221results about How to "High data reliability" patented technology

The invention discloses a temperature correction method and system for a hot press, and particularly relates to the technical field of hot press temperature control, and the method comprises the steps: obtaining and preprocessing multi-dimensional operation data, including a temperature time sequence, pressure setting and material attributes; constructing a coupling model based on the multilayer neural network, and predicting temperature distribution of different process stages; performing sensor drift compensation, analyzing temperature deviation characteristics, judging whether sensor drift or material thermal diffusion abnormity exists or not, and generating a local distortion mark; determining a compensation mode according to the distortion mark, and starting a local compensation mode or a global balance control mode if the distortion is recognized as over-limit distortion; and comparing with the output of the coupling model, verifying the temperature correction effect, and if the deviation is reduced and the distortion mark is converged, outputting a stable temperature correction result. The problems of temperature distortion and sensor drift are effectively solved, and the long-term precision and stability of the hot press under complex working conditions are improved.

The invention relates to the technical field of traffic safety management, in particular to a vehicle abnormal driving recognition and early warning method and system. The method comprises the following steps: firstly, acquiring vehicle position, speed, direction and driver operation data in real time, then correcting time sequence data by adopting a smooth denoising method of adaptive segmented clustering, generating an information confirmation code through standardization, and then carrying out weighted fusion on multi-source data to obtain a multi-source data fusion model; the strategy decision-making module is used for extracting vehicle speed change rate, lane deviation degree and driver behavior characteristic key indexes, identifying and grading abnormal driving behaviors by setting a threshold value, calculating a comprehensive abnormal score, and generating a grading intervention strategy for slight, medium and serious anomalies according to a comparison result of the abnormal score and the set threshold value. And finally, combining automatic intervention in the vehicle with global coordinated intervention of a road manager. According to the invention, the intervention strategy is generated based on multi-source data acquisition, processing, analysis and decision, so that the vehicle driving safety and the road management efficiency are improved.

The invention belongs to the field of artificial intelligence, and particularly relates to a bill information extraction method and system and a storage medium, and the method comprises the following steps: obtaining an electronic file containing a bill, and preprocessing the electronic file into an image file facilitating information extraction; extracting bill information in the image file by using a multi-modal large model and an OCR model, and outputting text information in a structured format; and analyzing, correcting and comparing text information respectively output by the multi-modal large model and the OCR model through the large language model, and performing fine tuning or cue word engineering guidance on the large language model for different tasks, so that an output result conforms to expectation. Compared with the prior art, the problems that in the prior art, OCR recognition accuracy is not high, and extracted information is incomplete are solved, the bill information processing speed is increased, the precision of the automatic processing process is greatly improved, and in financial, auditing and other related business scenes, the working efficiency and the data reliability are remarkably improved.

The invention discloses an unmanned ship navigation path intelligent optimization system and method based on ocean data, and particularly relates to the technical field of unmanned ship navigation. The accuracy of monitoring data of the sensor in a marine environment is continuously evaluated through a series of steps of preliminary calibration, data acquisition, filtering processing, abnormal marking, feature extraction and the like of the unmanned ship sensor, and real-time evaluation and time period division of the quality of the monitoring data are realized through comprehensive analysis of abnormal features of sound velocity and conductivity. The abnormal degree is predicted in the abnormal monitoring time period, and for the condition of high abnormal degree, a safety avoidance strategy is automatically set through a path planning system, and the route and the navigational speed of the unmanned ship are dynamically optimized, so that a risk area is avoided, the navigation precision and safety are improved, the reliability of sensor data is remarkably improved, and the safety of the unmanned ship is improved. The influence of data deviation on path planning is reduced, and the task success rate and the navigation safety of the unmanned ship in a complex marine environment are enhanced.

