613 results about "Acoustic vibration" patented technology

The invention discloses a distribution box fire early warning method and system based on multi-source information fusion, and particularly relates to the technical field of distribution box fire early warning. Temperature, smoke, acoustic vibration and current harmonic signals are synchronously acquired, time sequence alignment and amplitude normalization are performed, and a dynamic baseline is generated in real time; extracting multi-scale statistics and morphological characteristics according to an adaptive window, and calibrating an operation mode through unsupervised clustering; then retrieving a matched baseline signature in a historical feature library, and calculating a multi-modal standardization deviation of a current window; mapping the deviation index into a graph node, combining a covariance edge weight, a phase synchronization index and a smoke discrete index, obtaining a coupling risk coefficient through a fusion model, and outputting a comprehensive risk index; and finally, carrying out multi-scale rate and acceleration analysis on the comprehensive risk index, triggering three-level early warning of attention, warning and danger by adopting a dynamic threshold, and correcting the threshold by utilizing operation and maintenance feedback self-learning, thereby effectively solving the problems of early warning response lag and unknown early warning level.

The invention provides an intelligent pipe surface quality detection method and system based on machine vision, relates to the technical field of industrial automatic detection and machine vision, and aims to establish a pipe surface feature library and mark shape abnormal features. The method comprises the following steps: collecting an image of a pipe in a bright and dark composite light field, extracting gray and texture features after polarization filtering processing, reconstructing a three-dimensional point cloud covering a mortar layer and a concrete layer by matching a principal component analysis dimensionality reduction fusion feature set with a feature library, and converting the point cloud into a two-dimensional expansion graph through cylindrical projection; a mortar abnormal area and a concrete abnormal area are segmented, the hole volume is calculated through point cloud residual errors in the mortar area, and internal hollowing is detected in combination with acoustic vibration excitation and thermal response; the concrete area locates defects based on point cloud features; according to the sequence of the concrete covering process before the mortar covering process, a correlation model is constructed to match and coincide the defect sites, and the detection result is output, so that the detection automation degree and accuracy can be improved.

The invention discloses a rapid demolding device and method for a small prefabricated part, and relates to the technical field of prefabricated part production. The mold bearing table is mounted on the substrate of the demolding rack and is integrated with a multi-point temperature sensor and an acoustic vibration signal collector; the ejection demolding assembly is installed on the stand columns of the demolding rack in a liftable mode and comprises an ejection plate assembly, and an ejection force sensor and a high-frequency vibrator are arranged on the ejection plate assembly; the visual identification module is mounted on the demolding rack; and the controller is electrically connected with the multi-point temperature sensor, the sound vibration signal collector, the ejection force sensor, the high-frequency vibrator, the visual recognition module and a driving mechanism of the ejection demolding assembly. Multi-source sensing information is fused, the component condensation state and the demolding time are accurately judged, the ejection force and vibration in the demolding process are adaptively controlled, accurate and flexible control over the demolding time and process is achieved, and the demolding success rate and the component yield are remarkably increased.

The invention relates to the technical field of offshore oil safety assessment, in particular to a process pipeline fatigue damage identification and prediction method, which comprises the following steps: step 1, key pipeline primary selection and failure possibility assessment; 2, collecting and preprocessing multi-modal data; 3, performing model construction and optimization on damage identification; 4, fatigue life prediction and failure early warning are carried out; 5, carrying out correlation analysis on the stress spectrum and the service life; 6, multi-parameter dynamic early warning is carried out; and 7, integrating a real-time monitoring system. According to the method, through multi-modal evaluation of fluid-to-vibration, fluid pulsation, high-frequency acoustic vibration and the like, a stress spectrum is generated by utilizing a rain-flow counting method, the crack growth rate and the residual life are predicted in combination with an S-N curve or a Paris formula, and through correlation analysis of the stress spectrum and the life and multi-parameter dynamic early warning, the crack growth rate and the residual life are predicted. Therefore, the method has the advantages that an online system integrating vibration, acoustic emission and stress monitoring is provided, and real-time evaluation and life prediction of fatigue damage are achieved.

