Online wear detection device and wear detection method for reinforced diesel engine friction pair

Abstract

The invention provides a reinforced diesel engine friction pair on-line wear detection device and a wear detection method. The reinforced diesel engine friction pair on-line wear detection device comprises a wear calculation terminal, an NI-PXIe8115 acquisition instrument, a sampling detection circulating oil path, a cylinder pressure sensor, a rotating speed sensor, a vibration sensor, an acoustic emission sensor, a six-in-one lubricating oil physical and chemical sensor, an abrasive particle sensor, an abrasive particle visual sensor and a CAN / USB / RS485 communication interface. The method has the beneficial effects that the load of a friction pair of the strengthened diesel engine is large, the process from symptoms to failure is extremely short, and serious fault events are difficult to control, the device can quickly warn an abnormal state after being implemented, gives a corresponding action instruction to a user, and provides a reliable identification means for strengthening research, development and operation safety of the diesel engine.

Description

Technical Field

[0001] The present invention belongs to the technical field of diesel engine wear detection, and in particular relates to an enhanced on-line wear detection device and wear detection method for a diesel engine friction pair. Background Technique

[0002] Before the occurrence of severe faults in a highly enhanced diesel engine, the instability of the operation of the friction pair is always the origin. Therefore, by detecting the severe wear state of the friction pair, the abnormal operation of the diesel engine can be monitored in advance, so as to carry out targeted measures such as cooling and speed reduction, shutdown, etc., to avoid the losses caused by severe faults. On the one hand, currently used on-line single-factor monitoring means such as vibration and abrasive particles lack the description of abnormal state characteristics under the corresponding mechanism due to the self-limitation of their macroscopic limits after warning the occurrence of fault initiation. On the other hand, due to the different technical cognitions of on-site and design personnel, and often due to the lack of auxiliary detection tools or the unclear description of state characteristics, subsequent trial operation and process reproduction are required to further locate the problem, resulting in the further expansion of abnormal problems until serious damage, which brings great challenges to the repair of the diesel engine after the occurrence of faults.

[0003] Traditionally, the lubricating oil sampling detection optical ferrograph is used to determine the macroscopic composition of wear particles and the increment of particle concentration, and the abnormal wear reminder is given by using the increment gradient limit value. Because the discrete sampling interval of the oil sample cannot follow the working conditions synchronously and the offline detection process is time-consuming, it is difficult to effectively prevent the harm of severe wear faults in real time.

[0004] Currently used on-line fault detection means focus on single-factor fault monitoring. For example, methods such as using vibration on-line tracking detection to indicate abnormal operation of components, using multi-in-one oil physical and chemical on-line tracking detection to detect the degradation of the quality performance of lubricating oil, and using classified abrasive particle on-line means to detect the cumulative amount of large abrasive particles to indicate the severe spalling degree of the friction pair are all fault alarm processes based on macroscopic limits, and the source of the abnormal state of the friction pair cannot be determined. After the warning appears, certain offline means and data analysis and processing cycles are still required to specifically eliminate false alarms and missed alarms to determine the severity of the wear fault and give subsequent work instructions.

[0005] Summarize the main disadvantages of the above-mentioned currently used detection methods as follows: 1. Traditional offline detection methods such as spectroscopy, ferrography, surface roughness meter, and scanning electron microscope have a lag in the verification process of detection means and cannot give warnings for on-line abnormal wear detection of highly enhanced diesel engines. Severe faults such as diesel engine cylinder pulling and bearing seizure often occur, and the whole machine is easily scrapped after the fault. 2. On-line warning means using single vibration and macroscopic data trends of lubricating oil abrasive particles for monitoring and alarming cannot be used for multi-state migration of alarm limits. The fault detection rate and early warning rate are greatly interfered by detection conditions, and the proportion of false alarms and missed alarms is high. It is difficult to determine the cause of abnormal problems in the occurrence of faults, and they will develop into severe faults under continuous operation, resulting in the damage of the whole machine. 3. The prior art fails to accurately identify the deterioration trend of diesel engine performance, cannot determine the different wear stages of the diesel engine based on the wear identification situation, and lacks methods for strengthening the continuous operation and preventive maintenance management of the diesel engine. SUMMARY OF THE INVENTION

[0006] In view of this, the present invention aims to propose an on-line wear detection device and wear detection method for strengthening the friction pair of a diesel engine to solve at least one of the problems existing in the above prior art.

[0007] To achieve the above object, the technical solution of the present invention is realized as follows: In a first aspect, the present invention provides an on-line wear detection device for strengthening the friction pair of a diesel engine, including a wear calculation terminal, an NI-PXIe8115 acquisition instrument, a sampling detection circulation oil circuit, a cylinder pressure sensor, a rotational speed sensor, a vibration sensor, an acoustic emission sensor, a 6-in-1 lubricating oil physical and chemical sensor, a wear particle sensor, a wear particle visualization sensor, and a CAN / USB / RS485 communication interface. The cylinder pressure sensor and the vibration sensor are installed on the diesel engine, and the output electrical connection interface is connected to the AI interface of the PXIe8115 acquisition instrument through a charge amplifier; the rotational speed sensor and the acoustic emission sensor are installed on the diesel engine, and the electrical connection interface is directly connected to the AI interface of the PXIe8115 acquisition instrument; the 6-in-1 sensor and the wear particle sensor are installed in the sampling detection circulation oil circuit, and the data transmission interface is connected to the PCIe8115 acquisition instrument through an RS485 MODBUS RTU communication interface; the wear particle visualization sensor is installed on the sampling detection circulation oil circuit, and the data transmission interface is connected to the PXIe8115 acquisition instrument through USB; the thermal sensor is installed on the diesel engine or the dynamometer load, and is connected to the PXIe8115 acquisition instrument through the CAN bus by the test bench acquisition terminal.

[0008] Furthermore, the sampling detection circulation oil circuit controls the temperature and flow rate of the sampled lubricating oil, and discharges the bubbles in the sampling channel of the lubricating oil. Among them, the sampling temperature range is 60°C to 70°C, the sampling flow rate is constant at 1000 mL / min, and the automatic defoaming rate is 98%. The sampling detection circulation oil circuit includes a non-destructive oil suction pump, a circulation oil pump, a cooling heat exchanger, a heating heat exchanger, a buffer tank, a three-way valve, a defoamer, and valves.

[0009] Furthermore, the bubble detector adopts a reticulated filter structure and simultaneously utilizes the 0.4 MPa working environment established by the circulation oil pump.

[0010] Further, during the initial preheating of the system, the on-off valve is closed and the system preheating valve is opened. A circulation loop is formed by the sampling inlet valve, the oil suction pump, the lubricating oil buffer tank, the circulation pump, the air-cooled radiator, the heat exchanger, the bubble detector, the system preheating valve, and the sampling outlet valve. The lubricating oil medium conducts the calorific value in the heat exchanger and the air-cooled radiator to each component in the circulation loop.

[0011] Further, it also includes an offline sampling oil distribution channel and an abrasive deposit oil distribution channel to meet the requirements of offline ferrography and energy spectrum detection of lubricating oil.

