CN107966449A - A kind of oil cleanliness detector and its detection method - Google Patents

A kind of oil cleanliness detector and its detection method Download PDF

Info

Publication number
CN107966449A
CN107966449A CN201711220326.5A CN201711220326A CN107966449A CN 107966449 A CN107966449 A CN 107966449A CN 201711220326 A CN201711220326 A CN 201711220326A CN 107966449 A CN107966449 A CN 107966449A
Authority
CN
China
Prior art keywords
fluid
sampling
sample
power microscope
grade
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201711220326.5A
Other languages
Chinese (zh)
Inventor
王素均
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to CN201711220326.5A priority Critical patent/CN107966449A/en
Publication of CN107966449A publication Critical patent/CN107966449A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854Grading and classifying of flaws

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Sampling And Sample Adjustment (AREA)

Abstract

This application discloses a kind of oil cleanliness detector and its detection method, detector includes fluid sampling unit, high-power microscope, image identification unit, data processor, data store and communication module and high-precision digital-display screen, wherein, fluid sampling unit is according to standard acquisition sample fluid, data processor analyzes collection information, draw the cleannes grade of sampling fluid, and contrast is stored in the reference fluid cleannes grade photo in detector automatically according to obtained cleannes grade, it is delivered in high-precision digital-display screen and carries out contrast and show, by directly detecting the particulate matter in fluid sample, then its species is obtained, size and number, data intuitive strengthens, be conducive to improve testing result accuracy, and detection mode is simple to operation, operated suitable for live quick-speed large-scale.

