343 results about "Physical quantity" patented technology

The invention belongs to the technical field of industrial automation control, and discloses a PLC-based fault diagnosis method and device. The method comprises the following steps: acquiring data of target equipment acquired by a sensor through a data acquisition point; according to a preset conversion method, determining the data as a physical quantity numerical value of a corresponding physical quantity type, and storing the physical quantity numerical value to a circular buffer area with a preset time window length; determining a period according to a preset time length, and determining a plurality of characteristic values of the physical quantity values in the circular buffer area based on the data acquisition points; inputting the plurality of feature values into a pre-trained decision tree fault recognition model, and outputting a fault recognition result of the target equipment, and according to the target fault type label of the fault identification result, triggering an alarm signal, and recording a fault log of the target equipment. Whether the equipment breaks down or not can be identified based on the data during the operation of the equipment, and the fault type can be determined.

A processing machine (10) is provided with: a main shaft (14) that rotatably supports a cutting tool (15); a stage (16) on which the workpiece (W) is placed; a measurement unit (17) that measures a physical quantity generated by contact between the cutting tool (15) and the workpiece (W); a comparison unit (111) that calculates the depth of cutting of the workpiece (W) by the cutting tool (15) on the basis of the physical quantity, and compares the calculated depth of cutting with a reference depth of cutting; and an adjustment unit (112) that adjusts the position of at least one of the cutting tool (15), the spindle (14), and the stage (16) on the basis of the result of the comparison by the comparison unit (111).

The invention relates to a method for controlling physical quantity of underwater explosion near a naval vessel based on a multiphase flow model, and belongs to an anti-impact technology of underwater explosion near the naval vessel. According to the method, an additional correction equation related to total mixed energy is created, and a model is expanded into seven equation models. A mixed energy correction equation is introduced, and a more accurate gas state equation is combined, so that the difference between the predicted thermodynamic states under the shock wave condition is solved; an algorithm program of an improved six-equation model is provided on an unstructured grid system, a homogeneous hyperbolic equation is solved by using a second-order MUSCL-Hancock format based on least square reconstruction and a Barth-Jespersen limiter and a two-phase flow HLLC Riemann solver, and then an instantaneous pressure relaxation equation is solved by using a Newton-Raphson iteration method. By improving the six-equation model in the diffusion interface method, the interface capture precision and the numerical algorithm stability are improved.

The invention discloses a data processing method, an idle stroke eliminating method, an anti-collision method and related equipment thereof. The idle stroke eliminating method comprises the following steps: acquiring a real-time physical quantity of a main shaft when a machine tool machines a first workpiece; processing the real-time physical quantity according to a preset rule to determine a first threshold value; the first threshold value serves as a boundary threshold value when the second workpiece is machined; compared with the problem that a fixed boundary threshold value is determined depending on manual experience at present, the method comprises the steps that the real-time physical quantity of a main shaft is obtained when a machine tool machines a first workpiece; processing the real-time physical quantity according to a preset rule to determine a first threshold value; the first threshold value is used as the boundary threshold value when the second workpiece is machined, so that the boundary threshold value when the machining tool machines can be adjusted in real time.

The invention discloses a surface material point embedding method for a multi-body contact problem, and belongs to the technical field of computational mechanics and numerical simulation. The method comprises the following steps: 1, performing discretization and parameter setting on a physical model of a multi-body contact system; 2, calculating a contact force; 3, transmitting the physical quantity of the material points of the contact body to background grid nodes to obtain node mass, momentum and force; 4, updating the grids; 5, updating the speed, the displacement, the stress and the density of the material point; 6, resetting the physical quantity of the background grid; seventhly, repeating the first step, the fourth step, the fifth step and the sixth step, sequentially updating the physical quantities of the material points of other contact bodies and the positions and the speeds of the slave nodes, and distributing background grid node memories of the areas where the corresponding contact bodies are located; and 8, after all contact bodies are updated, updating the current time to obtain a dynamic simulation result. According to the method, the boundary of the object can be accurately represented, complicated problems such as impact and multi-body contact can be effectively simulated, and meanwhile, the method has good stability and relatively low memory consumption.

A fibre-optic sensor for measuring a physical quantity, such as a pressure, force, acceleration or tilt, includes an optical fibre having a measurement section for measuring a strain in the fibre, and first and second structural members. The optical fibre is connected to a first fibre connection section of the first structural member and to a second fibre connection section of the second structural member. The first and second connection sections are arranged on opposite sides of the measurement section, such that at least the measurement section is suspended between the first and second fibre connection sections. At least one of the structural members is movable relative to the other in dependence of the physical quantity that is measured. The structural members are made from materials having different coefficients of thermal expansion such that a temperature induced strain in said optical fibre due to a temperature change is reduced.