[0012] Further, the physical and chemical indexes, wear severity trend, and abrasive microscopic morphology of the lubricating oil are detected through the sampling detection circulation oil circuit. The physical and chemical parameters of the lubricating oil include dynamic viscosity, temperature, density, dielectric constant, micro water, and water activity; there are 6 grades of abrasive particle size parameters, including ≤10μm, 10 - 20μm, 20 - 40μm, 40 - 80μm, 80 - 125μm, ≥125μm; the visual abrasive particle parameters can realize the classification of cutting, sliding, fatigue, and non-metallic abrasive particles.

[0013] In the second aspect, based on the same inventive concept, the present invention also provides a method for on-line wear detection of the friction pair of a reinforced diesel engine, including the following contents: Based on the detection parameters of the on-line wear detection device for the friction pair of the reinforced diesel engine; Combined with the rotational speed, torque, diesel fuel consumption, lubricating oil pressure, and lubricating oil temperature communicated during the operation of the diesel engine test bench, the operating conditions of the diesel engine are segmented into three-order operating conditions according to the rotational speed, torque, and lubricating oil temperature; Among them, the rotational speed segmentation gradient is not less than 100r / min, the torque segmentation gradient is not less than 500N·m, and the temperature segmentation is 85℃ - 105℃ working temperature and other non-working temperatures; Early warning MAPs of vibration acceleration, vibration velocity, vibration displacement, lubricating oil viscosity, lubricating oil water content, abrasive particle concentration, abrasive particle size scale, cylinder friction force, transmission gear wear ring, and main shaft wear ring are formed under the three classifications of "rotational speed - torque", "rotational speed - lubricating oil temperature", and "torque - lubricating oil temperature", and early warning of abnormal wear during the operation of the reinforced diesel engine is given.

[0014] Further, it also includes a specific positioning method for the components after warning, and the process of the specific positioning method is as follows: The vibration acceleration, vibration velocity, vibration displacement, cylinder friction force, transmission gear wear ring, and main shaft wear ring are used as warning symptom detection parameters, and the vibration velocity warning is used as the basic warning; When the vibration velocity warning does not appear, other warnings are invalid warnings; Taking the vibration acceleration gear envelope spectrum characteristics, the ringing of worn transmission gears, and the precipitated abrasive particles as the wear location detection and classification of the transmission system; Taking the acceleration main shaft excitation spectrum, the cylinder friction torque, the abrasive particle concentration, the ringing of the main shaft wear, the diesel fuel consumption, and the lubricating oil pressure as the wear location detection and classification of the crankshaft rotor system; Taking the diesel fuel consumption, the lubricating oil pressure, the dielectric constant, the viscosity, and the density as the wear location detection and classification of the fuel supply system, and taking the density, the water content, and the cylinder friction as the leakage detection of the cylinder cooling system; Taking the cylinder friction torque, the vibration displacement, the vibration acceleration cylinder excitation spectrum, and the precipitated abrasive particles as the wear location detection and classification of the piston motion system; According to the above classification, the information after the fault warning is pushed to the specific abnormal fault location.

[0015] Furthermore, it also includes a wear degree method under the warning classification, and the method includes: When all the classified parameters are alarmed, it is indicated as a serious warning and an emergency stop must be made; When 50% of the classified warning parameters are alarmed as the abnormal germination warning, it can still continue to work but be vigilant, and the operation process is controlled according to the warning increment number; When 75% of the parameters are alarmed, it is a functional damage warning, and it is recommended to run again after repair.

[0016] Compared with the prior art, the enhanced diesel engine friction pair online wear detection device and wear detection method described in the present invention have the following advantages: (1) For the enhanced diesel engine friction pair online wear detection device and wear detection method described in the present invention, the load of the enhanced diesel engine friction pair is large, the process from symptom to failure is extremely short, and serious fault events are difficult to control. After the implementation of this device, it can quickly alarm the abnormal state and give corresponding action instructions to the user, providing a reliable identification means for the research and development and operation safety of the enhanced diesel engine.

[0017] (2) For the enhanced diesel engine friction pair online wear detection device and wear detection method described in the present invention, in order to reduce the false alarm rate and misreport rate of the online wear detection device, this device adopts the lubricating oil sampling principle and uses the sampling circulation oil circuit to keep the working conditions of the lubricating oil abrasive particle online sensor constant, reducing the outlier rate of the collected data.

[0018] (3) For the on-line wear detection device and wear detection method of the friction pair of the enhanced diesel engine of the present invention, in order to synchronously enhance the operating state of the diesel engine and improve the sensitivity of detecting abnormal wear, this device combines the rotational speed, torque, diesel fuel consumption, lubricating oil pressure, and lubricating oil temperature communicated during the operation of the diesel engine test bench, divides the operating conditions of the diesel engine into three-order operating conditions according to the rotational speed, torque, and lubricating oil temperature, designs an early warning MAP, warns of abnormal wear during the operation of the enhanced diesel engine, and proposes a specific positioning method for abnormal components after on-line wear warning and a method for determining the wear degree under the warning classification, so that users can take corresponding actions.

[0019] (4) For the on-line wear detection device and wear detection method of the friction pair of the enhanced diesel engine of the present invention, in order to minimize the loss of abnormal states during the R & D verification and operation process of the enhanced diesel engine, acoustic emission, vibration, cylinder friction force, and instantaneous rotational speed are used to collect data at high speed as supplementary monitoring tools, forming a synchronous detection of comprehensive multi-parameter factor wear collection, and using multi-source information characteristic indexes that can be calculated on-line and on-line wear detection indexes to quickly classify abnormal states. Brief Description of the Drawings

[0020] The drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings: Figure 1 Schematic diagram of the connection structure of the detection device described in the embodiment of the present invention; Figure 2 Schematic diagram of the principle of the sampling detection circulation oil circuit described in the embodiment of the present invention; Figure 3 Schematic diagram of the structure of the on-line wear detection system described in the embodiment of the present invention; Figure 4 Schematic diagram of the flow chart of the feature fusion algorithm driven by deep learning described in the embodiment of the present invention; Figure 5 Schematic diagram of the detection of abnormal wear alarm of the friction pair described in the embodiment of the present invention; Figure 6 Schematic diagram of the envelope and filtering of the bearing vibration signal described in the embodiment of the present invention; Figure 7 Schematic diagram of the instantaneous rotational speed fluctuation curve of the diesel engine described in the embodiment of the present invention; Figure 8 Schematic diagram of the instantaneous rotational speed fluctuation curve of the first cylinder misfire of the diesel engine described in the embodiment of the present invention; Figure 9 Schematic diagram of the change of the average ring count of the acoustic emission signal with the wear process described in the embodiment of the present invention; Figure 10Schematic diagram of the change of the root mean square energy of the acoustic emission signal with the wear process according to the embodiment of the present invention; Figure 11 Schematic diagram of the measured value of the in-cylinder pressure and the calculated value of the cylinder head vibration displacement according to the embodiment of the present invention; Figure 12 Schematic diagram of identifying the wear state of the friction pair by the characteristics of the lubricating oil abrasive particles according to the embodiment of the present invention. Detailed implementation manners

[0021] The present invention will be described in detail below with reference to the drawings and in conjunction with embodiments.

