118results about How to "Rich data support" patented technology

The invention discloses a bridge damage detection method and system, and belongs to the technical field of bridge engineering.The method comprises the steps that image data, point cloud data and spectral data of a to-be-detected bridge are obtained; inputting the obtained image data, point cloud data and spectrum data of the to-be-detected bridge into an input module of the constructed bridge damage detection model, and determining feature vectors of the image, the point cloud and the spectrum; and a feature fusion module of the constructed bridge damage detection model fuses feature vectors of images, point clouds and spectrums, interacts and fuses obtained fused feature representations of all modals on different levels to obtain fused feature vectors, and outputs a bridge damage detection type through a classifier in a DNN classification layer. The method can improve the accuracy of bridge damage detection.

The invention relates to the technical field of police service management, discloses a police service management system and method based on an image recognition technology, and aims to improve the police service management efficiency and accuracy. The system comprises a data receiving module, a data preprocessing module, a target detection module, a behavior analysis module and an information integration module. A monitoring video stream is received, data is preprocessed to form an image data set, and then a specific target is detected by using a deep convolutional neural network and a track sequence is output. And carrying out behavior analysis on the target track by adopting a long-short-term memory network, and identifying an abnormal mode. And finally, integrating the detection result and the behavior analysis data, and generating a police service management report. According to the invention, intelligent processing of monitoring videos is realized, police service departments are assisted to respond to abnormal conditions in time, and urban public security is maintained. Through the deep learning technology, the accuracy of target detection and behavior recognition is improved, and powerful support is provided for modern police service management.

The invention discloses an AED intelligent first-aid management system based on the Internet of Things, and relates to the technical field of first-aid management, and the system comprises a data collection and transmission module, a first-aid decision support module, a resource scheduling and cooperation module, and a first-aid training and evaluation module. The first-aid decision support module processes acquired data by using big data analysis and an artificial intelligence algorithm, quickly judges the type and severity of cardiac arrest, generates a personalized first-aid scheme and pushes the personalized first-aid scheme to first-aid personnel equipment, and the resource scheduling and collaboration module tracks AED equipment and personnel information in real time, plans and deploys a path and an attendance route in combination with road conditions, and sends the path to the first-aid personnel equipment. The system is connected with a hospital system to realize efficient cooperation of first aid; through deep fusion of the Internet of Things technology, big data and artificial intelligence, an efficient and intelligent AED first-aid management system is constructed, the first-aid response speed and success rate are remarkably improved, and precious treatment time is won for patients.

The invention relates to the field of bridge construction, and discloses a real-time monitoring system for a bridge construction process, and the system comprises a high-precision sensing module which is used for monitoring the data of all aspects in the bridge construction process in real time; the communication module is used for transmitting the data acquired by the sensor to a monitoring center in real time; the intelligent analysis module is used for preprocessing, storing, comprehensively analyzing and predicting the collected data and generating early warning information; the visual monitoring module is used for displaying an analysis result and real-time data to construction management personnel; the high-precision sensing module, the communication module, the intelligent analysis module and the visual monitoring module are in communication connection through a network. According to the invention, the real-time condition of the construction site can be comprehensively and accurately reflected through the high-precision sensing module, and compared with a traditional manual patrol and regular detection method, potential safety hazards can be quickly found and pre-warned, so that the safety and reliability of the construction process are ensured.

The invention relates to the technical field of intelligent traffic, and discloses a deep learning-based expressway traffic flow detection method and system, and the method comprises the steps: obtaining multi-modal traffic data and environment data in real time from each key road section of an expressway, and carrying out the preprocessing of the multi-modal traffic data obtained in real time, including the time-space alignment of the multi-modal traffic data; inputting the preprocessed multi-modal traffic data and environment data into a pre-trained deep fusion network model, and outputting various vehicle parameters for representing expressway traffic flow characteristics; inputting the various vehicle parameters into a pre-trained high-speed traffic flow detection model, and outputting traffic flow grade information; dynamically updating the deep fusion network model at the key road section by adopting a model fusion mode according to the vehicle parameter change condition at each key road section within the preset time; and updating the high-speed traffic flow detection model according to external conditions introduced by the traffic flow grade information in actual use. And the accuracy and real-time performance of high-speed traffic flow detection are improved by combining deep learning.

