1466results about "Internal-combustion engine testing" patented technology

The invention relates to the technical field of fault detection, and discloses a diesel generating set fault detection method and system based on deep learning, and the method comprises the steps: obtaining first vibration signal data, and carrying out the time-frequency decomposition, and obtaining a dynamic change feature; de-noising processing is carried out on the dynamic change features to obtain a time-frequency feature sequence; extracting a peak energy distribution data set, and calculating each frequency band entropy value to obtain a frequency band entropy value sequence; classifying the frequency band entropy sequence, determining a random fluctuation reference mode, and separating to obtain an abnormal frequency component; calculating a spectral line spacing and amplitude ratio, obtaining a spectral line feature data set, classifying the spectral line feature data set, and determining a fault classification result; obtaining current second vibration signal data, performing similarity calculation on the current second vibration signal data and a pre-established normal mode library, and outputting a fault feature vector; and verifying the fault feature vector to obtain a final fault detection result. According to the method, closed-loop diagnosis from signal acquisition to fault classification can be realized, and the fault detection precision of the diesel generating set is improved.

The invention provides an engine oil burning diagnosis and maintenance system, and relates to engine oil burning diagnosis. The method comprises a multi-source data acquisition model, a heterogeneous data deep fusion module, a multi-level diagnosis module and a prediction maintenance module. The multi-source data acquisition model is used for acquiring multi-source data in the operation process of an engine in real time through an integrated sensor array, and the multi-source data comprises vibration data, acoustic data, exhaust component data and temperature distribution data; the heterogeneous data deep fusion module is used for performing data conversion on the multi-source data to obtain unified multi-source feature representation; the multi-level diagnosis module is used for performing multi-level diagnosis on the multi-source feature representation to obtain a multi-level diagnosis result; and the prediction maintenance module is used for carrying out maintenance analysis according to the multi-layer diagnosis result to obtain a maintenance decision suggestion containing a predicted life value, a fault evolution path and optimal maintenance time. By means of the scheme, the comprehensiveness and accuracy of engine oil burning diagnosis and maintenance are improved.

The present invention relates to the technical field of railway-locomotive diesel-engine fault diagnosis systems, and particularly relates to a railway-locomotive diesel-engine fault diagnosis system based on a knowledge graph. The system comprises a data collection module, a transmission module, a preprocessing module, an algorithm application module, a storage module and a front-end display module, wherein one end of the data collection module is used for performing signal collection by means of a sensor, and the other end thereof is connected to the preprocessing module by means of the transmission module; the preprocessing module performs diagnosis and positioning on a specific faulty part in combination with a fault classification algorithm of the algorithm application module; and an original signal collected by the data collection module and algorithm diagnosis information are scheduled and stored in the storage module by means of back-end management software, and display interaction materials are then provided for the front-end display module. The present invention retains the previous operation mode of an expert knowledge base in terms of fault diagnosis so as to ensure the basic accuracy of cause analysis, and a neural network intelligent algorithm is introduced to reduce the manual workload and individual difference of people in terms of professionalism.

A method for monitoring a rotating machine in order to detect a fault in a bearing, the method including acquiring, from the rotating machine, a vibration signal measured by a vibration sensor; determining a first-order spectrogram by first-order cyclostationary analysis of the vibration signal using a delta transform and spectral standardisation; determining a second-order spectrogram by second-order cyclostationary analysis of the vibration signal using averaged cyclic coherence, a delta transform and spectral standardisation; and detecting a vibration signature of the fault in the bearing on the basis of the first-order spectrogram and the second-order spectrogram.

The invention discloses a digital twin intelligent test run system based on a marine medium-speed diesel engine and a monitoring method, relates to the technical field of monitoring, and is used for solving the problems of degeneration identification lag and low emission early warning precision of an oil injector. The system comprises a multi-source heterogeneous data preprocessing module and a running state intelligent diagnosis module. The multi-dimensional data acquisition module is used for acquiring in-cylinder pressure, crankshaft torsional vibration and transient air-fuel ratio signals to construct multi-dimensional data vectors, and the multi-dimensional data acquisition module is used for analyzing combustion fluctuation characteristics based on an attention mechanism LSTM (Long Short Term Memory) network, identifying early deterioration of an oil injector and outputting an oil injection consistency coefficient and a fault type identifier. The method comprises the steps that according to an oil injection consistency coefficient, electromagnetic valve response delay and combustion parameter correlation are tracked, a degradation trend is predicted, and emission early warning is generated; and according to prediction and early warning results, fuel injection compensation parameters are dynamically adjusted in the digital twinborn model, a recursive least square method is adopted to identify combustion parameters and feed the combustion parameters back to an electric control unit, and self-adaptive optimization and closed-loop control in the test run stage are achieved.