[0022] As Figures 1 to 5 shown, an on-line wear detection device for a reinforced diesel engine friction pair mainly consists of a wear calculation terminal, an NI-PXIe8115 collector, a sampling detection circulation oil circuit, a cylinder pressure sensor, a rotational speed sensor, a vibration sensor, an acoustic emission sensor, a 6-in-1 lubricating oil physical and chemical sensor, an abrasive particle sensor, an abrasive particle visualization sensor, and a CAN / USB / RS485 communication interface. Among them, the cylinder pressure sensor and the vibration sensor are installed on the diesel engine, and the output electrical connection interface is connected to the AI interface of the PXIe8115 collector through a charge amplifier; the rotational speed sensor and the acoustic emission sensor are installed on the diesel engine, and the electrical connection interface is directly connected to the AI interface of the PXIe8115 collector; the 6-in-1 sensor and the abrasive particle sensor are installed in the sampling detection circulation oil circuit, and the data transmission interface is connected to the PCIe8115 collector through an RS485 MODBUS RTU communication interface; the abrasive particle visualization sensor is installed on the sampling detection circulation oil circuit, and the data transmission interface is connected to the PXIe8115 collector through USB; the thermal sensor is installed on the diesel engine or the dynamometer load, and is connected to the PXIe8115 collector through the CAN bus by the test bench acquisition terminal; a part of the circulating lubricating oil during the operation of the diesel engine is extracted through the sampling detection circulation oil circuit and sent to the detection channels of the 6-in-1 sensor, the abrasive particle counting sensor, and the abrasive particle visualization sensor, and is also sent to the off-line sampling and sedimentation filtration channels. The specific connection structure diagram is shown in Figure 1 shown.

[0023] In a preferred embodiment of the present invention, the detection device also integrates vibration, acoustic emission, cylinder pressure, and instantaneous rotational speed data, and constructs calculation functions for vibration acceleration, vibration velocity, vibration displacement, acoustic emission ring, and cylinder friction force in the time domain, frequency domain, and angular domain, forming a synchronous detection method for comprehensive multi-parameter factors of lubricating oil and vibration, acoustic emission, cylinder pressure, and instantaneous rotational speed, with real-time detection that can completely follow the operation process of the diesel engine. The followability of the parameters is within 1 s, meeting the requirements for alarm detection and fault problem location and classification in the rapid failure process of the high-reinforcement diesel engine friction pair.

[0024] In a preferred embodiment of the present invention, the detection device further has an online index calculation and addition function. It collects the Python secondary development environment associated with the running program, and can load the wear post-processing algorithm developed by Python into the RT index management environment of the online wear detection device to run synchronously with the acquisition process and calculate the wear-related indexes.

[0025] In a preferred embodiment of the present invention, the lubricating oil contains rich wear information of friction pairs. Different abrasive particle features in terms of morphology and size correspond to different wear parts and wear degrees. Detecting the abrasive particle information in the lubricating oil through abrasive particle technology sensors, 6-in-1 sensors, and abrasive particle visualization sensors requires reliable detection conditions to ensure a constant detection environment for the detection sensors and prevent the occurrence of outlier detection data. To meet the working stability requirements of the 6-in-1 sensor, abrasive particle counting sensor, and abrasive particle visualization sensor, a sampling detection loop oil circuit is set up. The sampling detection loop oil circuit controls the temperature and flow rate of the sampled lubricating oil and discharges the bubbles in the sampling channel of the lubricating oil. The schematic diagram of the sampling detection loop oil circuit is as follows Figure 2 As shown, the designed sampling temperature range is 60°C to 70°C, the sampling flow rate is constant at 1000 mL / min, and the automatic defoaming rate is 98%. The loop oil circuit mainly consists of a non-destructive suction oil pump, a circulation oil pump, a cooling heat exchanger, a heating heat exchanger, a buffer tank, a three-way valve, a defoamer, valves, etc.

[0026] Specifically, the lubricating oil enters the sampling detection loop oil circuit along the sampling inlet, enters the 1L buffer tank through the suction oil pump, stabilizes the oil pressure and exhausts the air in the buffer tank, and then reaches the temperature control link. The cooling and heating heat exchangers are used to control the temperature of the oil. The cooling heat exchanger uses air as the refrigerant, and the heating heat exchanger uses water as the heat medium. After stable temperature control, the oil reaches the bubble detector for defoaming treatment, and then is respectively distributed to the 6-channel inlet valve through the measurement on-off valve. After the flow rate is adjusted by the static balance valve, the lubricating oil reaches the abrasive particle visualization sensor, the abrasive particle counting sensor, the 6-in-1 parameter sensor, the lubricating oil sampling channel, the 20μm abrasive particle deposition filter holder, and the 40μm abrasive particle deposition filter holder, which are respectively used for physical and chemical detection such as the moisture content, pollution degree, viscosity, and density of the lubricating oil, for ferromagnetic and non-ferromagnetic abrasive particle counting detection, and for abrasive particle visualization parameter detection of the abrasive particle chain concentration distribution and large abrasive particle morphology. The lubricating oil also reaches the flow control valve and the system circulation preheating valve through the bubble detector. The flow control valve is used to balance the change in the sampling circulation volume caused by the pressure and flow rate changes in the return oil pipeline under different operating conditions of the diesel engine, so that the lubricating oil flow parameter limit values of the measurement branches adjusted by the 6 static balance valves do not shift. The system circulation preheating valve is used for the preheating process after the equipment is started, and transfers the sampled lubricating oil medium through the cooling and heating unit to components such as pipelines, valves, and bubble detectors in the loop oil circuit.

[0027] In a preferred embodiment of the present invention, the bubble detector adopts a reticulated filter structure. Meanwhile, by using the 0.4 MPa working environment established by the circulating oil pump, it can remove bubbles in a timely manner when the oil passes through, and make the bubbles automatically run above the bubble detector, and then realize automatic exhaust through a highly sensitive bubble detection switch. During the initial preheating of the system, the measurement on-off valve is closed and the system preheating valve is opened. A circulation loop is formed by the sampling inlet valve, the oil suction pump, the lubricating oil buffer tank, the circulation pump, the air-cooled radiator, the heat exchanger, the bubble detector, the system preheating valve, and the sampling outlet valve. The lubricating oil medium conducts the calorific value in the heat exchanger and the air-cooled radiator to each component in the circulation loop.

[0028] In a preferred embodiment of the present invention, oil distribution channels such as offline sampling and abrasive particle deposition are also supplemented to meet the requirements of off-line optical ferrography and energy spectrum detection of lubricating oil.

[0029] According to the requirements of each integrated sensor or device, the total flow range of the sampling oil circuit is set to 5 - 25 L / min, and the independent input oil sample distributed to each oil circuit is 1 L / min. There is actually a 4-fold sampling reserve, which can be used as an interface for on-line continuous sampling. The features are as follows: 1. The lubricating oil sampling end is divided into 6 paths in total, including 1 path for abrasive particle visualization, 1 path for abrasive particle counting, and 1 path for 6-in-1 physical and chemical detection. 2 paths are prepared for abrasive particle deposition (>20μm, >40μm), and 1 path for sampling as bench retention or analysis; 2. The lubricating oil inlet end is arranged at the sampling port position of the diesel engine return pipe, and the outlet end is arranged on the diesel engine return pipe and more than 1 m away from the sampling port; 3. The oil pump is a piston pump, which will not cause secondary damage to the abrasive particles so as not to affect the test results; 4. To facilitate the maintenance and cleaning of the connections of each path, maintenance valves are set on each branch; 5. Considering the flow field stability of each branch, a static balance valve is set to ensure a constant flow rate in each sampling branch.