Description

A kind of oil cleanliness detector and its detection method
Technical field
This application involves hydraulic pressure, lubricating area, more particularly to a kind of oil cleanliness detector and its detection method.
Background technology
Oil cleanliness is mainly the solid particulate matter dustiness index in fluid liquid, in hydraulic pressure, lubricating area fluid Cleannes are a very crucial parameters, its service life on whole system suffers from vital influence with reliability, has Statistics shows that hydraulic pressure, the failure of lubricating system 70% are because caused by oil cleanliness reason.
Oil cleanliness detector on the market is all based on laser particle count principle, the detector of this technology at present It is a kind of Statistics indirectly and sensor cannot observe directly contaminant particle thing size, the shape in fluid sample, With inaccuracy, and bubble is remained to testing result and very big influence in fluid, so the biography based on such counting Sensor is not high with detector confidence level, is generally only used as detection reference.In addition, single laser particle thing sensor for countering or Detector can not also tell the species of particulate matter, can not instruct the prevention work of oil cleanliness.In addition to cleannes detector, It is exactly that laboratory optical loupes are analyzed to also have a kind of more accurately detection method at present, although such method conclusion ratio It is relatively accurate, but laboratory equipment operation can only be completed, laboratory environment requirement is not suitable for by special messenger with very strong professional The requirement that scene quickly checks, also brings many inconveniences to oil cleanliness detection work.In short, existing fluid cleaning It is not directly perceived to spend inaccurate detector testing result, detection process and detection data;Existing test in laboratory mode time and effort consuming, Be not suitable for scene quick-speed large-scale to use, and intuitive is also very poor, and what user had no way quicklook recognizes desired knot By.
The content of the invention
The embodiment of the present application provides a kind of oil cleanliness detector and its detection method, of the prior art to solve Following technical problem:Testing result is inaccurate, detection process and detection data be not directly perceived, and detection mode time and effort consuming, no It is adapted to scene quick-speed large-scale to use.
In order to solve the above technical problems, what the embodiment of the present application was realized in:
A kind of oil cleanliness detector provided by the embodiments of the present application, including:
Fluid sampling unit, high-power microscope, image identification unit, data processor, data storage with communication module and High-precision digital-display screen, it is characterised in that fluid sampling unit is according to standard acquisition sample fluid and connects high-power microscope, high power Microscope can either automatically or manually complete paired samples fluid amplification factor segmentation, focusing, image identification unit connection high power Microscope, image in real-time collecting sample are simultaneously exported obtained information in the form of electronic pictures, and data processor can be automatic The cleannes grade that the electronic pictures are handled to distinguish variable grain species and fluid is calculated, high-precision digital-display screen For showing sample fluid picture, oil cleanliness grade, standard solid thing grade picture, and variable grain species can be directed to Class, forms different signs and distinguishes display.
The embodiment of the present application further includes a kind of detection method of oil cleanliness detector, including:
Fluid sampling unit is according to standard acquisition sample fluid, after being filtered by ready filter paper, by filter paper from Dynamic be sent under high-power microscope is amplified, and high-power microscope selects corresponding object lens, eyepiece to carry out classification and put according to amplification factor Greatly, after by the object lens of high-power microscope, eyepiece amplification, the electronic chart for the image identification unit being connected with high-power microscope eyepiece As identifying system gathers the image in filter paper sample in real time, preserved with million grades of high-resolution digital forms, the picture quilt of preservation Send to data processor and analyzed, draw the cleannes grade of sampling fluid, data processor is according to obtained cleannes etc. The automatic contrast of level is stored in the reference fluid cleannes grade photo in detector, and is delivered in high-precision digital-display screen and carries out pair Than display.
Above-mentioned at least one technical solution that the embodiment of the present application uses can reach following beneficial effect:
The application then obtains its species, size and number by directly detecting the particulate matter in fluid sample, and data are straight The property seen enhancing, is conducive to improve testing result accuracy, and detection mode is simple to operation, suitable for live quick-speed large-scale Operation, can solve the problems of the prior art.
Brief description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, below will be to embodiment or existing There is attached drawing needed in technology description to be briefly described, it should be apparent that, drawings in the following description are only this Some embodiments described in application, for those of ordinary skill in the art, in the premise of not making the creative labor property Under, other attached drawings can also be obtained according to these attached drawings.
Fig. 1 is a kind of structure diagram of oil cleanliness detector provided by the embodiments of the present application.
Wherein, 1-fluid sampling unit, 2-high-power microscope, 3-image identification unit, 4-data processor, 5- Titer presses sample image, 6-high-precision digital-display screen, the storage of 7-data and communication module.
Embodiment
The embodiment of the present application provides a kind of oil cleanliness detector and its detection method.
It is in order to make those skilled in the art better understand the technical solutions in the application, real below in conjunction with the application The attached drawing in example is applied, the technical solution in the embodiment of the present application is clearly and completely described, it is clear that described implementation Example is merely a part but not all of the embodiments of the present application.It is common based on the embodiment in the application, this area Technical staff's all other embodiments obtained without making creative work, should all belong to the application protection Scope.
As shown in Figure 1, a kind of oil cleanliness detector, including fluid sampling unit 1, high-power microscope 2, image recognition Unit 3, data processor 4, data storage and communication module 7 and high-precision digital-display screen 6, wherein, fluid sampling unit 1 is according to mark Quasi- collecting sample fluid, is filtered by ready filter paper, and the filter paper after the completion of sampling will be transmitted by micro-step motor To 2 detection station of high-power microscope, high-power microscope 2 is amplified in filter paper by its object lens and eyepiece filters the particle left Thing, also under the driving and control of micro-step motor, high-power microscope 2 automatic or complete paired samples fluid can be put Big multiple segmentation, focusing, above detection engineering can also be completed manually.Image identification unit 3 connects high-power microscope 2, Image in real-time collecting sample and by obtained information in the form of the electronic pictures that million grades of high-resolution digital forms preserve Output, electronic pictures are sent to data processor 4 and are analyzed, and data processor 4 can automatically process electronic pictures, be known with image Other method calculates particulate matter size and quantity, and is classified by the sampling picture of multiple points to particulate matter quantity according to size Statistics, distinguishes the species of particulate matter, so as to draw the cleannes grade of sampling fluid, high-precision digital-display screen 6 is used to show sample Fluid picture, oil cleanliness grade, standard solid thing grade picture, and variable grain species can be directed to, formed different Sign distinguishes display.Wherein, data storage with communication module 7 can store the picture of sample fluid, cleannes grade, Grain species statistical information, in order to user's copy, reads, printing information needed, or it is connected with direct with computer Relevant information is shown on computers.
User selects corresponding detection pattern according to the mode that fluid samples:Fluid on-line period pattern takes offline with fluid Original mold formula.Used when in hydraulic pressure, lubrication on-line system, what is typically gathered has the fluid of pressure source, this pattern Down, it is necessary to which oil cleanliness detector is connected on oil sources, pressure oil is depressurized by fluid sampling unit 1, further according to the world And after the requirement of national sector standard carries out accurate measurement processing, flow into fluid sampling unit 1 and filtered.It is if offline Sampling mode, the metering pump in fluid sampling unit 1 can collect that satisfaction is international and national sector standard will from offline sampling bottle The fluid amount asked simultaneously carries out filtration treatment.Both the above detection pattern, simply the method in fluid sampling is different, sampling filtering Afterwards, the operation principle of two kinds of detection patterns is identical.
As needed, data processor 4 can carry out particulate matter category identification to the sampling fluid particulate matter picture of collection:With Image-recognizing method automatic identification includes the variable grain species such as metal, rubber, paint.Variety classes particulate matter is carried out automatic Sign is handled and is shown in display screen, allows technical staff to get information about very much particle species so as to find oil contaminant Source.
The foregoing is merely embodiments herein, is not limited to the application.For those skilled in the art For, the application can have various modifications and variations.All any modifications made within spirit herein and principle, be equal Replace, improve etc., it should be included within the scope of claims hereof.