The invention provides an anti-interference sound and vibration detection method and device, and relates to the field of sound and vibration detection. The method comprises the following steps: acquiring target special equipment and an equipment type corresponding to the target special equipment; according to the equipment type, acquiring a multi-channel high-sensitivity sensing array combination corresponding to the equipment type from a preset inspection method database; acquiring sound vibration signal data corresponding to the target special equipment based on the multi-channel high-sensitivity sensing array combination; performing modal decomposition on the sound vibration signal data by applying an improved empirical mode decomposition algorithm, eliminating pseudo-modal components and reconstructing effective modal signal data; and inputting the reconstructed effective modal signal data into a sound-vibration collaborative recognition model, and outputting a structural state recognition result of the target special equipment through the sound-vibration collaborative recognition model. According to the method and the device, the problem of low sound vibration detection accuracy of a traditional sound vibration detection technology when mechanical impact, fluid disturbance, electromagnetic interference or multi-source background noise is accompanied in the environment where the detected equipment is located is solved.

The invention relates to the technical field of solid-state battery energy conversion, and discloses a high-safety sodium-ion battery energy conversion method based on a solid-state electrolyte, which comprises the following steps: identifying an interface dynamic mismatch risk time period in a charging and discharging process, and applying micro-amplitude high-frequency acoustic vibration disturbance to a solid-state electrolyte and a sodium negative electrode interface in the time period, sodium ion microscopic distribution is regulated and controlled through the acoustic streaming effect, contact stress is dredged, dendritic crystal early nucleation is inhibited, dynamic reconstruction and optimization of the interface state are achieved, the solid-state sodium-electricity interface is converted into dynamic self-adaption from static mismatch, the ion transmission uniformity is actively maintained through the acoustic streaming effect, and dynamic reconstruction and optimization of the interface state are achieved. And meanwhile, real-time sensing of an interface state and dynamic adjustment of acoustic vibration parameters are realized in combination with an acoustic probing mechanism, so that the interface stability and dendritic crystal inhibition capability are effectively improved, and the energy conversion efficiency and the safety performance of the battery are remarkably enhanced.

The invention relates to the technical field of switch cabinet temperature measurement, and discloses a method for measuring the temperature of a switch cabinet in real time through an infrared matrix based on multi-modal sensing. The method comprises the following steps: synchronously acquiring an infrared image sequence, an acoustic vibration signal and current waveform data of the switch cabinet through a multi-mode sensor array, and capturing equipment operation and temperature associated information; constructing a three-dimensional temperature field reconstruction mechanism model based on a heat conduction physical equation, outputting a theoretical temperature distribution value fitting a physical rule, processing multi-source data by using a spatial-temporal feature extraction network, and outputting a temperature prediction value reflecting a real-time working condition; inputting the two into a dynamic fusion module based on a Markov decision process to generate a fusion temperature distribution value, and generating a temperature anomaly positioning instruction through a rolling time domain optimization strategy according to the fusion temperature distribution value; when the deviation between the actual temperature sampling value and the fused temperature distribution value exceeds a preset threshold value, calibrating a network output layer parameter; and triggering a linkage control protocol of the switch cabinet protection system according to the abnormal positioning instruction.

The invention discloses a spiral air duct predictive operation and maintenance method and system based on digital twinning, and relates to the technical field of air duct system state monitoring and operation and maintenance, and the method comprises the following steps: deploying a high-frequency acoustic emission AE sensor and a low-frequency vibration acceleration sensor at key nodes of a spiral air duct, and taking a fan start-stop signal and operation power as working condition labels; a high-frequency acquisition mode is automatically triggered, noise reduction processing is carried out, and a multi-mode acoustic vibration original signal data set which is provided with a time sequence and a working condition label and is subjected to preliminary noise reduction is output; the high-frequency acoustic emission AE sensor and the low-frequency vibration acceleration sensor are arranged in the spiral duct, the health state of the thin-wall structure is monitored in real time through the high-frequency acoustic emission technology, weak early-stage fault signals in the duct can be accurately captured and early warning can be given out in the fault germination stage of fretting wear, sealant aging and the like of the spiral duct, and the fault early-warning effect is achieved. Real-time monitoring, early warning and accurate operation and maintenance of the spiral air pipe are achieved.

