128 results about "Time spectrum" patented technology

The invention discloses a method for selecting and triggering gamma instant radiation pulse events, and belongs to the technical field of nuclear radiation detection. The method comprises the following steps: carrying out normalization preprocessing on an original gamma pulse radiation time spectrum; s time-frequency transformation is carried out on the preprocessed data, and time-frequency features are extracted; optimizing parameters of the frequency threshold and the amplitude threshold after S time-frequency transformation by adopting a deep reinforcement learning model to obtain an optimal frequency threshold and an optimal amplitude threshold; performing filtering processing on the signal of the S time-frequency conversion result, and separating noise from an effective signal; and searching a pulse radiation event for the filtered signal by applying a morphology-based peak searching method, and positioning the position and the characteristic of a real gamma instant radiation pulse event. According to the method, time-frequency analysis is carried out through S time-frequency transformation, the problem that the frequency of an analysis window cannot be adjusted through short-time window Fourier transformation is solved, the method has better frequency resolution and phase retention characteristics, and gamma pulse signal characteristics can be represented more accurately.

The invention discloses a scanning high-resolution double-optical-comb spectrum system based on Raman gain modulation. The method is suitable for real-time spectrum detection with a wide spectrum range and high spectral resolution. The system comprises a single-frequency laser and driver, an optical coupler, a mode-locked laser, a rare earth doped amplifier, a wavelength division multiplexer, a Raman gain fiber, a sample to be tested, a photoelectric detector, a data processor and a wavemeter. The single-frequency laser couples part of light to the wavemeter, and the remaining light is divided into two paths to be coupled with the two amplified mode-locked lasers to enter the Raman gain optical fiber for Raman gain modulation and is converted into high-mutual-dryness double optical combs. The double combs pass through a to-be-measured sample in a combined manner, and interference signals are measured by the photoelectric detector and received by the data processor. And meanwhile, the processor sends a tuning signal to the single-frequency laser driver, so that the double combs scan in a wide spectrum range to obtain high-resolution spectrum information. Electrical feedback locking is not needed, and high-precision spectrum acquisition with megahertz resolution in a terahertz range can be completed within a few minutes.

The embodiment of the invention provides a space instant gamma radiation detection device and monitoring method, and relates to the technical field of gamma radiation monitoring, the device comprises a device body and a signal acquisition and processing system; the device body comprises a shell, and a scintillator array assembly and an anti-coincidence scintillator assembly which are fixed in the shell; the center of the anticoincidence scintillator assembly is provided with a cuboid groove, and the scintillator array assembly is located in the cuboid groove. Wherein the scintillator array assembly and the anticoincidence scintillator assembly are both connected with the signal acquisition and processing system. According to the technical scheme, the problem of instant gamma radiation time spectrum measurement in a space complex radiation background environment is solved, the signal-to-noise ratio and the time performance of gamma radiation time spectrum measurement are improved on the basis of ensuring lightweight design, and the accumulation probability is reduced while the sensitivity upper limit is expanded.

The invention discloses a magnesium oxide grinding monitoring method and system, and particularly relates to the technical field of grinding monitoring, and the method comprises the following steps: firstly, collecting a reference spectrum generated by light reflection from the surface of a reference substrate with a target thickness; in the grinding process, the reflection spectrum of the surface of the magnesium oxide grinding base material is captured from multiple angles through a plurality of optical sensors; then, calculating a picture dust influence coefficient of each optical sensor according to the K value and the dust space-time concentration distribution; determining an angle correction factor and a picture dust influence coefficient, and comprehensively distributing a reflection spectrum weight coefficient obtained by each optical sensor; fusing and outputting the reflection spectrums acquired by the optical sensors according to the weight coefficients of the reflection spectrums acquired by the optical sensors; finally, matching the real-time spectrum with a historical spectrum library; comparing the target thickness of each region, and determining a rate deviation; the grinding pressure of different areas is dynamically adjusted through a pressure control system; and the grinding end point time of all the areas tends to be consistent.

