CN117072660A - HMCVT filter automatic replacement device and replacement method based on semi-supervised learning - Google Patents
HMCVT filter automatic replacement device and replacement method based on semi-supervised learning Download PDFInfo
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- CN117072660A CN117072660A CN202311182829.3A CN202311182829A CN117072660A CN 117072660 A CN117072660 A CN 117072660A CN 202311182829 A CN202311182829 A CN 202311182829A CN 117072660 A CN117072660 A CN 117072660A
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- replacing device
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- 238000000034 method Methods 0.000 title claims abstract description 16
- 230000005540 biological transmission Effects 0.000 claims abstract description 66
- 239000012535 impurity Substances 0.000 claims description 14
- 239000013618 particulate matter Substances 0.000 claims description 14
- 230000008859 change Effects 0.000 claims description 9
- 238000009434 installation Methods 0.000 claims description 9
- 239000002184 metal Substances 0.000 claims description 8
- 229910052751 metal Inorganic materials 0.000 claims description 8
- 239000000428 dust Substances 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 3
- 238000005461 lubrication Methods 0.000 abstract description 6
- 230000002035 prolonged effect Effects 0.000 abstract description 4
- 230000009286 beneficial effect Effects 0.000 abstract description 3
- 239000003921 oil Substances 0.000 description 73
- 238000001914 filtration Methods 0.000 description 7
- 229910000831 Steel Inorganic materials 0.000 description 4
- 238000010801 machine learning Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 239000010959 steel Substances 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 239000002245 particle Substances 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 239000002783 friction material Substances 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 238000007476 Maximum Likelihood Methods 0.000 description 1
- 239000010718 automatic transmission oil Substances 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 230000007786 learning performance Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H57/00—General details of gearing
- F16H57/04—Features relating to lubrication or cooling or heating
- F16H57/0402—Cleaning of lubricants, e.g. filters or magnets
- F16H57/0404—Lubricant filters
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H57/00—General details of gearing
- F16H57/04—Features relating to lubrication or cooling or heating
- F16H57/0405—Monitoring quality of lubricant or hydraulic fluids
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H57/00—General details of gearing
- F16H57/04—Features relating to lubrication or cooling or heating
- F16H57/0434—Features relating to lubrication or cooling or heating relating to lubrication supply, e.g. pumps ; Pressure control
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- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Quality & Reliability (AREA)
- General Details Of Gearings (AREA)
Abstract
The invention discloses an automatic HMCVT filter replacing device and method based on semi-supervised learning, comprising an automatic filter replacing device; the automatic filter replacing device is arranged between the hydraulic pump and the oil pan, the inside of the oil pan is connected with the input end of the automatic filter replacing device through an oil way pipe, and the hydraulic pump is connected with the output end of the automatic filter replacing device through the oil way pipe; the automatic filter replacing device comprises a gear; a plurality of support arms A are fixedly connected to the outer circumferential surface of the gear at equal intervals; the extending end of the supporting arm A is hinged with a supporting arm B; the extending end of the supporting arm B is fixedly connected with a transmission oil filter. According to the automatic filter replacement device, the automatic filter replacement is realized, the service time of the transmission oil can be prolonged, and the excellent quality of the transmission oil is more beneficial to working scenes such as gear shifting, gear lubrication and the like.
Description
Technical Field
The invention relates to the technical field of transmissions, in particular to an automatic HMCVT filter replacing device and method based on semi-supervised learning.
Background
Machine learning is to simulate or realize the learning behavior of human beings to acquire new knowledge and skills and continuously perfect own performances, for example, a semi-supervised learning method in machine learning is to enable a learner to automatically utilize unlabeled samples to improve learning performances without external interaction, so that a large number of unlabeled samples are easy to obtain in reality, but a large number of manpower and material resources are required to obtain the labeled samples. Semi-supervised learning is a learning method that combines supervised learning and unsupervised learning. The method utilizes a large amount of unlabeled data and simultaneously utilizes the labeled data for pattern recognition. In semi-supervised learning, one part of the dataset is used to tag the data and the other part is used to generate new data for training the model. This method can be trained without complete knowledge of the tag information of the dataset and is therefore widely used in many machine learning tasks such as image classification, speech recognition and natural language processing.
