117 results about "Signal envelope" patented technology

The invention relates to the technical field of vibration monitoring, in particular to a self-powered transmission line fitting aeolian vibration damage diagnosis system and method, and the system comprises a sensing collection module, a signal decoupling module, a damage identification module, a damage association module and a risk assessment module. According to the method, stress wave velocity and acceleration data are synchronously collected, time alignment is implemented, feature coupling precision is enhanced, wave crest offset and energy density are respectively extracted by using moving average filtering and wavelet transform, effective data segments are dynamically screened, and environmental noise interference is suppressed. A stress wave propagation change rate is quantified based on a path attenuation model, a continuous energy abnormal node is matched to realize damage positioning, a breeze response abnormal region is identified by combining vibration direction change and a signal envelope offset degree, multi-dimensional features are coded and subjected to risk judgment through a neural network, a damage positioning and risk assessment closed-loop framework is formed, and the risk assessment accuracy is improved. And the spatial resolution and evaluation precision of aeolian vibration damage identification under complex working conditions are significantly improved.

The invention discloses a method for identifying interference signals of weld defects under different lifts-off conditions, which comprises the following steps of: S1, de-trending processing: carrying out de-trending processing on original detection signals; s2, Gaussian wavelet transform: carrying out Gaussian wavelet transform on the detrended signal; s3, optimal wavelet basis selection: by calculating correlation coefficients or energy ratios of different wavelet basis and defect signals, selecting the wavelet basis with the highest matching degree for reconstruction; s4, envelope processing: extracting a signal envelope based on Hilbert transform; s5, mean filtering: applying sliding window mean filtering to the envelope signal; and S6, threshold processing: setting a self-adaptive threshold screening signal, and retaining the feature points of which the amplitudes exceed the threshold. According to the method, de-trending and Gaussian wavelet transform are used for de-noising enhancement. According to the method, wavelet functions of different orders are constructed and matched with defects, secondary signal enhancement is carried out by selecting a filtering method, finally, threshold stripping interference is calculated, reliable defect identification is carried out, and technical support is provided for uneven welding seam quality monitoring.

The invention provides a high-voltage circuit breaker abnormity identification method based on a vibration signal envelope line. The method comprises the following steps: acquiring an operation vibration signal of a high-voltage circuit breaker, generating vibration data by a conditional GAN, filtering the vibration signal by wavelet transform, extracting the envelope line of the vibration signal and associating an operation state label to form a sample library; an AM-CNN-based high-voltage circuit breaker abnormity identification model is constructed, and sample library data is used for training so as to predict the operation state of the circuit breaker on line; and perfecting the sample library according to the prediction state and updating the circuit breaker abnormity identification model. According to the method, the fault state of the high-voltage circuit breaker is diagnosed by automatically extracting the fault features of the vibration signals, the error state and the unknown fault state are judged through self-learning so as to continuously improve the abnormal recognition precision of the circuit breaker, power transformation operation and maintenance personnel are assisted to make decisions, and the operation state recognition efficiency of the high-voltage circuit breaker is improved.

The invention belongs to the technical field of ultrasonic detection, and provides an ultrasonic phased array defect detection system and method for laser penetration stitch welding, and the method comprises the following steps: determining amplitude threshold values among all layers of materials of a laser penetration stitch welding workpiece; the ultrasonic phased array probe is instructed to emit sound waves to the laser penetration stitch welding workpiece, and echo signals are obtained; extracting a signal envelope line of the preprocessed echo signal through Hilbert transform; determining an over-threshold signal segment of which the amplitude is greater than an amplitude threshold in the signal envelope; extracting a time domain feature and a frequency domain feature of the super-threshold signal segment, and inputting the time domain feature and the frequency domain feature into a pre-trained dual-channel CNN model to obtain an incomplete fusion probability; time domain features and frequency domain features are mined through a two-channel CNN model, a time association rule and a frequency distribution mode are learned through parallel processing, then the time domain features and the frequency domain features are fused, and the subtle difference of the time domain features and the frequency domain features of an incomplete fusion defect and a normal interface can be amplified.