The present invention comprises a method for jointly processing data from the nuclear magnetic resonant (NMR) response of oil and rock samples in in natura condition, and its main product is the delimitation of the oil saturation (So) present in the rock samples, i.e., the determination of the range of admissible values of the volumetric fraction of the porous volume of the rock occupied by such fluid. The method requires a small volume of oil, originating from or of a composition similar to the oil present in the rock being tested, since it is based on both the measurement of the NMR response of the rock sample and the response of the fluid sample. These two sets of data feed a statistical inference scheme that (1) determines a range of admissible values for the So of the sample, delimited by the minimum and maximum oil saturation values compatible with the two sets of data presented; (2) produces, for each of these extreme values of admissible So, a decomposition of the rock relaxation time spectrum into two complementary spectra, the first highlighting the signatures relating to oil and the second comprising the distribution of the rock relaxometric signatures that cannot correspond to such fluid under the prescribed saturation condition.

The invention discloses a thin film spectrum door lock management system and method based on data analysis, and relates to the technical field of data analysis, and the method comprises the following steps: 1, collecting same-batch intact thin film spectrum data, disturbance spectrum samples and corresponding environment parameters; step 2, carrying out denoising smoothing, baseline correction, derivative operation and normalization processing on the spectral data; step 3, extracting spectrum key features to construct vectors, combining the vectors, and decomposing the vectors into a substrate and a coefficient matrix by using a non-negative matrix; step 4, respectively calculating intact and disturbance thresholds, and constructing a regression model by using environmental parameters and coefficient offset; and 5, collecting real-time spectrum and environmental parameters, carrying out projection solution on a coefficient vector after preprocessing, and dynamically adjusting a judgment reference and carrying out decision making. The method can effectively improve the situation that in the prior art, thin film spectrum door lock management mainly depends on a fixed threshold value and is difficult to adapt to disturbance and environmental changes.

The invention discloses a multi-channel integrated radio frequency system based on double-threshold interference detection and dynamic spectrum aggregation. A radio frequency front-end unit is used for realizing broadband spectrum access and performing analog-to-digital conversion; the digital channel processing unit is used for realizing channelized segmentation through up-conversion and down-conversion, carrying out band elimination filtering to shield unavailable channels and outputting filtering parameters to support dynamic channel recombination; the digital signal parallel processing unit performs parallel access by using the divided channels; the spectrum sensing unit is used for carrying out double-threshold channel interference detection and real-time spectrum analysis according to the parallel access signals; and the frequency spectrum decision-making unit is used for judging the channel state and fusion detection judgment according to the interference detection result, judging the availability of a specific channel in the data link network and carrying out cooperative dynamic frequency spectrum aggregation. According to the method, a consistent spectrum access decision is realized by adopting a spectrum monitoring, sensing convergence and fusion decision mechanism, and consistent understanding of an available frequency set and high-reliability network domain dynamic spectrum aggregation are guaranteed.

The invention belongs to the technical field of electromagnetic spectrum management, and particularly relates to an intelligent planning method for an electromagnetic spectrum time sequence. Comprising the following steps: collecting real-time spectrum use data through a sensor network or wireless communication equipment; carrying out preprocessing operation on the collected data; constructing an electromagnetic spectrum time sequence intelligent planning model based on the preprocessed data; formulating a dynamic spectrum allocation strategy according to a prediction result of the intelligent planning model; and the allocation strategy is continuously optimized and adjusted in the spectrum allocation process. According to the algorithm provided by the invention, efficient and reasonable time sequence planning is carried out on electromagnetic spectrum resources in an intelligent mode, so that the increasing wireless communication requirements are met, and the utilization rate of the spectrum resources and the overall performance of a communication system are improved.