The invention discloses a portable swallowing function screening system based on multiple modes. The portable swallowing function screening system comprises a signal acquisition device, a data processing device and an interactive display device which are connected in sequence, the signal acquisition device is used for acquiring a laryngeal pressure signal, a laryngeal acoustic vibration signal and a swallowing acoustic wave signal of a patient; the data processing device is used for performing feature extraction and feature fusion according to the throat pressure signal, the throat sound vibration signal and the swallowing sound wave signal to obtain a multi-modal fusion feature, and calculating a swallowing disorder risk probability through a preset deep learning model according to the multi-modal fusion feature; the interactive display device is used for judging the swallowing function according to the swallowing disorder risk probability and displaying the screening result of the swallowing function according to the judgment result.

The invention relates to a tunnel water leakage detection method and system based on sound vibration signals, in particular to the technical field of tunnel engineering. Comprising the following steps: adjusting equipment working parameters by using a tunnel water leakage monitoring model based on environment sensing data monitored by an environment sensor through a self-adaptive module; wherein the tunnel water leakage monitoring model is established based on a machine learning model, historical environment perception data and historical equipment working parameters are taken as training samples, the tunnel water leakage monitoring model is used for predicting equipment working parameters under the environment perception data, and the equipment working parameters comprise working parameters of an acoustic vibration sensor and / or an analyzer; after the working parameters of the equipment are adjusted, analyzing and processing the environment sensing data and acoustic vibration signals collected by the acoustic vibration sensor through an analyzer to obtain analysis data; and comparing the analysis data with a tunnel water leakage state change curve through a computer, and determining a tunnel water leakage area.

The invention relates to the technical field of concrete bubble monitoring, in particular to an aluminum film system concrete bubble dynamic monitoring and regulating method which comprises the following steps: applying a high-frequency alternating current with a first preset parameter to an aluminum film system to induce eddy current in an aluminum film and enable the aluminum film to generate thermally induced acoustic vibration; meanwhile, an eddy current thermally induced acoustic response signal reflected by an internal interface of the concrete is obtained; based on the response signal, determining current bubble state information in the concrete, including amplitude attenuation characteristics based on the sound pressure signal, frequency spectrum characteristics based on the sound pressure signal and phase delay information; and based on the bubble state information, a regulation and control instruction of a second preset parameter is generated, the regulation and control instruction is executed to adjust the parameter of the high-frequency alternating current applied to the aluminum film system, and directional traction regulation and control are conducted on the bubbles in the concrete. According to the invention, by means of an eddy current thermally induced sound technology, dynamic distribution, including the number, the particle size, the motion trail and the like, of bubbles is captured in real time, and instantaneous changes in the pouring process can be accurately reflected.

The invention provides a safety risk control method for geological storage of carbon dioxide and electronic equipment. A distributed optical fiber sensing system is arranged in at least one injection well of the target sealing and storage area in the axial direction of a shaft and penetrates through a main cover layer and a reservoir; the method comprises the following steps: acquiring background data through a distributed optical fiber sensing system, and establishing a multi-parameter baseline model including a temperature field, a strain field and background noise; temperature, strain and sound wave vibration signals are collected in real time, and key features are extracted; the key features extracted in real time are compared with a preset risk feature library, the types of risk events are identified, and the identified risk events are graded according to the spatial range and intensity of the abnormal signals; and according to the type and the grade of the risk event, generating and executing a corresponding control instruction. According to the embodiment of the invention, the optical fibers are distributed in the whole area along the shaft and the target stratum, a three-dimensional monitoring network covering the sealing body is constructed, and the hysteresis quality of traditional point type measurement and periodic exploration is overcome.