The invention discloses a self-adaptive parameter control system and method for a halfpace field rice transplanter based on full-hydraulic transmission, particularly relates to the technical field of hydraulic parameter control, and aims to solve the technical problem of dynamic power competition between a walking system and a planting device when the full-hydraulic transmission rice transplanter works in a halfpace field. Working pressure signals of a walking motor and a planting device are monitored in real time, the divergence degree of envelope lines of the two pressure signals is calculated so as to recognize the power competition state of a system, and when power competition is detected, the required power of two execution mechanisms is dynamically calculated, and a hydraulic pump displacement distribution coefficient is generated; and then the interaction characteristics of the outlet pressure of the main pump and the output flow signal and the transmission characteristics of the pressure signal of the executing mechanism are fused, the dynamic balance degree of the system is generated, the displacement distribution coefficient is corrected, and finally the opening degree of the walking motor and the proportional valve of the planting device is synchronously adjusted based on the corrected coefficient. Accurate distribution and dynamic balance control of the power of the hydraulic system are achieved.

The invention discloses a miniature front scattering type visibility meter capable of being carried on an unmanned aerial vehicle, which is applied to the field of visibility meters and is characterized in that modulated light rays are irradiated to a reflector I through an emission light path collimating lens cone and then are reflected out of a detection cabin along the direction of an emission channel, and when passing through atmospheric dispersion substances on the lower side of the detection cabin, the light rays are reflected out of the detection cabin along the direction of the emission channel; part of light rays are scattered, enter a receiving chamber through a receiving channel, are reflected by a second reflector, penetrate through a receiving light path collimating lens barrel and irradiate a receiving detector, received electric signals pass through a signal amplification circuit and then are subjected to AD sampling, analog signals are converted into digital signals, the digital signals are sent to a control chip, the digital signals are filtered, and the digital signals are sent to the control chip. The forward scattering visibility meter has the advantages that signal envelope is extracted through transformation, wavelet transformation and noise reduction are performed, extinction coefficients and visibility are finally calculated, the forward scattering visibility meter is miniaturized through special design of a light path system, the use requirements of small size, small wind resistance and light weight are met, and the problem that the visibility meter is difficult to apply to an unmanned aerial vehicle is solved.

The invention discloses a communication method based on a low-noise high-dynamic full-wave radio frequency channel amplification circuit, and relates to the field of wireless communication and radio frequency integrated circuits. The method comprises the following steps: firstly, sampling a baseband signal and constructing a multi-dimensional time sequence feature vector containing a historical state and a change rate; predicting a signal envelope peak value in a future time window by using a lightweight long short-term memory network (LSTM); a dynamic bias control signal is then generated based on reverse mapping and parasitic parameter compensation. Digital delay is introduced into a radio frequency main path, so that bias voltage is pre-loaded to a grid electrode of an amplifier before a radio frequency signal arrives, and negative delay control is realized; and finally driving the amplifier through asymmetric filtering. According to the invention, the problem of signal truncation distortion caused by response lag in the traditional dynamic bias technology is solved, the amplifier is in a deep AB-class or B-class state of low quiescent current for a long time while ensuring no distortion in a high dynamic range, the power consumption and the thermal noise are greatly reduced, and the signal-to-noise ratio of the system is improved.

The application relates to the technical field of underwater detection, in particular to an underwater vehicle autonomous detection system and method based on seabed seismic wave signals. The system comprises a three-axis seismic wave signal acquisition module, a signal superposition amplification module, a signal filtering module, a signal envelope extraction module, an environmental noise integration module and a threshold comparison determination module. The acquisition module is orthogonally arranged to receive three-axis seismic wave signals and convert the signals into charge signals, the superposition amplification module completes signal conversion and superposition, the filtering module suppresses noise, the envelope extraction module extracts a detection value, the noise integration module obtains a noise integral value, the comparison module compares the two values, and when the detection value is greater than the integral value, an underwater vehicle existing signal is output. The application uses seabed seismic waves as a detection source, has strong anti-interference performance, works in a passive mode, is concealed and has low power consumption, can accurately capture weak seismic wave signals of the underwater vehicle, realizes autonomous detection of the underwater vehicle, and is suitable for long-term unattended deployment on the seabed.