The invention provides a data link wireless communication timing synchronization method, which comprises the following steps of: adopting a plurality of groups of PN sequences as the basis of synchronous timing, detecting TOD after PN serial numbers when an effective synchronization symbol number is detected, carrying out CRC (cyclic redundancy check) on information contents, adopting RS (Reed-Solomon) coding and decoding, and then carrying out 8-time spectrum spreading; and the demodulation end determines an effective timing position according to serial numbers of different hops by taking the verified correct position as a basis for synchronizing the timing time point. The method has the beneficial effects that the synchronization signal-to-noise ratio can be reduced to be lower than 0db, and meanwhile, the false alarm probability and the missing alarm probability are greatly reduced, so that the frame synchronization performance is improved; and the anti-interference capability of the time domain and the frequency domain is enhanced.

The present invention discloses a method for effectively disassembling a nuclear magnetic resonance relaxation time spectrum, comprising the following steps: S1, constructing a probability density function of pores and caves according to the distribution characteristics of pores and caves in a core nuclear magnetic resonance T2 spectrum; S2, setting the sum of the nuclear magnetic spectrum areas to 1, randomly generating n data points within the interval of pore distribution, and dividing all the data points into multiple data sets by screening peak values; S3, calculating a likelihood function; S4, calculating a priori probability that each data point belongs to a pore or a cave; S5, updating various parameters in an iterative method using the priori probability; and S6, calculating a new logarithmic likelihood based on the updated parameters, and updating the expected E in the iterative method. p and E v , expected E p and E v Repeat steps S2 to S5 until the convergence condition is met and the iteration is terminated. The present invention combines nuclear magnetic resonance testing with an iterative method to decompose the nuclear magnetic resonance spectrum, thereby improving the accuracy of the spectral shape distribution.

The application provides an audio signal alignment method and device, a medium and a terminal, and relates to the technical field of audio processing. The method comprises the following steps: calculating a short-time frequency domain representation of an audio signal, wherein the audio signal comprises a first audio signal and a second audio signal; calculating a frequency response of a time-varying linear prediction error filter according to the short-time frequency domain representation of the audio signal, and calculating a short-time spectrum of a linear prediction error; extracting a low-frequency coefficient from the short-time spectrum and calculating a short-time spectrum of a corresponding linear prediction error envelope; calculating a short-time cross-power spectrum of the linear prediction error envelope corresponding to the audio signal according to the short-time spectrum of the linear prediction error envelope; calculating a frame-based time delay between the two audio signals according to the short-time cross-power spectrum of the linear prediction error envelope; and performing a variable-speed constant-pitch processing on the first audio signal or the second audio signal according to the calculation result of the frame-based time delay, so as to obtain an aligned audio signal. The present scheme can improve the accuracy of time delay estimation.

The invention provides a frequency spectrum knowledge graph construction method based on machine learning and Neo4j, and aims to realize intelligent management of radio frequency spectrum information. The method comprises the following steps: step 1, collecting real-time spectrum data through radio spectrum monitoring equipment; step 2, identifying and extracting feature information of the signal from the frequency spectrum data collected in the step 1; step 3, training and classifying the identified and extracted signal feature information by using a machine learning algorithm to obtain a signal modulation type; and step 4, constructing a spectrum knowledge graph based on the classified signal feature information, and performing visual display. According to the invention, through combination of machine learning and the Neo4j graph database, intelligent processing and display of radio frequency spectrum information are realized, the efficiency and accuracy of spectrum information management are improved, and the method is suitable for the fields of wireless communication and artificial intelligence.

The invention relates to a method for realizing full-time frequency spectrum monitoring based on a nest unmanned aerial vehicle and a fixed monitoring station. The method comprises the following steps: issuing a full-time frequency spectrum monitoring task; continuously scanning the monitoring target frequency band; extracting a signal frequency, and performing parameter measurement; signal parameters which are not matched with the known signal library are stored, and the equipment state is recovered; setting a time interval, and generating a direction finding task list; the unmanned aerial vehicle advances according to a preset track and performs a monitoring direction finding task; the unmanned aerial vehicle returns to enter the nest, and charging and heat dissipation reconditioning are automatically completed; and updating the signal positioning data. By adopting the method, the system, the device, the processor and the computer readable storage medium for realizing full-time frequency spectrum monitoring based on the nest unmanned aerial vehicle and the fixed monitoring station, a reliable positioning result is given through a multi-point direction finding result of the unmanned aerial vehicle on the whole track, high-frequency weak signals are easy to capture, the monitoring utilization rate of the unmanned aerial vehicle is greatly improved, and the real-time performance of the unmanned aerial vehicle is improved. The total element information of the signal is collected, and the management is scientific and accurate.