The machining diagnosis device (1) includes a data acquisition unit (11) that acquires a physical quantity related to the operating state of a machining machine (90) that machines a workpiece, and the machining conditions when the physical quantity is obtained, a feature quantity calculation unit (12) that calculates, for each machining condition, a statistical feature quantity of the physical quantity obtained during machining under the same machining conditions based on the physical quantity and the machining conditions, and an inference unit (16) that performs machining diagnosis based on the statistical feature quantity for each machining condition.

The invention relates to a self-adaptive control method, system and device for environment test equipment, and the method comprises the following steps: S1, data collection: collecting environment detection data and data of a corresponding actuator according to a to-be-controlled physical quantity; s2, selecting or constructing a control object according to the physical quantity to be controlled; s3, performing online identification operation when an identification condition is met, otherwise, directly executing the step S4; s4, feedforward and feedback: calculating feedforward compensation and feedback compensation according to the value of the to-be-estimated quantity, and superposing the feedforward compensation and the feedback compensation to obtain a control instruction; and S5, performing constraint allocation on the actuator: performing saturation constraint processing on the control instruction to obtain a control quantity of the corresponding actuator. Joint online identification can be carried out on the to-be-estimated quantity only through perturbation excitation; different loads and test object states are automatically adapted; saturation constraint processing is adopted; the model and the algorithm are low in calculation amount, and precision, speed and engineering realizability are considered.

The present invention provides a flying apparatus that can accurately measure a weight of a transported objected in a simple configuration. The flying apparatus 10 includes rotors 11, motors 12, a flight sensor 13, an electric power conversion unit 14, and a computation control unit 15. The flight sensor 13 measures physical quantities acting on a fuselage base portion 16. The computation control unit 15 generates instruction signals based on the physical quantities to cause the fuselage base portion 16 to be at a predetermined position in a predetermined attitude. The electric power conversion unit 14 adjusts amounts of electric power supplied to the motors 121 and the like based on the received instruction signals. Moreover, the computation control unit 15 calculates an estimated weight that is an estimation value of a weight of the transported object, based on magnitudes of the instruction signals.

The invention discloses a food plastic package seal online detection method and system, and relates to the technical field of food package quality nondestructive detection.The method comprises the steps that based on a multi-physical-quantity data set, amplitude attenuation parameters in acoustic data are extracted, and food plastic package thickness distribution is scanned; dynamically correcting the amplitude attenuation parameter through a sound wave energy absorption model to obtain calibrated acoustic data; inputting the physical quantity matrix into a pre-trained convolutional neural network model, outputting a multi-scale feature map, analyzing multi-modal feature association of the physical quantity matrix through an attention fusion mechanism, and outputting a defect probability score; and according to the defect probability score, detecting the sealing state of the seal, removing the invalid food plastic package, integrating multi-source data to generate a structured detection log, and optimizing a convolutional neural network model through back propagation to generate a detection report. According to the invention, the recognition capability and classification precision of complex defects are enhanced, and precise judgment and efficient sorting of the sealing state of the seal are realized.

The invention relates to the technical field of physical quantity measurement, and discloses a multi-physical quantity measurement method and device for a passive multi-parameter optical fiber sensing unit, and the method comprises the steps: synchronously collecting temperature, humidity, air pressure and inclination angle four-parameter optical signals, calculating a time sequence cross correlation function in real time, and quantifying the parameter coupling strength and causal conduction time delay; constructing an initial weighted causal map based on the time sequence causal index, automatically detecting a chain enhancement path, positioning an initial abnormal node, and iteratively predicting a subsequent fault probability; drawing a dynamic arrow chain along an enhanced path in the three-dimensional digital twin model by taking the initial abnormal node as a starting point, and rendering according to a fault probability; according to the method, discrete multi-physical-quantity abnormal signals are converted into topological and visual causal chains, full-link transparent mapping of abnormal sources-propagation paths-potential fault nodes is achieved, and the pre-judgment precision and operation and maintenance decision timeliness of the state evolution trend of a complex structure are remarkably improved.

The invention relates to the technical field of big data analysis and application operation and maintenance, and discloses a multi-data fusion-based application operation and maintenance planning method, which comprises the following steps of: combining multi-source sensor data into a multi-dimensional state vector representing a local space-time state, and comparing the multi-dimensional state vector with a baseline vector representing a normal operation mode to generate a drift vector; according to the method, the stability of the correlation mode in the multi-dimensional data is analyzed, and then the stability of the modulus length and the direction of the drift vector in the time sequence is analyzed, so that potential risks which cannot be perceived by a traditional threshold value mode can be recognized. The focus point of risk recognition is transferred from isolated value out-of-limit to analysis of the stability of the correlation mode in the multi-dimensional data; the early gradual change risk formed by the synergistic effect of a plurality of physical quantities can be effectively identified, and the risk source can be traced based on the analysis process, so that the predictability and decision reliability of operation and maintenance planning are remarkably improved.