The invention discloses a community street environmental health supervision system and method based on big data, and relates to the technical field of environmental health supervision. According to the community street environmental health supervision system and method based on big data, garbage station data and cleaning data are collected in real time through multiple sensors, a periodic mode of garbage generation is identified by using a time sequence analysis technology, and the cleaning priority of garbage stations is evaluated. Based on a regression prediction algorithm, the system can predict the change trend of the garbage output, timely recognize the garbage accumulation problem and dynamically adjust the cleaning frequency and route of the garbage truck. By comprehensively analyzing the garbage cleaning efficiency and the cleaning coverage, the system generates a sanitary condition index of each street to help to judge whether the street meets the cleaning standard or not. According to the method, resource allocation can be optimized in real time according to data, the garbage cleaning efficiency and precision are improved, the garbage truck cleaning route is optimized, and the overall sanitation level of streets is effectively improved.

The invention discloses a financial service platform and method supporting dynamic product access and data backflow, belongs to the technical field of data transmission, and aims to solve the technical problem of how to quickly and flexibly access different financial institution products and realize efficient data backflow. Comprising a user interaction interface, a product access configuration module, a dynamic access engine, a data analysis module, a data backflow module, a security convergence module and a database, rapid access of financial institution products is achieved in a configuration mode, and the development time and cost are greatly reduced; the dynamic access engine can adapt to product interface changes of different financial institutions, and the flexibility and expandability of the system are improved; the data backflow module realizes efficient backflow of data, provides rich data support for a financial service platform, and facilitates data analysis and decision making.

The invention relates to the technical field of physical detection of deep soil, in particular to soil detection equipment for determining components of deep soil, which comprises a deep soil detection mobile rack; a bearing top frame is fixedly assembled on the surface, and a vertical groove is formed in the inner wall of the front side of the bearing top frame; a deep soil sampling device is arranged on the bearing top frame; an outer gear ring drives a drilling bit to rotate into the ground, along with rotation of the drilling bit, a first servo motor is started, a lifting frame box drives a deep soil detection structure, a soil depth extension assembly and a deep soil drilling assembly to descend, and the drilling bit continuously opens a hole along an adjusting hole; according to the deep soil sampling structure, the deep soil drilling assembly and the soil depth extension assembly penetrate into the ground, the deep sampling applicability is high, the soil depth extension assembly and the deep soil drilling assembly in the deep soil sampling structure are modularly arranged, and the number of the soil depth extension assemblies can be increased according to needs so as to meet the sampling requirements of deep soil at different depths; the flexibility is high.

The present disclosure provides a workpiece clamping force monitoring system for a clamp, belonging to the technical field of tooling clamps. The workpiece clamping force monitoring system for the clamp comprises a plurality of sensor modules for monitoring the pressure information of the workpiece when the clamp clamps the workpiece in real time and transmitting the pressure information to a data processing module. The data processing module can transmit the processed pressure data to a central control module through a first communication module. The central control module can transmit the data information to a display module to display the pressure fluctuation curve, and can also intelligently analyze the plurality of pressure information to determine a target adjustment strategy. When the pressure information is abnormal, the first alarm module is triggered, an alarm is given and emergency shutdown measures are taken. The workpiece clamping force monitoring system for the clamp provided by the present disclosure can improve the control accuracy, accuracy and anti-interference of the clamping force of the clamp, and based on the abnormal pressure information, an alarm is given to avoid causing greater losses, ensure the stability of the machining process and improve the production efficiency.

This invention designs a multi-scale star surface impact crater detection method, system, and medium. The method includes the following steps: S1: Acquire star surface images and segment them into image patches of different scales; S2: Construct multiple impact crater detection sub-models; S3: Train each sub-model using star surface image patches of different scales; S4: Input the segmented star surface image to be detected into each pre-trained sub-model to obtain the detection results; S5: Select the bounding boxes with high confidence and large area among all candidate bounding boxes of each impact crater as the final detection result for that impact crater. This invention can simultaneously identify impact craters of different scales in star surface images with high accuracy, especially improving the accuracy and efficiency of identifying small impact craters, providing more accurate and comprehensive data support for lunar science research, and promoting the in-depth development of lunar exploration and geological research.

The invention discloses a distributed optical fiber-grating-based rockburst test system and method, solves the problem that in the prior art, only strain parameters are simply obtained in a rockburst test, and has the beneficial effects of accurately simulating rockburst and obtaining related parameters of the rockburst. According to the specific scheme, the rockburst test system based on the distributed optical fiber-grating comprises a test device, the test device comprises a vibration table, and the vibration table supports a supporting box body; the rock sample is provided with an optical fiber channel, and the distributed optical fiber penetrates into the optical fiber channel; the vibration table, the stress applying component and the drilling disturbance component are respectively connected with the control unit; the monitoring unit is connected with the distributed optical fiber and the grating optical fiber; the monitoring unit sends monitored data to the control unit, and the control unit judges when rockburst is triggered and obtains stress change, elastic strain energy release amount and strain abrupt change time difference at the moment of rockburst when the rockburst occurs.