The invention discloses a regional heavy pollution discriminating and forecasting system and method based on big data, and relates to the technical field of environmental pollution monitoring. Comprising a multi-source data acquisition module, an adaptive weight distribution module, a feature extraction module, a heavy pollution discrimination module, a pollution diffusion path simulation module, an intelligent early warning and protection suggestion module, an event-driven dynamic monitoring module and a multi-scale meteorological prediction optimization module. And the pollution diffusion path simulation module performs prediction analysis on a pollution diffusion path and an influence range by using a diffusion path simulation algorithm. By designing the pollution diffusion path simulation module and the intelligent early warning and protection suggestion module, the pollutant diffusion path prediction and early warning functions are realized, and the problem that early warning lags due to the fact that the pollution diffusion path simulation and early warning module is separated and cannot realize timely linkage of prediction results and protection suggestions is solved; and a more timely and effective prevention and control strategy is provided, and the capability of coping with heavy pollution events is enhanced.

The invention relates to a performance optimization method for a Ceph cache system based on a persistent memory, and the method comprises the steps: enabling a Ceph storage system based on the persistent memory to adjust the related parameter configuration of a cache and the persistent memory through a parameter optimization system, feeding back performance data through performance monitoring, completing the adjustment and optimization of configuration parameters, and finally obtaining an optimal performance parameter combination. Comprising the following steps: S1, configuring a persistent memory device; step S2, configuring a Ceph OSD (On Screen Display); s3, performance monitoring and sampling are carried out, and a sample set is generated; s4, dynamically adjusting the parameter optimization system; step S5, testing and verifying; the problem of slow data storage performance of a storage system constructed by a common HDD hard disk is solved, data caching is accelerated by utilizing the characteristics of high bandwidth, high throughput and data persistence of the persistent memory, and then the overall performance of the Ceph storage system is improved by integrally optimizing the parameters of the storage system after the persistent memory device is used.

The invention discloses a vibration stress monitoring method for a wireless telemetering rotary transmission system. The method comprises the following steps: S1, collecting multi-dimensional vibration acceleration data of the rotary transmission system in real time; s2, performing signal conditioning on the multi-dimensional vibration acceleration data output by the vibration acceleration sensor through a signal conditioning circuit; s3, generating a vibration signal data packet with a timestamp and a sensor identifier; s4, dynamically adjusting a data transmission frequency band according to the environment interference condition; s5, automatically generating a normal working state reference model of the rotary transmission system, wherein the normal working state reference model covers feature distribution of the multi-dimensional vibration acceleration data under different working conditions; s6, generating abnormal vibration characteristic data; and S7, storing the abnormal vibration characteristic data in a vibration data storage module of the mobile terminal, and sending an alarm signal to an operator through an alarm module. According to the invention, the defects of vibration signal acquisition, transmission, processing and environmental adaptability in the prior art are overcome.

The invention discloses a method and a system for constructing a double-layer coupled network infectious disease transmission model based on a game strategy. The construction method comprises the following steps: constructing an information dissemination network and a physical contact network; in the information propagation network, modeling is carried out on evolution of individual consciousness by adopting a UAU model according to individual states, and in the physical contact network, modeling is carried out on evolution of individual states by adopting an SIS infectious disease model; introducing a game strategy mechanism of individual consciousness into the information propagation network; constructing a feedback mechanism of individual behaviors in the physical contact network; according to an MMCA method, an information transmission network of a game strategy mechanism and a physical contact network of a feedback mechanism are introduced to construct a double-layer coupled network infectious disease transmission model, and threshold analysis is performed on the double-layer coupled network infectious disease transmission model; according to the method, game strategies and behavior feedback made by individuals after the individuals receive infectious disease information are considered, and the method is used for solving the problem of complex coupling between information transmission and infectious disease transmission in a double-layer coupling network.

The invention discloses an area rainfall forecasting method based on Beidou GNSS water vapor, and the method specifically comprises the following steps: firstly, collecting original observation data and ephemeris data through GNSS equipment; surface water vapor distribution is obtained; and finally, a space-time prediction model of the area rainfall is constructed and trained, and for rainfall prediction, in order to suppress the predicted rainfall output by mistake of the model when no rainfall exists and improve the capability of the model to accurately output rainfall, a fusion prediction layer based on classification prediction is designed in a decoder part. According to the areal rainfall forecasting method based on Beidou GNSS water vapor, the areal rainfall condition in a certain area can be monitored and predicted in a high-precision mode, and the areal rainfall forecasting method has the advantages of being all-weather, free of influences of weather and environment, high in data reliability and low in equipment cost; therefore, the technology has wide application prospects in small and medium-sized drainage basins with limited resources and economically underdeveloped areas.