To provide a waveform output device capable of causing a waveform to be suitably displayed even when a data volume of measurement results is large.SOLUTION: A waveform output device 1 outputs a waveform that represents a change over time in a measurement result of a physical quantity to be measured via communication. The waveform output device 1 acquires measurement data that represents a measurement result of a predetermined physical quantity, generates waveform data that indicates a waveform from the measurement result of the obtained measurement data, and outputs the waveform data to a user terminal for causing the user terminal used by a user to display the waveform. At this time, the waveform output device 1 extracts a part of the measurement result included in the measurement data based on a predetermined condition, generates partial waveform data that indicates a partial waveform from a part of the extracted measurement result, and outputs the partial waveform data to the user terminal.SELECTED DRAWING: Figure 5

The invention relates to the technical field of machine vision and optical measurement mechanics, and discloses a deformation identification and measurement method based on machine vision and deep learning, and the method comprises the following steps: S1, system calibration and base library construction; s2, offline training of the hybrid model; s3, real-time decoupling and coefficient regression are carried out; and S4, final assembly and physical quantity calculation of the deformation field. According to the method, a deformation field is decoupled into a global nonlinear deformation field () and a residual deformation field () through S3, and the global nonlinear deformation field () and the residual deformation field () are superposed. The physical significance and the stability of a deformation main body are ensured by utilizing the physical deformation base library constructed in S1 and model reconstruction; meanwhile, a luminosity residual image () generated in the S3 is used for driving module reconstruction, local high-frequency disturbance which is not covered by a physical model is accurately compensated, a high-dimensional deformation field is decoupled into low-dimensional global physical prior regression and residual correction, and efficient real-time measurement is achieved; meanwhile, numerical difference is replaced by analytic derivation, so that the signal-to-noise ratio and the measurement precision of the strain field are remarkably improved.

To provide an information processing device, a control method, a program and a storage medium that stores the program, with which it is possible to suitably generate information even at fault occurrence time.SOLUTION: A computation block 17 of a control unit 13 generates first measurement information generated on the basis of a first combination, out of measured physical quantities measured by a plurality of sensors (detection units) that respectively measure the measured physical quantities of mutually different measurement objects, and second measurement information generated on the basis of a second combination different from the first combination. A abnormality determination block 18 of the control unit 13 detects the abnormality of each individual measured physical quantity. An output control block 19 of the control unit 13 controls the output of measured information, out of the first and second measured information, that is measured by the sensor (detection unit) having measured the measured physical quantity for which abnormality was detected by the abnormality detection block 18.SELECTED DRAWING: Figure 4

The invention relates to a filtering method (200) for a leak test cycle of a certain type of object to be tested, for constructing a database capable of determining at least one reference value relating to a leak test of said object type, in particular suitable for an early leak detection method; the invention relates to a method (200) for measuring a test cycle comprising the measurement of a physical quantity related to the degree of leakage in at least one part of an object to be tested or in a peripheral cavity of the object to be tested, said method (200) comprising at least the following steps: determining (E2) a deviation between the measured values of the physical quantity at the starting time and the ending time of the test cycle, referred to as a total deviation; the total deviation is compared (E3) with a total deviation reference value.

The invention provides a time step determination method and device for solving a physical quantity of a transient physical process. The method comprises the following steps: acquiring first time step iteration information corresponding to a historical moment in the transient physical process; the first time step iteration information is used for representing the condition of iteratively updating the time step in the process of solving the convergence solution corresponding to the target physical quantity and the historical moment; the target physical quantity is a to-be-solved physical quantity in the transient physical process; determining a first predicted time step corresponding to the current moment according to the first time step iteration information corresponding to the historical moment and the first predicted time step corresponding to the previous moment; and iteratively updating the first prediction time step corresponding to the current moment to obtain a target time step enabling the target physical quantity to converge with a solution corresponding to the current moment. According to the method, the time step length enabling the physical quantity to converge in the transient physical process can be quickly determined.