1. The name of the design product: graphical user interface for portable spectrum analyzer (ZP128). 2. The use of the design product: the design product is used for basic spectrum and real-time spectrum analysis, interference analysis and positioning, demodulation analysis, and 4G, 5G base station measurement. 3. The design points of the design product: the graphical user interface display content of the portable spectrum analyzer. 4. The picture or photo that best indicates the design points: interface change state diagram 1. 5. Belongs to the usual design, omit other views. 6. The use of the graphical user interface: for the operation, running management of the portable spectrum analyzer. 7. The area of the graphical user interface in the product: the graphical user interface of the design product is located on the front of the portable spectrum analyzer, which is embodied in the front view. 8. The human-computer interaction mode of the graphical user interface: the front view is the product carrier diagram with graphical user interface; the front interface enlargement is the screen enlargement in the front view, which is the startup interface automatically displayed after the product is started; interface change state diagram 1 is automatically entered after the display of the front interface enlargement is completed, which is the interface at the last shutdown; interface change state diagram 2 is the optional interface entered by clicking the "four-square icon" in the upper left corner of interface change state diagram 1; interface change state diagram 3 is the 5G measurement interface entered by clicking "5G-NR analysis" in interface change state diagram 2; interface change state diagram 4 is the setting interface entered by clicking "setting" in interface change state diagram 3; interface change state diagram 5 is the threshold editing interface entered by clicking "SINR threshold" in interface change state diagram 4.

The present application discloses a method, device and computing equipment for determining the lower limit of effective reservoir physical properties. The method includes: obtaining a first transverse relaxation time spectrum of any measurement point obtained by performing nuclear magnetic resonance logging on the target formation; calculating the first effective porosity of the measurement point based on the first transverse relaxation time spectrum of the measurement point; extracting the second transverse relaxation time spectrum of the invading mud from the first transverse relaxation time spectrum of the measurement point, and calculating the second effective porosity of the measurement point based on the second transverse relaxation time spectrum; establishing a first intersection diagram of the first effective porosity and the second effective porosity based on the first effective porosity and the second effective porosity of different measurement points; determining the inflection point of the first intersection diagram, and using the first effective porosity corresponding to the inflection point as the lower limit of the effective porosity of the target formation. This solution can improve the accuracy of determining the lower limit of effective reservoir physical properties, lower the data threshold, and improve the efficiency of determining the lower limit of effective reservoir physical properties.

The present application relates to a kind of communication system howling detection method and device, it is related to howling detection technique, the method is based on peak power spectrum stability measure detects whether there is first type howling frequency point index in the short time spectrum to be detected at t frame, if not, it is based on peak-average amplitude ratio stability measure and peak-harmonic power ratio detects whether there is second type howling frequency point index in the short time spectrum to be detected at t frame, first type howling frequency point index is the local peak frequency point index of peak power spectrum stability measure greater than preset peak power spectrum stability measure threshold, second type howling frequency point index is the local peak frequency point index corresponding to peak-average amplitude stability measure greater than preset peak-average amplitude stability measure threshold and peak-harmonic power ratio greater than preset peak-harmonic power ratio threshold, the scheme is combined with judgment using two kinds of howling frequency point index, effectively improve howling detection accuracy.