The invention belongs to the field of safe transmission of video monitoring code streams, and particularly relates to a method for realizing disaster recovery and rapid recovery of national standard superior services by using Redis record cascade and equipment information. A Redis storage management system is constructed to record cascading and equipment information, and when a service is restarted abnormally, link recovery or waiting for registration online is quickly judged according to Redis information. Multi-thread storage is adopted for first retrieval of shared device information, Redis and reported information at this time are compared during second retrieval, a lower level synchronously retrieves resource information from an upper level, a database and Redis are accurately operated according to information content by means of a Kafka component, all the steps work cooperatively, and the efficiency is improved. Disaster recovery and rapid recovery are effectively achieved when existing national standard cascade services face various emergencies such as service faults and network anomalies, the overall performance, the disaster recovery capacity and the data accuracy are improved, and the requirements of a video monitoring system for efficient, stable and reliable operation and accurate resource sharing are met.

The invention discloses a data processing method and system of a chromatographic instrument, and relates to the technical field of data processing, and the method comprises the following steps: collecting whole-course original detection signals and external interference signs generated in a chromatographic analysis process, carrying out time alignment under a unified time scale, generating an interference rhythm index, and calculating the interference rhythm index; the reference is used as a unified reference for subsequent signal comparison; and based on the interference rhythm index, performing phase drift comparison on the acquired signal, calculating the phase difference between the detection signal and the interference signal, drawing a beat frequency wandering graph, extracting candidate signal segments of pseudo-period interference according to beat frequency change, and generating a pseudo-period candidate segment list. According to the invention, by establishing the interference rhythm index and comparing the interference rhythm index with the phase drift, the time decoupling of the detection signal and the interference signal is realized, and the sampling anti-interference capability is improved; and through dynamic control of a false peak characteristic fingerprint draft and a misjudgment reason table, signal rhythm correction and peak identification optimization are completed, so that the detection accuracy and the data stability are improved.

The invention relates to a test device and method for researching horizontal load of a suction bucket under high compactness of sandy soil. The device comprises a model box, a suction bucket model system, a suction bucket mounting and up-pulling system and a horizontal loading and measuring system. A high-compactness sandy soil sample is prepared and contained in the model box. The suction bucket model system simplifies sensor arrangement and reduces penetration resistance. And the suction bucket mounting and upward pulling system realizes mounting and pulling of the suction bucket by utilizing a hydraulic oil cylinder and a lifting cross beam. The horizontal loading and measuring system applies static force and dynamic load through a pulley, a steel wire rope, a servo motor and a balancing weight to form sinusoidal waveform bending moment, simulates the real stress condition and measures the horizontal displacement and inclination angle change of the suction barrel. According to the device, a loading system is optimized, the reliability and precision of test data are improved, the cost is reduced, and the device is suitable for safety and stability research of an ocean engineering structure.

The invention discloses an intelligent detection data calibration system based on enhancement algorithm driving, and particularly relates to the technical field of data calibration, a plurality of sensors are arranged at different positions in an environment, each position comprises a plurality of sensors of the same type, potential abnormal sensors are detected by using a redundancy or machine learning algorithm, and the data calibration accuracy is improved. The range of the abnormal sensor is quickly narrowed and the efficiency is improved; the monitoring data fluctuation curve is analyzed, an expected input cost description parameter and an expected calibration similarity are obtained through analysis, non-calibrated sensors are screened out from an abnormal sensor set based on an analysis result, and waste of calibration resources on the sensors which are not worthy of input is avoided; it is ensured that only the sensors capable of being calibrated are included in the calibration process, and the data accuracy and reliability of the whole monitoring system can be improved; detailed cost analysis about sensor maintenance or replacement is provided for decision makers, more economic and reasonable decisions can be made, and the problem of resource waste in the intelligent detection data calibration process is solved.