Claims (10)

1. a kind of oil cleanliness detector, including:Fluid sampling unit, high-power microscope, image identification unit, data processing Device, data storage and communication module and high-precision digital-display screen, it is characterised in that fluid sampling unit is according to standard acquisition sample oil Liquid simultaneously connects high-power microscope, high-power microscope can either automatically or manually complete paired samples fluid amplification factor segmentation, it is right Jiao, image identification unit connection high-power microscope, image in real-time collecting sample and by obtained information with electronic pictures shape Formula exports, and data processor can automatically process the electronic pictures to distinguish variable grain species and fluid is calculated Cleannes grade, high-precision digital-display screen are used to show sample fluid picture, oil cleanliness grade, standard solid thing grade figure Piece, and variable grain species can be directed to, form different signs and distinguish display.
A kind of 2. oil cleanliness detector according to claim 1, it is characterised in that:The fluid sampling unit collection Sample fluid, after being filtered by ready filter paper, be automatically transmitted to amplify under high-power microscope.
A kind of 3. oil cleanliness detector according to claim 1, it is characterised in that:Described image recognition unit is first Calculate particulate matter size and quantity with image-recognizing method, by the sampling pictures of multiple points to particulate matter quantity according to size into Row statistic of classification, so as to draw the cleannes grade of sampling fluid.
A kind of 4. oil cleanliness detector according to claim 1, it is characterised in that:The data storage and the mould that communicates The block storage picture of sample fluid, cleannes grade, particle species statistical information, for copy, read, print analyze or with Computer is connected directly to show on computers.
A kind of 5. oil cleanliness detector according to claim 1, it is characterised in that:Described image recognition unit is with hundred Ten thousand grades of high-resolution digital forms preserve the electronic pictures of output.
6. a kind of detection method of oil cleanliness detector according to claim 1, it is characterised in that fluid sampling is single Filter paper after being filtered by ready filter paper, is automatically transmitted to high-power microscope by member according to standard acquisition sample fluid Lower amplification, high-power microscope select corresponding object lens, eyepiece to carry out classification amplification, pass through high-power microscope according to amplification factor After object lens, eyepiece amplification, the electronic image identifying system for the image identification unit being connected with high-power microscope eyepiece gathers in real time Image in filter paper sample, is preserved with million grades of high-resolution digital forms, and the picture of preservation is sent to data processor progress Analysis, draws the cleannes grade of sampling fluid, contrast is stored in inspection to data processor automatically according to obtained cleannes grade The reference fluid cleannes grade photo in instrument is surveyed, and is delivered in high-precision digital-display screen and is carried out contrast and show.
7. detection method according to claim 6, it is characterised in that:The picture of the preservation be sent to data processor into Row analysis further comprises that processor calculates particulate matter size and quantity with image-recognizing method first, passes through adopting for multiple points Master drawing piece carries out statistic of classification to particulate matter quantity according to size, so as to draw the cleannes grade of sampling fluid.
8. detection method according to claim 6, it is characterised in that:Wherein, data storage and communication module storage sample The picture of fluid, cleannes grade, particle species statistical information, for copying, reading, printing analysis or being connected with computer Directly to show on computers.
9. detection method according to claim 6, it is characterised in that:According to the sample mode of sample fluid, set and correspond to Detection pattern, the detection pattern includes fluid on-line period pattern and the offline sampling mode of fluid.
10. detection method according to claim 9, it is characterised in that:When the oil carried out in hydraulic pressure, lubrication on-line system Under liquid on-line period pattern, detector is connected on oil sources, pressure oil by fluid sampling unit depressurize and according to standard into After row accurate measurement processing, the filter paper for flowing into fluid sampling unit is filtered;When under the offline sampling mode of fluid, fluid takes Metering pump in sample unit is collected from offline sampling bottle to be met the fluid amount of standard and carries out filtration treatment.
CN201711220326.5A 2017-11-29 2017-11-29 A kind of oil cleanliness detector and its detection method Pending CN107966449A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711220326.5A CN107966449A (en) 2017-11-29 2017-11-29 A kind of oil cleanliness detector and its detection method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711220326.5A CN107966449A (en) 2017-11-29 2017-11-29 A kind of oil cleanliness detector and its detection method