The invention belongs to the technical field of remote sensing antennas, and relates to a space-time processing method for communication antenna array element failure, which realizes effective coverage of complex road conditions by adopting a transceiving antenna and a plurality of airborne antennas. According to the invention, a clutter driving mode is adopted, the airborne antenna is installed on the opposite state isolation strip to realize the space-time spectrum of the slope, the airborne antenna and the transmit-receive antenna adopt filters, the coverage of driving echoes can be expanded far away, and the scene of the echoes of the airborne antenna is driven by a detector. A whole set of driving method formed by the transmitting and receiving antenna and the airborne antenna adopts a wind and light clutter mode to supply power, does not depend on a power system and Beidou satellite global coverage, and can be arranged in a low-cost and large-area manner, and the airborne antenna of the aircraft can flexibly intervene in a region covered by the airborne antenna, so that an urban state early warning system is quickly constructed, and the early warning efficiency is improved. The radar imaging problem under the array element failure condition is solved.

The described systems and related test methods provide a significant improvement in test accuracy, as well as a reduction in test time for system-level electromagnetic environmental effects (E3) testing. The systems may include a real-time spectrum analyzer, a network analyzer, and a switching / filtering / coupling network, controlled by an information processing device such as a general-purpose computer. These systems can scan all frequencies at each receiver.

The invention provides a satellite channel multipath parameter high-precision measurement method, which comprises the following steps of: receiving and preprocessing a signal, and constructing a receiving signal matrix of space-time sampling; performing spatial smoothing solution coherence to generate a smoothed spatial domain and time domain covariance matrix; according to the angle and time delay joint estimation algorithm, a space-time spectrum function is generated through characteristic decomposition and noise subspace projection, and joint estimation of the azimuth angle, the pitch angle and time delay is achieved. The invention also comprises a device for realizing the method. According to the technical scheme, the problem that the parameter estimation precision is reduced due to coherent multipath signals in a satellite channel is solved, and the accuracy and communication performance of channel modeling are improved.

The present invention relates to a neutron time-of-flight spectrum zero-point correction method for neutron energy spectrum measurement. The method comprises placing a first scintillator detector on a neutron beam behind a target as a start signal detector in the time-of-flight; placing a second scintillator detector at a distance L from the first scintillator detector in a preset angular direction of the neutron beam as a stop signal detector for the neutron time-of-flight; the two scintillator detectors remove gamma signals through pulse shape discrimination, and then provide an initial neutron time-of-flight spectrum through a coincidence method. Since the initial neutron time-of-flight spectrum has a zero-point deviation T_L0, a zero-point correction is required. The method disclosed in the present invention utilizes accompanying gamma in the neutron generation process to correct the zero-point deviation T_L0 of the neutron time-of-flight spectrum when measuring the neutron energy spectrum using a dual-scintillator time-of-flight spectrometer, thereby improving the measurement accuracy of the neutron time-of-flight and, therefore, the accuracy of the neutron energy spectrum measurement.

The application provides a remote sensing image cloud removal method and system fusing gradient fidelity and time spectrum consistency, relates to the technical field of remote sensing image processing and tensor modeling, and comprises the following steps: firstly, acquiring multi-temporal remote sensing images and cloud mask data, and generating a fault mask through active fault identification; then, calculating a guided gradient tensor and performing low-rank approximation processing to obtain spatial feature factors and time spectrum feature factors; based on this, a multi-objective optimization model of a gradient domain fidelity term, a pixel domain fidelity term and a time spectrum consistency constraint term is constructed; a proximal alternating minimization algorithm of an embedded alternating direction multiplier method is used for efficient solution, and the reconstruction result is modified in combination with the cloud mask and the active fault mask, and a high-quality cloud-removed image sequence is output. The application can effectively maintain the image edge structure, texture details and space-time consistency under a complex cloud coverage scene, and significantly improves the availability and analysis value of remote sensing data.

