6019 results about "Signal source" patented technology

The invention provides an automatic walking and positioning method and system for a signal positioning and measuring robot in a complex environment, and relates to the field of technical positioning and measuring robots, and the method comprises the steps: obtaining an indoor three-dimensional map and multi-mode perception data, carrying out the semantic segmentation through a graph neural network, and achieving the environment matching through the combination of a point cloud registration technology; and generating robot motion track planning data. Multi-dimensional signal features are collected through a phased-array antenna system, and a signal feature distribution diagram is constructed in combination with a robot pose and an environment electromagnetic propagation model. A partitioning strategy and a multi-constraint optimization algorithm are adopted to calculate three-dimensional coordinates of a signal source, and finally, the signal source is accurately positioned through a depth calibration network.

The invention relates to the technical field of communication optimization, in particular to a wireless communication method and system of a vehicle diagnosis system. The method comprises the following steps: identifying a plurality of signal sources in an environment and three-dimensional space data of a current position of a vehicle; performing scene interference intensity comprehensive evaluation on the plurality of signal sources in the environment to obtain a current scene interference intensity evaluation value of the vehicle; environment obstacle space layout analysis is carried out on the three-dimensional space data of the current position of the vehicle, environment three-dimensional modeling is carried out, and a vehicle environment three-dimensional point cloud model is constructed; signal multi-path propagation evolution is carried out according to the current scene interference intensity evaluation value of the vehicle and the vehicle environment three-dimensional point cloud model, and optimal signal frequency band analysis is carried out, so that optimal signal frequency band parameters are extracted; and carrying out dynamic transmission frequency modulation and signal adaptive coding based on the optimal signal frequency band parameter, and constructing a dynamic signal transmission strategy. According to the invention, efficient and stable wireless communication is realized, and the vehicle-mounted communication performance is improved.

The invention relates to the technical field of electromagnetic pulses, and discloses an electromagnetic pulse data transmission method. The method comprises the following steps: collecting natural electromagnetic pulse signal data of a detection target area through a six-dimensional complementary electrode array structure, and executing Kalman filtering peak extraction and characteristic frequency locking to obtain frequency-optimized signal data; executing first-order and second-order gradient difference matrix calculation and space vector synthesis to obtain signal source position coordinate data and signal intensity data; performing spectral domain reconstruction and multilayer dynamic threshold analysis to obtain a spatial clustering abnormal data packet; and selecting an optimal transmission channel to transmit the spatial clustering abnormal data packet to a cloud server. According to the invention, the influence of an external interference source is effectively eliminated, accurate extraction and characteristic frequency locking of effective frequency band signals are realized, power frequency and harmonic interference thereof are effectively suppressed, the signal-to-noise ratio of the effective frequency band of the signals is improved, and the reliability and timeliness of data transmission in a severe field environment are ensured.

Methods, systems, and bitstream syntax are described for video coding and decoding using source picture timing information which is captured by an encoder and is signaled as metadata to a decoder to assist in decoding. The proposed methods include example syntax for signaling source picture timing metadata as supplemental enhancement information (SEI) messaging for both single-layer and multi-layer video sequences.

The invention provides an antenna radio frequency performance test system and method, and relates to the technical field of antenna testing, the system adopts an intelligent signal source module, uses a quantum random number generator to generate a test signal of an ultra-wide frequency spectrum, and an adaptive matching network module can automatically adjust impedance according to impedance characteristics of an antenna to be tested. The space electromagnetic environment reconstruction module accurately simulates various electromagnetic environments through an electromagnetic radiation source and a wave-absorbing material, the multi-dimensional signal acquisition module simultaneously acquires electric field, magnetic field, phase and frequency spectrum information, and the intelligent analysis and diagnosis module analyzes signal data by using an artificial intelligence algorithm and performs fault diagnosis based on a machine learning model. In general, the system and the method improve the comprehensiveness, the accuracy and the intelligentization of the antenna test, and provide a new test solution for the field of wireless communication.

The invention provides a circuit breaker equipment reliability diagnosis method, a medium and a system, and belongs to the technical field of switch safety identification of circuit breaker equipment.Audio signals and vibration signals in the operation process of a circuit breaker are continuously obtained, and the reliability of the circuit breaker equipment is obtained through short-time Fourier transform, adaptive median filtering, wavelet denoising, envelope analysis and the like. And clean audio and vibration signals are obtained. Then, performing time alignment and fusion on the two types of signals to generate a plurality of groups of fusion signals; feature extraction is carried out on the fusion signals, the feature weight is optimized by adopting a genetic algorithm, and the optimal fusion feature is calculated; and finally, inputting the optimal fusion feature into a pre-trained fault diagnosis model, and outputting a fault diagnosis vector of the circuit breaker. The technical problem that a diagnosis result is unstable due to the fact that a single-signal-source diagnosis method in the prior art is difficult to comprehensively reflect the operation state of the circuit breaker and is easily influenced by environmental noise and interference is solved.