Semi-supervised learning is a machine learning method that combines the advantages of supervised learning and unsupervised learning while utilizing both signature data and generated data to improve the performance of the model. In semi-supervised learning, the dataset is divided into two parts: marked data and unmarked data. Marked data refers to data that has been marked, and unmarked data refers to data that has not been marked. These unlabeled data are typically generated by the generative model, rather than being directly acquired from the dataset. The principle of semi-supervised learning is to build a model based on similarities between samples. During the training process, the model learns the similarity between samples from the labeled data while generating new samples using unlabeled data. This approach can utilize unlabeled data to some extent while avoiding over-labeling the data set.
The use of transmission oil in HMCVT can reduce friction, reduce wear, control clutch friction and synchronizer performance. Meanwhile, the device has the functions of bearing low-speed large torque, vibrating load, radiating heat, removing pollutants at the meshing position of the teeth and the like. The transmission filter is used for filtering foreign matters, filtering friction material fibers with constant friction production of clutch friction plates, steel sheets and friction products, and filtering scraps generated by friction of metal parts such as gears, steel belts, chains and the like. In the running process of the gearbox, oil in the gearbox can be continuously dirtied, and the effect of the gearbox oil filter is to filter impurities generated in the working process of the gearbox, clean gearbox oil is supplied to each kinematic pair, the electromagnetic valve and the oil path pipe, so that the effects of lubrication, cooling, cleaning, rust prevention and friction resistance are achieved, parts are protected, the performance of the gearbox is guaranteed, and the service life of the gearbox is prolonged.
The transmission filter needs to be replaced regularly, and the following technical problems exist in the prior art: the transmission filter is arranged in the HMCVT, whether the filter needs to be replaced or not can be judged only by means of the service time or the driving mileage, a large amount of uncertainty exists, and the replacement efficiency is low. The filter has too long service time, which can cause excessive impurities (friction material fibers with constant friction production of clutch friction plates, steel sheets and friction products, and scraps generated by friction of metal parts such as filtering gears, steel belts, chains and the like) in the transmission oil, thereby affecting the friction of the clutch, the performance of the synchronizer and the function of filtering extraneous matters. How to know the impurity content in the transmission oil and make the impurity content in the transmission oil less in the service time, and the problem caused by lubrication in reducing the overlong use of the HMCVT is the current problem.
Disclosure of Invention
The present invention aims to solve the above-mentioned drawbacks and disadvantages, and this object is achieved by the following technical solutions.
The invention provides an automatic filter replacing device of an HMCVT based on semi-supervised learning, which comprises an automatic filter replacing device; the automatic filter replacing device is arranged between the hydraulic pump and the oil pan, the inside of the oil pan is connected with the input end of the automatic filter replacing device through an oil way pipe, and the hydraulic pump is connected with the output end of the automatic filter replacing device through the oil way pipe; the automatic filter replacing device comprises a gear; a plurality of support arms A are fixedly connected to the outer circumferential surface of the gear at equal intervals; the extending end of the supporting arm A is hinged with a supporting arm B; the extending end of the supporting arm B is fixedly connected with a transmission oil filter; the support arm A and the support arm B are connected with each other through an electric cylinder.
The supporting arm A is arranged along the excircle tangent plane of the gear.
Oil is arranged in the oil pan, and symmetrically arranged particulate matter sensors and capacitance sensors are respectively arranged on the inner wall surface of the oil pan.
The automatic filter replacing device is electrically connected with a motor for driving the automatic filter replacing device to move.
An automatic HMCVT filter replacing method based on semi-supervised learning, which is replaced according to the automatic HMCVT filter replacing device, comprises the following steps:
s1, acquiring and collecting data of the transmission oil containing dust, metal and other impurities with different degrees based on semi-supervised learning to obtain marked data and unmarked data;
s2: training a model according to the marked data and the unmarked data;
s3: predicting transmission oil quality using the model;
s4: when the HMCVT works, the dielectric constant and the particulate matter content in oil are detected through a particulate matter sensor and a capacitance sensor which are arranged in an oil pan;
s5: predicting whether the quality of the transmission oil reaches a filter replacement threshold value at the moment through semi-supervised learning;
s6: ending the detection if the threshold value of the filter replacement is not reached;
and S7, if the threshold value for replacing the filter is reached, the transmission control unit controls the working assembly to work, so that an electric cylinder in the automatic HMCVT filter replacing device is reset, the filter is removed, the motor drives the automatic filter replacing device to rotate, and the electric cylinder works to complete the installation of the filter.
