CN112115575A - Equipment lubricating oil state evaluation system and method - Google Patents
Equipment lubricating oil state evaluation system and method Download PDFInfo
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- 239000010687 lubricating oil Substances 0.000 title claims abstract description 114
- 238000011156 evaluation Methods 0.000 title claims abstract description 44
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000013210 evaluation model Methods 0.000 claims abstract description 33
- 238000004364 calculation method Methods 0.000 claims abstract description 5
- 238000012549 training Methods 0.000 claims description 47
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 23
- 239000003921 oil Substances 0.000 claims description 14
- 238000012706 support-vector machine Methods 0.000 claims description 9
- 238000012423 maintenance Methods 0.000 abstract description 9
- 239000000463 material Substances 0.000 abstract description 4
- 238000012360 testing method Methods 0.000 description 12
- 229910052742 iron Inorganic materials 0.000 description 7
- 239000000314 lubricant Substances 0.000 description 7
- 230000008569 process Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- PXHVJJICTQNCMI-UHFFFAOYSA-N Nickel Chemical compound [Ni] PXHVJJICTQNCMI-UHFFFAOYSA-N 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
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- 238000012986 modification Methods 0.000 description 2
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- 238000003466 welding Methods 0.000 description 2
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 1
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- ZOKXTWBITQBERF-UHFFFAOYSA-N Molybdenum Chemical compound [Mo] ZOKXTWBITQBERF-UHFFFAOYSA-N 0.000 description 1
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 229910052804 chromium Inorganic materials 0.000 description 1
- 239000011651 chromium Substances 0.000 description 1
- 230000002860 competitive effect Effects 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000007429 general method Methods 0.000 description 1
- 239000011133 lead Substances 0.000 description 1
- 229910052750 molybdenum Inorganic materials 0.000 description 1
- 239000011733 molybdenum Substances 0.000 description 1
- 229910052759 nickel Inorganic materials 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000033764 rhythmic process Effects 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
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- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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Abstract
The invention discloses a system and a method for evaluating the state of equipment lubricating oil, wherein the system comprises: the parameter acquisition unit is used for acquiring the operation parameters of the equipment; the parameter calculation unit is used for obtaining index parameters representing the state of the lubricating oil by utilizing a pre-established lubricating oil evaluation model according to the operation parameters; and a state evaluation unit for evaluating the state of the lubricating oil according to the index parameter to determine whether to replace the lubricating oil. According to the method and the device, the lubricating oil state is evaluated through the acquired running parameters of the device and the pre-established lubricating oil evaluation model, the lubricating oil state of the device can be evaluated according to the running current situation of the device without spending manpower and material resources, the device maintenance strategy can be effectively optimized, and the device maintenance operation cost is greatly reduced.
Description
Technical Field
The invention relates to a device lubricating oil state evaluation technology, in particular to a device lubricating oil state evaluation system and a device lubricating oil state evaluation method.
Background
The purpose of modern enterprises for carrying out automatic production and intelligent production is to reduce the cost continuously. Excessive equipment maintenance entails increased costs in terms of manpower and material resources. However, it is unacceptable to the enterprise that necessary maintenance is not performed, which in turn causes long periods of equipment downtime. How to make equipment maintenance schemes more scientifically with the most lean cost under the condition of continuously reduced human resources is a problem which needs to be solved by modeling enterprises in the future.
Taking industrial robots as an example, industrial robots in China are started from the 20 th century and the 80 th century, and after the past thirty years of efforts, some competitive industrial robot research institutions and enterprises, particularly in the field of automobile industry, have been formed. The automobile industry has the biggest characteristics of high yield, fast production rhythm and high product uniformity, and is very suitable for large-scale application of industrial robots. In the case of a welding process in a four-large process of a complete vehicle, a production line may have evolved from the first few robots to hundreds or even thousands of industrial robots. The large number of industrial robots poses an unprecedented challenge for equipment management.