The invention provides a simultaneous multiband superheterodyne receiver based on Rydberg atoms, and relates to the technical field of microwave electric field measurement, probe light provided by a probe light laser and coupling light provided by a coupling light laser oppositely enter an alkali metal atom gas chamber; the microwave signal sources of the multiple wave bands generate two paths of signals, one path of microwave signal is emitted to the space through the local oscillator microwave electric field emission horns of the wave bands, and the microwave electric field receiving horns of the wave bands receive corresponding echo signals. After frequency mixing of each wave band, the microwave electric field emission horn irradiates the alkali metal atom gas chamber at the same time, microwave fields of multiple wave bands are sequentially coupled with multiple pairs of continuous adjacent Rydberg states, and superheterodyne receiving is carried out on microwaves of multiple wave bands at the same time; and superheterodyne and high-sensitivity detection of microwave signals of multiple wave bands can be realized.

The invention discloses a 3D underwater electric field source positioning method based on cross array arrival angle estimation, and belongs to the field of electromagnetic positioning detection. The method comprises the steps of setting two groups of receiving electrode array components, obtaining respective noise subspaces of an X-axis array signal and a Y-axis array signal, constructing a first spatial spectrum function of a signal source rotating around an X axis and a second spatial spectrum function of the signal source rotating around a Y axis, performing two-dimensional search based on the first spatial spectrum function and the second spatial spectrum function, and obtaining a two-dimensional search result. And according to the rotation mapping relation in the space coordinate system, solving and obtaining a 3D coordinate result of the signal source based on the search result. According to array symmetry and matrix operation invariance, a processing mode of imaginary axis-around arrival angle estimation based on a cross array is provided, three-dimensional space searching is converted into two-time two-dimensional plane searching, the dipole moment direction is simplified, and therefore rapid and accurate positioning of a near-field space signal source is achieved.

The invention relates to the technical field of traffic monitoring, in particular to a Beidou-based traffic flow real-time monitoring method and system, and the method comprises the following steps: receiving signal data and analyzing a signal source based on a Beidou short message communication terminal, extracting vehicle positioning information and road occupation information in vehicle operation state data, and transmitting the vehicle positioning information and the road occupation information to a Beidou short message communication terminal; and analyzing the vehicle speed and the traffic flow density, and carrying out matching operation on the analysis result and the road section number to obtain traffic flow state data. According to the method, vehicle positioning and road occupation information is extracted through signal analysis, efficient acquisition and integration of traffic state data are realized, road section numbers are matched to improve data space precision, traffic pressure is reflected, dynamic flow analysis is supported, adjacent road section data are integrated, abnormal areas are positioned, shunting paths and proportions are optimized, and emergency response efficiency is improved. Real-time regulation and control of traffic flow are realized through dynamic pushing, the flexibility and responsiveness of traffic operation are enhanced, and the monitoring precision and the road network operation efficiency are comprehensively improved.

The invention relates to the technical field of unmanned aerial vehicle remote identification, in particular to an unmanned aerial vehicle flight path detection method and system, and the method comprises the following steps: obtaining an airspace broadcast signal, detecting a newly added signal, correcting a terminal time difference, recognizing an information source position, extracting a position sequence, reconstructing an unmanned aerial vehicle flight path, comparing a declaration path, and recognizing the identity of an unmanned aerial vehicle. And detecting an abnormal unmanned aerial vehicle and an abnormal flight path, extracting a broadcast time sequence, identifying a time overlapping interval, detecting a remote control end, and obtaining a control identification result. According to the invention, by monitoring the airspace signal in real time and dynamically detecting the newly added signal source, the monitoring precision of the signal source is improved, the time difference correction and space cross reconstruction of a plurality of monitoring terminals are combined, the positioning precision of the unmanned aerial vehicle position is optimized, and a track reconstruction method is adopted, so that the real-time monitoring capability of abnormal behaviors is enhanced; by identifying the information source of the control end and extracting the position information, the airspace safety management and illegal flight prevention capability is improved.