A physical quantity sensor assembly, an inclinometer, and a structure monitoring device are provided, offering a technique for correcting nonlinearity in the output signal of the physical quantity sensor without increasing the size of the physical quantity sensor assembly. The physical quantity sensor assembly (1) comprises: a frequency-varying physical quantity sensor (3) whose frequency varies according to the change of the physical quantity; a reference signal oscillation unit (5) that outputs a reference signal; a frequency Δ-Σ modulation unit (10) that generates a frequency Δ-Σ modulated signal by frequency Δ-Σ modulation of the reference signal using an action signal based on the measured signal output by the frequency-varying physical quantity sensor (3); a first low-pass filter (20) disposed on the output side of the frequency Δ-Σ modulation unit (10) and operating synchronously with the measured signal output by the frequency-varying physical quantity sensor (3); and a second low-pass filter (60) disposed on the output side of the first low-pass filter (20) and operating synchronously with the reference signal.

The invention relates to a microsensor (10) for measuring a physical quantity (14), comprising a first measuring element (16) with a first measuring characteristic (C1) and a second measuring element (56) with a second measuring characteristic (C2), which is mechanically delimited and offset from the first measuring area (54) by means of a second measuring characteristic (C2), and a second measuring element (18) with a micromechanical first deflection element (18) which is deflectable depending on the quantity (14), and a second measuring element (28) which is measurable in a third measuring area (52) with a third measuring characteristic (C3), wherein the third measuring area (52) overlaps a transition (53) between the first and second measuring areas (54, 56) and forms a first overlap area (58) with the first measuring area (54) and a second overlap area (60) with the second measuring area (56).wherein the measured quantity (14) present at least at the transition (53) can be measured by measuring the second measuring element (28) based on the third measuring characteristic (C3). Furthermore, the invention relates to a method for measurement and a method for sensor condition monitoring.

The application relates to the technical field of data processing of multi-source data fusion, and discloses a survey data integrated analysis method and system based on multi-source data fusion. The scheme deploys a multi-source sensor and collects original voltage, and normalizes in the range of each physical quantity; temperature, pressure and vibration three-dimensional observation and state are constructed based on a unified time index, and initial values are set; a constant value is kept to recursively predict; the variances of multiple measuring points are statistically calculated in a static window, and the observation noise is determined by combining the minimum quantization step to calculate the fusion gain; the covariance is linearly updated and corrected, and then the amplitude of each dimension is limited according to the abnormal upper limit; the three-dimensional results of multiple measuring points at each sampling time are spatially averaged, and if necessary, the results are rolled back; a fusion sequence and a statistical report are formed in the whole cycle. The method unifies the data scale, reduces subjective parameters and algorithm burden, models the noise adaptively according to the environment, stably suppresses noise and prevents faults, and guarantees continuous output and comparable analysis.

This physical quantity measuring device comprises a first sensor capable of measuring a first physical quantity value of an object being measured, a second sensor capable of measuring the first physical quantity value of the object being measured or a second physical quantity value correlated with the first physical quantity value, and a calibrating unit that calibrates the first sensor using the measurement value from the first sensor and the measurement value from the second sensor, wherein the first sensor is provided so as to be positioned on a first pathway through which the object being measured flows, and the second sensor is disposed in a measuring environment in which deterioration is less likely to occur than in the measuring environment of the first sensor.

The present application belongs to the technical field of load transfer monitoring, and discloses a load transfer monitoring method and system for multi-ship cooperative float-over operation. The load transfer process is divided into at least two monitoring stages according to the structural contact state, and different monitoring mechanisms are adopted for different stages to realize continuous monitoring of load transfer. By identifying the evolution law of the force path and the structural contact relationship in the load transfer process, the whole process is decomposed into multiple stage problems with clear physical mechanisms, and measurable physical quantities matching the dominant mechanical characteristics of each stage are selected to realize stage inversion of the load. The method for quantitatively monitoring the whole process of load transfer in the multi-ship cooperative float-over installation process is first proposed, which changes the operation from "experience control" to "data-driven control", effectively reducing the structural damage and operation risk caused by unknown load.

The invention discloses a method, a device, equipment and a medium for predicting oil production of an oil well in a multi-physical field. The method comprises the steps that target characteristic data of a target oil well are determined, the characteristic data are physical quantities adopted when oil displacement is conducted on the target well at different historical time points, and the physical quantities at least comprise the potential gradient, the ultrasonic frequency, the pulse discharge voltage, the frequency and the pulse width; a prediction model is determined, the target feature data are input into the prediction model to predict the oil production of the target oil well in the future first preset time period, and the prediction model is used for describing the oil production corresponding to the oil well under different feature data at different time points. According to the technical scheme, accurate prediction of the oil production of the oil well in multiple physical fields is realized according to the prediction model.