Compared with the prior art, the invention has the beneficial effects that: compared with the traditional HMCVT which cannot sense the quality of the transmission oil and the filter, the automatic filter replacement device can realize the automatic filter replacement, so that the service time of the transmission oil can be prolonged, and the excellent quality of the transmission oil is more beneficial to working scenes such as gear shifting, gear lubrication and the like; the invention marks the data of the impurities such as dust and metal with different degrees and unmarked data based on semi-supervised learning to train out a model, predicts the quality of the transmission oil and judges whether the filter reaches the use limit. The automatic filter replacing device is more accurate than the traditional automatic filter replacing device which replaces the transmission oil and the transmission filter through the service time and the driving mileage, and provides accurate data support for the automatic filter replacing device.
Drawings
FIG. 1 is a schematic view of an automatic filter replacement apparatus according to the present invention;
FIG. 2 is a schematic view of a return structure of a support arm of an automatic filter replacement device according to the present invention;
fig. 3 is a schematic view showing the installation position of the automatic filter replacing apparatus according to the present invention.
Fig. 4 is a flow chart of the operation of the present invention.
In the figure: 1. the automatic transmission oil filter comprises a transmission oil filter 2, support arms B and 3, an electric cylinder 4, support arms A and 5, gears 6, an automatic filter replacing device 7, a particulate matter sensor 8, an oil pan 9, oil liquid 10, a capacitance sensor 11, a motor 12, an oil way pipe 13 and a hydraulic pump.
Detailed Description
The invention is described with reference to the accompanying drawings.
An automatic filter replacing device of an HMCVT based on semi-supervised learning as shown in figures 1-3 comprises an automatic filter replacing device 6; the automatic filter replacing device 6 is arranged between the hydraulic pump 13 and the oil pan 8, the installation position of the automatic filter replacing device 6 is arranged between the hydraulic pump 13 and the oil pan 8, when the transmission oil is pumped out by the hydraulic pump 13 and used for meeting working conditions, the automatic filter replacing device plays a role in filtering impurities, the inside of the oil pan 8 is connected with the input end of the automatic filter replacing device through an oil path pipe 12, and the hydraulic pump 13 is connected with the output end of the automatic filter replacing device 6 through the oil path pipe 12; the automatic filter replacing device 6 comprises a gear 5; a plurality of support arms A4 are fixedly connected to the outer circumferential surface of the gear 5 at equal intervals; the extending end of the supporting arm A4 is hinged with a supporting arm B2; the extending end of the supporting arm B2 is fixedly connected with a transmission oil filter 1; the support arm A4 and the support arm B2 are connected with each other through the arranged electric cylinder 3. The supporting arm B2 stretches and contracts through the electric cylinder 3 to realize up-and-down movement of the transmission filter 1, so that the transmission filter 1 is mounted and dismounted; the supporting arm A4 is arranged along the external circular tangential plane of the gear 5; the oil pan 8 is internally provided with oil 9, transmission oil in the HMCVT is stored in the oil pan 8, the oil is pumped out by a hydraulic pump 13 to meet the requirements of gear shifting, output, lubrication and the like, the inner wall surface of the oil pan 8 is respectively provided with a particle sensor 7 and a capacitance sensor 10 which are symmetrically arranged, and the particle sensor 7 and the capacitance sensor 10 are arranged in the oil pan and are used for detecting the quality of the transmission, namely the dielectric constant and the particle content in the oil; the automatic filter replacing device 6 is electrically connected with a motor 11 for driving the automatic filter replacing device to move.
As shown in fig. 4, a method for automatically replacing an HMCVT filter based on semi-supervised learning, according to the HMCVT filter automatic replacing apparatus as described above, includes the steps of:
s1, acquiring and collecting data of the transmission oil containing dust, metal and other impurities with different degrees based on semi-supervised learning to obtain marked data and unmarked data;
s2: training a model according to the marked data and the unmarked data;
s3: predicting transmission oil quality using the model;
s4: when the HMCVT works, the dielectric constant and the particulate matter content in oil are detected through a particulate matter sensor and a capacitance sensor which are arranged in an oil pan;
s5: predicting whether the quality of the transmission oil reaches a filter replacement threshold value at the moment through semi-supervised learning;
s6: ending the detection if the threshold value of the filter replacement is not reached;
and S7, if the threshold value for replacing the filter is reached, the transmission control unit controls the working assembly to work, so that an electric cylinder in the automatic HMCVT filter replacing device is reset, the filter is removed, the motor drives the automatic filter replacing device to rotate, and the electric cylinder works to complete the installation of the filter.