The invention relates to an anti-deception-interference joint detection method and system based on space-time frequency, and the method comprises the steps: obtaining a signal source direction of a received satellite signal, and dividing the signal source direction into channels according to angles based on a beam forming criterion; based on a preset capture rule, initiating capture search for the signal in each channel, and synchronously performing correlation peak detection and array antenna anti-interference detection on the signal to obtain angle information of the signal in each channel and satellite PRN information in the capture process; null processing is carried out on the signal source directions of two or more satellite signals appearing at the same angle; outputting a capture result based on the capture rule, and tracking the capture result conforming to the capture rule; doppler frequency shift consistency detection and signal power calculation are carried out on the signals subjected to rotation tracking, and deception signals are recognized and fed back to the antenna array for filtering processing. The application has the effects of expanding the application range of the anti-deception jamming detection method and improving the anti-jamming capability of navigation positioning.

The invention discloses an unmanned aerial vehicle antenna dynamic adjustment method and device under single Beidou support, and relates to the technical field of antenna control, and the method comprises the steps: carrying out the positioning of a target unmanned aerial vehicle, and obtaining a spatial positioning data signal; transmitting and receiving signals to obtain a signal transmitting and receiving record log; analyzing the flight area of the target unmanned aerial vehicle to obtain terrain environment parameters, performing flight analysis, and generating flight attitude change information; performing operation calculation on an antenna module of the target unmanned aerial vehicle, generating an antenna dynamic operation coefficient, and formulating an antenna adjustment strategy; and performing optimization, generating an antenna adjustment optimization strategy, and performing dynamic adjustment. The technical problem of poor communication and positioning accuracy and stability caused by insufficient antenna adjustment precision of the unmanned aerial vehicle in a complex environment in the prior art is solved, and the technical effects of realizing accurate tracking of the antenna of the unmanned aerial vehicle on the target signal source in the complex environment and improving the accuracy and stability of communication and positioning of the unmanned aerial vehicle are achieved.

The invention discloses an electromagnetic shielding effectiveness evaluation system for an environmental laboratory, which relates to the technical field of electromagnetic shielding effectiveness evaluation and comprises a signal source module, a shielding body test module, an electromagnetic field detection module, a data acquisition and processing module and a verification and calibration module. Wherein the signal source module and the shielding body test module are used as hardware parts and are necessary parts in the evaluation system, and the electromagnetic field detection module, the data acquisition and processing module and the verification and calibration module are used as software parts, so that high-efficiency evaluation processing on a product is also realized; the technical key points are as follows: the scheme not only ensures the accuracy and reliability of an evaluation result, but also improves the consistency and repeatability of evaluation, and a scientific and effective method is provided for the evaluation of the shielding effectiveness of the wire sleeve; meanwhile, the scheme is also helpful to timely discover and correct problems in evaluation, and ensures that the product can meet specific requirements in actual use.

The invention discloses an extensible deep reinforcement learning unmanned aerial vehicle cluster collaborative search method based on digital twinning. According to the method, an extensible multi-agent reinforcement learning algorithm SAMARL is adopted, a multi-agent near-end strategy optimization algorithm and a multi-head attention mechanism are fused, and the effectiveness and the adaptability of the algorithm are improved. In an SAMARL framework, a complex observation space containing graphic representation and an environment cognitive map is constructed, and the target search rate, the area coverage rate, the search time and the collaborative security are comprehensively optimized. An observation space based on a view field range is designed, and the model training speed is improved. Then, a search training framework of'twin training, distributed execution and persistent evolution 'is provided, and migration of the decision model from simulation to reality is achieved; the intelligent decision model is deployed to each unmanned aerial vehicle, and the cluster uses a field intensity meter and a communication radio station to cooperatively search unknown signal sources in a distributed manner. A large number of experimental results show that the method is superior to an existing advanced strategy in search efficiency and system expansibility.

A system (11) for controlling a set of one or more lighting devices (31-32) based on an analysis of audio and / or video content and / or based on a light script associated with the audio and / or video content is configured to receive an audio and / or video signal from a source (43-45), determine an identifier of the source, and select the set of one or more lighting devices from a plurality of lighting devices (31-34) by selecting a set of one or more lighting devices associated with the identifier of the source. The audio and / or video signal comprises the audio and / or video content. The system is further configured to determine light effects based on the analysis of the audio and / or video content and / or based on the light script associated with the audio and / or video content and control the selected set of one or more lighting devices to render the light effects.