The application discloses a kind of calibration method and device for rotary variation soft decoding, calibration method includes: according to N times oversampling frequency respectively sampling rotary variation feedback sine and cosine feedback signal envelope surface and obtaining positive, cosine oversampling signal;Positive, cosine oversampling signal is handled to obtain the zero position offset of rotary variation positive, cosine envelope signal;Positive, cosine oversampling signal is handled to obtain the amplitude of rotary variation positive, cosine envelope surface;Positive, cosine oversampling signal is handled to obtain the phase deviation of rotary variation positive, cosine envelope surface;Through the amplitude, zero position offset, phase deviation obtained by calculation, the envelope surface of rotary variation positive, cosine is compensated, and the signal after compensation is sent into phase-locked loop to obtain the angle and rotational speed information of rotary variation.The application obtains accurate amplitude, zero position offset, phase difference in turn, and then carries out error compensation, finally obtains corrected positive, cosine signal, effectively guarantees the efficiency of motor.

The application provides a fracture patient muscle mass detection method based on electromyographic signal analysis, and relates to the technical field of medical treatment. The method comprises the following steps: acquiring electromyographic signals of a target muscle and its adjacent muscles of a patient; when the correlation coefficients of the target muscle and the adjacent muscle signals and their envelope lines meet preset conditions, judging whether the target muscle is interfered by the adjacent muscles based on the signal difference degree; when the adjacent muscles interfere, extracting independent frequency component sequences of the target muscle and the adjacent muscle signals, removing interference components based on the time domain correlation coefficients and the frequency overlap degree of each independent frequency component group, and obtaining a real target muscle signal; determining the muscle recovery state of the patient based on the amplitude variation trend of the real target muscle signal sequence of the patient in a target period, and the amplitude difference between the contraction state sequence segment and the relaxation state sequence segment in the signal envelope line of the target sub-sequence of the sequence, and formulating a rehabilitation training scheme accordingly. The application can more accurately determine the muscle recovery state of the patient.

The application discloses a kind of self-adapting nonlinear impairment compensation methods based on low-cost optical performance monitoring, and its technical scheme main points are as follows: in transmitting end, low-speed mark is modulated to the envelope of high-speed data signal on top signal;A section of zero-power gap is inserted into signal, after digital-analog conversion and electro-optical conversion are successively carried out to data, into optical fiber link;In receiving end, the signal received is successively carried out photoelectric conversion, analog-digital conversion, IQ orthogonalization, clock recovery;Combining the step number of FD-Volterra-CDE back propagation process in different optical transmission link state parameter range N span Nonlinear effect introduced by the calculation of nonlinear impairment causes optical signal-to-noise ratio penalty;The adaptive nonlinear impairment compensation method in the application solves the problem of too high calculation complexity in the traditional nonlinear impairment compensation process, and by establishing the LUT of the step number N step , filter number N k In the process of FD-Volterra-CDE back propagation in different optical transmission link state parameter range, the calculation complexity is effectively reduced while the compensation accuracy is guaranteed.