The invention discloses a wire-powder composite ultrasonic-assisted additive and subtractive material forming device and a manufacturing method, the wire-powder composite ultrasonic-assisted additive and subtractive material forming device comprises a rack, an additive manufacturing module, a subtractive material milling module, an ultrasonic-assisted module and a forming platform, the rack comprises a Z1-axis assembly, a Z2-axis assembly and an XY plane moving platform; the additive manufacturing module is fixed to the Z1-axis assembly, and the subtractive milling module is fixed to the Z2-axis assembly. The ultrasonic auxiliary module comprises an ultrasonic generator, an ultrasonic vibration head and a mounting frame; the mounting frame is fixed on the XY plane moving platform, and a thrust cylinder is fixed in the inner space of the mounting frame; in the additive manufacturing process, the thrust air cylinder pushes the ultrasonic vibration head to move along the guide rail, so that the ultrasonic vibration head upwards penetrates through the middle hole of the mounting frame and then is vertically pressed on the lower surface of the forming platform, and vibration of the ultrasonic vibration head is controlled through the ultrasonic generator. According to the method, the performance and morphology of the part in the manufacturing process can be regulated and controlled, and therefore high-efficiency and high-quality integrated forming of a complex structure is achieved.

The invention discloses a harbor area communication optical cable intelligent operation and maintenance method and system based on the AI technology. The method comprises the steps that optical cable sound wave vibration intensity parameters, environment parameters and positioning signal parameters are obtained in real time; performing quantitative preprocessing on each parameter and generating a vibration energy entropy coefficient, an environment stress coefficient and a positioning confidence coefficient; calculating a health index according to the optical cable health assessment model fusing the coefficients; triggering corresponding response measures according to the health indexes; generating a maintenance priority list, and performing path planning of a plurality of operation and maintenance nodes based on a Dijkstra algorithm; and updating the health assessment model. The system comprises a data acquisition module, a database storage module, an intelligent operation and maintenance center and an operation and maintenance module. According to the method, multi-dimensional sensing data is collected and quantified into corresponding coefficients, the optical cable concealment damage and potential risk sensing capacity is improved, the evaluation model is established to predict and accurately judge the operation state of the optical cable, active preventive and repairable maintenance is guided to be implemented, and the comprehensive operation and maintenance capacity of the system is improved.

The invention discloses a hydrogen leakage condition multi-parameter monitoring and identification and leakage rate deduction method and device, and relates to the technical field of hydrogen safety monitoring, and the method comprises the steps: obtaining multi-parameter sensing data; carrying out noise reduction processing on the multi-parameter sensing data; based on a temperature signal, a pressure signal and a fastening force signal in the denoised data, establishing a temperature-pressure-fastening force coupled physical model by adopting a porous medium model; performing short-time Fourier transform and variational mode decomposition on sound vibration signals in the denoised data to obtain characteristic parameters; based on the characteristic parameters, establishing an initial data sample set; adding the leakage rate and the concentration signal in the denoised data into the initial data sample set to obtain a data sample library; and establishing a multi-parameter leakage prediction model by using a convolutional neural network based on the data sample library and the physical model. According to the invention, the online real-time monitoring of the hydrogen leakage state, the accurate judgment of the leakage size and the rapid prediction of the leakage development trend can be realized.

The invention belongs to the technical field of rolling bearing manufacturing, and discloses a preparation method of a high-precision robot turntable bearing, which comprises the following steps: applying a static load simulating a preset working load to a bearing ring workpiece subjected to heat treatment, and executing a set of closed-loop acoustic vibration treatment on the workpiece in a state of keeping the static load, the processing can dynamically track the resonant frequency of the workpiece to update excitation, can monitor acoustic response characteristic parameters of the workpiece in real time, and automatically terminates when the time change rate of the parameters meets a stable condition. According to the method, the specific directivity is provided for the stress release process driven by acoustic vibration energy, so that an original disordered residual stress field in a workpiece forms an optimized form capable of actively adapting to future working loads, and the problem that the static geometric precision and the dynamic service precision of a bearing are inconsistent in a traditional process is solved.