The utility model discloses a global navigation satellite system (GNSS) displacement monitoring terminal and corner reflector combined system for ground subsidence monitoring, which comprises a global navigation satellite system (GNSS) and a plurality of monitoring point positions, the global navigation satellite system (GNSS) comprises a plurality of satellites, subsidence monitoring components are distributed on the monitoring point positions, and the monitoring point positions are connected with the ground subsidence monitoring components. Each settlement monitoring assembly comprises an InSAR corner reflector and a plurality of GNSS (Global Navigation Satellite System) monitoring terminals arranged around the InSAR corner reflector, and the InSAR corner reflector is matched with the GNSS monitoring terminals. The settlement monitoring assemblies are arranged on the ground to be monitored according to monitoring points, relative position change data and absolute position change data can be obtained through monitoring, the two kinds of data can be conveniently fused for composite analysis of ground settlement monitoring, the change data of the ground to be monitored can be described more accurately and vividly, the data precision and reliability are improved, and the monitoring accuracy is improved. And the monitoring data is obviously enriched.

The invention relates to the field of sensors, and discloses a sensor drift correction method and system based on transfer learning, and the method comprises the following steps: S1, collecting sensor data, including three-axis acceleration data, temperature, humidity and air pressure environmental parameters, and S2, calculating the modulus length of a three-axis composite vector. A combined kernel function combining a periodic kernel, a linear kernel and an RBF kernel can simultaneously capture periodic fluctuation of environmental factors, a long-term aging trend of a sensor and short-term random noise, adaptive distribution alignment of a source domain and a target domain is realized through a maximum mean value difference loss function, the model is enabled to be rapidly adapted in the target domain, and meanwhile, the adaptive distribution alignment of the model in the target domain is realized. A slope intercept combined judgment matrix is introduced, accurate distinguishing of zero drift, real motion and tilt events is achieved, the accuracy rate reaches 96% or above, measurement distortion caused by error compensation is effectively avoided, and the system reliability and the data credibility are remarkably improved.

The invention provides a pipeline welding real-time feedback control method and system based on machine vision. According to the method, multi-modal data such as a three-dimensional point cloud, a temperature field and a welding seam image are synchronously collected, and key characteristics such as a pose deviation gradient, a cooling rate curve and a welding seam size sequence are extracted after time sequence alignment, filtering and correction fusion. And a CNN and LSTM mixed adaptive deep learning model is utilized to analyze the welding quality state in real time, and sub-optimal parameters are dynamically optimized based on a reinforcement learning strategy, or a three-level response mechanism including heat reduction input, expert knowledge base matching and precise repair is triggered to process defect early warning. The system has an incremental learning capability and can be self-optimized along with a control period. The full-flow intelligent monitoring, real-time feedback and self-adaptive accurate control of the welding process are achieved, and the welding quality and the automation level are remarkably improved.

The invention relates to the technical field of remote sensing, and discloses a forestry loss value evaluation method, device and equipment and a storage medium. A second time sequence image data set and a first fitting model are combined to calculate a first difference image; and the change condition of the vegetation in the cloud-free area of the remote sensing image after typhoon disaster relative to the non-disaster state can be intuitively and quantitatively displayed. Furthermore, model training is carried out by using the environmental influence factor set and the first difference image, and a deep relationship rule of the influence of the typhoon disaster hidden behind the complex data on the forest can be mined. Furthermore, the normalized vegetation index difference value of the cloud coverage area is predicted by using the constructed model to generate a second difference value image, so that the spatial representation information of the disaster condition of the whole typhoon disaster area can be perfected. And finally, in combination with the real forestry loss value, the first difference image and the second difference image, rapid evaluation of the forestry loss value in the whole typhoon affected area can be realized.