In a data obtaining step, a data obtaining unit may obtain certain data at a plurality of sampling times. The data may include measurement information regarding the amount of wear of the cutting tool and measurement information regarding a physical quantity of the cutting tool during cutting. In a clustering step, a clustering unit may cluster a plurality of pieces of the obtained data on the basis of the measurement information regarding the physical quantity included in each of the plurality of pieces of data. In a model creation step, a model creation unit may create, for each of clusters on the basis of the measurement information regarding the physical quantity and the measurement information regarding the amount of wear included in the data, a model for obtaining estimation information regarding the amount of wear from new measurement information regarding the physical quantity.

The invention relates to a battery pole piece slurry conveying method and system and coating equipment. The battery pole piece slurry conveying method comprises the steps that the physical quantity of slurry weighed by a weighing mechanism is obtained; comparing the size relationship between the physical quantity of the slurry and a set physical quantity; if the physical quantity of the slurry is smaller than the set physical quantity, driving parameters of the conveying mechanism are determined based on a preset target calculation model according to the difference value between the set physical quantity and the physical quantity of the slurry; and controlling the conveying of the slurry according to the driving parameters. According to the scheme provided by the invention, accurate prediction and control of the slurry conveying amount can be realized through the preset target calculation model, and the response speed and precision are improved, so that the production cost is reduced and the production efficiency is improved.

A physical quantity sensor includes a substrate provided with a first fixed electrode, a movable body provided to be swingable with respect to the substrate about a rotation axis along a Y axis, and a stopper restricting rotation of the movable body. The movable body is provided with an elastic portion at a position overlapping the stopper in a plan view viewed from the Z axis direction. The first mass portion includes a first region, and a second region far from the rotation axis. A first gap distance of a first gap between the first mass portion and the first fixed electrode in the first region is smaller than a second gap distance of a second gap between the first mass portion and the first fixed electrode in the second region.

According to the present invention: time-series physical quantity data related to the operation of an injection molding machine is acquired, the physical quantity data being obtainable in an injection molding step of a molded article by using the injection molding machine; the acquired physical quantity data is stored in a storage unit for each shot; quality data indicating the quality of the molded article obtained by injection molding when the acquired physical quantity data is acquired is stored in association with the physical quantity data; the quality of the molded article is calculated on the basis of physical quantity data acquired during estimation of the quality of the molded article and the stored physical quantity data and quality data in the storage unit; and prescribed processing is executed when the quality of the molded article becomes lower than prescribed quality.

A physical quantity distribution estimation method for an object is a method for estimating a distribution of a physical quantity of the object when the object is cooled by spraying a cooling liquid from a nozzle, and includes: a heat dissipation amount acquisition step for acquiring a heat dissipation amount by inputting a plurality of flow rates in a normal direction and a plurality of flow rates in a tangential direction with respect to the object in the cooling liquid into a machine learning model; acquiring information related to the heat dissipation amount of the cooling liquid to the object; and a physical quantity distribution calculation step for calculating the physical quantity distribution of at least one of the surface and the interior of the object using the heat dissipation amount as a boundary condition.

The application discloses a neutron transport constitutive relation and low-dimensional control equation modeling method based on sparse regression, which comprises the following steps: a neutron flow matrix under multiple state parameters is formed by state parameters of each state and physical quantity parameters calculated through a neutron transport program; fitting physical quantity parameters are filled into a sparse regression physical quantity matrix; a coefficient matrix is obtained by using a least square method to calculate an inverse matrix; and a neutron transport constitutive relation under multiple state parameters is obtained by assembling. The application utilizes the accurate characteristics of the calculation result of the neutron transport equation, grasps the cause of the larger deviation of the calculation result of the neutron diffusion equation in a small scale range, combines sparse regression fitting to obtain the neutron transport constitutive relation, and further obtains a low-dimensional macroscopic neutron transport control equation. The theoretical derivation is less difficult, the research progress is easier, the effect of improving the calculation precision is more obvious, the applicability is better, the gap with the situation under the actual reactor core working condition is not large, and the application has certain practicality.

The present invention achieves excellent performance related to the cutting edge in a cutting tool. A cutting system includes a cutting tool for milling, a plurality of sensors, and a processing unit. The cutting tool performs cutting using two or more cutting edges, the plurality of sensors measuring physical quantities representing a state related to the load on the cutting tool during cutting. The processing unit generates two-dimensional data related to the load at each measurement timing based on the measurement results of each of the sensors at multiple measurement timings. The load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool. Each of the generated two-dimensional data is classified into any one of a plurality of unit areas within the plane, equal to or greater than the number of the cutting edges, and an abnormality of the cutting edge is detected based on the two-dimensional data of each unit area.