The invention relates to the technical field of cable joint diagnosis, in particular to a cable joint abnormity early warning method and system, and the method comprises the steps: carrying out the feature extraction of infrared thermal image data and acoustic vibration data, and obtaining a multi-modal feature data set; quantifying the coupling correlation degree between the hot spot diffusion gradient and the vibration frequency component according to the multi-modal characteristic data set to obtain a regional thermal vibration coupling anomaly index; calculating a regional defect risk score according to the regional defect type distribution; obtaining a modal fusion weight distribution value based on the regional defect risk score and the regional thermal vibration coupling anomaly index; performing weighted fusion on the infrared thermal image feature data and the acoustic vibration feature data according to the modal fusion weight distribution value to obtain a regional defect coupling feature vector; and obtaining the defect probability of the cable joint according to the regional defect coupling feature vector, and carrying out graded early warning according to the defect probability of the cable joint. According to the method, the infrared thermal image and the acoustic vibration data are fused, so that accurate early warning of the abnormity of the cable joint is realized.

The invention relates to the technical field of oil pipe leakage detection, in particular to an underground oil pipe leakage detection system, which comprises an underground permanent monitoring unit, which comprises at least one optical fiber sensor, and the optical fiber sensor clings to the outer wall of a production oil pipe or is integrated in an oil pipe coupling and extends along the depth of a whole shaft; the ground signal processing and analyzing unit is in communication connection with the underground permanent monitoring unit; wherein the optical fiber sensor is used as a distributed temperature sensor and a distributed sound wave vibration sensor at the same time, real-time on-line monitoring of oil pipe leakage is achieved, early warning can be given out at the initial stage of leakage, the accuracy of leakage recognition is improved through collaborative analysis of bimodal sensing data, the false alarm situation is effectively reduced, and the reliability of oil pipe leakage detection is improved. A distributed measurement mode provides meter-scale spatial resolution, the depth position of a leakage point is accurately positioned, normal production operation does not need to be interrupted during system operation, and the operation cost of an oil field is reduced.

The invention discloses a robot inspection control method for textile equipment monitoring, and relates to the technical field of textile equipment monitoring, and the method comprises the following steps: a robot scans an environment along a preset path at a variable sampling rate through a mobile noise fingerprint collection method, synchronously collects working condition associated noise decomposition of textile equipment, and constructs a dynamic noise substrate; performing space-time-frequency domain constraint blind source separation by taking a dynamic noise base as a physical constraint and combining a sound vibration sensor, decoupling a background noise component, an equipment global vibration component and a residual signal, performing kurtosis detection on the residual signal, and performing preliminary screening on a fault signal by combining a preset abnormal triggering mechanism; according to the method, dynamic reconstruction of the noise base is achieved through multi-sensor cooperative working condition correlation modeling, the problems of noise time-varying characteristics and spatial isomerism are solved, an accurate reference is provided for subsequent noise suppression, the noise base serves as a physical anchor point for separation, the fault component separation purity is improved, and suspicious fault signals are effectively and preliminarily screened out.

The invention discloses a nondestructive testing device and method for the compactness of a pier based on sound wave vibration, and the device comprises a first annular track which comprises a plurality of spliced inner tracks and sleeves a concrete pier column; the second annular track comprises a plurality of spliced outer tracks, the diameter of the second annular track is larger than that of the first annular track, and fixing assemblies are arranged between the spliced inner tracks and the spliced outer tracks; a plurality of groups of crab walking mechanisms are mounted on the spliced outer track through deformable fixing assemblies; the ultrasonic detection system is mounted on the inner side of the spliced inner track; the visual detection systems are respectively mounted on the spliced outer track; and the ultrasonic detection system and the visual detection system are connected with the terminal system. According to the invention, surface defects can be captured, the internal compactness problem can be detected, and omnibearing detection of the internal and external states of the pier is realized.

The invention relates to the field of fan spindle state monitoring, and aims at synchronously acquiring sound and vibration signals through multiple channels, realizing nanosecond time alignment by adopting a precision time protocol, and performing denoising and normalization preprocessing on the signals to improve data integration and signal fidelity. Furthermore, short-time Fourier transform and continuous wavelet transform are combined to extract multi-scale time-frequency features, and a high-dimensional combined feature vector is generated in combination with cross-correlation analysis. And mapping the feature vectors to a low-dimensional manifold space through a local linear embedding algorithm, and constructing a dynamic mode reference template. Indexes such as curvature, track length and direction entropy are monitored in real time, whether the spindle has an abnormal evolution trend or not is judged through a self-adaptive curvature threshold, and abnormity judgment is achieved in combination with track backtracking verification. According to the scheme, the abnormal starting boundary of the spindle state can be caught in a refined mode, and the early warning and operation and maintenance response capacity of fan operation is effectively improved.

