on the brand new design angle of wave absorbing performance complementation, the limitation of the wave absorbing performance of a single structure is broken through, the wave absorbing performance is improved from the microstructure level, meanwhile, efficient electromagnetic wave energy absorption is achieved in a wider frequency range, multi-stage dissipation and broadband impedance matching of incident electromagnetic waves are achieved, and the wave absorbing performance is improved. And the technical limitation of thickness constraint and narrow-band response of the traditional wave-absorbing material is broken through.

The invention relates to the technical field of power internet of things, in particular to a broadband / narrowband self-adaptive switching power internet of things communication system and a control method, which intelligently identify the priority and quality of service (QoS) requirements of different services by collecting network states, terminal states and service flow data in real time. And an optimal communication mode switching strategy is dynamically generated based on a pre-trained machine learning model, seamless switching of broadband and narrowband communication links is realized, and the decision accuracy is continuously improved through a feedback optimization mechanism. According to the method, the problems that a traditional electric power Internet of Things communication mode is fixed and single and cannot intelligently adapt to services and network states are effectively solved, the system communication reliability is remarkably improved, the transmission time delay and energy consumption are reduced, and high-adaptability and high-reliability intelligent communication guarantee in a complex electric power scene is achieved.

The invention relates to a narrowband minimum mean square error echo suppression method introducing a complex neural network, and belongs to the field of adaptive echo cancellation. An existing neural network method still has the problem of inaccurate priori knowledge modeling, and phase information in complex signals is not fully utilized. According to the method, a plurality of DNNs are adopted to carry out modeling and estimation on step length, loudspeaker nonlinear distortion and error signals respectively. And the adaptive capacity to an echo channel in a complex environment is improved by utilizing the efficient parameter learning capacity of a plurality of neural networks. According to the method, the phase information of complex data is fully utilized, the nonlinear distortion problem of the loudspeaker can be effectively suppressed, meanwhile, the small model parameter quantity is kept, efficient echo suppression is achieved, high practicability and hardware adaptability are achieved, and the method is suitable for various practical application scenes.

The invention relates to the technical field of chip verification, in particular to a verification method of a low-power-consumption narrowband communication chip based on a UVM (Universal Verification Model), which comprises the following steps: firstly, constructing a verification platform based on a UVM framework; based on the verification platform and the test function points, the environment configuration module configures the reference model and the input component; then, the to-be-tested system starts to run, and corresponding data or interrupt response is generated; at the moment, a monitor in the verification platform is inserted into a monitoring node, and the running state and data output of the to-be-tested system are captured in real time; and then, comparing the captured data with a calculation result of the reference model, recording the result, reading an interrupt register or other indication registers of the system to be tested at the same time, and comparing the result with an expected result to judge the correctness. In this way, the technical problems that in the prior art, a chip verification method is insufficient in function coverage rate, lacks system-level random verification and is low in verification efficiency are solved.

A ranging method and an apparatus are provided. The ranging method is applied to a first communication apparatus, and the first communication apparatus includes a first ultra-wideband system and a first narrowband system. The ranging method includes: The first ultra-wideband system receives ranging configuration information from the first narrowband system, where the ranging configuration information is determined by the first narrowband system and a second narrowband system of a second communication apparatus through negotiation (S310); and the first ultra-wideband system generates a first ranging frame based on the ranging configuration information, where the first ranging frame is used to measure a distance between the first communication apparatus and the second communication apparatus (S320). This can implement a process of ranging between the first communication apparatus and the second communication apparatus in a more secure manner.

The invention discloses an optical probe of a closed space lithium battery thermal runaway gas real-time spectrum monitoring system, and the optical probe comprises a laser, Raman scattering light emitted by the laser is emitted in parallel through a collimating mirror, enters a narrow band filter, is reflected by a plane mirror, enters a dichroscope for refraction, and is reflected by a light source. The target detection objective lens gathers on a detected target; raman scattering light returned by the detected target passes through an objective lens target detector and a dichroscope, is modulated by a long-wave-pass optical filter, and is converged into an optical fiber receiving end through a Raman scattering light collecting mirror to enter a spectrograph system. The Raman spectrum technology is applied to monitoring gas component changes in the electrochemical reaction process when the lithium battery is charged and discharged in the closed space, and the lithium battery thermal runaway real-time monitoring based on the Raman spectrum technology can provide a guarantee for the thermal runaway risk in the transportation and storage process of the lithium battery.

Ultra-Wideband (UWB) technology exploits modulated coded impulses over a wide frequency spectrum with very low power over a short distance for digital data transmission. Today's leading edge modulated sinusoidal wave wireless communication standards and systems achieve power efficiencies of 50 nJ / bit employing narrowband signaling schemes and traditional RF transceiver architectures. However, such designs severely limit the achievable energy efficiency, especially at lower data rates such as below 1 Mbps. Further, it is important that peak power consumption is supportable by common battery or energy harvesting technologies and long term power consumption neither leads to limited battery lifetimes or an inability for alternate energy sources to sustain them. Accordingly, it would be beneficial for next generation applications to exploit inventive transceiver structures and communication schemes in order to achieve the sub nJ per bit energy efficiencies required by next generation applications.

In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a reader device. The reader device transmits an incident signal to an ambient internet of things (A-IoT) device. The reader device receives a response from the A-IoT device. The reader device adjusts a power of the incident signal based on a status of the response such that the power of the incident signal is at a level sufficient for communication with the A-IoT device while controlling interference with other devices.

