846 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 relates to the technical field of mold injection molding production, and discloses a fault diagnosis and prediction maintenance method and device for an intelligent injection mold, and the method comprises the steps: obtaining an original sound vibration signal and a real-time sound vibration signal; performing signal decomposition operation on the original acoustic vibration signal to obtain an acoustic vibration high-frequency component and an acoustic vibration low-frequency component; performing feature extraction operation on the sound vibration high-frequency component and the sound vibration low-frequency component to obtain a high-frequency feature set and a low-frequency feature set; inputting the high-frequency feature set and the low-frequency feature set into a detection model for model training to obtain an original detection model; inputting data acquired by different injection molding machines and molds into the original detection model for generalization learning to obtain a generalization detection model; and the real-time sound vibration signals are input into the detection model for mold state reasoning, a fault alarm type and a mold fault position are obtained, and fault diagnosis and mold maintenance of the injection mold are conducted according to the fault alarm type and the mold fault position. The method can realize fault diagnosis and maintenance of the injection mold.

The invention discloses a roughness optimization method and system for ultrasonic vibration assisted magneto-rheological deterministic polishing, and the method comprises the steps: placing an ultrasonic vibration table on a workpiece rotating shaft of a magneto-rheological machine tool, and connecting and fixing a workpiece to be machined with a clamp of the ultrasonic vibration table; the position posture of the workpiece to be machined is adjusted through a leveling mechanism and a center adjusting mechanism of the magneto-rheological machine tool, and it is ensured that the press-in position and the press-in depth of a magneto-rheological polishing ribbon formed on a polishing wheel in the magneto-rheological machining process are consistent; the viscosity and the flow of the magnetorheological polishing liquid are kept stable; detecting surface shape error data of the workpiece to be processed by the wave surface interferometer and generating a processing code; and the obtained machining code is input into a magneto-rheological machine tool, so that the magneto-rheological polishing ribbon conducts deterministic polishing on the detected workpiece to be machined based on the fixed press-in position and the press-in depth. The ultrasonic vibration assisted magneto-rheological deterministic polishing roughness optimization method aims at achieving ultrasonic vibration assisted magneto-rheological deterministic polishing roughness optimization, material removal uniformity is promoted, and the roughness of a workpiece is effectively reduced.

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 discloses an acoustically enhanced driven parallel piezoelectric micropump and a driving method thereof. The input layer, the supporting structure and the output layer are sequentially arranged in a stacked mode. The device is characterized by further comprising a plurality of actuators arranged in the supporting structure. The actuators are arranged in a linear array or a matrix. And an input cavity which is connected into a whole is formed between each actuator and the input layer. And a plurality of mutually independent output cavities are formed between each actuator and the output layer. The actuator is used for pumping fluid through self vibration. The input layer is provided with a plurality of inflow structures staggered with the through-flow structures on the actuator. The output layer is provided with a plurality of outflow structures aligned with the through-flow structures on the actuator. The multiple pump flow units are connected in parallel, acoustic vibration is coupled with mechanical vibration, the multiple flow inlet structures are arranged at the multiple antinode points of acoustic resonance, flowing of fluid is further enhanced, and the air pumping efficiency is improved.

The invention discloses a switch discharge detection method and system based on multi-source information fusion voiceprint signals. The method comprises the following steps: acquiring multi-source data of an open switch; preprocessing the acoustic vibration signal to obtain an acoustic vibration reconstruction signal, and performing feature extraction on the acoustic vibration reconstruction signal according to an optimized MCKD algorithm to obtain an acoustic vibration reconstruction signal feature; and constructing a CNN-LSTM fault identification model, introducing an attention mechanism, inputting the acoustic vibration reconstruction signal features in combination with the voltage data, the current data and the temperature data into the CNN-LSTM fault identification model for feature classification, and obtaining a fault type by using a softmax activation function according to the classified features. By combining the respective characteristics of the convolutional neural network and the long and short base memory network, the defect information existing in the voiceprint signal is effectively extracted, and the accurate diagnosis of the open switch state is 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 discloses a method and equipment for double-ultrasonic cooperative in-situ auxiliary electric arc additive manufacturing of a large metal component, an electric arc additive manufacturing system and an ultrasonic vibration auxiliary electric arc additive manufacturing system. The ultrasonic vibration auxiliary electric arc additive manufacturing system comprises two ultrasonic impact guns, an optical sensor, a temperature sensor and a calculation control system. The optical sensor collects optical characteristics of the deposition channel and the molten pool and converts the optical characteristics into electric signals to be transmitted to the calculation control system, and the temperature sensor is used for monitoring and collecting temperature information of the deposition channel and transmitting the temperature information to the calculation control system to draw an isotherm; the calculation control system adjusts the distance between the ultrasonic impact gun and the center of the molten pool according to the isotherm and the optical characteristics of the optical sensor mobile phone, and the ultrasonic power is adjusted; one of the ultrasonic peening guns applies ultrasound from the component side edge as materials are added to the component edge. By means of the multi-axis freedom degree and accuracy of the mechanical arm, double-ultrasonic vibration is applied to all positions of a large metal component in the material adding process, and the mechanical property is improved.