The invention relates to a conduit assembly (70, 90) for a fluid line (39, 42, 43) for a system (1, 101) for semiconductor technology, comprising at least one damping element (72.1, 72.2, 92) for damping acoustic vibrations in the fluid (79), wherein the conduit assembly (70, 90) has a compressible primary volume (77.1, 77.2, 97) into which the damping element (72.1, 72.2, 92) moves at least partially upon deformation. The conduit assembly (70, 90) is characterized in that it has a compressible secondary volume (78.1, 78.2, 98) which is formed as a part of the primary volume (77.1, 77.2, 97). The invention further relates to a system (1,101) for semiconductor technology with a conductor assembly (70,90) according to one of the embodiments described.

The invention discloses an acoustic excitation digital modulation noise reduction method and system for laser acoustic vibration detection and application. Comprising the following steps: step 1, acquiring single-point measurement time sequence parameters of laser vibration measurement equipment, step 2, measuring response characteristics of an audio excitation device, and determining pre-stabilization time required by an audio excitation signal from starting to reaching a stable amplitude; step 3, constructing an on-off keying modulation function, generating a digital gating function according to the time sequence parameter and the pre-stabilization time, and performing time domain multiplication on the audio excitation signal and the digital gating function to generate a modulated intermittent audio excitation signal; and 4, controlling the audio excitation device to play intermittent audio excitation signals, and synchronously triggering the laser vibration measurement equipment to scan and collect the measurement points on the surface of the object to be measured according to the time sequence parameters. Through the on-off keying digital modulation technology, audio excitation can be started only in the effective detection time period of laser vibration measurement, and therefore the average noise level and equipment power consumption are remarkably reduced.

The invention discloses a communication machine room environment monitoring system and device, and relates to the technical field of machine room environment monitoring, and the communication machine room environment monitoring system comprises a fusion alarm module, a fault root cause analysis module and a dynamic air duct optimization energy saving module. The fusion alarm module significantly reduces false alarms through heterogeneous sensor space-time alignment, confidence weighting and sound vibration interference filtering; the fault root cause analysis module constructs an equipment dependence graph based on CAD topology and CFD wind resistance, and uses a Bayesian network to lock root cause equipment in a second level and perform 3D visual positioning; the dynamic air duct optimizing and energy-saving module controls a fan and a flow guide plate in a closed-loop mode through a high-resolution thermodynamic diagram and reinforcement learning, cold energy is precisely put according to needs, energy is saved, and consumption is reduced. The system effectively improves the alarm reliability, shortens the fault positioning time, and reduces the PUE of a machine room.

The invention relates to an ultrasonic vibration assisted large-width copper plate strip continuous extrusion short-process technology, and belongs to the technical field of metal processing. A copper raw material is subjected to mechanical cleaning and then ultrasonic cleaning, and the surface cleanliness of the raw material is guaranteed; the cleaned copper raw materials are fed into continuous extrusion equipment, and ultrasonic vibration is adopted for assisting continuous extrusion; after the extruded copper plate strip is cooled, spraying a suspension containing cerium (IV)-sodium dodecyl benzene sulfonate-pyrrolidone nano aluminum oxide additive on the surface of the copper plate strip, and drying; straightening by using a multi-roll straightening machine to obtain a large-width copper plate strip; the cerium (IV)-sodium dodecyl benzene sulfonate-pyrrolidone nanometer aluminum oxide auxiliary agent is prepared from nanometer aluminum oxide, DMF (Dimethyl Formamide), sodium dodecyl benzene sulfonate, N-vinyl pyrrolidone, ammonium persulfate and cerous sulfate (IV); the copper plate strip prepared by the invention has relatively high density, relatively high tensile strength and ductility, and the mechanical property of the copper plate strip is remarkably improved.