The application discloses a natural gas hydrate stratum and wellbore working fluid interaction simulation experiment system, and relates to the field of experimental instruments, which comprises a high-pressure kettle, a gas injection unit, a liquid injection unit, a wellbore working fluid circulation unit, a vacuum preparation module and a monitoring unit; the high-pressure kettle is internally provided with a simulated stratum and a vertical simulated wellbore with a liquid permeation hole; the gas injection unit and the liquid injection unit are respectively used for injecting methane gas and working fluid into the high-pressure kettle; the wellbore working fluid circulation unit comprises a magnetic circulation pump and a high-pressure filter and is used for driving the working fluid to circulate in the simulated wellbore; the vacuum preparation module is used for preparing an initial experimental environment; and the monitoring unit comprises temperature, pressure and displacement sensors, an ultrasonic detection system, a resistivity imaging system and a microscopic imaging system and is used for monitoring and collecting parameter changes of the simulated stratum under the action of multiple physical fields in real time. The application can simulate a wellbore working fluid circulation invasion process and comprehensively evaluate the influence of the working fluid on the stability of a natural gas hydrate stratum and the phase change of hydrates.

The invention belongs to the technical field of coal rock mechanical property testing, particularly relates to a mechanical testing device and method for coal rock loading, and solves the problems that an existing device is single in function, fragments splash, cleaning is inconvenient, and protection and cleaning are not linked. The device comprises a supporting mechanism, and a modular loading mechanism is detachably mounted on the supporting mechanism and comprises a static extrusion loading module and a dynamic impact loading module; the linkage type protection mechanism is provided with two protection half barrels, and fragments can be prevented from splashing when the two protection half barrels are closed; the sweeping mechanism is started when the protective half barrels are unfolded, a rotating ring drives a Z-shaped plate to rotate, an annular inclined panel is driven to vibrate, and fragments are swept; the device integrates a static extrusion function and a dynamic impact function, so that the equipment utilization rate and the application range are improved; protection and cleaning are linked, safety is guaranteed, cross contamination is avoided, and the experiment accuracy and efficiency are improved.

The invention relates to the technical field of logistics intelligent management, and particularly discloses a large logistics cognitive collaborative management system which is constructed based on AI and an industrial internet platform and is provided with an edge layer, a platform layer, an engine layer and an application layer. The edge layer is constructed based on an IT system, OT equipment and manual filling of the logistics transportation industry, and corresponding data acquisition capability is activated according to a received data request; the platform layer starts a corresponding data processing flow according to the received task instruction; the engine layer performs analysis, identification and task planning processing on the received request, and performs intelligent analysis processing on the received data; and the application layer analyzes the received user request and outputs the received data result. According to the invention, the IT system and the OT equipment in the logistics transportation industry are integrated, intuitive and efficient cognitive collaborative management can be formed for large logistics, and a timely, comprehensive and accurate data support basis is provided for business and technical decisions of enterprises.

This invention discloses an adaptive weight-based power load forecasting method. The method includes: constructing a multi-source feature matrix based on pre-collected data of the region to be predicted; calculating an enhanced feature matrix based on the multi-source feature matrix using a preset dual-branch attention module; determining a dynamic weight vector based on real-time feature data of the region to be predicted; calculating a dynamic feature matrix based on the dynamic weight vector and the enhanced feature matrix; training a preset deep learning model using the dynamic feature matrix to obtain a load forecasting model; and forecasting the power load of the region to be predicted at a preset target time using the load forecasting model to obtain predicted load data. This invention can improve the accuracy of power load forecasting.