The invention discloses an uplink channel signal time delay calibration method and system adopting a far field calibration system. The method comprises the steps that an uplink channel calibration unit generates an uplink channel calibration reference signal and an uplink channel calibration modulation signal and sends the uplink channel calibration reference signal and the uplink channel calibration modulation signal to a reference antenna and an antenna to be calibrated respectively; the reference antenna and the antenna to be calibrated send the received signals to a far-field calibration system; the far-field calibration system converts the received signal into a downlink signal and sends the downlink signal to the uplink channel calibration unit; the uplink channel calibration modulation signal demodulates the received signal into a signal envelope, and according to the signal envelope, a phase difference caused by the difference of the uplink channel of the to-be-calibrated antenna relative to the reference antenna is obtained; and selecting different uplink frequency points to calibrate the uplink channel relative phase difference of the to-be-calibrated antenna relative to the reference antenna to obtain the signal relative delay inequality of the to-be-calibrated antenna relative to the uplink channel of the reference antenna. According to the invention, the time delay calibration precision of the uplink channel of the antenna is improved.

The invention discloses a distributed acoustic sensing road cavity detection method based on an active excitation source. The method is based on distributed acoustic sensing (DAS), and comprises the following steps of: firstly, acquiring a DAS signal sampling data sequence to be processed; preprocessing the data of each DAS channel; calculating a short-time zero-crossing rate to remove channels with abnormal data records; then, signal space-time positioning is carried out through sliding window detection, signal envelopes in a signal area are extracted, and space-time distribution information of signals is obtained; and finally, extracting spatial correlation features and energy distribution features of the signals, and realizing automatic detection of the road cavity based on feature judgment. According to the method, all-weather sensing and high-resolution precision characteristics of the DAS array are fully utilized, accurate estimation of road cavity detection is achieved with small calculation amount, large-range sensing can be achieved, and the method is suitable for real-time engineering application occasions.

Methods for detecting power system events in an electrical power system. An example method comprises determining a signal envelope for each of at least first and second power system signals and performing density-based spatial clustering of a series of points formed by combining respective values of the signal envelopes for at least the first and second power system signals. The example method further comprises detecting one or more power system events by identifying outlier points or groups of points in the spatial clustering. Some methods may further comprise automatically classifying power system events by collecting a data set comprising, for each detected power system event, power system signal features corresponding to the detected power system event, and classifying each of the detected power system events using the data set and a machine-learning-based classification algorithm, where said classifying comprises determining a classification label from among two or more predetermined classification labels.

The application discloses a kind of modulation signal envelope extraction algorithm and electronic equipment, wherein algorithm includes the following steps: S1, according to modulation data, generate waveform image and obtain the image area corresponding to waveform image;S2, extract the original boundary of image area, obtain boundary pixel coordinate point set;S3, the coordinate point set after screening processing is handled to boundary pixel;S4, based on the coordinate point set after screening processing, complete envelope extraction, obtain the envelope set of modulation signal.The present application converts discrete data into waveform image, extracts target area using image segmentation algorithm, extracts area edge point coordinates using edge extraction algorithm of image processing, and then converts irregular area boundary at pixel level into an ordered coordinate set after screening, reduces data volume and improves the accuracy of subsequent envelope extraction, effectively solves the shortcomings in the existing commonly used algorithm;The present application has the characteristics of fast detection speed, safety and reliability, good practicability, high accuracy and the like.

The invention discloses a signal identification and measurement method based on 5GNR SSB time-frequency feature matching, and aims to solve the problems that in the prior art, a traditional 5GNR module chip is high in complexity and high in cost, and a simple analog detection scheme is prone to noise interference and cannot effectively distinguish LTE and 5G signals. The method comprises the following steps: extracting an energy envelope contour of a digital signal sample, adaptively calculating a detection threshold based on a dynamic range of the energy envelope contour, identifying candidate signal envelopes, and carrying out LTE interference pre-judgment; after the candidate envelopes are paired, verifying an effective envelope group through matching of multi-dimensional time-frequency characteristics including time domain periodicity, frequency domain form, waveform correlation and the like, and executing periodic suspicion rejection to eliminate interference; and finally, calculating the 5GNR signal intensity based on the effective envelope group. According to the invention, high-accuracy identification, high-efficiency measurement and strong anti-interference performance of the 5GNR SSB signal can be realized, and the hardware cost is reduced.

