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扫描电子显微镜

Scanning Electron Microscope

 
 
 
 
 

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扫描电镜应用之:颗粒度分析  

2011-02-25 17:20:54|  分类: 默认分类 |  标签: |举报 |字号 订阅

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Particle Characterization and Sizing 颗粒特征描述及标准化
Scanning Electron Microscopy (SEM) 扫描电子显微镜

Utilizing Automated Electron Beam and Automated Feature Analysis (AFA) Software 利用自动电子束和自动的特征分析软件进行颗粒计数和颗粒特征描述

For Particle Counting and Particle Characterization

  

Introduction:介绍

In recent decades oil analysis laboratories have used automatic particle counters to determine the number and size of particles in many oil wetted systems.  Once determined, there has been the question of what are they?  The logical next step was to look at the metals analysis or extract them onto a filter membrane and view them under magnification.  Characterizing the make-up of the particles is very useful in determining the source.  Once the type of particles was determined a cost effective action plan could be undertaken to rectify the problem.  The problem with these two approaches is; the metals analysis is often unreliable in identify larger particles and; under optical magnification it is not possible to tell for sure the make up of the particles.
     最近几十年,油品分析实验室已经使用自动颗粒计数装备来确定在许多湿油系统中的颗粒的数量和尺寸。一旦决定,有一个这些颗粒是什么的问题?下一步必然要考虑金属分析或者把这些颗粒用过滤膜提取并且放大观察。描述出粒子的构成对于判断粒子来源是非常有用的。一旦断定粒子的类型,接下来可以形成一个很好成本效益的行动计划将会用来改善问题。金属分析在鉴定大量颗粒时经常不可靠,光学显微镜下放大不可能辨别出确定的颗粒成分组成,这两个途径都存在问题。

 In some cases SEM analysis was undertaken to further identify the particles.  This proved to be time consuming for the SEM operator and it was left to the operator to judge which areas of the sample to investigate.
       在某些情况下,扫描电镜被用来进一步对颗粒进行分析。对于扫描电镜操作者来说,已经被证明是非常耗费时间的,留给操作者来判断样品的哪些区域需要检测。

This report illustrates the performance and innovative approach to resolving the aforementioned limitations on sizing and identifying particles using an “Automated Electron Beam Particle Analyzer” equipped with “Automated Feature Analysis” (AFA) software to characterize complex matrix of particles extracted onto a membrane filter from oil samples. 
       本文阐述使用自动电子束颗粒分析器,配备自动特征分析软件来表征复杂的用过滤膜从油样品中提取的粒子模型,在颗粒定形和识别方面解决前述问题的局限性的性能和创新方法。

 Conclusion:  The SEM/AFA analysis offers the analyst a superior method of determining the size and make up of particles in lubricating oil, grease, filters
        结论:扫描电镜/自动特征分析为分析师提供一个确定在润滑油、润滑脂、过滤器和过程材料中的粒子尺寸和构成的超级分析方法。通过这个认识和适当的手段,而不必再去推测,不对称的花费,可以为工厂节省大量开销。and process materials.  This knowledge and appropriate actions can save a plant thousands of dollars in needless speculation and inappropriate expenditure.

Methods:

In the case studies Automated Feature Analysis (AFA) was performed using the Rotating Chord Analysis algorithm to determine Size, Shape, Number and Type of particles > 4 um that were on the surface of a filter sample.  Most often, prior to analysis, a liquid sample was filtered on 0.45 ?m pore filter membrane. Once analyzed, Tabular Reporter is used to mine the data, and determine the best way to interpret and visualize the data. Microsoft Excel? is used to do graphical representations of tabular data. Each filter when analyzed is divided into stage movements and electronic fields. The electron beam analyzers do not take an image and then processes/analyzes the image; rather it is a dynamic scanning of the filter. When a particle is located based on a defined signal change, the system stops the scan and acquires an Energy Dispersive Spectroscopy (EDS) spectrum. The spectrum is analyzed in real-time to provide the elemental composition of the individual particle.  Table 2 provides “Guaranteed Performance Characteristics”.
      

Definitions:

 Dmax: The maximum detected diameter of a particle. See figure below.

 Dperp: The diameter perpendicular to Dmax. See figure below.

 Aspect Ratio: The Aspect Ratio is defined by dividing the Dmax by Dperp.