[0030] The device detects the physical and chemical indexes, wear severity trend and microscopic morphology of abrasive particles of the lubricating oil through the sampling detection circulation oil circuit. The physical and chemical parameters of the lubricating oil include dynamic viscosity, temperature, density, dielectric constant, micro water, and water activity; there are 6 grades of abrasive particle size parameters, including ≤10μm, 10 - 20μm, 20 - 40μm, 40 - 80μm, 80 - 125μm, ≥125μm; the visible abrasive particle parameters can realize the classification of cutting, sliding, fatigue and non-metallic abrasive particles. Therefore, a lubricating oil six-in-one sensor based on piezoelectric resonance, an abrasive particle sensor based on electromagnetic principle, and a visible graphic sensor based on pattern recognition are selected for the method.

[0031] Specifically, the detection parameters of the 6-in-1 sensor are all related to the vibration generated by the flowing lubricating oil. It can directly measure the viscosity, density, dielectric constant, temperature, water activity, and water content of the lubricating oil, and perform the conversion of contamination degree, dynamic viscosity, and kinematic viscosity based on the physical relationship between the parameters. This conversion process needs to build a conversion model in the software to achieve. At the same time, while meeting the monitoring of abnormal working states of components, it can also be used as an oil change indication detection for lubricating oil products, reducing the consumption of the verification process.

[0032] Most of the failures of friction pairs are caused by severe wear. Monitoring the wear particles in the lubricating oil path can truly reflect the wear condition of the equipment. The traditional ferrographic analysis equipment used to evaluate the wear of key friction pairs requires off-line sampling and long-duration chemical analysis, with slow tracking timeliness and lagged detection results. According to its magnetic circuit saturation principle, the wear particle sensor designs the detection of wear particles under different magnetic fluxes, and can be customized with different wear particle range classifications according to needs, and can be used to distinguish the abnormal wear characteristics of working components under non-steady-state working conditions.

[0033] The range of wear particles precipitated from diesel engine lubricating oil is 0 - 800 μm. The existing magnetoelectric on-line wear particle detection technology can only distinguish wear particle information above 40 μm, and seriously underestimates the fatigue wear particles. Therefore, by taking macro pictures of wear particles visually and performing wear particle detection by image method, a visual wear particle sensor is formed to supplement the problem of insufficient identification of wear particles below 40 μm. The visual wear particle sensor is based on high-speed micro-imaging, and can distinguish the characteristics of particles by identifying the color of wear particles and the cross-section of wear particles, forming the ability of visual wear particle detection.

[0034] In a preferred embodiment of the present invention, in order to avoid the situation that the detection of lubricating oil wear particles fails to recognize the signs of abnormal wear states in a timely manner and cannot give a shutdown indication quickly. This device integrates indirect characterization abnormal wear signals such as vibration, acoustic emission, cylinder pressure, and instantaneous speed through the AI interface of PXIe8115, and constructs physical quantity decoding programs and time-domain, frequency-domain, and angle-domain conversion functions for vibration acceleration, vibration velocity, vibration displacement, acoustic emission ring count, and cylinder friction force in the PXIe8115 host for use by the wear calculation terminal.

[0035] Based on the real-time detection requirements of abnormal wear faults in high-strengthened diesel engines, in view of the false negatives, false positives of current in-use online single parameters, and the fault problems that need to be supplemented by off-line means for identification and data analysis to determine, this device uses comprehensive detection parameters such as force, sound, vibration, and abrasive particles related to the sliding components of the diesel engine cylinder, the rolling components of the crankshaft rotor system, and the sliding components of the transmission system to carry out synchronous real-time calculation of wear parameters, correlate with the thermal engineering data of the diesel engine working process, construct multi-source abnormal wear fault discrimination indicators and detection logics. At the same time, to ensure that the online wear detection trend has high stability and consistency, an online lubrication partial flow standard detection condition is constructed to control the outlier rate of abrasive particle and oil product detection data during the stable operation process, and prevent false alarm problems from occurring.

[0036] Aiming at the characteristics of high-strengthened diesel engines, such as large unit load of friction pairs, low selection of component structure safety factors, and fast time variation from abnormal wear to rapid functional failure, and the current lack of effective rapid detection means during the accompanying operation process, making it difficult to detect abnormal wear and inaccurate in judging the performance degradation trend, and prone to serious faults during the operation process. The present invention proposes an online wear detection device and a wear detection method for the friction pairs of high-strengthened diesel engines. Using lubricating oil density, viscosity, water content, metal abrasive particle concentration, pollution degree, abrasive particle morphology, friction work, surface vibration, acoustic emission ringing, etc. as wear detection parameters, an online wear detection device with synchronous acquisition function is formed by combining the data streams collected by each parameter to real-time monitor the characteristic parameters related to wear during the operation of the diesel engine, interact with the thermal engineering working conditions data during the operation of the diesel engine, and give an alarm of abnormal deviation and a shutdown indication of the wear of the friction pair in a timely manner to ensure the safe operation of the high-strengthened diesel engine. The purpose of the present invention is to use wear identification parameters to real-time monitor the wear process of high-strengthened diesel engines, jointly divide the alarm limit values according to the operating conditions of the diesel engine, refine the detection of the abnormal wear process, and give a fast-response shutdown indication to avoid economic losses caused by serious faults of the diesel engine.

[0037] An online wear detection method for the friction pairs of high-strengthened diesel engines, implemented based on the online wear detection device for the friction pairs of high-strengthened diesel engines, includes Figure 3 the shown detection system structure. The PXIe8115 host includes a physical quantity decoding program, an external driver program, a time / frequency / angle domain conversion program, and a data buffer pool. The wear calculation terminal includes a protocol configuration layer, a parameter configuration layer, a communication interaction layer, an index real-time calculation layer, a historical data pool, an alarm monitoring layer, and a trend visualization layer.

[0038] Specifically, the high and low speed sensors, oil circuit control, visualization sensors, and bench thermal parameters all interact with the RT (Real-Time) system in the PXIe8115. The PXIe8115 host determines the acquisition and decoding of the physical quantities of the sensor power such as abrasive particle counting, visualized abrasive particles, 6-in-1 sensors, vibration, acoustic emission, and cylinder pressure according to the instructions of the wear calculation terminal protocol configuration layer and parameter configuration layer, forms detection data with physical significance, and forms time-domain data blocks, frequency-domain data blocks, and angular domain cyclic blocks according to the instructions of the parameter configuration layer, and determines the data buffer space. At the same time, after restarting the machine, the engineering parameters of the parameter configuration layer and protocol configuration layer are cross-checked to ensure that the PXIe8115 provides physical data consistent with that obtained by the wear calculation terminal. At the same time, it also drives the oil circuit control according to the cyclic oil circuit working conditions issued by the wear calculation terminal to make the lubricating oil detection sensor work stably.