The invention provides a fault diagnosis method based on multi-modal multi-scale feature fusion, and the method comprises the steps: collecting signal sources when faults occur at different positions of an aero-engine bearing through a sensor, the signal sources including but not limited to vibration signals, sound signals, temperature, humidity and current; performing unified de-noising processing on the vibration signal to obtain an initial one-dimensional signal X0; performing one-dimensional feature extraction on the initial one-dimensional signal X0 through an MCNN module; performing image conversion on the initial one-dimensional signal X0 to obtain an initial two-dimensional image T1, and performing two-dimensional feature extraction on the initial two-dimensional image T1; fusing the extracted one-dimensional features with the extracted two-dimensional features to generate a multi-modal feature H1; and inputting the fused multi-modal feature H1 into an LSTM network for fault diagnosis and classification. According to the method, the fused multi-modal features are input into the LSTM classification module for fault diagnosis and classification, so that fault detection of the aero-engine bearing is realized.

The invention discloses a multi-scene positioning and intelligent warning system and method for industrial equipment, and the system comprises a track analysis module which obtains the radar signal data of the industrial equipment, carries out the denoising, extracts a signal intensity change feature, and generates a human body dynamic track when the matching degree of the feature and a preset metal reflection model exceeds a threshold value; the abnormity judgment module is used for acquiring the vibration sensing data of the key position, generating a vibration frequency spectrum by applying wavelet decomposition, and generating abnormal vibration alarm information if the vibration frequency spectrum exceeds a range; the intrusion alarm module is used for acquiring node signal sources, performing weighted fusion to obtain an initial positioning coordinate group, inputting the initial positioning coordinate group into a three-dimensional map model, obtaining a final coordinate result through multi-source fusion, and sending out intrusion alarm information if the result falls into a dangerous fence boundary; and the safety evaluation module is used for performing time alignment and deep fusion on the human body dynamic track, the abnormal vibration alarm information and the intrusion alarm information to generate a safety evaluation report. According to the invention, omnibearing safety monitoring and management of industrial equipment are realized.

The invention relates to the technical field of dynamic weighing, and discloses an intelligent load prediction and adjustment method in a dynamic weighing system, which comprises the following steps of: separating a weighing signal into a space domain static load characteristic (pressure point distribution sparsity and gravity center geometric vector) and a time domain dynamic inertial interference component (acceleration coupling noise) through space-time double-domain decoupling; the frequency spectrum aliasing problem of a traditional filtering algorithm is eliminated from a signal source; the future interference trend is predicted based on the real-time motion state of the carrier, a feed-forward compensation signal is generated through a pre-training dynamic basis function library, and dynamic errors are actively counteracted; in combination with sensor array space consistency detection and lightweight online learning, decoupling model parameters are dynamically corrected. According to the method, space geometric analysis and kinematics feedforward prediction are combined, a traditional signal processing framework is strided out, error source separation and real-time compensation are achieved, and the dynamic weighing precision of transient working conditions such as sudden stop and speed change is remarkably improved.

The invention discloses a single-bit direction of arrival estimation method and system with signal amplitude recovery, a terminal and a storage medium, and the method comprises the steps: obtaining each snapshot time signal from a signal source of a uniform linear array receiver, introducing a non-zero threshold value to carry out the single-bit quantization of each snapshot time signal, and obtaining a signal model; reconstructing the signal model, replacing a sign function of the reconstructed signal model with a smooth hyperbolic tangent function, and performing reconstruction to obtain a target signal model; based on the target signal model, constructing a single-bit DOA estimation optimization problem by using a truncated Frobenius norm and an L2, 0 norm, and converting the optimization problem into a target optimization problem by using a semi-quadratic technology; and solving a target optimization problem by using a near-end alternating minimization algorithm and a forward-backward splitting algorithm to obtain a signal source estimation direction, a signal source estimation number and a signal estimation amplitude. According to the method, the amplitude of the signal source is accurately estimated while the prior dependence on the number of the signal source is eliminated.

The invention discloses a continuous terahertz wave imaging quantitative detection system and method for internal defects of a multilayer nonmetal structure, and belongs to the technical field of terahertz nondestructive testing. The detection system comprises a continuous wave linear frequency modulation signal source, a spread spectrum module, a terahertz transceiving probe, a focusing lens, a system control and processing computer, a four-dimensional scanning frame, a scanning frame controller, a detected test piece and a lifting platform, the detection method comprises the steps of determining detection parameters of the detection system; collecting a terahertz detection signal; performing wavelet transform on the terahertz detection signal to obtain a continuous wavelet coefficient; using empirical mode decomposition to decompose the continuous wavelet coefficient into an intrinsic mode function and a residual function; and positioning and imaging the internal defects of the non-metallic material by using the first-order intrinsic mode function as an imaging parameter. According to the method, high-resolution visual detection and accurate positioning can be effectively carried out on the internal defects of the multi-layer non-metal structure, and the method has a relatively high application value for ensuring the safe operation of a major structure.