According to the manufacturer's suggestion, the robot needs to change the lubricating oil once every 5 years or 20000 hours of operation, and the cost of changing the lubricating oil of one thousand industrial robots in a welding workshop needs ten million RMB, and the manpower resources consumed by the task of changing the lubricating oil of one thousand industrial robots are very huge. Although the state of the lubricating oil can be evaluated by using an oil detection technology, the lubricating oil of the robot is in a sealed state and moves along with the robot, so that online real-time detection is difficult to achieve, and if an offline testing method is adopted, the workload and the detection cost of thousands of large-scale robots for repeated extraction and testing are still difficult to achieve the purpose of cost control.
Disclosure of Invention
The invention aims to provide a system and a method for evaluating the state of equipment lubricating oil, which are used for solving the problem of reducing the replacement cost of the equipment lubricating oil.
In order to achieve the above object, the present invention provides an equipment lubricating oil state evaluation system, including: the parameter acquisition unit is used for acquiring the operation parameters of the equipment; the parameter calculation unit is used for obtaining index parameters representing the state of the lubricating oil by utilizing a pre-established lubricating oil evaluation model according to the operation parameters; and a state evaluation unit for evaluating the state of the lubricating oil according to the index parameter to determine whether to replace the lubricating oil.
Preferably, the system further comprises a model establishing unit for establishing the lubricating oil evaluation model; the parameter acquisition unit is further used for acquiring training parameters of the equipment, wherein the training parameters comprise operation parameters and index parameters for establishing the lubricating oil evaluation model; and the model establishing unit is used for carrying out model training by adopting a support vector machine regression algorithm according to the training parameters to obtain the lubricating oil evaluation model.
Preferably, the operating parameters include: shaft torque data, shaft temperature data, and shaft current data, and at least one of: the number of the shafts, the running time of the shafts and the load of the equipment where the shafts are located; the index parameter includes the content of the component in the lubricating oil.
Preferably, the shaft torque data comprises shaft maximum torque, shaft minimum torque and shaft average torque, the shaft temperature data comprises shaft maximum temperature and shaft average temperature, and the shaft current data comprises shaft maximum current, shaft minimum current and shaft average current; the index parameter is the content of iron element.
Preferably, the parameter acquiring unit includes: a torque acquisition subunit for acquiring the shaft torque data; a temperature acquisition subunit for acquiring the shaft temperature data; a current acquisition subunit for acquiring the shaft current data; and a lubricating oil component obtaining subunit for obtaining the component content in the lubricating oil.
Preferably, the apparatus is an industrial robot.
Correspondingly, the invention also provides a device lubricating oil state evaluation method, which comprises the following steps: acquiring the operation parameters of the equipment; obtaining index parameters representing the state of the lubricating oil by utilizing a pre-established lubricating oil evaluation model according to the operation parameters; and evaluating the state of the lubricating oil according to the index parameter to determine whether to replace the lubricating oil.
Preferably, the method further comprises: acquiring training parameters of the equipment, wherein the training parameters comprise operation parameters and index parameters for establishing a lubricating oil evaluation model; and performing model training by adopting a support vector machine regression algorithm according to the training parameters to obtain the lubricating oil evaluation model.
Preferably, the operating parameters include: shaft torque data, shaft temperature data, and shaft current data, and at least one of: the number of the shafts, the running time of the shafts and the load of the equipment where the shafts are located; the index parameter includes the content of the component in the lubricating oil.
Preferably, the shaft torque data comprises shaft maximum torque, shaft minimum torque and shaft average torque, the shaft temperature data comprises shaft maximum temperature and shaft average temperature, and the shaft current data comprises shaft maximum current, shaft minimum current and shaft average current; the index parameter is the content of iron element.
According to the method and the device, the lubricating oil state is evaluated through the acquired running parameters of the device and the pre-established lubricating oil evaluation model, the lubricating oil state of the device can be evaluated according to the running current situation of the device without spending manpower and material resources, the device maintenance strategy can be effectively optimized, and the device maintenance operation cost is greatly reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 is a block diagram of an equipment oil condition evaluation system provided by the present invention;
FIG. 2 is a block diagram of another equipment oil condition evaluation system provided by the present invention;
FIG. 3 is a comparison graph of the training parameter evaluation results and the true values provided by the present invention;
FIG. 4 is a comparison of the test parameter evaluation results provided by the present invention with the true values; and
FIG. 5 is a flow chart of a method for evaluating the state of equipment lubricating oil provided by the invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are intended for purposes of illustration and explanation only and are not intended to limit the scope of the invention.