Firstly, based on semi-supervised learning, data of the transmission oil containing dust, metal and other impurities with different degrees are acquired and collected, the acquired and collected data and unlabeled data are marked to train out a model, and then the model is used for predicting the quality of the transmission oil. The marked transmission oil contains data of impurities such as dust, metal and the like with different degrees, the data are obtained by a particulate matter sensor and a capacitance sensor, the particulate matter sensor and the capacitance sensor are generally placed in an oil pan, the quality of the transmission oil is monitored in real time, and whether a filter needs to be replaced or not is judged.
The training model approach is to assume that all data (whether labeled or not) is generated by the same potential model, and to link unlabeled data to learning targets by potential model parameters, the unlabeled data being considered as parameters of model loss. The maximum likelihood estimation solution is typically performed using the EM algorithm. After the model is trained through data, the dielectric constant and the particulate matter content in the oil are detected through the particulate matter sensor 7 and the capacitance sensor 10 which are arranged in the oil pan during the operation of the HMCVT. The semi-supervised learning is used to predict whether the quality of the transmission oil at this point reaches a filter change threshold. If the threshold value of the filter replacement is not reached, continuing to detect; if the threshold value for replacing the filter is reached, the transmission control unit controls the working assembly to work.
After the transmission control unit controls the working assembly to work, the electric cylinder 3 in the HMCVT filter automatic replacing device is reset at the moment, so that the filter 1 is removed, and the filter 1 moves downwards to be close to the gear 5. After the electric cylinder 3 is reset, the motor 11 is connected with a gear in the HMCVT filter automatic replacing device 6, and the transmission control unit sends out a signal to control the gear to rotate, so that the filter automatic replacing device is driven to rotate. Since the positions of the 4 filters in the gear 5 are determined at the time of the pre-mechanism manufacture, the rotation angle is set, and the rotation is stopped until the next cartridge reaches the installation position, at which time the filter 1 position corresponds to its installation position in the HMCVT. When the filter core is replaced to the designated position, the motor 11 stops working at the moment. The transmission control unit sends out a signal to control the electric cylinder 3 to work, so that the electric cylinder drives the supporting arm to move upwards, and the filter is installed.
The following is a typical scenario encountered when an HMCVT filter automatic change device based on semi-supervised learning is operated.
Scenario one: the HMCVT does not require replacement of the transmission oil and transmission filter during normal operation. Because the HMCVT is changed in section and is required to control the clutch to be combined and separated so as to realize the speed change to meet the working condition requirement, the transmission control unit sends a signal to start the hydraulic pump 13 to work at the moment, and the transmission oil 9 is transmitted from the oil pan 8 through the automatic filter changing device 6 and the oil way pipe 12. The transmission control unit controls solenoid valves to be energized, so that transmission oil is supplied to a hydraulic system in the HMCVT, a gear shifting brake in a mechanical system and a pump-motor system in a corresponding clutch, the pressure and flow of the pump-motor system of the hydraulic system and the clutch separation and combination in the mechanical system are changed, and the output meets the working condition rotation speed.
Scenario two: when the transmission control unit sends out a signal to start the hydraulic pump 13 to operate, and the transmission oil 9 is transmitted from the oil pan 8 through the automatic filter replacing device 6 and through the oil pipe 12, the transmission oil is recycled in the HMCVT, the transmission oil is recycled to contain worn scrap iron and particulate matters, most of impurities are filtered after passing through the automatic filter replacing device 6, but when the filter reaches the use limit, the filtering capacity is greatly reduced. The data detected by the particulate matter sensor 7 and the capacitance sensor installed in the oil pan 8 predicts whether the impurity in the transmission oil reaches a threshold value, i.e., the filter 1 in use at this time has reached the use limit, based on the semi-supervised learning model. The transmission control unit signals that the electric cylinder 3 in the HMCVT filter automatic change device is reset at this time, thereby removing the filter 1 and moving the filter 1 downward to a position close to the gear 5. After the electric cylinder 3 is reset, the motor 11 is connected with a gear in the HMCVT filter automatic replacing device 6, and the transmission control unit sends out a signal to control the gear to rotate, so that the filter automatic replacing device is driven to rotate. Since the positions of the 4 filters in the gear 5 are determined at the time of the pre-mechanism manufacture, the rotation angle is set, and the rotation is stopped until the next cartridge reaches the installation position, at which time the filter 1 position corresponds to its installation position in the HMCVT. When the filter core is replaced to the designated position, the motor 11 stops working at the moment. The transmission control unit sends out a signal to control the electric cylinder 3 to work, so that the electric cylinder drives the supporting arm to move upwards, and the filter is installed.