[0039] In a preferred embodiment of the present invention, after the sensor passes through the RT system of the PXIe8115 host, the diesel engine working process data becomes time history data, cyclic history data, and frequency data, and provides fixed call variables through the communication interaction layer, which is convenient for the calculation and call of wear detection indicators. The communication interaction layer includes time series variables, synchronization tags, cyclic sequence variables, frequency domain sequence variables, images, and pre-calculated variable management, and has an index real-time calculation layer to clean the collected data, preprocess the data, calculate the data indicators, enter all the data into the data pool management, and perform alarm identification during the data entry process. The alarm trigger process uses a strategy program, including continuous, step, and multiple crossings, and can implement second-order and third-order alarms.

[0040] In a preferred embodiment of the present invention, to meet the increase of wear detection indicators and implement calculation functions, the index real-time calculation layer is compiled using the python open source environment and uses the C# joint call method. There is no need to perform additional processing and compilation on the software version formed based on the python platform, so that the subsequent development program process is carried out in python, and the on-site upper computer is only a loader to manage the program codes under different versions. At the same time, a re-calculation function is developed to enable different loading programs to directly interact with historical data to complete the calculation of indicators and meet the needs of historical analysis.

[0041] In a preferred embodiment of the present invention, the bench thermal parameters are transmitted in real time through CAN communication: including speed, torque, lubricating oil pressure, lubricating oil temperature, etc. Among them, the speed and torque are measured by the dynamometer load Hall sensor and the tension and pressure sensor, and the lubricating oil pressure and temperature are measured by the bench test pressure sensor and the temperature sensor. They are uniformly sent through the RAW-CAN interface of the bench data acquisition system industrial computer and enter the PXIe8115 host cache pool. After data synchronization, pre-calculation and other processing, they interact with the wear calculation terminal.

[0042] In a preferred embodiment of the present invention, the index real-time calculation layer in the wear calculation terminal constructs the following basic wear correlation indexes: 1. Collect vibration velocity signals, calculate vibration displacement and vibration acceleration through integration and differentiation. Since the characterization effect of the instantaneous amplitude in the time domain on wear is not ideal, in order to reduce the influence of random factors, statistical and waveform features are extracted from the time-domain vibration signals to describe the time-domain waveform characteristics of the vibration signals. The main calculated characteristic parameters include: maximum value, minimum value, mean value, peak-to-peak value, average value of absolute values, variance, standard deviation, kurtosis, skewness, root mean square value, waveform factor, peak factor, pulse factor, and margin factor. To further reduce the influence of random factors, a frequency-domain analysis method is supplemented. The time-domain waveform diagram is converted into a frequency spectrum diagram by using the fast Fourier transform (FFT). The main characteristic parameters include: center frequency, average frequency, root mean square frequency, and frequency standard deviation. Other frequency-domain analysis methods include envelope spectrum analysis, power spectrum analysis, Hilbert-Huang transform, wavelet transform, etc. The wear states of various components of the diesel engine can be effectively evaluated through the time-domain and frequency-domain characteristics of vibration, and at the same time, sensitive detection of early abnormal wear signals can be carried out.

[0043] Table 1 Correspondence between vibration characteristic parameters and faults .

[0044] 2. Collect instantaneous rotational speed signals. The main time-domain characteristic parameters calculated are: rotational speed rise value, which represents the difference between the peak value in the fluctuation caused by gas pressure and the previous trough value. The cylinder with an obvious decrease is the faulty cylinder. Perform FFT transformation on the instantaneous rotational speed of the diesel engine to obtain the frequency spectrum diagram of the instantaneous rotational speed of the diesel engine. The main frequency-domain characteristic parameter is: fundamental frequency energy amplitude / firing frequency amplitude. According to this characteristic parameter, a threshold is set, and it is compared whether it exceeds the threshold. If it exceeds the threshold, it can be judged that the work of a certain cylinder of the diesel engine is uneven at this time.

[0045] 3. Collect acoustic emission signals. The main time-domain characteristic parameter calculated is the acoustic emission ring count, which refers to the number of oscillations when the voltage of the acoustic emission signal exceeds the threshold voltage. As the wear degree of the detected friction pair increases, its average ring count also continuously rises. The main angle-domain characteristic parameters are acoustic emission amplitude and phase. Through angular domain analysis, the changes in vibration, noise, and other physical quantities of the engine at different working angles can be effectively identified, helping to diagnose faults such as uneven combustion and abnormal cylinder pressure.

[0046] 4. Collect the cylinder pressure signal. The main time-domain characteristic parameters calculated are: maximum value, minimum value, and peak-to-peak value. To further characterize the change of cylinder friction, an angular domain calculation method is supplemented. Combining with the rotational speed signal, a combustion analysis calculation module is constructed. The angular domain characteristic parameters (based on the P-φ indicator diagram and P-V indicator diagram) mainly include: heat release rate, pressure change rate, indicated work, mean indicated pressure, effective work, mean effective pressure, combustion duration angle, combustion start angle, piston speed, etc. The cylinder friction increases with the increase of cylinder pressure, piston speed, and the viscosity of the lubricating oil. The viscosity of the lubricating oil is measured by a 6-in-1 sensor.

[0047] Table 2 Correspondence between Cylinder Pressure Characteristic Parameters and Faults 。

[0048] In a preferred embodiment of the present invention, the characteristics of a single data source often have limitations and are difficult to comprehensively reflect the complex behavior state of the diesel engine. Therefore, the index real-time calculation layer in the wear calculation terminal includes multi-dimensional feature fusion real-time calculation indexes. The basic calculation indexes formed include statistical parameters (such as mean value, mean square value, standard deviation, etc.) of online synchronous processing integration parameters, state characteristics (such as spectrum characteristics, envelope spectrum characteristics, power spectrum characteristics, etc.) corresponding to the operating information of the diesel engine as data sets. Using a feature fusion method driven by deep learning, a feature fusion index under an artificial intelligence algorithm is constructed, and the trained artificial intelligence algorithm model is loaded in the real-time calculation layer to calculate the fusion index and quickly classify the state characteristics online.

[0049] In a preferred embodiment of the present invention, the following Figure 4 A multi-dimensional feature fusion model is provided. By self-learning the non-linear relationship between different features from the data set and adaptively assigning weights to each feature, it provides calculation methods for the fusion of lubricating oil abrasive indexes such as abrasive concentration, abrasive count, water content, viscosity, density, etc. and the statistical feature fusion indexes of vibration, acoustic emission, and friction force collected at high speed in abnormal wear events such as bearing shell wear, connecting rod bearing wear, cylinder liner wear, piston ring wear, etc., thereby further improving the classification accuracy of abnormal wear of the diesel engine.

[0050] Specifically, for a multi-dimensional feature fusion model, the subsets of the collected data feature set are first processed separately by a convolutional neural network to achieve deep fusion of features extracted from a single data source for abnormal wear such as bearing shell wear, connecting rod bearing wear, cylinder liner wear, and piston ring wear. Then, the central feature fusion layer is used to achieve feature fusion of multiple data source feature sets. The central feature fusion layer adopts a series of fusion points for multi-scale fusion. Taking the first fusion point as an example, the features extracted from each branch network are fused and reconstructed at this fusion point, and then returned to each branch network. Further, the input features and the reconstructed features are combined and input into the next convolutional layer. For each branch network, the features are reconstructed through fusion operations to obtain the representative information of multiple feature sets. In this way, sufficient information fusion between the features extracted from multiple feature sets can be ensured. Finally, the deep features after fusion under each branch network are processed through global average pooling and a fully connected layer, and then added together to obtain the final deep fusion features.