The invention discloses a conveyor carrier roller online monitoring method and device and electronic equipment. The method comprises the following steps of: firstly, acquiring a sound wave vibration signal generated in real time when the carrier roller of the conveyor moves; wherein the sound wave vibration signal is obtained based on reverse Rayleigh scattering light in the optical fiber; performing feature extraction from the sound wave vibration signal to obtain an energy feature value of each frame; performing normalization processing on the energy characteristic value to obtain a target characteristic value; judging whether the target characteristic value exceeds a preset threshold value or not: if the target characteristic value exceeds the preset threshold value, inputting the target characteristic value into a pre-constructed target neural network model, so that the target neural network model outputs a fault type corresponding to the target characteristic value; therefore, online monitoring of the conveyor carrier roller based on optical fiber sensing multi-feature fusion is completed. According to the method, the fault type can be automatically and accurately identified and output, so that the overall performance and safety of the conveyor carrier roller are enhanced.

The invention discloses a steel-concrete composite beam sound and vibration calculation method based on FEM-BEM-SEA, and belongs to the technical field of rail transit bridge vibration and noise reduction. The method comprises the following steps: determining the upper limit cut-off frequency of boundary element calculation; determining a lower limit starting frequency of statistical energy analysis; determining a boundary frequency based on the upper limit cut-off frequency and the lower limit start frequency; constructing a bridge finite element model of a bridge structure, and calculating vibration response in a full-frequency-band range when the train passes through the bridge; inputting the vibration response into the bridge boundary element model, and calculating an acoustic response within a range below the boundary frequency when the train passes through the bridge; establishing a bridge statistical energy analysis model of the bridge structure, and calculating acoustic response in a range above the boundary frequency; and jointly using the vibration response and the acoustic response as an acoustic vibration calculation result of the steel-concrete composite beam. According to the method, the problem that high-precision calculation and low calculation workload cannot be met at the same time during sound and vibration calculation of an existing bridge structure is solved.

The invention provides an ultrasonic vibration auxiliary brazing device for a superhard abrasive formed grinding wheel and an operation method of the ultrasonic vibration auxiliary brazing device, the device comprises a motion control system, an ultrasonic vibration system, a high-frequency induction brazing system and a formed grinding wheel fixing device, and the formed grinding wheel to be brazed is fixed on the fixing device through a spring chuck. The motion control system is composed of a sliding block arranged on the movable guide rail and a motor controlling the sliding block to move and can control the vertical moving speed and direction of the sliding block on the guide rail. The ultrasonic vibration system comprises two ultrasonic vibration amplitude-change poles, a piezoelectric ceramic transducer and an external ultrasonic power supply, each piezoelectric ceramic ultrasonic amplitude-change pole can provide longitudinal vibration, and two-dimensional oval ultrasonic vibration in the brazing process is achieved through synthesis of the longitudinal vibration in the two vertical directions; the motion control system drives the brazing head to move up and down according to the brazing progress, and cooling water circulates in an induction coil of the brazing head. The problems that in the brazing process of the formed grinding tool, brazing filler metal distribution is not uniform, the machining quality is low, the brazing temperature is too concentrated, and the metallurgical reaction is serious in the process are 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.

Systems, devices, methods, and implementations related to contact detection are described herein. In one aspect, a system is provided. The system includes a first piezoelectric microelectromechanical systems (MEMS) transducer coupled to configured to generate a first analog signal when the first analog signal is transduced from vibrations propagating through the object. The system includes a second piezoelectric MEMS transducer having configured to generate a second analog signal transduced from acoustic vibrations at a location of the object, and classification circuitry coupled to the output of first piezoelectric MEMS transducer and the output of the second piezoelectric MEMS transducer, where the classification circuitry is configured to process data from the first analog signal and data from the second analog signal, and to categorize combinations of the first analog signal and the second analog signal received during one or more time frames.

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 an ultrasonic vibration thermal aging treatment method and a high-performance aluminum-magnesium-silicon alloy material. Firstly, solution treatment and water-cooling quenching are carried out at the temperature of 555 DEG C, and then coupling treatment of ultrasonic vibration and thermal aging is carried out at the temperature of 150 DEG C; and under the combined action of ultrasonic vibration and a temperature field, precipitation of a beta ''phase is remarkably accelerated, proliferation and movement of dislocation are improved, grain refinement and microstructure optimization are promoted, and comprehensive improvement of the comprehensive mechanical property of the 6082 aluminum alloy is achieved within short aging. After the obtained high-performance 6082 aluminum alloy is treated for 1-3 hours, the hardness is improved to 120-125 HV, and the tensile strength is improved to 320-330 MPa. The ultrasonic aging vibration device comprises an ultrasonic generator, a transducer, an amplitude-change pole, a drying box, a fixed base and a fixed frame, efficient transmission of ultrasonic energy and stable vibration are ensured, and therefore the comprehensive mechanical property and machining quality of 6082 aluminum alloy are remarkably improved.