Fig. 1 is a block diagram of an equipment lubricating oil state evaluation system provided by the present invention, and as shown in fig. 1, the equipment lubricating oil state evaluation system includes a parameter acquisition unit 1, a parameter calculation unit 2, and a state evaluation unit 3.
The parameter acquiring unit 1 is used for acquiring the operation parameters of the equipment. The parameter acquiring unit 1 may be an existing unit inside the device or a unit patented for the purpose of the present invention. The process of acquiring the operation parameters by the parameter acquiring unit 1 may be, for example, a process of acquiring relevant parameters by a device configured by the equipment and sending the relevant parameters to the equipment lubricating oil state evaluation system provided by the invention, or a process of receiving the relevant operation parameters by a human-computer interaction interface.
The parameter calculation unit 2 is configured to obtain an index parameter representing a state of the lubricating oil by using a pre-established lubricating oil evaluation model according to the operation parameter. The lubricating oil evaluation model is a model constructed by an algorithm in the prior art, and a general method is to train through training parameters to obtain a corresponding model. The index parameter herein is the content of components contained in the lubricating oil that can characterize the state of the lubricating oil.
The state evaluation unit 3 is used for evaluating the state of the lubricating oil according to the index parameter to determine whether to replace the lubricating oil. The index parameter is a relevant parameter capable of representing the state of the lubricating oil, and the state evaluation unit 3 obtains an evaluation value according to the index parameter, and accordingly obtains the state of the lubricating oil so as to prompt whether a worker should change the lubricating oil.
Fig. 2 is a block diagram of another device oil state evaluation system provided by the present invention, and as shown in fig. 2, the oil state evaluation system further includes a model establishing unit 4, and the model establishing unit 4 is used for establishing an oil evaluation model. The parameter obtaining unit 1 is further configured to obtain training parameters of the device, where the training parameters include an operation parameter and an index parameter for establishing a lubricating oil evaluation model; the model establishing unit 4 is used for performing model training by adopting a support vector machine regression algorithm according to the training parameters to obtain a lubricating oil evaluation model.
When a support vector machine regression algorithm is adopted to carry out model training, training parameters are required to be utilized, wherein the training parameters comprise input characteristic data used as input and output characteristic data used as output. Those skilled in the art will appreciate that the input feature data and the output feature data may be used for model training directly, or the input feature data and the output feature data may be normalized at their respective latitudes for model training. The technique of performing model training by using the support vector machine regression algorithm is well known in the art, and is not described herein.
The operating parameters in the present invention include: shaft torque data, shaft temperature data, and shaft current data.
The shaft torque data is data relating to shaft torque of the apparatus, and preferably, the shaft torque data may include, for example, shaft maximum torque, shaft minimum torque, and shaft average torque, where the shaft torque data are arithmetic values, and in general, the shaft maximum torque is a positive value and is a maximum value of an absolute value of the positive torque, the shaft minimum torque is a negative value and is a maximum value of an absolute value of the negative torque, and the shaft average torque is an arithmetic average of the torques, where the shaft average torque is calculated as an average of the shaft torques during a steady operation period of the apparatus. The period of stable operation of the apparatus referred to in the present invention may be understood as a period of normal operation of the apparatus.
The shaft temperature data is data relating to the shaft temperature of the device, and preferably may include, for example, a shaft maximum temperature and a shaft average temperature. Here, the shaft average temperature is calculated as an average value of the shaft temperature during the steady operation period of the apparatus.
The shaft current data is data related to the shaft current of the device, and preferably, the shaft current data may include, for example, a shaft maximum current, a shaft minimum current, and a shaft average current, where the shaft current data are arithmetic values, and in general, the shaft maximum current is a positive value and is a maximum value of an absolute value of a positive current, the shaft minimum current is a negative value and is a maximum value of an absolute value of a negative current, and the shaft average current is an arithmetic average value of currents, where the shaft average current is calculated as an average value of the shaft current during a steady operation period of the device.