The invention discloses a multi-client real-time spectrum monitoring system and method based on a GPU, and belongs to the technical field of spectrum analysis, and the method comprises the steps: obtaining a spectrum state, behavior information, a host state and a business service quality demand of a client; calculating a client interference intensity coefficient, a behavior state coefficient, a host state coefficient and a service quality coefficient through a corresponding model; dynamically distributing the calculation power of each client by using a power distribution model based on the coefficients; and finally, outputting a target refresh rate of each client through a refresh rate optimization model in combination with the distributed power and the service quality coefficient. Through multi-dimensional state sensing and modeling, the problems that in the prior art, resource distribution is rigid, and differentiation requirements of multiple clients cannot be met are solved, intelligent, dynamic and efficient distribution of system computing resources is achieved, and the overall energy efficiency and stability of the system are improved while the multi-business service quality is guaranteed.

The invention discloses a borehole influence factor aperture correction method for uranium fission instant neutron logging, and aims to solve the problem of neutron counting rate response deviation caused by borehole size change in a uranium mine logging process. Time spectrums of thermal neutrons and epithermal neutrons in different apertures in uranium fission instant neutron logging are obtained, and the rule that the time spectrums of the thermal neutrons and the epithermal neutrons change along with the hole diameter is researched. And based on a numerical simulation result, a fitting formula and a correction coefficient of the aperture influence factors are solved. The correction method can be used for analyzing the influence of the aperture size change on the counting rate of the neutron detector, effectively improves the uranium mine grade evaluation accuracy under the complex borehole condition, and is especially suitable for well logging interpretation of non-standard borehole diameters and diameter-expanded stratums.

This invention provides a deep learning-based method for calculating the relaxation time distribution of nuclear magnetic resonance (NMR) signals. Based on the characteristics of Laplace NMR signals, a mathematical model of an exponentially decaying signal with noise and an ideal relaxation time spectrum are constructed. The ideal relaxation time spectrum serves as a label, and the position of the spectral peak represents the exact value of either the T1 or T2 relaxation time. The full width at half maximum (FWHM) of the spectral peak corresponds to the uncertainty of the result. Simulated signals are generated from the mathematical model, and training and test sets are constructed. A network model is built, and the training data is input into the network model for training. The test data is then input into the network model for testing. The method provided by this invention relies on a mathematical model of the exponentially decaying signal during the relaxation process to construct a dataset for training. This eliminates the need to collect large amounts of real data and allows for NMR relaxation time spectrum calculations to be completed within seconds. Furthermore, it exhibits high robustness to test data with different signal-to-noise ratios.

The invention discloses a radio partial discharge detection positioning method, device and equipment, and relates to the technical field of radio monitoring, and the method comprises the following steps: obtaining the real-time spectrum data of an electromagnetic environment, carrying out the feature learning through a deep reinforcement learning algorithm, and constructing an electromagnetic environment feature fingerprint database; filtering the real-time spectrum data, extracting a target pulse characteristic quantity, inputting the target pulse characteristic quantity into a deep twin network, and screening out an effective pulse signal; performing signal decomposition on the effective pulse clusters by applying an improved variational mode decomposition algorithm to obtain each discharge source signal; and carrying out TDOA time difference correction calculation on each discharge source signal, carrying out dynamic error correction in combination with an environment adaptation coefficient of the electromagnetic environment fingerprint database, and outputting a three-dimensional positioning result. According to the invention, high-precision detection and positioning of multi-source discharge signals can be realized in a complex electromagnetic environment, the sensitivity and reliability of partial discharge monitoring are significantly improved, and meanwhile, accurate data support is provided for fault early warning and maintenance of power equipment.

The invention provides a wireless communication positioning method and device, electronic equipment and a storage medium, and belongs to the technical field of communication. The method comprises the following steps: acquiring a received signal; performing channel estimation on the received signal to obtain a channel estimation value and a signal-to-noise ratio of each antenna array element; based on the channel estimation value, an arrival time spectrum and an arrival direction spectrum are respectively constructed, the arrival time spectrum comprises arrival time spectrum data on each antenna array element, and the arrival direction spectrum comprises arrival direction spectrum data on each observation frequency point; based on the signal-to-noise ratio and the arrival time spectrum of each antenna array element, calculating to obtain an observation time spectrum corresponding to each transmission delay; obtaining a signal transmission time delay based on the maximum value in the observation time spectrum corresponding to each transmission time delay; determining a signal arrival direction angle based on the arrival direction spectrum; and obtaining positioning information based on the signal transmission time delay and the signal arrival direction angle. The influence of noise on the search result is suppressed, and the positioning precision is improved.