[0051] In a preferred embodiment of the present invention, the alarm monitoring layer divides the operating conditions of the diesel engine into three-order operating conditions according to rotational speed, torque, and lubricating oil temperature, according to the following division rules: the rotational speed division gradient is not less than 100 r / min, the torque division gradient is not less than 500 N·m, and the temperature division is 85°C to 105°C for the working temperature and other non-working temperatures, forming early warning MAPs of vibration acceleration, vibration velocity, vibration displacement, lubricating oil viscosity, lubricating oil water content, abrasive concentration, abrasive particle size scale, cylinder friction force, transmission gear wear ring, and main shaft wear ring under three classifications of "rotational speed - torque", "rotational speed - lubricating oil temperature", and "torque - lubricating oil temperature", so as to indicate abnormal wear during the operation process of the enhanced diesel engine.

[0052] In a preferred embodiment of the present invention, the alarm monitoring layer also proposes the discrimination conditions for the operating conditions. Figure 5The identification "X1.X2.X3" shown in the example, where X1 is the identification for the monitoring sub - range of the rotational speed operating condition, X2 is the identification for the monitoring sub - range of the torque operating condition, and X3 is the identification for the monitoring sub - range of the lubricating oil temperature operating condition. The upper and lower limit values of the operating condition of the diesel engine are determined by three parameters: rotational speed, torque, and lubricating oil temperature. While dividing the operating conditions, at the real - time index calculation layer, through time - domain operation, frequency - domain operation, and angle - domain operation, the calculation of force, sound, and vibration characteristic indicators is completed; then, by deeply self - learning the relationship between different features of the on - line detection indicators and abrasive particle indicators, a feature fusion model is constructed to obtain the final deep - level fusion features; finally, at the alarm monitoring layer, the user can design vibration intensity alarms, order alarms, FFT alarms, etc. based on the self - learning module in the python environment, including continuous, step - by - step, and multiple crossings, and can achieve second - order and third - order alarms. It can also display the regular curve in ways such as 1D / 2D / 3D, realizing a more comprehensive and accurate characterization of the wear state of the diesel engine during operation from multiple information sources. Design the early warning MAPs of vibration acceleration, vibration velocity, vibration displacement, lubricating oil viscosity, lubricating oil water content, abrasive particle concentration, abrasive particle size scale, cylinder friction force, transmission gear wear ring, and main shaft wear ring to indicate abnormal wear during the operation of the enhanced diesel engine.

[0053] In a preferred embodiment of the present invention, an on - line wear detection method for the friction pair of an enhanced diesel engine further includes the specific positioning of components after warning. Vibration acceleration, vibration velocity, vibration displacement, cylinder friction force, transmission gear wear ring, and main shaft wear ring are used as warning symptom detection parameters, and vibration velocity warning is used as the basic warning. Specifically, when the vibration velocity warning does not appear, other warnings are invalid warnings. The vibration acceleration gear envelope spectrum feature, transmission gear wear ring, and precipitated abrasive particles are used as the wear location detection and classification of the transmission system. The acceleration main shaft excitation spectrum, cylinder friction torque, abrasive particle concentration, main shaft wear ring, diesel fuel consumption, and lubricating oil pressure are used as the wear location detection and classification of the crankshaft - rotor system. Diesel fuel consumption, lubricating oil pressure, dielectric constant, viscosity, and density are used as the wear location detection and classification of the fuel supply system. Density, water content, and cylinder friction force are used as the leakage detection and classification of the cylinder cooling system. Cylinder friction torque, vibration displacement, vibration acceleration cylinder excitation spectrum, and precipitated abrasive particles are used as the wear location detection and classification of the piston motion system. According to the above classifications, the information after the fault warning is pushed to the specific abnormal fault location.

[0054] In a preferred embodiment of the present invention, after the alarm monitoring layer detects a fault alarm, it gives the user an action instruction and recommends the next action according to the classified wear degree. Specifically, when all the parameters of the classification index are alarmed, it is indicated as a serious warning, and an emergency stop is required; when 50% of the classified warning parameters are abnormally generated warnings, it can still continue to work but be vigilant, and the operation process is controlled according to the warning increment number; when 75% of the parameters show warnings, it is a functional damage warning, and it is recommended to run again after repair.

[0055] Key points of the present invention: An on-line wear detection device for enhancing the friction pairs of a diesel engine is proposed, a stable standard detection environment for lubricating oil wear particle means is constructed, and the partial flow sampling theory is adopted. A 6-in-1 sensor, a wear particle sensor, a visible wear particle sensor, and a deposition sensor are integrated in the standard environment to achieve constant sampling flow rate, constant sampling temperature, and constant detection time under different operating conditions of the diesel engine, and to obtain stable lubricating oil viscosity, density, dielectric constant, water content, wear particle concentration, deposited wear particles, and wear particle image parameter information, which is used to provide characteristic data related to monitoring the wear of the lubricating oil, and to give warnings for the condition monitoring of the fuel supply system, the cylinder cooling system, the gear transmission system, and the crankshaft rotor system; An integrated acquisition method for on-line wear detection of enhancing the friction pairs of a diesel engine is proposed. A 6-in-1 sensor, a wear particle sensor, a visible wear particle sensor, a deposition sensor, a vibration sensor, an acoustic emission sensor, a cylinder pressure sensor, and an instantaneous speed sensor are integrated, and calculation functions of vibration acceleration, vibration velocity, vibration displacement, acoustic emission ring, and cylinder friction force in the time domain, frequency domain, and angular domain are constructed, forming a synchronous detection of comprehensive multi-parameter factors of lubricating oil, vibration, acoustic emission, cylinder pressure, and instantaneous speed. It has real-time detection that completely follows the operation process of the diesel engine, and the followability of the parameters is within 1 s, meeting the alarm detection and fault problem location and classification of the rapid failure process of the friction pairs of a highly enhanced diesel engine.

[0056] A method for calculating and adding on-line wear detection indexes of enhancing the friction pairs of a diesel engine is proposed. A Python secondary development environment associated with the operation program is collected, and the wear post-processing algorithm developed by Python can be loaded into the RT index management environment and run synchronously with the acquisition process to continuously monitor the indexes related to wear.

[0057] A wear detection method is proposed. Based on the detection parameters of the on-line wear detection device for enhancing the friction pairs of a diesel engine, combined with the speed, torque, diesel fuel consumption, lubricating oil pressure, and lubricating oil temperature communicated during the operation of the diesel engine test bench, the operating conditions of the diesel engine are segmented into three orders according to speed, torque, and lubricating oil temperature. The speed segmentation gradient is not less than 100 r / min, the torque segmentation gradient is not less than 500 N / m, and the temperature segmentation is 85 °C to 105 °C working temperature and other non-working temperatures, forming early warning MAPs of vibration acceleration, vibration velocity, vibration displacement, lubricating oil viscosity, lubricating oil water content, wear particle concentration, wear particle size scale, cylinder friction force, transmission gear wear ring, and main shaft wear ring under three classifications of speed-torque, speed-lubricating oil temperature, and torque-lubricating oil pressure, and warning of abnormal wear during the operation process of the highly enhanced diesel engine.