The invention belongs to the technical field of mechanical test tool equipment, and particularly relates to an electro-hydraulic speed regulator test testing device. Comprising the steps that a virtual diesel engine model generates a signal and supplies the signal to a rotating speed controller, an alternating current power supply supplies power to a frequency converter to drive a motor to operate, and the rotating speed of the motor is transmitted to an electro-hydraulic speed regulator through a first coupler to drive a main pump in the electro-hydraulic speed regulator to build pressure; a hydraulic bridge circuit in the electro-hydraulic speed regulator acts to drive the output shaft to rotate, the output shaft transmits an output signal back to the virtual diesel engine model through the flywheel, the magnetic powder brake and the angle sensor, and the virtual diesel engine model feeds back the signal to the magnetic powder brake through the brake controller; and the output torque of the electro-hydraulic speed regulator is ensured to meet the operation requirement and is confirmed by the torque sensor. The electro-hydraulic speed regulator test device has the advantages that the electro-hydraulic speed regulator test device is provided with the outer circulation oil way, and the test requirements of various electro-hydraulic speed regulators can be met.

The invention discloses a diesel engine fault diagnosis method, system and device and a medium, and relates to the technical field of diesel engine fault diagnos.The method comprises the steps that vibration signal data of a diesel engine are collected; constructing a fault diagnosis model in parallel based on the improved one-dimensional convolutional neural network; vibration signal data are input into a fault diagnosis model, time domain features and frequency domain features of vibration signals are extracted through a dual-channel convolution layer, the time domain features and the frequency domain features are input into a gating circulation unit layer after passing through a three-layer pooling layer for time sequence modeling, and dynamic change information of the time domain features and the frequency domain features is obtained; key information of dynamic change information is extracted through an attention mechanism layer and fused, the key information passes through a global maximum pooling layer and then is input into a Softmax layer, and a classification result is output to diagnose faults of the diesel engine; according to the method, key information of dynamic change information is extracted by introducing a gating circulation unit and an attention mechanism, and the fault detection precision is improved.

The invention discloses a variable environment fuel oil atomization quality test system and test method. The system comprises a high pressure common rail injection system, a low temperature refrigeration system, an electronic control system, an image data acquisition system and an environment test chamber. The low-temperature refrigerating system reduces the temperature of fuel oil in the oil injector through convective heat exchange; the environment test cabin simulates the environment air pressure, temperature and humidity in the cabin according to the actual environment parameters in the cylinder in the engine operation process; the image data acquisition system acquires spray image information of low-temperature fuel oil in a variable environment and performs image processing, and by actually measuring the circulating oil injection quantity during fuel oil injection, the Sott average diameter is calculated according to different empirical formulas, and the fuel oil atomization characteristics are comprehensively analyzed. The invention provides a reliable experimental means for researching the fuel oil atomization condition of the fuel oil in a low-temperature state in a low-temperature environment in the cold start process of the engine, deeply analyzing the influence of a complex environment on the cold start of the engine, and seeking to improve the cold start performance of the engine.

The invention discloses an engine fault diagnosis method, device and equipment and a storage medium, and relates to the technical field of fault diagnosis. The method comprises the following steps: synchronously acquiring a sound signal and a vibration signal of an engine in a normal operation state, and performing feature extraction on the sound signal and the vibration signal to obtain corresponding target features; the target features comprise time domain features, frequency domain features and time-frequency domain features; determining a statistical index of each target feature through statistical characteristic analysis, and performing feature fusion on all the target features according to a target fusion mode based on the statistical indexes to obtain a fusion index; and an early warning threshold value is determined according to the data statistical characteristics of the fusion index, so that fault monitoring is carried out on the engine by using the early warning threshold value. Fault diagnosis is carried out according to the early warning threshold value determined according to the sound vibration data of the engine in the normal operation state, high dependence on fault samples is avoided, and the comprehensiveness of fault analysis is improved.