The present application discloses an interference suppression method and apparatus for ultra-high frequency partial discharge signal detection. The method comprises: constructing a normalized envelope detection model for continuous partial discharge signals and a normalized envelope detection model for continuous mixed signals; solving for envelope characteristic parameters of each partial discharge signal based on the normalized envelope detection model for the continuous partial discharge signal, and solving for envelope characteristic parameters of each mixed signal based on the normalized envelope detection model for the continuous mixed signal; wherein a mixed signal refers to a signal that is a mixture of the partial discharge signal and an interference signal; the envelope characteristic parameters include at least a root mean square error, skewness, and steepness of the envelope; and eliminating each partial discharge signal for which the deviation between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal is greater than an error ratio, thereby obtaining an interference suppression result for the ultra-high frequency partial discharge signal.

The present invention discloses an efficient power management system for a radio frequency power amplifier, which relates to the field of power management technology and includes: a main control display module for realizing the display of liquid crystal display status and parameters, precise adjustment of device gain, data communication and status monitoring; a power supply module for receiving AC power, processing to form a stable DC bus, and providing DC power supply through multiple DC-DC converters; an analog front-end module for processing radio frequency signals, performing pre-amplification, and realizing stable control of the signal amplitude of each channel through voltage adjustment and control circuits; a power amplifier module for multi-stage signal amplification, the output stage of which is composed of high-power switching devices, and is also provided with feedback adjustment and protection circuits for parameter matching and safety protection of power devices. By real-time acquisition of the radio frequency signal envelope and its complex entropy, dynamic adaptive adjustment of the power supply voltage is realized, effectively reducing nonlinear distortion and meeting the demand for high linear output in complex radio frequency environments.

The invention relates to the technical field of data processing, in particular to a sludge treatment equipment operation state monitoring method and system. The method comprises the following steps: acquiring a multi-dimensional time sequence signal of an operation parameter of sludge treatment equipment, and determining an instability index according to the multi-dimensional time sequence signal; determining a working condition change index according to the average change rate of the signal envelope of the multi-dimensional time sequence signal in different dimensions, and determining a fault significance weight according to the ratio of the instability index to the working condition change index; determining a weighted covariance matrix for principal component analysis according to a plurality of fault significance weights in a preset time window at the target moment; and performing principal component analysis by using the weighted covariance matrix to obtain a reconstructed signal, and determining whether the operation state of the sludge treatment equipment is abnormal or not according to a reconstruction error between the reconstructed signal and the multi-dimensional time sequence signal. Through the technical scheme, the running state of the sludge treatment equipment can be monitored.

Bandwidth adaptation in a transmission circuit is provided. The transmission circuit includes a power amplifier circuit that amplifies a radio frequency (RF) signal based on a modulated voltage, an envelope tracking integrated circuit (ETIC) that generates the modulated voltage based on a modulated target voltage, and a transceiver circuit that generates the RF signal and the modulated target voltage. The RF signal may have a wide modulation bandwidth but the ETIC may have a lower bandwidth limit, which can cause distortion in the modulated voltage and the RF signal. In this regard, the transceiver circuit is configured to generate the modulated target voltage in a lower bandwidth than the bandwidth limit when the modulation bandwidth of the RF signal exceeds the bandwidth limit of the ETIC. As such, the transmission circuit can process the RF signal across the wide modulation bandwidth without causing distortion in the RF signal.

The invention relates to a distributed optical fiber vibration intelligent monitoring method and system adaptive to multiple scenes. The method comprises the following steps: detecting light intensity data along a sensing optical cable; demodulating the light intensity data within the effective length to obtain vibration signal data along the sensing optical cable; analyzing a time domain peak energy characteristic value, a signal envelope energy characteristic value and a main frequency band energy characteristic value of the vibration signal data; self-adaptive flexible dynamic configuration is carried out on a time domain peak energy characteristic threshold value, a signal envelope energy characteristic threshold value and a main frequency band energy characteristic threshold value of each sensing unit; judging an external disturbance event by combining the time domain peak energy feature, the signal envelope energy feature and the main frequency band energy feature, and judging whether the external disturbance event is a disturbance event signal or not; and finally performing mode identification on the vibration signal type corresponding to the disturbance event. According to the method and the device, the complementarity of different energy characteristic values is utilized, and the target signal is analyzed by integrating multiple characteristic quantities and multiple dimensions, so that the precision and the robustness of vibration recognition are improved.