In addition, the operating parameters in the present invention may further include at least one of: the shaft number, the shaft run time, and the load of the equipment in which the shaft is located. The shaft number is the number of the shaft of the device mentioned in the present invention, and the shaft number and the position correspond to each other for the same device, that is, the shaft number is fixed. For example, if a piece of equipment has 6 axes, then the axis numbers of the equipment are 1 to 6, and the axis numbers of the axes of the same equipment at the same position are the same. The axis running time is generally the running time of the equipment where the axis is located, and it is understood that the running time of all axes on the same equipment is generally the same. The load of the equipment where the shaft is located may be, for example, a rated load of the equipment where the shaft is located, and the rated load may be obtained by means of an equipment model or an equipment specification.
The lubricating oil is provided for each shaft of the device, and the amount of the lubricating oil is influenced by the position of the shaft, the operating time of the shaft or the load of the device in which the shaft is located. It will be understood by those skilled in the art that the lubricant evaluation model of the present invention is provided for the same equipment, and that different lubricant evaluation models should be used for different equipment.
In the process of model training, in order to make the selection of the training parameters more reasonable, the training parameters may be grouped according to the position of the axis, the running time of the axis, or the load of the equipment where the axis is located, and then the training parameters are selected for each group according to the grouping result.
The shaft numbers can be grouped according to the shaft numbers, that is, for the same machine, several shafts can be divided into several groups, and for example, one device has 6 shafts, which can be divided into 6 groups. For the axis running time, the running times of the devices with running times of 5000 hours to 20000 hours may be collected, and may be grouped according to the running times, for example, may be grouped in the interval of 1500 hours or 3000 hours or 5000 hours. In the case of 5000 hours, it can be divided into 3 groups having operating times of more than 5000 hours and less than or equal to 10000 hours, more than 10000 hours and less than or equal to 15000 hours, and more than 15000 hours and less than or equal to 20000 hours. The load of the equipment with the shaft may be collected, and specifically, the load of the equipment with the shaft may be grouped according to the load of the equipment with the shaft, for example, the load may be grouped in an interval of 30kg, 50kg, 70kg, or 100kg, and the load may be divided into 6 groups of more than 10kg and less than or equal to 60kg, more than 60kg and less than or equal to 110kg, more than 110kg and less than or equal to 160kg, more than 160kg and less than or equal to 210kg, more than 210kg and less than or equal to 260kg, and more than 260kg and less than or equal to 300kg, taking 50kg as an example.
The three grouping modes are provided according to the shaft serial number, the shaft running time and the load of the equipment where the shaft is located, any one or two of the three grouping modes can be adopted, and the three grouping modes can also be adopted simultaneously. In the case of adopting three grouping modes at the same time, taking the above example as an example, for example, the training parameters are divided into 6 groups according to the shaft serial number, 3 groups according to the shaft running time, and 6 groups according to the load of the device where the shaft is located, then the relevant parameters should be reasonably collected in 108 groups (the number of groups of shaft serial numbers is 6 × the number of groups of shaft running time is 3 × the number of groups of load of the device where the shaft is located is 6 ═ 108) respectively when selecting the training parameters, that is, the collected training data should be appropriately grouped in the 108 groups to obtain a better lubricating oil evaluation model.
In addition, in order to make the robustness of the lubricating oil evaluation model higher, some training parameters can be specially selected for equipment in a high fault area for model training.
The above-described way of selecting the training parameters is only for optimizing the application of the present invention, and is not intended to limit the present invention, and training parameters not collected according to the above-described rules may also be applied to the present invention.
The index parameters in the invention comprise the content of components in the lubricating oil, and the components in the lubricating oil can comprise iron, copper, aluminum, silicon, molybdenum, nickel, lead, chromium and the like, wherein the content of iron element can most obviously represent the state of the lubricating oil. In the present invention, for example, the index parameter may be selected as the content of iron, an iron content threshold may be set, the lubricant oil replacement is prompted when the content of iron in the lubricant oil exceeds the threshold, and the state of the lubricant oil is the state of whether the content of iron exceeds the iron content threshold when the evaluation value obtained from the index parameter is the content of iron.