The utility model relates to the technical field of air tightness detection, and especially relates to an automobile engine manifold air tightness detection device comprising a clamping assembly; mounting parts are symmetrically arranged on one side of the top end of the test box, supporting shafts are rotationally arranged in inner holes of the mounting parts, an operation table is arranged on the supporting shafts, the clamping assembly is arranged on the operation table, the engine manifold is fixed to the operation table through the pressurizing assembly, and a cavity of the test box is filled with test liquid. The engine manifold completely enters the test liquid during testing; the pressurizing assembly is arranged on the operation table, and the pressurizing assembly is used for filling the engine manifold with gas; the driving assembly is arranged on the test box, and the driving assembly is used for providing rotation power for the supporting shaft to drive the operation table; the operation procedure is simple, and the shape adaptability is high.

The invention provides a method and a device for predicting engine noise of a vehicle. The engine noise separated from the vehicle noise is predicted. The method may include: acquiring engine noise data not including vehicle noise; acquiring vehicle noise data not including engine noise; generating training data by mixing the engine noise data and the vehicle noise data; providing a deep learning model differently constructed for each vehicle through transfer learning based on a pre-training model pre-trained by the training data; and predicting engine noise of each vehicle by using the deep learning model.

This application provides a fault determining method of a reciprocating device and a port control method. The method includes: obtaining target signal data acquired by a sensor located on a component at a predetermined location of a reciprocating device; determining, according to a data type of the target signal data, a target processing mode; processing, according to the target processing mode, the target signal data, to obtain a running status eigenvalue reflecting a running status of the component; and determining, according to the running status eigenvalue, a fault result indicating whether the component is faulty. The present disclosure solves a technical problem that it is unlikely to accurately determine a fault of a reciprocating device in the related art.

The invention relates to the technical field of generator test equipment, and particularly discloses a comprehensive test platform for a generator. The bearing assembly, the hoisting assembly and the testing instrument are installed on the vehicle body, the bearing assembly comprises two bearing arms and a driving mechanism, and weighing sensors are installed on the bearing arms and can be far away from and close to each other; the test instrument can obtain related test data based on weighing data fed back by the weighing sensor. The comprehensive test platform for the generator can move, can automatically complete loading and unloading of the diesel generator, does not need assistance of other equipment, and remarkably reduces the requirements for site conditions; data such as the whole machine weight, the fuel consumption rate and the operation stability can be measured, the test items are rich, and the functions are complete; and the transfer frequency in the comprehensive test process can be effectively reduced. After the test is completed, the diesel generator can be transferred and loaded to another test device, which is efficient and fast; and meanwhile, the method has the technical advantages of good applicability, easiness in implementation, relatively low cost and the like.

The invention provides an energy management strategy verification platform for a plug-in series hybrid power ship propulsion system. The energy management strategy verification platform comprises a power source module, a power output module, a load simulation module, a transmission module, a sensor measurement module and a control system module, the power source module outputs electric energy through multi-energy cooperation; the power output module generates propelling power according to the electric energy; the load simulation module simulates load characteristics according to the propulsion power; the transmission module is connected with the power source module and the power output module as well as the power output module and the load simulation module; the sensor measurement module collects operation parameters of the verification platform; and the control system module executes an energy management strategy according to the operation parameters and outputs a control instruction. A graphical programming environment is constructed by adopting a modeling code automatic generation system, and a strategy rapid prototype development verification closed loop is formed in combination with a range extender intelligent start-stop control strategy and a multi-mode power generation control strategy.