A method for improving sound quality of a speaker includes: performing frequency division on an input signal of the speaker to obtain a first low-frequency input signal and a first high-frequency input signal, where the input signal is a time domain signal; performing transient detection on the first low-frequency input signal to determine whether the first low-frequency input signal is a transient signal; if the first low-frequency input signal is a transient signal, performing signal envelope modulation on the first low-frequency input signal to obtain a second low-frequency input signal; determining an output signal of the speaker based on the second low-frequency input signal and the first high-frequency input signal, where a startup voltage of the second low-frequency input signal is higher than a startup voltage of the first low-frequency input signal, and loudness of the second low-frequency input signal is greater than loudness of the first low-frequency input signal.

Embodiments of the present disclosure provide a signal envelope detection circuit and chip. The signal envelope detection circuit comprises: N cascaded first amplification circuits, an input end of a first-stage first amplification circuit being used for receiving a target input signal; M cascaded attenuation circuits, an input end of a first-stage attenuation circuit being used for receiving the target input signal; M second amplification circuits, an input end of each second amplification circuit being correspondingly connected to an output end of one attenuation circuit; and a plurality of rectifiers, an output end of each first amplification circuit and an output end of each second amplification circuit each being connected to an input end of one rectifier. Output ends of all of the rectifiers are connected together and are used for outputting a target output signal. N and M are both integers greater than 1, and amplification multiples of the N first amplification circuits are the same as amplification multiples of the M second amplification circuits. The embodiments of the present disclosure can expand the dynamic range of the signal envelope detection circuit and improve detection accuracy.

The present application relates to the technical field of aquaculture monitoring, and discloses a Chinese octopus health state monitoring system based on voiceprint recognition, which comprises a multi-source sensing module for acquiring synchronous acoustic signals and environmental parameters, a signal purification module for adjusting a step length to restore residual signals by using a step length control formula based on a feedback delay phase error, an envelope demodulation module for separating breathing rhythm and chewing frequency by using Hilbert transform dimension reduction, a rhythm tracking module for calculating a physiological cycle and feeding back an error to the signal purification module, a dynamic affine module for obtaining a target vertex by remodeling vertices of a final feasible polyhedron by using synchronous dissolved oxygen data and synchronous water temperature data, and a state decision module for mapping a feature vector to a dynamic geometric space to generate a monitoring evaluation result. The present application effectively isolates physiological compensation interference induced by physical field natural fluctuation by implanting an environmental nonlinear compensation mechanism into an acoustic feature judgment space, and reduces the false alarm rate of health evaluation under complex working conditions.

Method and system for automatic modulation classification (AMC) use time-series voltage signals representative of radio frequency (RF) signal envelope and frequency components as input features to a deep learning-based neural network, which enables classification of both modulation type and symbol rate without requiring in-phase and quadrature (IQ) demodulation. A feature extraction circuit captures RF signal envelope amplitude and frequency using stub-based sensing, and a Long Short-Term Memory (LSTM) neural network processes these features in a digitized form to classify the modulation and symbol rate with high accuracy and minimal latency.