The invention provides a multiband photoresponse nerve synapse device based on a two-dimensional and organic heterostructure, an array and application, and belongs to the technical field of organic electric solid-state devices. The device provided by the invention adopts a three-end bottom gate top contact structure and comprises a gate substrate, an insulating layer, a channel layer and a source / drain electrode, and the channel layer forms an II-type heterojunction by a two-dimensional semiconductor material with a narrow-band gap characteristic and an organic semiconductor material. The heterostructure realizes ultraviolet to far infrared (365nm-10 [mu] m) multiband photoelectric response, and shows synaptic plasticity under light pulse modulation, including short-term enhancement, long-term enhancement and learning-forgetting-re-learning characteristics. Large-area array preparation of the device can be realized through methods such as chemical vapor deposition, solution spin coating, jet printing or layer-by-layer self-assembly. The technology not only can be used for brain-like learning and memory simulation, but also can be applied to the fields of sensing and memory integrated intelligent systems, optical neural networks, artificial vision, multi-mode intelligent sensing and the like.

The invention provides an ocean satellite Internet of Things multi-modal data narrow-band transmission scheduling method and device, belongs to the technical field of ocean satellite Internet of Things, and innovatively provides a multi-modal data narrow-band transmission scheduling strategy for challenges of ocean observation equipment in an energy-limited and dynamic satellite channel environment. The core of the method comprises the following steps: constructing a multi-modal data dynamic transmission model, and carrying out data value evaluation based on space-time intelligence; designing a congestion perception and hierarchical congestion control strategy to guarantee data timeliness; the transmission fairness is optimized in combination with the data value weight factor, the PAoI and the Jain fairness index; an energy dynamic evolution model is constructed, and long-term energy revenue and expenditure balance of equipment is guaranteed; based on a deep Q network and imitation learning, in combination with a security reinforcement learning framework, information timeliness, energy consumption and congestion are jointly optimized. According to the method, the deep and far sea observation and detection data transmission time delay, energy consumption and the congestion occurrence rate are remarkably reduced, and the information timeliness and the multi-modal data transmission scheduling fairness are improved.

The invention provides a fault signal detection system and an analysis positioning method, and relates to the technical field of signal detection. An injection module is used for periodically applying narrowband acoustic disturbance capable of adaptively selecting frequency and power to an optical cable sheath; the passive wireless label nodes arranged along the line collect multi-dimensional data such as arrival timestamps, amplitudes, frequencies, phases, local temperatures and the like in real time, and upload the data through near-field coupling. And the convergence module completes node identification association and batch aggregation, the analysis and construction module constructs an acoustic propagation path map, and after temperature difference segmentation compensation, an actual laying path is dynamically recovered by adopting a map search algorithm. And the projection and identification module maps the map to a geographic information system coordinate system and outputs a fault space position, thereby realizing real-time and accurate optical cable fault positioning under a topology-free prior condition, remarkably reducing manual inspection and misjudgment rates, and being suitable for a multi-branch and multi-repair long-distance communication or power optical cable scene.

The invention relates to the technical field of optical communication, and discloses a multi-dimensional and multi-phase-based 50G PON signal noise compensation method, which comprises the following steps: S1, generating a mixed signal, including superposing a multi-phase orthogonal pilot signal into a data signal time domain at a transmitting end according to a preset proportion lower than the power of a data signal; and S2, transmitting the mixed signal in a polarization multiplexing mode, wherein the polarization multiplexing adopts double-channel parallel transmission of an X polarization state and a Y polarization state. Multi-phase orthogonal pilot signals are superposed to a data signal time domain in a low-power proportion at a transmitting end, polarization multiplexing dual-channel transmission is adopted, a narrow-band filter is utilized at a receiving end to separate pilots and calculate channel damage parameters, and a finite impulse response filter is configured to perform linear equalization compensation. And the simplified Kalman filtering algorithm is combined to estimate the phase noise and correct the phase, so that collaborative suppression of the linear channel damage and the phase noise in the 50G PON signal is facilitated.

The invention discloses an intelligent monitoring system for high-voltage power supply equipment, which belongs to the technical field of power distribution equipment monitoring and comprises three-in-one monitoring equipment including a temperature measuring device, a leakage current monitoring device and an ultrahigh-frequency partial discharge monitoring device. And data is transmitted to the wireless receiving unit through ultra-narrow-band wireless communication, and is finally summarized to a background intelligent data analysis platform, so that real-time monitoring and efficient and accurate judgment of the running state of the high-voltage equipment are realized. The system has the advantages of being high in intelligent degree, convenient to install, low in power consumption and the like, solves the problems that a traditional monitoring device is difficult to supply power, complex in wiring, unstable in data transmission and the like, and is suitable for state sensing and health management of large-scale high-voltage power distribution equipment. By using the system, field detection can be reduced, a large amount of manpower and material resources can be saved for power enterprises, the power facility management efficiency can be improved, the maintenance management level is improved, and stable operation of a power grid is ensured.

The invention discloses a spectral interference system resolution improving method and system, and the method comprises the steps: building an ISE-Net end-to-end deep neural network model, enabling the convolution kernel size of an efficient channel attention module of the ISE-Net end-to-end deep neural network model to be adaptively determined according to the number of input channels, and constructing a mapping relation between narrowband and broadband interference signals; and generating an ideal narrowband signal and a double-bandwidth target signal according to a spectral interference physical formula, defining a loss function by minimizing deviation between model output and the target signal, updating parameters and dynamically adjusting a learning rate by using an AdamW optimizer until model loss is converged, and completing data generation and training. An input narrowband signal horizontal axis is converted to a corresponding frequency domain axis, and is subjected to time shifting and intensity scaling preprocessing to adapt to the model. A signal processing flow suitable for a single / multi-layer structure is constructed, a bandwidth expansion signal is obtained through decomposition, expansion and reconstruction, and the resolution of a spectrum interference system is improved. The method has the advantages of high calculation efficiency, high generalization and flexible deployment.