The invention relates to a three-dimensional heterogeneous formation water control oil extraction multi-parameter synchronous simulation experiment device which comprises a device body, a plug, a production pipe column and a sensor unit. The device body is of a coaxial multi-layer nested structure, a plurality of independent simulation units are constructed in an internal annular sand filling area through replaceable sieve pore partition plates, and heterogeneous stratum reconstruction of fluid communication and sand body isolation is achieved. The production pipe column adopts a modular water control short section series connection structure, a replaceable fluid sensitive valve and a tracer agent storage cabin are integrated, and performance evaluation and fluid traceability of multiple types of water control tools are achieved; the sensor unit synchronously acquires outlet, wall surface and radial gradient pressure through three-dimensional arrangement of mandrels with various lengths, and realizes multi-dimensional data collaborative analysis in combination with flow and water content monitoring. The problems that an existing device is difficult to restore complex fluid channeling physical characteristics and is single in monitoring dimension are solved, full-process high-fidelity simulation from stratum seepage to tool water control is achieved, and key technical support is provided for water control strategy optimization.

The application provides an AI-based eye health management and lens fitting recommendation method and system, which captures eye state information through a collection device, synchronously acquires optometry data and eye detection data and pre-processes; inputs the data into an AI analysis model, identifies eye features and analyzes eye health conditions, and generates a health assessment report; based on the report, matches correction and protection schemes and screens adaptive contact lenses in combination with eye use requirements; through the linkage of intelligent wearable devices and special function contact lenses, eye data is monitored and health management suggestions are generated, visual expansion effect is realized, and the evaluation results and recommended schemes are continuously iterated and optimized, realizing the individualization and intelligentization of eye health management and lens fitting recommendation.

The application provides a kind of road marking thickness continuous detection method and system, belong to marking detection technical field;The method comprises: by distance sensor when detecting car each travel set distance triggers 3D laser profiler and observation camera synchronous acquisition point cloud profile data and two-dimensional image;In two-dimensional image, identify the junction of marking and ground, determine the corresponding junction in point cloud profile using the mapping relationship of pre-calibration;Each point cloud profile is matched and aligned based on shape template, and the 3D point cloud model of the marking after the correction of the detection vehicle is constructed;In 3D point cloud model, the marking plane and the ground plane are fitted respectively, and the height difference is calculated as the marking thickness.The application eliminates the jitter error in vehicle detection by template matching, without knowing the vehicle attitude, can realize sub-millimeter level precision marking thickness continuous measurement, can also calculate the marking width synchronously, high detection efficiency, and suitable for various road environments.

The invention relates to the technical field of reservoir dam body remote monitoring, in particular to an ultra-long-distance reservoir dam body monitoring system and method based on a flexible inclinometer. The method comprises the following steps: acquiring survey data of a reservoir dam body at different acquisition points based on a flexible inclinometer, acquiring a posterior sample of random field model parameters through Bayesian inversion analysis based on the survey data, and executing reliability analysis based on the posterior sample to calculate a posterior failure probability of the reservoir dam body. The stability reliability of the reservoir dam body is obtained based on the posterior failure probability; obtaining a reservoir dam settlement prediction value based on the survey data; and obtaining the stability reliability of the reservoir dam body and a reservoir dam body settlement prediction value, and generating an early warning signal based on the stability reliability of the reservoir dam body and the reservoir dam body settlement prediction value. According to the ultra-long-distance reservoir dam body monitoring system based on the flexible inclinometer, comprehensive monitoring of the whole reservoir dam body area can be achieved, and the monitoring accuracy and reliability are improved.

This application discloses a data-processing-based intelligent management method and system for thermal power fuel, comprising the following steps: collecting multi-dimensional data of the entire life cycle of thermal power fuel; cleaning, standardizing, and fusing the collected multi-dimensional data to obtain pre-processed fuel data; constructing a multi-dimensional analysis model to analyze the pre-processed fuel data, comparing the analysis results with preset condition information, generating procurement adjustment instructions, inventory scheduling instructions, coal blending execution instructions, and equipment operation and maintenance early warning instructions, and pushing the instructions to the corresponding execution terminals, collecting feedback data in real time during the instruction execution process; obtaining instruction execution status data based on the feedback data, visualizing the instruction execution status data, fuel data, and analysis results, and generating multi-dimensional statistical reports; this invention establishes a unified data collection and integration mechanism, breaks down data barriers at each stage, and forms a complete data link for the entire fuel life cycle.