This invention discloses a hardware-software co-processing method for real-time spectral signal processing in Raman microscopy, belonging to the field of spectral signal processing technology. The method includes: establishing strict temporal constraints between physical displacement and cloud inference, and initiating asynchronous communication using the physical gaps in stage movement; simultaneously, deploying a deep learning model (F2P) pre-trained with a self-supervised masking strategy in the cloud. This pre-trained model utilizes the structural correlation between the Raman broadband background and narrowband characteristic peaks to directly perform real-time forward inference on the input single-frame noisy spectrum, achieving millisecond-level high-fidelity reconstruction of a single frame without any complex parameter tuning or the need for a clean control spectrum. This invention completely eliminates the physical lag in multi-frame processing and the general technical bias of supervised learning algorithms, achieving true "synchronization between acquisition and display," and significantly improving the real-time processing performance and cross-device automated deployment capabilities of in-situ Raman imaging.

The present application relates to a kind of discrete shared frequency band spectrum sensing system and method, belong to wireless communication technical field.The system includes base station, edge computing device and several sensing terminals, multiple sensing terminals collect spectrum data and carry out spectrum sensing, and sensing result is sent to base station, and base station forwards sensing result to edge computing device and carries out multiple sensing result fusion processing, and edge computing device is fused after multiple sensing results by a pre-trained binary prediction model Prediction of subsequent multiple time steps of spectrum occupation, and spectrum prediction result is sent to base station, and base station filters idle spectrum frequency point according to spectrum prediction result and carries out communication with sensing terminal.The method is based on the system and carries out discrete shared frequency band sensing, can adapt to the signal coverage range of discrete frequency band, unknown communication system exists and needs real-time spectrum analysis.

The application provides a process state real-time correction method based on acoustic characteristics, and relates to the technical field of process control, and comprises the following steps: collecting acoustic signals generated by interaction between a processing medium and a processing unit when the processing unit is executing a processing task; performing real-time spectrum analysis on the acoustic signals to extract characteristic frequencies and energy distribution characteristics thereof which are related to the current physical state of the processing medium; determining whether the current physical state of the processing medium is in an abnormal critical region in real time based on changes of the characteristic frequencies and the energy distribution characteristics thereof relative to a preset reference; the abnormal critical region comprises a first precursor state in which the processing medium tends to be excessively dried or a second precursor state in which the processing medium tends to be excessively accumulated; and if it is determined that the processing medium is in the abnormal critical region, the physical state of the processing medium being currently processed is corrected in real time by adjusting at least one execution parameter which influences the physical state of the processing medium before the processing medium being currently processed reaches a target region.

The invention provides a multi-band radar anti-interference method, which comprises the following steps of: 1, acquiring an enhanced model in an offline state through offline dynamic confrontation training; 2, obtaining an original echo signal in an online state, carrying out adaptive filtering, and carrying out space-time spectrum feature extraction by using an enhanced model; 3, performing feature fusion and target separation according to the extracted space-time spectrum features; step 4, performing optimization according to the separation result, and judging whether a termination condition is met or not; if yes, ending and outputting the multi-dimensional data packet; and if not, returning to the step 2. According to the method, through triple technical breakthrough of hardware reconstruction, a dynamic confrontation training method and closed-loop feedback, the anti-interference performance and the vital sign monitoring precision reach the industry leading level, and the method is particularly suitable for extreme scenes such as fire rescue and battlefield search and rescue. In the next step, light weight of the model can be emphatically optimized, and the deployment efficiency of the mobile platform is further improved.