  

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

                                    

Dperp

 

Dmax

Detected Particle

 Rotating Chord Algorithm (RCA)

Description: Rotating chord is a computer algorithm which uses a two-step “Detect-and-Measure” mode. The Detect mode allows the instrument to search and detect when a feature/article is present, or not, on the surface of the membrane patch based on atomic number contrasting using backscatter electrons. Once the feature/particle is detected the instrument switches automatically to the Measure mode. In RCA, the electron beam of the instrument rasters across the particle in lines that are called “chords”. These chords determine the center of the particle and the size and shape of the particle, by effectively drawing a series of chords which encompass the particle (See Figure 1). RCA provides different characterization parameters which commonly are used to determine the types of particles in a sample.                                                                                

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

 

 Figure 1.  Rotating Chord Analysis.

16 Chord illustration of how RCA determines the size

                                                                                       and shape of a particle ( DMAX 80 ?m)

                                                                  
Table 1 Lists possible parameters that are determined by RCA.

 Table 1 Definitions (41 Categories are available)


Name

Unit

Description

DAVE

?m

The average length of the sixteen chords through the feature centroid

DMAX

?m

The length of the longest of the sixteen chords through the feature centroid (Image #1)

DMIN

?m

The length of the shortest of the sixteen chords through the feature centroid (Image #2)

DPERP

?m

The length of the chord perpendicular to the longest chord (Image #3)

ASPECT

1

The ratio of DMAX/DPERP

AREA

?m2

The area of the feature

PERIMETER

?m

The perimeter of the feature as measured from one   chord end to the next (Image #4)

ORIENTATION

Degrees

The orientation of the longest chord. Zero is at noon and the angle increases clockwise


 

 

Table 2 - Guaranteed Performance Characteristics**


                 

Particle Detection Efficiency

Greater than 99%

Particle Sizing Precision

0.25 microns or better

Particle Sizing Accuracy

0.50 microns or better

Occurrence of False Positives

Less than 1 per mm2

Particles Sized per Hour

Up to 33,000

Particles Characterized per Hour

Up to 1,800


** Performance as measured using Performance Grading Software TM

for features 1 to 100 ?m

                    

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

 

                                                                      IMAGE #1                                                               IMAGE #2

 

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

                                                                         IMAGE #3                                                                       IMAGE #4

  Rules for Particle Characterization:

Initially the area of interest on the membrane filter is defined.  This can range from 100% of the effective area or as little as 1%.  The selection is usually based on the level of detail required for a thorough analysis vs. time and budget considerations.  The system is then set up to determine what size particles are of interest and in what ranges (bins).  After these decisions have been made the analysis can begin.  The system scans (rasters) the filter in as little as 0.5 micron if desired.  Once complete the results of the analysis can be viewed by the operator.  At this point the operator decides what particles are on interest.  The analysis rules can now be written and the data obtained and presented to the client.

 

In Case Study #1 the Rules are shown in Table #3.  After scanning the filter is was determine that the majority of the particles had the elements described in the Rule.  

Tin and iron being the most dominate, but certainly other particles and alloys were present.  So, the Rule was made requesting number and size of particle containing the elemental proportions in the Rule.

Table# 3


Classification

Rule

% Content

Stainless Steel

Fe > 30% and Cr > 5%

1.7%

Iron

Fe  > 30%

33.9%

Tin

Sn > 30%

49.0%

Silicates

Si > 5%

1.4%

Brass

Cu+Zn+Sn > 35%

6.6%

Sodium

Na > 10%

2.6%

Miscellaneous

All remaining particles

4.8%


CASE STUDY #1

SEM/AFA

January 9, 2007


Customer:  

Nuclear Power Plant
Description of Sample:  Containment Spray #1 - #1 Motor Inboard ID: 3485 6:31:23 AM MRSR# DB-2612 

Background:  Due to the critical nature of the application the client samples the Containment Spray Motors about every month.  The standard test package includes metals analysis, particle count and physical properties testing.  The particle count for this motor bearing oil had been consistently higher than all of the other motor of the same make and model (ISO Code 4406 = 21/18/14 vs. 16/14/10).  There was no indication of silicon or wear metals by the emission spectroscopy. 

 It was very important for the root cause investigation to determine what these particles were and their sizes.  It was decided to employ the SEM/AFA to resolve

any doubt in the analysis.