The invention discloses a liquid catalyst and a coal combustion efficiency improvement detection system thereof, and belongs to the technical field of coal chemical industry, the catalyst comprises active metal ions and other combustion performance adjusting substances, the activation energy of coal combustion can be reduced, and the combustion rate can be improved. Furthermore, according to the use requirement that the characteristics of all coal types are matched with the adaptability of the catalyst, in order to further optimize the proportion of all formulas of the catalyst, the invention provides a detection system for improving the coal combustion efficiency of the catalyst, the detection system comprises a plurality of test chambers, and the coal combustion efficiency of the catalyst is improved by accurately adjusting the test environment of the coal powder and the catalyst. According to the method, a high consistency test is provided, and a batch circulating test is adopted, so that the improvement effect of the catalyst on combustion of different coal types is quickly and efficiently verified, and the optimal proportion value of each component in the catalyst to a specific coal type is determined.

The invention discloses a discrete manufacturing multi-view BOM dynamic derivation method and system based on a tree-shaped network structure, and belongs to the technical field of intelligent manufacturing and product data management. The method comprises the following steps: constructing a tree body as a single product data source, and storing a hierarchical relationship, attribute definition and engineering semantics of a product in a tree structure; based on the tree body, dynamically matching derivation rules through a mesh mapping relation library; executing rule matching, semantic verification, structure reconstruction and dictionary verification by utilizing a dynamic view derivation engine to generate a target BOM view; semantic constraint and verification are carried out on the derivation process through a BOM data dictionary module; and realizing access control and audit based on role, scene and data sensitivity through the security and authority control module. According to the method, a new generation of xBOM dynamic derivation architecture which takes a tree form as an ontology, takes a net form as mapping, is configurable in rule and is strong in data specification is constructed; the fundamental problem of discrete manufacturing multi-view BOM management is solved, and engineering rationality and service flexibility are both achieved.

The invention discloses an intermediate-frequency surface shape white light interference splicing measurement method based on polynomial filtering. The method comprises the following steps: carrying out white light interference splicing measurement on an X-ray plane mirror to obtain a group of interference measurement surface shape results with overlapped adjacent sub-aperture space positions; fitting the surface shape result of each sub-aperture by using a Legendre polynomial to obtain a polynomial coefficient under a preset order; fitting according to a polynomial coefficient to generate a fitting surface shape of a corresponding order, and subtracting the fitting surface shapes of all orders from the measurement result to obtain a group of surface shape results subjected to Legendre polynomial filtering; and splicing the filtered shape results according to a least square algorithm to obtain a final measurement result. The method aims at meeting the splicing measurement of sub-nanometer PV precision required by the intermediate-frequency surface shape error detection of the X-ray plane mirror, the least square optimization splicing method is used, the method is not limited by the low-frequency characteristic of the measurement error of the white light interferometer, and the precision and flexibility of the splicing measurement are improved.

The invention discloses an intelligent management method, system and equipment for breeding duck breeding based on big data and a medium, and relates to the technical field of breeding duck breeding management, and the method comprises the following steps: obtaining breeding duck breeding data of big data, and carrying out the screening and grouping of the breeding duck breeding data; based on a screening and grouping result, extracting an optimal environment condition for breeding the breeding ducks; setting a control experiment group based on the optimal environment condition, testing the relationship between the feeding amount and the weight of the breeding ducks, and then testing the relationship between the weight of the breeding ducks and the egg yield as well as the egg weight; the method is used for solving the problems that according to an existing breeding duck breeding management technology, data setting is too subjective, and no specific data support is provided for proving improvement of the egg yield, so that the feeding result cannot be judged.

The invention discloses a dog traction rope burst test device, which comprises a mounting rack, a connecting part is arranged on the mounting rack, a connecting rope is arranged on the connecting part, the connecting part is connected with the upper end of a traction rope through the connecting rope, and a bearing rack is arranged on the mounting rack; the driving device is connected with the bearing frame and used for driving the bearing frame to move; the heavy block is connected with the lower end of the traction rope through the adjusting rope, when the bearing frame is located at the testing station, the bearing frame bears the heavy block, the traction rope is kept in a loosened state through the adjusting rope, when the bearing frame moves to the initial station, the heavy block is separated from the bearing frame, the traction rope is in a tightened state, and dog burst simulation is achieved through falling of the heavy block. And meanwhile, a driving device and a bearing frame are matched to realize simulation of multiple explosion rushing so as to complete testing of the fatigue strength of the traction rope.