Publications (1)

Publication Number Publication Date
CN107966449A true CN107966449A (en) 2018-04-27

Family

ID=61998976

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711220326.5A Pending CN107966449A (en) 2017-11-29 2017-11-29 A kind of oil cleanliness detector and its detection method

Country Status (1)

Country Link
CN (1) CN107966449A (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109682829A (en) * 2019-02-27 2019-04-26 三一汽车制造有限公司 Oil cleanliness detection device, hydraulic machinery and oil cleanliness detection method
CN110108536A (en) * 2019-06-18 2019-08-09 中国计量大学 A kind of standard board manufacturing method compared for settled date mirror area gray scale detection
CN110813890A (en) * 2019-11-13 2020-02-21 陕西航空电气有限责任公司 Cleaning method of oil cleanliness detection equipment
CN110887768A (en) * 2018-09-10 2020-03-17 人本集团有限公司 Cleaning kerosene cleanliness detection method
CN112051204A (en) * 2020-08-14 2020-12-08 一汽奔腾轿车有限公司 Method for detecting filtering cleanliness of water-based colored paint
CN113466091A (en) * 2021-05-20 2021-10-01 浙江中控太阳能技术有限公司 Heliostat cleaning and cleanliness measuring system and heliostat cleanliness measuring method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN201051080Y (en) * 2007-06-14 2008-04-23 南京航空航天大学 A microscopical image real time measurement and collection device for pollution and abrasion particle in oil
US20100057378A1 (en) * 2008-08-29 2010-03-04 Schlumberger Technology Corporation Downhole sanding analysis tool
CN101832902A (en) * 2010-04-09 2010-09-15 重庆大学 Oil analysis method for diagnosing equipment failure
CN105352858A (en) * 2015-11-16 2016-02-24 中国矿业大学 Image acquisition-based lubricating oil abrasive particle on-line monitoring device and work method thereof
CN205861498U (en) * 2016-08-04 2017-01-04 北京航峰科伟装备技术股份有限公司 In a kind of online oil, grain testing apparatus is polluted in abrasion
CN106483102A (en) * 2016-12-09 2017-03-08 长春市金佳光电科技有限公司 Analyser for the analyser degree on-line checking of free water in aerial kerosene and minute impurities concentration on-line checking

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN201051080Y (en) * 2007-06-14 2008-04-23 南京航空航天大学 A microscopical image real time measurement and collection device for pollution and abrasion particle in oil
US20100057378A1 (en) * 2008-08-29 2010-03-04 Schlumberger Technology Corporation Downhole sanding analysis tool
CN101832902A (en) * 2010-04-09 2010-09-15 重庆大学 Oil analysis method for diagnosing equipment failure
CN105352858A (en) * 2015-11-16 2016-02-24 中国矿业大学 Image acquisition-based lubricating oil abrasive particle on-line monitoring device and work method thereof
CN205861498U (en) * 2016-08-04 2017-01-04 北京航峰科伟装备技术股份有限公司 In a kind of online oil, grain testing apparatus is polluted in abrasion
CN106483102A (en) * 2016-12-09 2017-03-08 长春市金佳光电科技有限公司 Analyser for the analyser degree on-line checking of free water in aerial kerosene and minute impurities concentration on-line checking