Disclosed are an apparatus for a simulation test of diesel engine fuel spray in an alpine environment and a test method, the apparatus comprising a fuel storage and pretreatment device, a fuel injection system, an optical visualization system, an environment chamber, and a spray pretreatment system. In alpine environmental conditions, the apparatus can achieve high-pressure injection of liquid, separate injected atomized mist into fine droplets and impinge same on a wall surface by means of a multi-droplet generation apparatus and a wall surface apparatus, and observe and record the whole process by means of an optical visualization path. According to the present invention, the problem of difficulty in distinguishing droplets due to the coalescence of spray into a sheet is avoided, the costs of a traditional spray and droplet test solution can be significantly reduced, and the problem of a high level of dependence on a control program in a constant volume vessel solution is solved. According to the present invention, simulation of spray test in an alpine environment is possible, and the test apparatus has a simple structure. Moreover, it is possible to conduct regular research on free spray, multi-droplet wall impingement, spray wall impingement, and development characteristics thereof under conditions such as different altitudes and different temperatures.

The invention relates to a reliability test method and device for an emergency diesel engine of a nuclear power plant and a storage medium, and the test method comprises the following steps: obtaining the operation condition information of the emergency diesel engine, and obtaining the estimated total use time of parts of a connecting rod power assembly of the emergency diesel engine based on the operation condition information; structural information of a connecting rod power assembly of the emergency diesel engine is obtained, a dynamic calculation model of the connecting rod power assembly is constructed based on the structural information and the operation condition information, and the dynamic calculation model is used for simulating operation of the connecting rod power assembly in preset time; obtaining a wear coefficient of the part, and inputting the wear coefficient and the estimated total use duration into the dynamic calculation model to obtain the part wear loss of the connecting rod power assembly and the maximum wear loss of the cylinder sleeve; and determining the reliability of the emergency diesel engine according to the part abrasion loss and the maximum abrasion loss of the cylinder sleeve. The test method can guarantee reliable operation of the emergency diesel engine.

A system for detecting a source of a misfire for a turbulent jet ignition (TJI) engine having a first ignition device disposed in a pre-chamber of a cylinder head and a second ignition device disposed for communication with a main combustion chamber is presented. The system includes a controller that determines engine operating conditions; generates a first spark from the first ignition device at a first time; generates a second spark from the second ignition device at a second time; activates a skipfire mode based on a determination that the engine operating conditions are satisfactory, wherein in the skipfire mode, the controller generates a modified second spark at a modified second time, the modified second time being later than the second time; and determines a misfire event based on sensing ionization of gasses at the main combustion chamber subsequent to firing the first and second ignition devices.

The invention relates to the field of marine engine performance monitoring and optimization, and discloses a marine engine adaptive aging prediction method and a fault diagnosis model.The prediction method comprises the following steps that a digital twin model of a marine engine is constructed, and an engine reference health state is generated; acquiring operation parameters of the marine engine in real time, and inputting the operation parameters into the digital twin model to calculate a reference performance index; identifying the degradation offset of the actuating mechanism by comparing the output of the digital twin model with the operation data of the entity engine; constructing a multi-objective optimization problem based on performance indexes of a digital twin model, and generating a Pareto optimal solution set by using an NSGA-III algorithm; and an optimal solution under a specific working condition is selected through a fuzzy comprehensive evaluation method, and degradation state evaluation and optimal control strategy generation are realized. Compared with the prior art, the method can accurately predict the degradation state of the marine engine, reduces the maintenance cost, improves the operation efficiency and reliability, and meets the dynamic optimization requirements of complex working conditions.

A method for determining engine oil system health includes determining an oil level in an engine oil sump of an engine, determining an oil consumption rate of the engine based on a current oil volume and a time at which the oil was last replenished, determining a remaining useful oil volume based on the oil consumption rate and duty cycle data of the engine, and generating an alert in response to the oil consumption rate being greater than a predetermined threshold, the alert comprising a command to a controller associated with the engine to cause the engine to perform an action.

The invention relates to the technical field of electronic data processing, and discloses a diesel engine operation state real-time monitoring method and system, and the method comprises the steps: obtaining a vibration signal of a measurement point on the surface of an engine body as an original signal; modal decomposition is carried out to obtain a final intrinsic mode function, and the decomposition process comprises the steps that multiple times of lumped operation are executed, in each time of lumped operation, an auxiliary noise signal is added into a to-be-decomposed original signal, then the screening iteration process is executed repeatedly, and a set of temporary intrinsic mode functions are obtained through separation in sequence; performing weighted average on the temporary intrinsic mode functions of the same order obtained in all the lumped operations to obtain a final intrinsic mode function of the order; hilbert transform is carried out on the intrinsic mode function, joint distribution of instantaneous energy and instantaneous frequency of the intrinsic mode function is constructed, and statistical and geometric morphological features are extracted to form feature vectors; according to the method, modal aliasing can be inhibited, noise residues are eliminated, and the accuracy of a running state monitoring result is improved.