The invention relates to the field of wearable equipment, and discloses a data processing method for assisting old people based on a smart watch, and the method comprises the steps: building an old people individual physiological baseline library at a smart watch end, and carrying out the dynamic comparison of the dislocation difference between a real-time collection signal and the baseline library; performing behavior interference separation on the individual compensation sequence, and generating a health time sequence feature block after interference stripping based on a multi-scene embedding model; an event entropy triggering mechanism is introduced into the health time sequence feature block, and when the drift rate exceeds an individual self-adaptive threshold value, a candidate health abnormal event is automatically marked; calibrating a signal source corresponding to the candidate health abnormal event as a local feedback loop node, and performing coupling correction on a signal in a local feedback loop; and based on the health monitoring priority feedback map, in combination with the global circadian rhythm change trend and the accumulated weight of the abnormal event, generating a multi-level interaction prompt instruction. The method has the advantage of improving the accuracy of the health monitoring data of the old people.

The invention provides an electric energy meter PCB function test method and device, a medium and equipment, and the method comprises the steps: obtaining a multi-channel signal source, automatically adjusting the characteristics of an input signal based on a feedback signal of an electric energy meter through a self-adaptive algorithm, and determining the consistency of the working characteristics of the input signal and the working characteristics of the electric energy meter; a virtual power grid environment simulation model is constructed, through integrated power simulation software and dynamic interference simulation, simulation signal source automatic adjustment signal characteristics are input into the virtual power grid environment simulation model based on the integrated power simulation software to synthesize a composite signal, and load fluctuation of an electric energy meter in actual operation is simulated based on the composite signal. Determining an electric energy meter test data set; according to the invention, the fault mode of the electric energy meter can be automatically identified, the test data can be analyzed in real time, and fault diagnosis and optimization suggestions can be automatically given. The intelligent diagnosis mode is far better than a traditional manual detection method, and the speed and accuracy of fault diagnosis can be remarkably improved.

The invention discloses a zero-sequence pilot-frequency excitation method for a double-circuit line in an incomplete power failure environment, which comprises the following steps of: applying zero-sequence pilot-frequency signal excitation on a power failure line by using a pilot-frequency power supply as an excitation signal source of a zero-sequence network of the double-circuit line, different-frequency induced current and voltage are measured at secondary sides of a current transformer and a voltage transformer at two sides of the operation line, and different-frequency zero-sequence voltage and different-frequency zero-sequence current in the double-circuit line zero-sequence network are obtained; simultaneously solving a zero-sequence network equation, and calculating mutual impedance between double circuits; performing frequency conversion to obtain the power frequency mutual impedance of the line; and finally, carrying out simulation verification by constructing a non-full-stop double-circuit line zero-sequence mutual inductance impedance measurement system. According to the method, the multi-path coupling caused by the existing power frequency interference method and the accuracy problem caused by the signal measurement error of the zero sequence increment method are solved, the test calculation can be accurately completed under the complex interference working condition, and the safety risk caused by the single-phase reclosing operation is avoided.

The invention discloses an eSIM service cost intelligent optimization method based on different operator information sources, and particularly relates to the technical field of operator network management. The method comprises the following steps: collecting eSIM tariff rules of a plurality of operators and real-time charging data of eSIM terminals, extracting tariff terms and conditional expense trigger mechanisms hidden in charging behaviors of different operators by using an association rule mining algorithm, and constructing a multi-level cost structure model; on the basis of a network registration behavior log of the eSIM terminal, predicting the probability that each operator signal source has an abnormal registration event, and evaluating the risk that each operator signal source triggers a hidden cost trap in combination with a multi-level cost structure model; and according to the real-time network signal parameters of the eSIM terminal, a signal source recommendation strategy is generated in combination with the risk assessment result, and the eSIM terminal is driven to execute a signal source switching operation, so that real-time adjustment and cost optimization control of communication network selection are realized, and the service stability of the eSIM in a cross-network use scene is improved.