The invention relates to a pavement crack monitoring method and system, and belongs to the technical field of pavement state monitoring. According to the method, the problems of insufficient identification reliability, lack of three-dimensional geometric information and incapability of dynamic prediction caused by dependence on single sensing data in the prior art are solved. The method comprises the steps of synchronously collecting multi-modal sensing data containing a two-dimensional image and a three-dimensional point cloud, establishing a mapping relation between two-dimensional pixels and a three-dimensional space through space-time registration, extracting a candidate crack region based on a crack recognition algorithm, and projecting the candidate crack region to the three-dimensional point cloud to generate a candidate point cloud set, according to the method, geometric feature parameters including depth variance and normal vector consistency indexes are calculated, a real crack is judged by comparing the geometric feature parameters with a preset threshold value, three-dimensional form information is output, finally, the same crack is associated through feature matching based on the multi-cycle three-dimensional form information, the expansion rate is calculated, and the remaining service life is predicted according to a material fatigue model. The method and the system are mainly used for crack detection and state evaluation in road maintenance management.

The application discloses a kind of complex lighting conditions underwater artificial crack dataset construction method, it is related to image dataset production technical field, including, collection crack picture and extract crack curve generation coordinate information, based on this, construct crack 3D model and prepare concrete standard test block;The test block is placed in water, and underwater crack image under conventional, dim and uneven illumination is collected, and is classified after pre-processing according to illumination condition;Stable Diffusion model based on LoRA fine-tuning is used, and different illumination condition images are input respectively to train and optimize, and style expansion image is generated, and pre-processing image constitutes unlabeled data together;Through image enhancement algorithm processing the data, after the enhanced image is labeled, the label is corresponded with the original image, and the underwater artificial crack dataset under complex lighting conditions is constructed, the application solves the problem that actual underwater crack disease is difficult to collect, meets the core demand of engineering practice, and provides richer data support for underwater structure crack detection and segmentation model training.

The application relates to the technical field of foundation engineering construction, and discloses a device for detecting the thickness of deposited sediment in foundation engineering construction, which comprises a deposited sediment thickness detector installed on a foundation. The device is characterized in that the rolling assembly, the steel wire rope, the rotating disc and the turnover frame are cooperatively operated, the detection of different positions in a pile hole can be completed without repeated disassembly, and the detection efficiency is greatly improved; the positioning plate increases the contact area, the extrusion arm firmly clamps the side wall of the pile hole, stable support is provided for the probe puncture, the detection data is ensured to be accurate and reliable; the output end for adjusting the probe position acts on the steel wire rope, damage caused by the probe being stuck is avoided, and the service life of the device is effectively prolonged; meanwhile, the turnover frame, the rotating disc and other structures are matched, the flexible movement and multi-angle detection of the probe in the pile hole are realized, the detection range is significantly expanded, and more comprehensive and accurate data support is provided for the quality evaluation of foundation engineering construction.

The application provides a method and system for checking the cross-modal information consistency of a maintenance plan based on a large model, and relates to the technical field of big data analysis. The method comprises the following steps: identifying a target maintenance plan through a power large model, determining key maintenance content, an unstructured proportion, and an attachment type complexity; obtaining a text data complexity and a business risk index based on key maintenance content analysis, as a first checking difficulty coefficient and a second checking difficulty coefficient; determining a third checking difficulty coefficient according to the unstructured proportion and the attachment type complexity evaluation; taking the expected review time limit of the target maintenance plan as a constraint, formulating an adaptive checking depth and an adaptive checking breadth based on the first checking difficulty coefficient, the second checking difficulty coefficient, and the third checking difficulty coefficient; and performing cross-modal information consistency checking on the target maintenance plan according to the adaptive checking depth and the adaptive checking breadth. The dynamic allocation of resources for checking the cross-modal information consistency of a maintenance plan is achieved.

The invention relates to the technical field of wireless communication IC (integrated circuit) chips, and discloses a chip data acquisition method, which comprises the following steps of: acquiring physical layer acquisition data of different nodes in a physical layer and preprocessing the physical layer acquisition data; wherein the physical layer acquisition data comprises physical layer data and physical layer maintenance and measurement signals; sOC working information is recorded while physical layer collection data is collected, so that a current SOC maintenance and measurement signal is collected through a data bus; combining the SOC maintenance and measurement signal and the physical layer acquisition data into an acquisition signal, and performing data processing on the acquisition signal; wherein the data processing comprises data selection processing, extraction, trigger control and trigger length control; and the acquisition signal after data processing is written into the Memory unit through the data bus to be recorded or is output from the direct peripheral interface. According to the chip data acquisition method provided by the invention, the physical layer data and the maintenance signal of the chip are acquired, and the technical problem of how to acquire the chip data more efficiently, accurately and comprehensively is solved.