[0058] An online wear warning-based specific positioning method for abnormal components is proposed. Vibration acceleration, vibration velocity, vibration displacement, cylinder friction force, wear ring of transmission gears, and wear ring of the main shaft are used as warning symptom detection parameters. Vibration velocity warning is used as the basic warning. When the vibration velocity warning does not occur, other warnings are invalid warnings. The vibration acceleration gear envelope spectrum characteristics, wear ring of transmission gears, and precipitated abrasive particles are used as the wear positioning detection and classification of the transmission system. The acceleration main shaft excitation spectrum, cylinder friction torque, abrasive particle concentration, wear ring of the main shaft, diesel fuel consumption, and lubricating oil pressure are used as the wear positioning detection and classification of the crankshaft rotor system. Diesel fuel consumption, lubricating oil pressure, dielectric constant, viscosity, and density are used as the wear positioning detection and classification of the fuel supply system. Density, water content, and cylinder friction torque are used as the detection and classification of water leakage in the cylinder head and cylinder liner waterway. Cylinder friction torque, vibration displacement, vibration acceleration cylinder excitation spectrum, wear abrasive particles, and abrasive particle morphology are used as the wear positioning detection and classification of the piston. According to the above classifications, the information after the fault warning is pushed to the specific abnormal fault location.

[0059] A wear degree determination method under warning classification is proposed. The wear degree is divided into three levels. When all the parameters in the classification are alarmed, it is indicated as a third-level damage, corresponding to a serious warning that requires an emergency stop. When 50% of the warning parameters in the classification are abnormal initiation warnings, it is indicated as a first-level damage, and it can still continue to work but needs to remain vigilant, and the operation process is controlled according to the warning increment number. When 75% of the parameters show warnings, it is a functional damage warning, indicated as a second-level damage, and it is recommended to run again after repair.

[0060] The protected point of the present invention is to strengthen the online wear detection device for diesel engine friction pairs, as well as the wear detection methods of trend detection, limit warning, abnormal positioning, and wear classification under the corresponding device.

[0061] Advantages of the present invention: The load of the friction pair of the strengthened diesel engine is large, the process from symptom to failure is extremely short, and serious fault events are difficult to control. After the implementation of this device, it can quickly warn of abnormal states and give corresponding action instructions to users, providing a reliable identification means for the research and development and operation safety of the strengthened diesel engine.

[0062] To reduce the false alarm rate and misreport rate of the online wear detection device, this device adopts the lubricating oil sampling principle and uses the sampling circulation oil circuit to keep the working conditions of the lubricating oil abrasive particle online sensor constant, reducing the outlier rate of the collected data.

[0063] To synchronously strengthen the operating state of a diesel engine and improve the sensitivity of detecting abnormal wear, this device combines the rotational speed, torque, diesel fuel consumption, lubricating oil pressure, and lubricating oil temperature during communication in the operation of a diesel engine test bench. It divides the operating conditions of the diesel engine into three-order operating conditions according to rotational speed, torque, and lubricating oil temperature, designs an early warning MAP, warns of abnormal wear during the operation of the strengthened diesel engine, and proposes specific positioning methods for abnormal components after online wear warning and methods for determining the wear degree under warning classification, so that users can take corresponding actions.

[0064] To minimize the loss of abnormal states during the R & D verification and operation process of a strengthened diesel engine, acoustic emission, vibration, cylinder friction, and instantaneous rotational speed are used to collect data at high speed as supplementary monitoring tools, forming a synchronous detection of wear by comprehensively collecting multi-parameter factors. Multi-source information characteristic indicators that can be calculated online and online wear detection indicators are used to quickly classify abnormal states.

[0065] Embodiment 1 1. Identifying impact wear faults by vibration frequency domain envelope spectrum: Envelope analysis can extract the high-frequency components of impact wear and convert them into lower-frequency envelope spectra, which helps detect intermittent wear faults. After measuring the vibration signal of the bearing shell and taking the difference, as shown in Figure 6 (a), the abscissa t* and ordinate A* in the figure represent dimensionless time and vibration amplitude. Figure 6 (b) is its standardized squared envelope signal. To filter the matrix vibration signal and background noise signal, a zero-frequency resonator is applied to the squared envelope signal for filtering, and the filtered output is shown in Figure 6 (c), and the growth amplitude is very large. The residual signal is shown in Figure 6(d), and at this time, the signal characteristics of the fault vibration are already relatively obvious.

[0066] 2. Identifying uneven single-cylinder work by instantaneous rotational speed in the time domain: For an n-cylinder diesel engine, when the diesel engine is in normal operating conditions, the instantaneous rotational speed will show n periodic fluctuations within one working cycle. Because the ignition of each cylinder is uniform, the change trend within each cycle is basically the same, and the rotational speed increase caused by gas pressure in each cylinder is equal, as shown in Figure 7 ; when uneven work occurs in a certain cylinder of the diesel engine, that is, in a fault condition, at this time, the rotational speed increase caused by gas pressure in each cylinder is no longer equal, and the rotational speed increase of the fault cylinder is significantly less than that of the normal cylinder, as shown in Figure 7 . Figure 8 This is the instantaneous rotational speed fluctuation curve of the first cylinder misfiring of the diesel engine.

[0067] 3. Identifying the wear process during the operation of a diesel engine by acoustic emission time domain average ring count: Figure 9 The average ring count of the acoustic emission signal changes with the wear process. It can be clearly seen that as the wear degree increases, the average ring count is also continuously rising.

[0068] 4. Identifying the wear process during the operation of a diesel engine by the root mean square energy of acoustic emission: As can be seen from Figure 10 , the root mean square value of acoustic emission is proportional to the degree of wear. As the wear increases, the RMS energy will show an increasing trend. The main reason for using the RMS value to analyze the acoustic emission signal is that during the entire working cycle of the engine, affected by factors such as valve closing, combustion work, and fuel injection, the acoustic emission signal changes violently, which is reflected in a large amplitude change. If single amplitude analysis or counting analysis is used, the accuracy of the data is relatively low. The RMS value of acoustic emission is the mean value of the acoustic emission signal within a certain period of time, which is suitable for the activity evaluation of continuous acoustic emission signals and can well reflect the lubrication condition during the entire working cycle process.

[0069] 5. Identifying the leakage fault of the cylinder cooling system by the cylinder pressure angle domain curve and the cylinder head vibration displacement: The measured in-cylinder pressure signal and the cylinder head vibration displacement response are shown in Figure 11 . The two are very similar in the change trend, especially before the maximum combustion pressure; after the maximum combustion pressure, the fluctuation of the displacement response begins to become violent, but the trend is still relatively similar. The cylinder cooling system fault can be judged by combining the cylinder pressure angle domain curve and the cylinder head vibration displacement curve.