This application relates to a UAV frame for bridge inspection, belonging to the technical field of UAVs. It includes a UAV body with a connecting frame at its bottom. This application utilizes a plug-in engagement between a plug and the connecting frame, and a limiting block driven by a push spring in a snap-fit ​​assembly to achieve automatic initial positioning. Simultaneously, a bidirectional lead screw driven by a first servo motor in the limiting assembly drives a moving frame and its locking block for a secure secondary locking. This significantly simplifies the installation and disassembly process of the UAV body and the connecting frame. Furthermore, a buffer assembly located on the outside of the connecting frame, with its support plate sliding within the damping sleeve of the support leg via a slide rod, compresses the buffer spring. This effectively absorbs and dissipates the impact energy generated during UAV takeoff and landing or sudden collisions, maximizing the protection of the precision components inside the UAV body and the shooting and detection devices within the mounting frame. This significantly reduces data acquisition errors and improves operational safety and data reliability.

The invention discloses a carbon emission factor calculation verification method based on a block chain, particularly relates to the technical field of carbon emission accounting and block chain credible measurement, and is used for solving the problems that an existing carbon emission factor calculation process depends on a dispersed system and manual summarization, the publication caliber is not uniform, a traceable evidence chain is lacked, and the calculation efficiency is low. And a supervision mechanism and a third party are difficult to carry out independent re-calculation and credible verification on the factor result submitted by the enterprise. A carbon emission factor calculation template is taken as a core at an enterprise node side, a device range, a statistical period and a data preprocessing rule are configured in a unified manner, abstract identifiers are generated step by step for dimensionalized data abstracts and calculation evidence chain fingerprints, calculation certificates are written into an alliance chain, and a calculation result is obtained. And the verification node obtains a verification fingerprint and registers a verification result based on the same template fingerprint and data slice recalculation, so that an integrated evidence closed loop of factor calculation, recalculation verification and factor selection is formed, and the problems that a factor source is non-transparent, cross-subject recalculation is difficult and a credible basis is lacked are solved.

The invention discloses a fluid wall shear pressure stress composite array sensor chip, and belongs to the technical field of MEMS sensors. Comprising a plurality of shear stress sensors and pressure stress sensors which are integrated on a chip, the overall arrangement array of the shear stress sensors is in a regular cross shape, the overall arrangement array of the pressure stress sensors is in an X shape, and the two arrays are concentrically superposed to obtain a grid type array layout; the pressure sensor is arranged in the center of the grid-type array, the shear stress sensors are arranged in an outward radiation mode in the regular cross direction with the center pressure sensor as the radiation center and used for measuring the two-dimensional shear stress, and the pressure stress sensors are arranged in an outward radiation mode in the X-shaped direction with the center pressure sensor as the radiation center and used for measuring the two-dimensional shear stress. Gradient pressure is measured. According to the method, the problem that actual flow field stress distribution is difficult to fully reflect by single-point measurement in a complex fluid environment is solved.

The application discloses the technical fields of environmental monitoring and water analysis and relates to a water transparency detector with self-immunization of optical window pollution, which comprises a light source, a first reflector, a beam splitter, a sample cell, a second reflector and a third reflector. The first reflector reflects the light of the light source to the beam splitter, and the beam splitter divides the light into transmitted light and reflected light. The transmitted light transmits through the sample cell and is converged by the second reflector to a transmitted end photoelectric detector. The reflected light is converged by the third reflector to a reference end photoelectric detector. The water transparency can be calculated according to the light intensity of the transmitted end photoelectric detector and the reference end photoelectric detector. The application dynamically offsets the error caused by the optical window pollution, light source fluctuation and detector drift through a double-light-path signal and a clean and polluted window pollution error double-ratio real-time compensation algorithm, so that the measurement accuracy can be ensured without a physical cleaning device. In addition, the application can monitor the change trend of the light intensity ratio and actively sense the degree of optical window pollution.