The invention relates to the technical field of image processing, and discloses a landslide surface crack three-dimensional evolution unmanned aerial vehicle image extraction and quantification method and system, and the method comprises the steps: carrying out the bundle adjustment of an ultrahigh overlapping degree aerial image of a landslide surface, and obtaining an image shooting position, an image attitude parameter and a sparse three-dimensional point cloud; constructing a high-precision digital earth surface model; performing digital mosaic on the aerial image with the ultrahigh overlapping degree to obtain an orthoimage; performing semantic segmentation on the orthoimage to obtain a crack binary segmentation map of the orthoimage so as to identify a main crack and a secondary crack; performing three-dimensional geometric parameter analysis on the main crack and the secondary crack to obtain a crack three-dimensional space attribute parameter; carrying out evolution trajectory tracking on the crack three-dimensional space attribute parameters to obtain evolution data so as to construct a visual map of the landslide surface; according to the invention, the efficiency of extracting and quantifying the three-dimensional evolution unmanned aerial vehicle image of the landslide surface crack can be improved.

This invention discloses a method for testing the epitaxial structure performance of gallium oxide-based diodes, relating to the field of transistors. It solves the problem of detection effectiveness in existing epitaxial structure performance testing methods. The method includes the following steps: Step S1: Obtaining the luminous efficiency values ​​of the target diode under test at each preset power, and plotting a power-luminous efficiency coordinate graph accordingly. Based on the power-luminous efficiency coordinate graph, the qualified luminous efficiency power range corresponding to the target diode under test is obtained. Step S2: Obtaining the color rendering index values ​​of the target diode under test at each characteristic power, and plotting a color rendering index coordinate graph accordingly. Based on the color rendering index coordinate graph, the qualified color rendering power range corresponding to the target diode under test is obtained. Step S3: Performing performance testing on the sample gallium oxide-based diodes based on the qualified color rendering power range and the qualified luminous efficiency power range, and issuing performance warnings based on the test results. This invention can improve the accuracy of diode performance testing results.

The application belongs to the technical field of network attack and defense simulation, and discloses a network attack and defense simulation engine system based on discrete event driving, which comprises an event scheduling module, a simulation network construction module, an attack and defense simulation module, a simulation kernel module and a panoramic situation awareness module; the event scheduling module is constructed based on MITRE ATT&CK as a theoretical base and is used for converting all network activities into a schedulable discrete event sequence; the network activities comprise packet sending, protocol timeout and attack triggering; the simulation network construction module can construct a simulation network containing complete business logic. The application can convert the MITRE ATT&CK tactical intention into an ordered event stream through the event scheduling module, and can simultaneously perform dynamic decomposition and re-planning on a high-level target through a hierarchical task network planner in the attack and defense simulation module, and can also reconfigure an attack chain in real time by using an ATT&CK technology ID.

This invention provides a lithium carbonate price prediction method based on multimodal data collaborative driving, comprising the following steps: multimodal data source identification and data acquisition; multimodal data classification and standardization; personalized noise filtering and outlier correction of multimodal data; extraction of trend and correlation features from structured data; extraction of semantic and visual / speech features from unstructured data; extraction of key information and feature quantification from semi-structured data; weighted collaborative fusion and feature optimization of multimodal features; construction and training of a two-branch collaborative prediction model; model prediction and preliminary verification of prediction results; optimization and dynamic correction of prediction results; interpretability analysis and visualization of prediction results; and method effectiveness verification and continuous improvement. This method, based on multimodal data collaborative driving, addresses the pain points of existing lithium carbonate price prediction technologies, forming a comprehensive, high-precision, and highly practical prediction solution.

A reliability test bench for an oil distributor includes a driving device, a first coupling, a second coupling, a universal coupling, an intermediate shaft, a flange coupling and an oil distributor connected in sequence, the axes of the driving device and the first coupling are in a straight line, and the axes of the second coupling, the intermediate shaft, the flange coupling and the oil distributor are in a straight line; a first angle is formed between the axis of the oil distributor and the horizontal plane, which is an acute angle, and a sensor is arranged on the oil distributor; the driving device is arranged on the top surface of the first support frame, the intermediate shaft is arranged on the top surfaces of the second support frame and the third support frame, and the other end of the oil distributor is arranged on the top surface of the fourth support frame; the bottom surfaces of the first support frame, the second support frame, the third support frame and the fourth support frame are in a straight line; the test bench also includes a test method for the reliability test bench for an oil distributor. This design can not only reduce the failure rate of the ship's adjustable pitch propeller device, but also diagnose the failure of the adjustable pitch propeller device.