[0070] 6. Identifying the wear state of the friction pair by the characteristics of lubricating oil abrasive particles: Taking the assessment test of a certain diesel engine as an example, comprehensively judge the wear state of the friction pair through 6-in-1 physical and chemical detection, abrasive particle counting, and visual ferrography. Specifically, when the diesel engine is in the early running-in state, the number of abrasive particles will increase sharply and fluctuate greatly. When it is in the middle of the assessment period, the number of abrasive particles will tend to be stable. When no abnormal phenomenon occurs, it will also remain stable in the later period. The change trend of the number of abrasive particles is shown in Figure 12 (a); The IPCA value of the abrasive particle ferrography is relatively large during the early running-in period, and at the initial stage of each diesel engine start, due to the deposition of abrasive particles and the agitation of abrasive particles during startup, there will be a slight fluctuation of abrasive particles. In other periods, when no abnormal situation occurs, the IPCA value is in a stable state and there will be no continuous and relatively violent fluctuation, as shown in Figure 12 (b); At the same time, combining Figure 12 (c) physical and chemical detection parameters, Figure 12 (d) abrasive particle morphology, comprehensively judge and draw the following conclusion: During this assessment period, the characteristics of abrasive particles all meet the general rules and no abnormal wear is found.

[0071] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A device for strengthening online wear detection of friction pairs of diesel engines, characterized in that: It includes a wear calculation terminal, an NI-PXIe8115 collector, a sampling detection circulating oil circuit, a cylinder pressure sensor, a speed sensor, a vibration sensor, an acoustic emission sensor, a 6-in-1 lubricating oil physical and chemical sensor, a wear particle sensor, a wear particle visualization sensor, and a CAN / USB / RS485 communication interface. The cylinder pressure sensor and the vibration sensor are installed on the diesel engine, and the output electrical interface is connected to the AI ​​interface of the PXIe8115 collector via a charge amplifier; the speed sensor and the acoustic emission sensor are installed on the diesel engine, and the electrical interface is directly connected to the AI ​​interface of the PXIe8115 collector; the 6-in-1 sensor and the wear particle sensor are installed in the sampling detection circulating oil circuit, and the data transmission interface is connected to the PCIe8115 collector via the RS485 MODBUS RTU communication interface; the wear particle visualization sensor is installed in the sampling detection circulating oil circuit, and the data transmission interface is connected to the PXIe8115 collector via USB; the thermal sensor is installed on the diesel engine or the dynamometer load, and is connected to the PXIe8115 collector via the CAN bus through the test bench acquisition terminal.

2. The device for strengthening online wear detection of friction pairs of diesel engines according to claim 1 is characterized in that: The sampling and testing circulating oil circuit controls the temperature and flow rate of the sampled lubricating oil, and empties the bubbles of the lubricating oil in the sampling channel. The sampling temperature range is 60℃~70℃, the sampling flow rate is constant at 1000mL / min, and the automatic debubbling rate is 98%. The sampling and testing circulating oil circuit includes a non-destructive oil suction pump, a circulating oil pump, a cooling heat exchanger, a heating heat exchanger, a buffer box, a three-way valve and a debubbler, and a valve.

3. The device for strengthening online wear detection of friction pairs of diesel engines according to claim 1 is characterized in that: The bubble detector adopts a mesh filter structure and uses a circulating oil pump to establish a 0.4MPa working environment.

4. The device for strengthening online wear detection of friction pairs of diesel engines according to claim 1 is characterized in that: During the initial preheating of the system, the measuring on-off valve is closed and the system preheating valve is opened. A circulation loop is formed by the sampling inlet valve, oil suction pump, lubricating oil buffer tank, circulating pump, air-cooled radiator, heat exchanger, bubble detector, system preheating valve and sampling outlet valve. The lubricating oil medium transfers the heat value in the heat exchanger and air-cooled radiator to each component in the circulation loop.

5. The device for strengthening online wear detection of friction pairs of diesel engines according to claim 1, characterized in that: It also includes offline sampling oil distribution channel and abrasive deposition oil distribution channel to meet the needs of offline optical iron spectrum and energy spectrum detection of lubricating oil.

6. The device for strengthening online wear detection of friction pairs of diesel engines according to claim 1, characterized in that: The physical and chemical indicators of lubricating oil, the trend of wear intensity and the microscopic morphology of abrasive particles are detected by sampling and testing the circulating oil circuit. The physical and chemical parameters of lubricating oil include dynamic viscosity, temperature, density, dielectric constant, micro water and water activity. There are 6 levels of abrasive particle size parameters, including ≤10μm, 10-20μm, 20-40μm, 40-80μm, 80-125μm and ≥125μm. The visualized abrasive particle parameters can realize the classification of cutting, sliding, fatigue and non-metallic abrasive particles.

7. A method for strengthening online wear detection of diesel engine friction pairs, characterized by: Includes the following: Based on the detection parameters of the enhanced diesel engine friction pair online wear detection device according to any one of claims 1 to 6; Combine the speed, torque, diesel fuel consumption, lubricating oil pressure and lubricating oil temperature communicated during the operation of the diesel engine test bench, and divide the diesel engine operating conditions into three-level conditions according to speed, torque and lubricating oil temperature; Among them, the speed segmentation gradient is not less than 100r / min, the torque segmentation gradient is not less than 500N·m, and the temperature segmentation is 85℃~105℃ working temperature and other non-working temperature; A warning MAP of vibration acceleration, vibration velocity, vibration displacement, lubricating oil viscosity, lubricating oil water content, abrasive concentration, abrasive particle size, cylinder friction, transmission gear wear ringing, and main shaft wear ringing is formed under the three categories of "speed-torque", "speed-lubricating oil temperature" and "torque-lubricating oil temperature", and abnormal wear warning is given during the operation of the diesel engine.

8. The method for strengthening online wear detection of friction pairs of diesel engines according to claim 7 is characterized in that: It also includes a specific method for locating the components after the alarm. The specific locating method process is as follows: Vibration acceleration, vibration velocity, vibration displacement, cylinder friction, transmission gear wear ringing, spindle wear ringing are used as warning symptom detection parameters, and vibration velocity warning is used as basic warning; When the vibration speed warning is not presented, other warnings are invalid warnings; The vibration acceleration gear envelope spectrum characteristics, transmission gear wear ringing and precipitation abrasive particles are used as the wear location detection classification of the transmission system; The acceleration spindle excitation spectrum, cylinder friction torque, abrasive particle concentration, spindle wear ringing, diesel fuel consumption, and lubricating oil pressure are used as the wear location detection classification of the crankshaft rotor system; Diesel fuel consumption, lubricating oil pressure, dielectric constant, viscosity, and density are used as the detection classification for oil supply system wear, and density, water content, and cylinder friction are used as the detection classification for cylinder cooling system leaks; Cylinder friction torque, vibration displacement, vibration acceleration cylinder excitation spectrum, and precipitated abrasive particles are used as the wear location detection classification of the piston motion system; According to the above classification, the information after the fault alarm is pushed to the specific abnormal fault location.

9. The method for strengthening online wear detection of friction pairs of diesel engines according to claim 7, characterized in that: Also included are wear level methods under the warning category, including: When all parameters of the classification are in alarm, it indicates a serious alarm and an emergency stop is required; When 50% of the classified alarm parameters are abnormal initiation alarms, the system can continue to work but must remain alert and control the operation process according to the alarm increment number; When 75% of the parameters give an alarm, it is a functional damage alarm. It is recommended to repair it before running.

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