The invention discloses a marine diesel engine degradation performance prediction method and device based on Bayesian reasoning, and the method comprises the steps: collecting state information data, and making a training set and a test set; constructing a Bayesian neural network model and a Bayesian logistic regression model; jointly optimizing weight parameters of the Bayesian neural network model and parameters of the Bayesian logistic regression model; training a Bayesian neural network model and a Bayesian logistic regression model by adopting the training set; performing performance test on the trained model by adopting the test set; and obtaining state information data in the actual operation process of the marine diesel engine, and inputting the state information data into the trained model to respectively obtain a performance prediction result and a performance degradation curve of the marine diesel engine. The method has the advantages that the prediction precision is high, and the confidence interval can be generated to assist the adjustment of the operation and maintenance scheme of the diesel engine equipment.

The embodiment of the invention provides an automobile engine fault diagnosis method and device, a vehicle and a medium. The method comprises the steps that multiple types of sensor data related to an automobile engine are acquired; for each type of sensor data, performing feature extraction by adopting a feature extraction strategy adaptive to the type of the sensor data to obtain corresponding feature data; and fusing the feature data corresponding to the various types of sensor data to obtain comprehensive feature data, and performing fault diagnosis by adopting the comprehensive feature data to obtain an engine fault diagnosis result. According to the embodiment of the invention, the method achieves the fault diagnosis of the automobile engine in a multi-modal data fusion analysis mode, and improves the accuracy and reliability of the fault diagnosis of the automobile engine.

The invention aims to provide a marine diesel engine operation parameter anomaly detection method based on spatial-temporal feature fusion, and belongs to the field of diesel engine detection. The method comprises the following steps: collecting time sequence data of multiple sensors under a normal working condition of a diesel engine, and dividing the time sequence data into a training set and a verification set; multi-sensor monitoring data of the diesel engine in an abnormal state are collected to form an independent test set. And establishing an MsBTC-Net formed by a diesel engine operation parameter predictor and an operation parameter anomaly detector, inputting the verification set into an MsBTC-Net predictor model, obtaining a predicted value of the verification set at each time step of the diesel engine monitoring parameter, and calculating a predicted residual by combining an actual value of the monitoring parameter. And then a Mahalanobis distance threshold value is calculated, and an MsBTC-Net operation parameter anomaly detector is constructed. According to the method, the multi-dimensional operation monitoring parameters of the diesel engine are predicted, the performance of abnormal detection of the operation parameters of the diesel engine is effectively improved, the detection sensitivity of early fault weak signals of the diesel engine is remarkably enhanced, and the method has engineering application value.

The invention belongs to the field of instrument detection, and provides an aircraft engine parameter indication detection system and method, and the method comprises the steps: generating a first sensor signal for an engine parameter indicator simulation test according to a first parameter; the first sensor signal is output to an engine parameter indicator in an analog signal mode so as to simulate the working state of an engine; collecting a first indication response signal generated after the engine parameter indicator receives the analog signal; calling a first pre-training artificial intelligence model, judging whether the working state of the engine parameter indicator is abnormal or not based on the first sensor signal and the first indication response signal, and outputting a corresponding detection result; calling a second pre-training artificial intelligence model, and combining the first sensor signal and the first indication response signal to generate a second parameter; judging whether to continue to execute the test process based on the second parameter; therefore, the testing precision and efficiency of the aircraft engine can be effectively improved.

The invention discloses an excavator PEMS emission self-inspection equivalent working condition testing method, and relates to the technical field of excavator testing, and the method comprises the steps: operating an excavator to carry out actual working condition operation, and collecting working condition parameters in real time; performing equivalent working condition overflow loading operation on the actual working condition operation according to the working condition parameters to obtain equivalent working condition operation; operating similar excavators to perform equivalent working condition operation, and collecting working condition parameters and exhaust parameters in real time; and according to the working condition parameters and the exhaust parameters in the equivalent working condition operation process, the instantaneous acting amount and the instantaneous emission amount are obtained, and therefore the PEMS emission test result of the excavator is obtained through calculation. According to the corresponding relation between the continuous high load and the discharge level of the excavator, the excavator is operated to carry out a non-load movable arm, bucket rod and bucket single action and overflow loading combined working condition test through the proportional equivalent relation of two modes of multi-action overflow loading and actual operation, so that the PEMS discharge test is completed.