The invention belongs to the technical field of microwave passive devices, and discloses a millimeter wave duplex power divider based on a multilayer metal gap waveguide and a working method thereof, and the millimeter wave duplex power divider comprises a common channel, a low-frequency filtering power divider and a high-frequency filtering power divider; the input port of the common channel is used for being connected with an electromagnetic wave signal source, and the output end of the common channel comprises an upper output channel and a lower output channel. Wherein the first output channel is connected with the input port of the low-frequency filtering power divider, and the second output channel is connected with the input port of the high-frequency filtering power divider; the low-frequency filtering power divider and the high-frequency filtering power divider are stacked up and down and adopt double-layer metal gap waveguide structures; wherein a fourth-order resonant cavity is arranged in the double-layer metal gap waveguide structure so as to realize a duplex power division function; functions of a duplexer and a power divider are integrated, loss caused by machining and assembling errors is greatly reduced, and low insertion loss and high isolation between channels of the duplex power divider are achieved.

The invention provides a signal blind separation and intelligent reconstruction method and system in a complex scene, and relates to the technical field of signal processing, and the method comprises the steps: receiving an aliasing signal, and converting the aliasing signal into a multi-channel signal observation matrix; performing decomposition in a wavelet domain to obtain a wavelet coefficient, matching the wavelet coefficient with the sparse dictionary, and reconstructing a target signal source after optimization; estimating the number of signal sources based on covariance matrix eigenvalue distribution; mapping a signal source to a graph structure domain, extracting space and time sequence correlation through a mixed graph convolutional network, and obtaining a target separation signal through variational reasoning optimization; and finally, carrying out quality evaluation and post-processing to obtain a final reconstruction signal. According to the invention, the signal separation precision and robustness in a complex scene are improved.

The invention discloses a tiny residual focus detection method and system based on ultra-high depth sequencing, and relates to the technical field of tiny residual focus intelligent detection.The tiny residual focus detection method comprises the following steps that on the basis of a sequencing library, splitting is conducted according to a sample index to obtain a to-be-detected sample, and a consensus sequence is obtained according to a molecular identifier of the to-be-detected sample; based on a consensus sequence, filtering out the consensus sequence of which the mass value is less than 25 or the failysize is less than 3, and combining a subtype type and a distance from a fragment edge as noise introduced into an original nucleic acid molecular chain; a context sequence (context) and a chain direction are used as noise for introducing the capture level of PCR amplification; based on the noise level, in combination with tumor priori knowledge, the ctDNA level is estimated, and the MRD state is determined by detecting the significance of a molecular signal source. According to the invention, the sensitivity and specificity of MRD detection are improved.

The invention discloses a centrifugal pump cavitation state recognition method based on multi-source sensor signals, which comprises the following steps: collecting the multi-source sensor signals of a centrifugal pump at different water temperatures and power frequencies to obtain multi-modal data with cavitation state labels; resampling the multi-modal signal data by using a linear interpolation method, and synchronizing and aligning the signals in a time domain; performing time-frequency analysis on multi-sensor signals by using short-time Fourier transform, performing dimensionality reduction on features through principal component analysis, and extracting one-dimensional features and two-dimensional features; a one-dimensional convolutional neural network and a two-dimensional convolutional neural network are used to carry out deep learning on signal features of different modes, and feature layer fusion is carried out on multi-dimensional features through a feature fusion strategy; classifying the fused feature vectors by using time sequence characteristics in a mode of gating a circulation unit; and adopting a weighted fusion strategy, setting a weight coefficient of each signal source according to the classification accuracy of each signal source in fault diagnosis, and inputting weighted data into a classification identification model support vector machine to obtain a final cavitation state identification result. According to the method, through the synergistic effect of the signals of the multi-source sensor, the recognition precision and robustness of the cavitation state are comprehensively improved, and the method has important economical efficiency and technical popularization value.

The invention discloses an assembly line ADC background calibration method of an ant colony optimization time delay neural network, and relates to the technical field of ADC calibration, and the method comprises the steps: enabling a to-be-calibrated assembly line ADC and a high-precision reference ADC to be connected to the same signal source, constructing a time delay neural network through the combination of a time delay unit and a three-layer BP neural network, the output of the to-be-calibrated assembly line ADC is connected to a time delay unit of the time delay neural network, and the output of the time delay unit and the output of the to-be-calibrated assembly line ADC jointly form input data of neural network training; carrying out dimension optimization screening on the training data through an ant colony algorithm, and carrying out global optimization on the initial configuration of the time delay neural network weight and bias through the ant colony algorithm; and the time delay neural network outputs a calibrated result backwards.