Scenario three: according to the invention, four transmission filters are arranged, each time of replacement is judged according to semi-supervised learning model prediction, and the transmission control unit controls the motor 11 and the electric cylinder 3 to realize the replacement of the filters, so that the service time of transmission oil is prolonged, and the lubrication function and the impurity content of the transmission oil are maintained. When all four filters in the HMCVT filter automatic change device 6 have reached the use limit, the HMCVT is reminded to change the transmission oil and the filters.
The present invention is not limited to the above-mentioned embodiments, but any person skilled in the art, based on the technical solution of the present invention and the inventive concept thereof, can be replaced or changed equally within the scope of the present invention.
Claims (5)
1. An HMCVT filter automatic replacement device based on semi-supervised learning comprises a filter automatic replacement device (6); the method is characterized in that: the automatic filter replacing device (6) is arranged between the hydraulic pump (13) and the oil pan (8), the inside of the oil pan (8) is connected with the input end of the automatic filter replacing device (6) through an oil path pipe (12), and the hydraulic pump (13) is connected with the output end of the automatic filter replacing device (6) through the oil path pipe (12); the automatic filter replacing device (6) comprises a gear (5); a plurality of support arms A (4) are fixedly connected to the outer circumferential surface of the gear (5) at equal intervals; the extending end of the supporting arm A (4) is hinged with a supporting arm B (2); the extending end of the supporting arm B (2) is fixedly connected with a transmission oil filter (1); the support arm A (4) and the support arm B (2) are connected with each other through an electric cylinder (3) arranged between the support arms A and B.
2. The HMCVT filter automatic change device based on semi-supervised learning of claim 1, wherein: the supporting arm A (4) is arranged along the excircle tangent plane of the gear (5).
3. The HMCVT filter automatic change device based on semi-supervised learning of claim 1, wherein: oil (9) is arranged in the oil pan (8), and symmetrically arranged particulate matter sensors (7) and capacitance sensors (10) are respectively arranged on the inner wall surface of the oil pan (8).
4. The HMCVT filter automatic change device based on semi-supervised learning of claim 1, wherein: the automatic filter replacing device (6) is electrically connected with a motor (11) for driving the automatic filter replacing device to move.
5. A replacement method using the HMCVT filter automatic replacement device based on semi-supervised learning as recited in claim 1, characterized by: the method comprises the following steps:
s1, acquiring and collecting data of the transmission oil containing dust, metal and other impurities with different degrees based on semi-supervised learning to obtain marked data and unmarked data;
s2: training a model according to the marked data and the unmarked data;
s3: predicting transmission oil quality using the model;
s4: when the HMCVT works, the dielectric constant and the particulate matter content in oil are detected through a particulate matter sensor (7) and a capacitance sensor (10) which are arranged in an oil pan (8);
s5: predicting whether the quality of the transmission oil reaches a filter replacement threshold value at the moment through semi-supervised learning;
s6: ending the detection if the threshold value of the filter replacement is not reached;
and S7, if the threshold value for replacing the filter is reached, the transmission control unit controls the working assembly to work, so that the electric cylinder (3) in the HMCVT filter automatic replacing device (6) is reset, the filter is removed, the motor (11) drives the filter automatic replacing device (6) to rotate, and the electric cylinder (3) works to complete the installation of the filter.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311182829.3A CN117072660A (en) | 2023-09-14 | 2023-09-14 | HMCVT filter automatic replacement device and replacement method based on semi-supervised learning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311182829.3A CN117072660A (en) | 2023-09-14 | 2023-09-14 | HMCVT filter automatic replacement device and replacement method based on semi-supervised learning |
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| Publication Number | Publication Date |
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| CN117072660A true CN117072660A (en) | 2023-11-17 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311182829.3A Pending CN117072660A (en) | 2023-09-14 | 2023-09-14 | HMCVT filter automatic replacement device and replacement method based on semi-supervised learning |
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| Country | Link |
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| CN (1) | CN117072660A (en) |
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2023
- 2023-09-14 CN CN202311182829.3A patent/CN117072660A/en active Pending
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