The present invention discloses a blade tip sensor measurement accuracy detection method and device for simulating rotating turbine blades, and relates to the field of engine measurement technology. The method comprises: building a blade tip sensor measurement accuracy detection device; performing zeroing and retraction processing in sequence according to the blade tip sensor measurement accuracy detection device to obtain a standard distance value; obtaining a measurement voltage value based on the standard distance value using the blade tip sensor measurement accuracy detection device; and obtaining a blade sensor measurement accuracy detection result by performing detection according to the standard distance value and the measurement voltage value. The present invention simulates the monitoring behavior of the blade tip sensor on the rotating turbine blades in a real high temperature environment, and can more accurately and effectively complete the calibration or accuracy detection of the blade tip sensor.

The invention relates to a method for controlling a functional test on a moving motor vehicle. In order to deliver a meaningful result, the functional test relies on fluctuations in at least one operating parameter of the motor vehicle not exceeding a permissible level during the duration of the functional test. The method comprises the following steps: a) querying (S3, S8) information concerning a route ahead of the motor vehicle; b) based on the requested information, predicting (S4, S9) the development of the at least one operating parameter on the route; c) Carrying out (S5, S6, S7) the functional test from a point in time at which the forecast suggests that, from this point in time and for the duration of the functional test, fluctuations in at least one operating parameter will not exceed the permissible level.

The invention provides a vehicle diesel engine bench simulation emission test method, system, device and medium, and belongs to the bench test technology field, a test bench and a test device are configured, a flowmeter and an analyzer are calibrated through a linear regression equation, and a mapping relation between a measured value and an output quantity is established; an engine transient working condition model is constructed based on real vehicle data, and mapping of the rack control process and the real vehicle operation working condition is achieved; configuring the rotating speed, the torque, the air inlet temperature and the air inlet humidity controlled by the rack as boundary conditions, evaluating the control following performance through a correlation coefficient calculation mode, and verifying the environmental parameter consistency based on a mean value deviation; calculating the exhaust flow, and configuring measurement data based on the intake flow and the fuel consumption; executing a transient test, and obtaining real-time data of an engine running state and discharged pollutants; and under the condition that the double boundary condition constraints are met, carrying out equivalence analysis on a rack and a real vehicle emission result.

The invention discloses a method for testing the parking charging rotating speed of a hybrid vehicle. The method comprises the following steps: S1, arranging noise and vibration measuring points; s2, data acquisition; s3, testing the working condition; S4, processing data; and S5, determining the rotating speed of the engine by combining the parking charging noise and the vibration target set by the whole vehicle. Noise data is acquired using a microphone. A three-way acceleration sensor is adopted to collect vibration data, and the sensor is arranged at the 12 o'clock position of a spoke of a steering wheel. By adopting the testing method, the charging rotating speed of the engine under the parking working condition can be quickly determined, and a rotating speed reference is provided for subsequent exhaust tuning; noise and vibration under the parking charging working condition can be considered at the same time, and the development efficiency is improved.

The invention relates to the technical field of engine monitoring, in particular to an engine fault detection and diagnosis method, which comprises the following steps of: acquiring engine data, vibration data and cooling data; judging the vibration state of the engine; the engine cooling state is judged; the thermal expansion state of the turbine blade is judged; performing conjoint analysis on the engine cooling state and the thermal expansion state of the turbine blade to obtain an engine state index, and dividing engine fault grades according to the engine state index and the engine vibration state; analyzing the engine speed fluctuation state, and optimizing the division process of engine fault grades according to the engine speed fluctuation state; and performing data integration on the transmission shaft rigidity and the lubricating oil pressure to construct a rotating speed influence factor, and optimizing the analysis process of the engine rotating speed fluctuation state according to the rotating speed influence factor. The fault monitoring efficiency of the engine is effectively improved.