 Sample Preparation:  5 ml of thoroughly mixed oil was diluted in heptane solvent and drawn through a 0.45 um filter. 

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

SEM Observing conditions:  The specimen was observed under reduced vacuum at 15keV of beam energy to perform automated feature analysis on a non-conductive substrate.  Working distance was approximately 16 mm to facilitate x-ray spectroscopy.

General observations:  Approximately 9.5% of the surface area of the filter was analyzed with the automated process.  5618 particles were identified and classified by chemical composition and size.  This extrapolates to 1,182,740 total particles per 100 ml, which is approximately 6.67% lower than indicated by HL-1185 particle count.  The difference is mainly due to the way the two processes account for particles of less than 4 um in size. 

 Most debris in the sample is dominant in tin or iron.  The tin dominant material displays as a range from nearly pure tin to various brass-like mixtures with copper, zinc and lead. The iron-dominant particles are mainly a low chromium alloy or oxides, however about 5% of the iron particles contain greater than 5% chromium.

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

Graph 1- Shows the predominance of particle composition found in the sample

The particles were classified by chemical composition to sort out the most frequently appearing particle types. 

TABLE 1


Classification

Rule

% Content

Stainless Steel

Fe > 30% and Cr > 5%

1.7%

Iron

Fe  > 30%

33.9%

Tin

Sn > 30%

49.0%

Silicates

Si > 5%

1.4%

Brass

Cu+Zn+Sn > 35%

6.6%

Sodium

Na > 10%

2.6%

Miscellaneous

All remaining particles

4.8%

Table 1- Lists the classifications, their definitions and the relative percentages of each in the specimen.

 

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

 

Case Study #2
                       December 8, 2006
       Customer:  Coal Fired Power Generation
       Sample Description:  Pulverizer Gear Box, ISO VG 150
       Sample Preparation:  20 ml of thoroughly mixed oil was diluted in heptane and drawn through a 0.45 um nitrocellulose filter, followed by thorough rinsing with heptane.
       Analysis Parameters:  100% of the exposed filter area was searched with a criteria to find all particles of 4 um and greater in dimension.  15 keV beam energy and reduced vacuum were used with a backscatter electron detector. 

Summary of Findings:  A total of 2083 particles were identified on the filter.  Eight general categories of particles were identified based on their chemical composition.  The particles are identified and separated out of the group in the top to bottom order listed in the below table according to the listed criteria.  The criteria were selected based on the dominant patterns of chemical distribution in the 2083 particles.

Category Name

Criteria

Fe, Cr

Iron rich (>50%) with Cr >5%

Iron Rich

Fe >50%

Al

Al >60% and Si <5%

Si, Mg

Mg >7.5% and <27.5% and Si >20%

Si Rich

Si >60%

Silicates

Si >20%

Misc. Na

Na >50%

Misc.

Remaining particlesParticle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

This is a summary of the particles found, sorted by classification:

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

 

The table below shows the particles sorted by classification and ISO 4406 particle size criteria.

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---
 
The chart below shows the top % elemental composition by average for each of the listed elements in the 10.67% miscellaneous classification.

 Mining the Data:

The table below shows key parameters for a typical analysis.  There is far too much data to present it all here 285 Particles counted with 41 different categories of particle characteristics.  However, this table illustrates that you can easily sort by parameters of interest.  In this case we sorted on DMAX (descending). However, DAVE , the average length of all 16 Chords is the definition of the “particle size”.

It is clear these data show the particles are:

a. On average the particles are oblong due to their ASPECT ration of ~2.

b. The particles are primarily iron and silicates.

c. The average size is 59 ?m (DAVE).

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔--- 

ASPECT Ratio:  The aspect ratio gives information about the relationship of the length of a particle to the width.  Illustrated below are seven different aspect ratios ranging from 1 to 7.  If each square below represents a particle with an aspect ratio of 1 (DMAX/DPERP) you can see, the higher the aspect ratio the longer and narrower a particle is in size.  Examples of particles with large aspect ratios are cutting wear particles or fibers.  However, the aspect ratio is not always indicative of cutting wear.  We have demonstrated that different alloys produce cutting wear particles with aspect ratio nearing 1.  The alloy of 310 Stainless is an example of a alloy that forms low aspect ratio cutting were particles

 

Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---Particle Characterization and Sizing - 驰奔 - ---DEMA 驰奔---

 

 

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