The utility model discloses a self-adaptive force stabilizing device for characterizing a mechanoluminescence cycle process, and belongs to the technical field of material testing. According to the device, collaborative operation is achieved through a reciprocating testing mechanism and a force loading mechanism which are in linkage design; the reciprocating testing mechanism drives a lead screw transmission assembly through a servo motor to drive a single-axis moving platform, a pressure digital display and a material to achieve reciprocating friction in the y-axis direction; the force loading mechanism pulls a sliding platform to slide on a sliding rail through a spring, a round-bottom quartz tube is arranged at the end of the force loading mechanism and is in point contact with a sample of a pressure digital display accessory, and when the sample is slightly abraded to cause position change, the spring dynamically compensates pressure loss to ensure that force loading in the x-axis direction is constant. An optical fiber is integrated in the round-bottom quartz tube to synchronously collect mechanoluminescence signals. The device solves the problem of force attenuation in the existing cycle test, and is beneficial to systematic research on the cycle characteristics of the mechanoluminescent material.

The invention relates to the technical field of flow counting, in particular to a digital signal processing method and system for a Coriolis flowmeter, and the method comprises the following steps: S1, a Coriolis flowmeter sensor carries out signal collection and preprocessing; s2, carrying out processing and feature extraction on the collected signals; and S3, flow calculation and correction. Through signal acquisition and preprocessing, the sensor signal quality is improved, the subsequent processing reliability is ensured, time domain analysis and frequency domain conversion technologies are adopted for signal processing and feature extraction, key feature parameters are accurately extracted, the signal accuracy is improved, phase difference calculation and density and temperature compensation are utilized for flow calculation and correction, and the accuracy of flow calculation and correction is improved. Real-time measurement of instantaneous flow and accumulated flow is achieved, accuracy and real-time performance of data are guaranteed, normal work of all parts is guaranteed through system inspection and output, abnormal conditions are monitored and alarmed in real time, data reliability and system stability are guaranteed, the whole method is scientific and rigorous, and measurement accuracy and data reliability of the Coriolis flowmeter are effectively improved.

The invention relates to a portable cast-in-place pile hole bottom sediment thickness detection device. The detection device comprises a transportation plate trailer and a thickness detection assembly, a winding mechanism is arranged on the transportation plate trailer, one end of the winding mechanism is fixedly connected with the thickness detection assembly, and the thickness detection assembly comprises a bearing mechanism, a leveling mechanism, a detection mechanism and a moving mechanism; the bearing mechanism serves as a supporting mechanism of the whole detection assembly, the leveling mechanism adjusts the levelness of the detection mechanism and the bearing mechanism, the detection mechanism is used for detecting the sediment thickness, and the moving mechanism is used for driving the whole detection assembly to move. The overall flexible movement of the device is realized through the transportation plate trailer, the winding mechanism can stably lower the detection assembly into a cast-in-place pile hole, the detection assembly can be leveled in the hole through the leveling mechanism, the detection assembly is convenient to move through the moving mechanism, the heavy detection assembly does not need to be manually carried or dragged, and the detection efficiency is improved. The problems that existing equipment is large in size, and manual position adjustment is inconvenient are solved.

A rotor engine comprehensive bench test system and test method belong to the technical field of engine test. The system contains rotor engine, AC power dynamometer, main control unit and other groups of modules. The dynamometer can realize forward and reverse reversible rotation of the engine. The main control unit is provided with forward and reverse switching and three-stage alarm module. Each component is connected and communicated. Sensors, acquisition modules, analyzers and the main control unit are cooperatively networked. The test method sequentially completes bench building, system inspection, pre-starting verification, lubrication establishment, engine starting, top dead center searching, mechanical loss test, warming, full-range boundary monitoring, hot-state running-in, ECU online calibration and data evaluation. The combustion analyzer can calculate cylinder pressure parameters. ECU modified parameters take effect immediately. Data analysis covers power and economic indicators. The present invention solves the problem that existing benches cannot adapt to rotor engine tests, builds a safe and efficient comprehensive test platform and provides technical support for rotor engine research and development.