The utility model discloses an ultrasonic wire feeding additive manufacturing device which comprises a base plate, a tungsten electrode welding gun, a wire feeder and an ultrasonic vibration system. The tungsten electrode welding gun, the wire feeder and the ultrasonic vibration system are jointly connected with a positioning rod, and the positioning rod is movably arranged above the base plate. The ultrasonic vibration system is located on one side of the wire feeder and used for generating high-frequency vibration signals and transferring the generated high-frequency signals to a welding metal wire. According to the ultrasonic wire feeding additive manufacturing device, ultrasonic vibration is applied to the welding metal wire, so that a high-frequency vibration signal is transmitted into the molten pool through the welding metal wire, cavitation is generated in the molten pool, beta columnar crystals generated in the solidification process can be effectively broken, and the production efficiency is improved. And the anisotropy problem of the internal structure and the mechanical property in the wire feeding direction and the stacking direction is solved, that is, the performance of an additive manufacturing part is improved.

The application belongs to the technical field of distributed optical fiber sensing, and particularly relates to a long-distance distributed optical fiber broadband acoustic vibration sensing system. The application utilizes the same laser to transmit and generate back Rayleigh scattering light and interference light in the same sensing optical fiber, and further constructs a distributed optical fiber acoustic vibration sensing system combined with Φ-OTDR and MZI, which comprehensively utilizes the performance advantages of both, utilizes a very simplified optical system scheme, realizes the function fusion of the two sensing structures on one sensing optical fiber, reduces the resource waste caused by the transmission of sensing signals by different sensing optical cables respectively, maximizes the optical fiber resource utilization rate, and reduces the system cost; utilizes a frequency division multiplexing demodulation scheme in the digital domain, expands the frequency response range on the basis of ensuring the high positioning accuracy of the system, realizes the simultaneous detection of the two systems by a single core, simultaneously realizes the high positioning accuracy and the continuous non-blind area detection in the broadband frequency range, and improves the reliability.

The invention relates to the technical field of moisture content measurement, and discloses a corrugated board moisture content measurement method and system, and the method comprises near infrared spectrum data, microwave transmission data and acoustic vibration data; calculating a spectral feature vector; constructing a microwave response matrix; determining an acoustic damping coefficient; calculating stability indexes of the spectral feature vector, the microwave response matrix and the acoustic damping coefficient in a preset time window, and calculating a consistency index and a confidence coefficient weight; fusing the spectral feature vector, the microwave response matrix and the water content corresponding to the acoustic damping coefficient through a Kalman filtering algorithm, and outputting initial water content; dynamically adjusting a process noise covariance matrix of Kalman filtering, and when the residual error of any data source exceeds a preset statistical threshold value, resetting the confidence coefficient weight corresponding to the data source to zero; and repeatedly executing fusion, and outputting the water content. According to the method, three measurement means of near infrared, microwave and acoustics are adopted, the water content state of the corrugated board can be represented more comprehensively, and the water content measurement precision is improved.

The invention discloses a microwave cavity heating structure based on acoustic vibration and a microwave heating homogenization method. Comprising a microwave heating cavity, an acoustic vibration device, a dynamic metal structure, a microwave generator and a temperature sensor, the microwave heating cavity is internally provided with an inner cavity, and the bottom surface of the inner cavity is connected with a plurality of dynamic metal structures which are distributed at equal intervals in an array manner; the acoustic vibration device is arranged on the side wall of the inner cavity and used for generating acoustic vibration to the inner cavity, the microwave generator is arranged on the side wall of the inner cavity and used for injecting microwave energy into the inner cavity to form an electromagnetic field, and the dynamic metal structure generates mechanical vibration under the influence of the acoustic vibration so as to dynamically change the distribution of the electromagnetic field of the inner cavity; and the temperature sensor is arranged at the top of the microwave heating cavity. The problems of hot spots and non-uniform heating in the microwave heating process can be effectively solved, the heating efficiency and quality are improved, and the microwave heating device is suitable for the fields of food processing, material treatment, chemical reaction and the like.