This invention belongs to the field of wireless communication and signal processing technology, and relates to a digital predistortion method, system, and application for power amplifiers in shortwave communication systems. This invention can cover the wide dynamic range of the power amplifier's operating range in shortwave communication systems, maintaining excellent linearization compensation across the entire power range. It effectively improves modulation signal distortion, spectral broadening, and adjacent channel interference, significantly reducing the system bit error rate and improving the quality of the transmitted signal, thus meeting the requirements for spectral and linearity specifications. This invention eliminates the need for multiple predistortion models and complex switching logic, greatly reducing system implementation complexity and storage resource overhead. When power levels switch or the signal envelope changes rapidly, it avoids additional distortion introduced by abrupt changes in predistortion parameters, ensuring continuous and stable linearization. Furthermore, this invention supports online adaptive updates, enabling real-time adaptation to changes in the nonlinear characteristics of the power amplifier, improving system robustness and environmental adaptability.

This invention discloses a method and apparatus for heart sound segmentation based on a Hidden Markov Model (HMM) cardiac cycle. The method involves: extracting the signal envelope from the heart sound signal using Hilbert's algorithm; obtaining the peak positions of the first heart sound (S1) and the second heart sound (S2) after Hilbert envelope extraction based on preset baselines for different leads; locating the peaks based on the cardiac cycle; extracting the diastolic phase based on an improved HMM; locating the optimal time span of heart sound signals S1 and S2 using an improved Viterbi algorithm; and segmenting the original heart sound signal using the time span and the peak positions of S1 and S2. This invention employs an improved HMM and an improved Viterbi forward algorithm to calculate the duration of heart sound intervals S1 and S2, combined with the cardiac cycle, to accurately locate the peak positions of heart sound intervals, thus improving the performance of heart sound segmentation.

The application discloses a kind of outer wall waterproof layer thickness detection methods based on ultrasonic, it is related to building engineering nondestructive testing technical field, including using ultrasonic detection equipment to collect the original ultrasonic echo signal of the surface of the outer wall waterproof layer to be measured, baseline correction is carried out to signal to eliminate the system error caused by hardware characteristics, and the preprocessed ultrasonic echo signal is obtained.Initial wave peak position reflected on the surface of waterproof layer is identified, and the effective signal segment containing interface echo information is intercepted.The signal envelope is extracted, and the local peak and trough positions are determined, and multiple candidate echo intervals are divided.The fusion characteristic value of the time domain and frequency domain characteristics of each candidate echo interval is calculated, and the target echo interval corresponding to the main interface of the waterproof layer and the base material is selected.The waterproof layer thickness is obtained by calculating the two-way travel time and combining the ultrasonic propagation velocity.This method can eliminate hardware error interference, accurately locate the effective echo and main interface echo, and improve the accuracy of outer wall waterproof layer thickness detection.

An electronic device may include wireless circuitry having an amplifier configured to receive a radio-frequency signal generated from a baseband signal, a first adjustable load component coupled to an output of the amplifier, a second adjustable load component coupled to the output of the amplifier, and a control signal generator configured to output one or more control signals for tuning the first and second adjustable load components based on an envelope of the baseband signal or the radio-frequency signal. The first adjustable load component can provide a first tuning range covering a first subrange of an instantaneous signal envelope of the baseband signal or the radio-frequency signal, whereas the second adjustable load can provide a second tuning range covering a second subrange of the instantaneous signal envelope of the baseband signal or the radio-frequency signal. The first and second tuning ranges are combined to provide an extended tuning range.

The application discloses an intracranial pressure detection method, which comprises the following steps: acquiring regional signal envelope data corresponding to a preset acquisition region, the acquisition region being set as at least two key brain regions, each key brain region corresponding to one regional signal envelope data; inputting the regional signal envelope data into a corresponding intracranial pressure estimation model which has been pre-trained, and outputting initial intracranial pressure data of each region; extracting an intracranial pressure correlation feature vector based on the initial intracranial pressure data of each region, inputting the intracranial pressure correlation feature vector into a contribution index prediction model which has been pre-trained, and outputting a contribution index corresponding to the initial intracranial pressure data of the region; and calculating target intracranial pressure data based on the initial intracranial pressure data of each region and the contribution index. Thus, the dynamic change difference of intracranial pressure in different brain regions is captured, and the accuracy and reliability of intracranial pressure detection are improved.