The invention discloses an LPBF additive manufacturing system and method based on ultrasonic vibration and laser remelting, and the system comprises a control device which is used for setting process parameters and a process route, generating a user input parameter instruction, and transmitting the user input parameter instruction to a motion control card; the mechanical device is used for controlling the lifting of the powder cylinder and the working cylinder through a driving device and controlling the cyclic operation of powder feeding and returning of the scraper; the laser device is used for completing laser remelting under the assistance of ultrasonic vibration; the ultrasonic device is used for transmitting ultrasonic waves to a workpiece on the sintering disc through an ultrasonic concentrator and carrying out ultrasonic vibration assistance; the dust removal and passivation device is used for filtering micro powder generated in the laser cladding process, oxidizing the outer surface of the metal micro powder and passivating the metal micro powder; and the atmosphere device adopts argon as atmosphere gas. According to the method, ultrasonic vibration after powder laying and ultrasonic vibration assisted laser remelting are achieved in the LPBF process, the defects existing in the traditional LPBF process are overcome, and a novel and effective technology is provided for additive manufacturing.

The invention relates to a wooden bead polishing device, and belongs to the field of furniture processing. The wooden bead polishing device comprises an outer groove, an inner groove, a first driving mechanism used for driving the inner groove to rotate, a second driving mechanism used for driving an elastic ring to move repeatedly in the radial direction of the inner groove, a megasonic vibration generating device and a polishing medium. According to the wooden bead polishing device, the polishing effect on wooden beads can be remarkably improved under the multiple effects of rotating centrifugal force, vibration force generated by high-frequency vibration, magnetic force, radial acting force caused by elastic force and the like. The polishing mode that stirring is conducted through a stirring paddle is not adopted, the wooden beads do not need to be raised and thrown down during polishing, damage to the wooden beads is small, the polishing effect is good, and the polishing efficiency is high.

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.

An ultrasonic surgical device comprising of a proximal end and a distal end to be used in a robotic surgical system. The distal end comprises of a first jaw with an ultrasound transducer array and a second jaw with either a reflecting surface or an ultrasound transducer array. The distal end is configured to grasp a blood vessel or a living tissue. The proximal end is configured to apply a drive signal to the ultrasound transducer array. A plurality of rotary joints is connected at the distal end to facilitate its articulation. The ultrasound transducer array, generates acoustic vibrations in the grasped blood vessel, or living tissue, based on the applied drive signal by a control system of the robotic surgical system. The ultrasound transducer array, is configured to sense parameters of a target site on a grasped blood vessel or living tissue, based on the reflected acoustic vibrations.

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 target event positioning method and system for simultaneous adjacent sensing units. Relates to the technical field of target positioning. According to the scheme, a plurality of adjacent sensing units form an abnormal signal cluster for feature extraction, a plurality of classifiers are fused to make a decision on each sensing unit in the cluster and obtain confidence distribution of a corresponding event type, confidence distribution feature information of the event type is extracted, and the event type corresponding to the abnormal signal cluster is obtained by combining a BP network model. Determining the position information of the sensing unit where the target event is actually located; high-precision mode recognition and positioning of external disturbance events are realized; according to the scheme, the event confidence spatial distribution of each sensing unit in the cluster is calculated based on the event confidence spatial distance weighting formula, and the problems that the acoustic vibration signal propagation process is complex and the actual disturbance source is difficult to position due to the unknown buried condition of the optical cable are effectively solved.

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.

An unmanned aerial vehicle (UAV)-based system for contact inspection of civil infrastructure includes a UAV equipped with a modular payload comprising an actuated boom, contact-based end effector, and multi-modal sensor suite. The end effector uses spring-loaded strikers or toothed rollers to excite the structure surface, generating diagnostic acoustic vibrations. Onboard sensors measure the acoustic response, which is analyzed in real-time by a machine learning model to detect and quantify subsurface defects like delamination, voids, and cracks. Auxiliary sensors enable intelligent navigation relative to the structure surface and precise defect localization. The system allows remote, automated inspection of hard-to-reach areas, overcoming the safety and accuracy limitations of manual methods. By enabling efficient, comprehensive, and quantitative structural health evaluation, this invention will facilitate proactive infrastructure maintenance, extending service life and ensuring public safety.