As shown in fig. 2, the parameter acquiring unit 1 may further include a torque acquiring subunit 11, a temperature acquiring subunit 12, a current acquiring subunit 13, and a lubricating oil composition acquiring subunit 14. Specifically, the torque acquisition subunit 11 is configured to acquire shaft torque data; the temperature acquisition subunit 12 is configured to acquire shaft temperature data; the current obtaining subunit 13 is configured to obtain shaft current data; the lubricating oil component obtaining subunit 14 is used to obtain the component content in the lubricating oil.
Those skilled in the art will appreciate that the technique of the torque acquisition subunit 11 acquiring shaft torque data, the technique of the temperature acquisition subunit 12 acquiring shaft temperature data, the technique of the current acquisition subunit 13 acquiring shaft current data, and the technique of the lubricating oil composition acquisition subunit 14 acquiring the composition content of the lubricating oil are all implemented using techniques well known in the art. For example, the torque obtaining subunit 11 may obtain the shaft torque data, the temperature obtaining subunit 12 may obtain the shaft temperature data, and the current obtaining subunit 13 may obtain the shaft current data by collecting relevant data through a device configured in the apparatus and sending the data to the corresponding subunit, and the lubricating oil component obtaining subunit 14 may obtain the component content in the lubricating oil by detecting the lubricating oil by a third party and then receiving the component content through a human-computer interaction interface.
The equipment lubricating oil state evaluation system provided by the invention can be used for industrial robots.
In order to test the accuracy of the established lubricant evaluation model, the parameter obtaining unit 1 may further obtain test parameters of the device, the test parameters including an operation parameter and an index parameter for testing the lubricant evaluation model. Or all the pre-collected operation parameters and corresponding index parameters can be used as a data set, 90% of the data set is used as a training parameter, and the rest 10% is used as a testing parameter.
Fig. 3 is a comparison graph of the training parameter evaluation result and the true value provided by the present invention, and fig. 4 is a comparison graph of the test parameter evaluation result and the true value provided by the present invention, as shown in fig. 3 and 4, the horizontal axis in fig. 3 and 4 is the sample number, and the vertical axis is the content of iron element. Fig. 3 is the evaluation value obtained by the lubricating oil evaluation model using the training parameters, and fig. 4 is the evaluation value obtained by the lubricating oil evaluation model using the test parameters, and it can be seen that the accuracy of the evaluation result is high by comparing the training parameter evaluation result (evaluation value, i.e., iron element content) with the true value and comparing the test parameter evaluation result (evaluation value, i.e., iron element content) with the true value.
Fig. 5 is a flowchart of an apparatus lubricating oil state evaluation method according to the present invention, and as shown in fig. 5, the apparatus lubricating oil state evaluation method includes:
502, obtaining index parameters representing the state of the lubricating oil by utilizing a pre-established lubricating oil evaluation model according to the operation parameters;
and step 503, evaluating the lubricating oil state according to the index parameters to determine whether to replace the lubricating oil.
Preferably, the method for evaluating the state of the equipment lubricating oil further comprises the following steps: acquiring training parameters of equipment, wherein the training parameters comprise operation parameters and index parameters for establishing a lubricating oil evaluation model; and performing model training by adopting a support vector machine regression algorithm according to the training parameters to obtain a lubricating oil evaluation model.
Preferably, the operating parameters include: shaft torque data, shaft temperature data, and shaft current data, and at least one of: the number of the shafts, the running time of the shafts and the load of the equipment where the shafts are located; the index parameter includes the content of the component in the lubricating oil.
Preferably, the shaft torque data comprises shaft maximum torque, shaft minimum torque and shaft average torque, the shaft temperature data comprises shaft maximum temperature and shaft average temperature, and the shaft current data comprises shaft maximum current, shaft minimum current and shaft average current; the index parameter is the content of iron element.
It should be noted that the specific details and benefits of the method for evaluating the state of the equipment lubricating oil provided by the present invention are similar to those of the system for evaluating the state of the equipment lubricating oil provided by the present invention, and are not described herein again.
Although the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solutions of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications all belong to the protection scope of the embodiments of the present invention.
According to the technical scheme provided by the invention, on the basis of establishing the relation model between the equipment lubricating oil state and the equipment operation parameters by adopting the support vector machine regression algorithm, the lubricating oil state can be evaluated according to the equipment operation parameters without spending manpower and material resources on collecting and testing oil samples so as to determine whether the lubricating oil needs to be replaced, the accuracy is higher, the equipment maintenance strategy can be effectively guided and optimized, and the equipment maintenance operation cost is reduced.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention do not describe every possible combination.