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
王丽晖 等: "热轧生产线液压系统油品清洁度的检测方法", 《鞍钢技术》 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110887768A (en) * 2018-09-10 2020-03-17 人本集团有限公司 Cleaning kerosene cleanliness detection method
CN110887768B (en) * 2018-09-10 2022-02-22 人本股份有限公司 Cleaning kerosene cleanliness detection method
CN109682829A (en) * 2019-02-27 2019-04-26 三一汽车制造有限公司 Oil cleanliness detection device, hydraulic machinery and oil cleanliness detection method
WO2020173028A1 (en) * 2019-02-27 2020-09-03 三一汽车制造有限公司 Oil cleanliness testing device, hydraulic machinery, and oil cleanliness testing method
CN110108536A (en) * 2019-06-18 2019-08-09 中国计量大学 A kind of standard board manufacturing method compared for settled date mirror area gray scale detection
CN110108536B (en) * 2019-06-18 2021-10-01 中国计量大学 Standard plate manufacturing method for heliostat area gray level detection and comparison
CN110813890A (en) * 2019-11-13 2020-02-21 陕西航空电气有限责任公司 Cleaning method of oil cleanliness detection equipment
CN112051204A (en) * 2020-08-14 2020-12-08 一汽奔腾轿车有限公司 Method for detecting filtering cleanliness of water-based colored paint
CN113466091A (en) * 2021-05-20 2021-10-01 浙江中控太阳能技术有限公司 Heliostat cleaning and cleanliness measuring system and heliostat cleanliness measuring method

Similar Documents

Publication Publication Date Title
CN107966449A (en) A kind of oil cleanliness detector and its detection method
US11499908B2 (en) Urine analysis system, image capturing apparatus, urine analysis method
CN110414334B (en) Intelligent water quality identification method based on unmanned aerial vehicle inspection
CN103984979B (en) The algae automatic detection counting device and method being imaged without Lenses Diffractive
CN102171541B (en) Methods and apparatus for determining a liquid level in a container using imaging
Jayakody et al. Microscope image based fully automated stomata detection and pore measurement method for grapevines
JP5132050B2 (en) Specimen imaging apparatus, specimen imaging method, program for controlling the apparatus, and specimen analyzer
CN105136795A (en) Blood sample detection device, blood sample detection method and blood sample detection system
CN102323272A (en) Filter paper defect detecting system and detection method thereof based on machine vision technique
Hortinela et al. Identification of abnormal red blood cells and diagnosing specific types of anemia using image processing and support vector machine
CN103499303A (en) Wool fineness automatic measuring method
CN111340798A (en) Application of deep learning in product appearance flaw detection
CN101685060A (en) Sample imaging apparatus
CN101750272A (en) Blood cell image recognition counting method
TWI832435B (en) Water quality monitoring system and computer-readable recording media
CN114341619A (en) Measurement accuracy and reliability improvement
CN111583185A (en) Ki67 cell nucleus counting method and system based on pathological immunohistochemistry
CN101419151B (en) Industrial pure terephthalic acid particle size distribution estimation method based on microscopic image
CN109035219A (en) FICS golden finger defect detecting system and detection method based on BP neural network
CN202177587U (en) Filter paper defect detecting system based on machine vision technology
CN107543788A (en) A kind of urine erythrocyte abnormal rate detection method and system
CN113837159A (en) Instrument reading identification method and device based on machine vision
CN115063357A (en) Method and system for detecting surface defects, electronic device and storage medium
CN110533660B (en) Method for detecting silk-screen defect of electronic product shell
CN202815869U (en) Vehicle microcomputer image and video data extraction apparatus

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20180427

RJ01 Rejection of invention patent application after publication