In addition, any combination of various different implementation manners of the embodiments of the present invention is also possible, and the embodiments of the present invention should be considered as disclosed in the embodiments of the present invention as long as the combination does not depart from the spirit of the embodiments of the present invention.
Claims (10)
1. An equipment lubricating oil condition evaluation system, characterized by comprising:
the parameter acquisition unit is used for acquiring the operation parameters of the equipment;
the parameter calculation unit is used for obtaining index parameters representing the state of the lubricating oil by utilizing a pre-established lubricating oil evaluation model according to the operation parameters; and
and the state evaluation unit is used for evaluating the lubricating oil state according to the index parameter so as to determine whether to replace the lubricating oil.
2. The equipment oil condition evaluation system according to claim 1, further comprising a model establishing unit for establishing the oil evaluation model;
the parameter acquisition unit is further used for acquiring training parameters of the equipment, wherein the training parameters comprise operation parameters and index parameters for establishing the lubricating oil evaluation model;
and the model establishing unit is used for carrying out model training by adopting a support vector machine regression algorithm according to the training parameters to obtain the lubricating oil evaluation model.
3. The equipment oil condition evaluation system of claim 2, wherein the operating parameters include: shaft torque data, shaft temperature data, and shaft current data, and at least one of: the number of the shafts, the running time of the shafts and the load of the equipment where the shafts are located; the index parameter includes the content of the component in the lubricating oil.
4. The equipment oil condition evaluation system of claim 3, wherein the shaft torque data comprises a shaft maximum torque, a shaft minimum torque, and a shaft average torque, the shaft temperature data comprises a shaft maximum temperature and a shaft average temperature, and the shaft current data comprises a shaft maximum current, a shaft minimum current, and a shaft average current; the index parameter is the content of iron element.
5. The equipment lubricating oil condition evaluation system according to claim 3, characterized in that the parameter acquisition unit includes:
a torque acquisition subunit for acquiring the shaft torque data;
a temperature acquisition subunit for acquiring the shaft temperature data;
a current acquisition subunit for acquiring the shaft current data; and
a lubricating oil component obtaining subunit for obtaining the component content in the lubricating oil.
6. The system for evaluating the condition of the lubricating oil in an apparatus according to any one of claims 1 to 5, wherein the apparatus is an industrial robot.
7. A method for evaluating the state of equipment lubricating oil is characterized by comprising the following steps:
acquiring the operation parameters of the equipment;
obtaining index parameters representing the state of the lubricating oil by utilizing a pre-established lubricating oil evaluation model according to the operation parameters; and
and evaluating the state of the lubricating oil according to the index parameter to determine whether to replace the lubricating oil.
8. The apparatus lubricating oil condition evaluation method according to claim 7, characterized by further comprising:
acquiring training parameters of the equipment, wherein the training parameters comprise operation parameters and index parameters for establishing a lubricating oil evaluation model; and
and performing model training by adopting a support vector machine regression algorithm according to the training parameters to obtain the lubricating oil evaluation model.
9. The apparatus lubricating oil condition evaluation method according to claim 8, wherein the operating parameters include: shaft torque data, shaft temperature data, and shaft current data, and at least one of: the number of the shafts, the running time of the shafts and the load of the equipment where the shafts are located; the index parameter includes the content of the component in the lubricating oil.
10. The apparatus lubricating oil condition evaluation method according to claim 9, wherein the shaft torque data includes a shaft maximum torque, a shaft minimum torque, and a shaft average torque, the shaft temperature data includes a shaft maximum temperature and a shaft average temperature, and the shaft current data includes a shaft maximum current, a shaft minimum current, and a shaft average current; the index parameter is the content of iron element.
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| CN202010742756.9A CN112115575A (en) | 2020-07-29 | 2020-07-29 | Equipment lubricating oil state evaluation system and method |
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| CN202010742756.9A CN112115575A (en) | 2020-07-29 | 2020-07-29 | Equipment lubricating oil state evaluation system and method |
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