2008/11/12

A Puzzle on Data Relationship (Under resolve)

Q:

When we talk about data relationship, it always refers to the relationship between two entities of a data model. For example, in a traditional data model, a teacher only belongs to a department while a department has many teachers. In this case, the relationship between Teacher with Department is one to many. 

But in a WSN database, we regard a sensor note as an entity. That is, there is only a single entity here. The attributes of this entity is classified to two parts, a) the sensing data, including temperature, light, accelerometer, etc. b)the sensor status, such as battery life time, work mode (sleep / active). All these attributes are record in a same row (i.e. tuple). The network acquires the data according to the sample frequency or the query language from application layer to produce data serials. 

In a word, the data model in WSN is very simple, just like a basic Excel table. We even can not talk about anything in the data relationship, because there is only one entity. Third, when we come to the data structure that is how to compress, store and optimize the data, we will face a relationship inner data elements. 

Would you please let me know what kind of data relationship we will talk about?

A:

Try to analyse the research in broader picture. To find data relationship, you need to set up different experiment concurrently and  the raw data, that means those data from CHART. 


NP Problem, NPC Problem

什么叫做NP问题,什么叫做NPC问题?   

    首先说明一下问题的复杂性和算法的复杂性的区别,下面只考虑时间复杂性。算法的复杂性是指解决问题的一个具体的算法的执行时间,这是算法的性质;问题的复杂性是指这个问题本身的复杂程度,是问题的性质。
比如对于排序问题,如果我们只能通过元素间的相互比较来确定元素间的相互位置,而没有其他的附加可用信息,则排序问题的复杂性是O(nlgn),但是排序算法有很多,冒泡法是O(n^2),快速排序平均情况下是O(nlgn)等等,排序问题的复杂性是指在所有的解决该问题的算法中最好算法的复杂性。问题的复杂性不可能通过枚举各种可能算法来得到,一般都是预先估计一个值,然后从理论上证明。   

        为了研究问题的复杂性,我们必须将问题抽象,为了简化问题,我们只考虑一类简单的问题,判定性问题,即提出一个问题,只需要回答yes或者no的问题。任何一般的最优化问题都可以转化为一系列判定性问题,比如求图中从A到B的最短路径,可以转化成:从A到B是否有长度为1的路径?从A到B是否有长度为2的路径?。。。从A到B是否有长度为k的路径?如果问到了k的时候回答了yes,则停止发问,我们可以说从A到B的最短路径就是k。   

        如果一个判定性问题的复杂度是该问题的一个实例的规模n的多项式函数,则我们说这种可以在多项式时间内解决的判定性问题属于P类问题(Polynomial Problem)。P类问题就是所有复杂度为多项式时间的问题的集合。

       然而有些问题很难找到多项式时间的算法(或许根本不存在),比如找出无向图中的哈米尔顿回路问题,但是我们发现如果给了我们该问题的一个答案,我们可以在多项式时间内判断这个答案是否正确。比如说对于哈米尔顿回路问题,给一个任意的回路,我们很容易判断他是否是哈米尔顿回路(只要看是不是所有的顶点都在回路中就可以了)。
这种可以在多项式时间内验证一个解是否正确的问题称为NP问题(Non-deterministic Ploynomail Problem )。显然,所有的P类问题都是属于NP问题的,
所谓的非确定性是指,用极大的数量去解决来达成多项式时间解决的问题。


但是现在的问题是,P是否等于NP?这个问题至今还未解决。注意,NP问题不一定都是难解的问题,比如简单的数组排序问题是P类问题,但是P属于NP,所以也是NP问题,你能说他很难解么?   
      
    
  刚才说了,现在还不知道是否有P=NP或者P<>NP,但是后来人们发现还有一系列的特殊NP问题,这类问题的特殊性质使得很多人相信P<>NP,只不过现在还无法证明。这类特殊的NP问题就是NP完全问题(NPC问题,C代表complete)。NPC问题存在着一个令人惊讶的性质,即如果一个NPC问题存在多项式时间的算法,则所有的NP问题都可以在多项式时间内求解,即P=NP成立!!这是因为,每一个NPC问题可以在多项式时间内转化成任何一个NP问题。比如前面说的哈米尔顿回路问题就是一个NPC问题。NPC问题的历史并不久,cook在1971年找到了第一个NPC问题,此后人们又陆续发现很多NPC问题,现在可能已经有3000多个了。所以,我们一般认为NPC问题是难解的问题,因为他不太可能存在一个多项式时间的算法(如果存在则所有的NP问题都存在多项式时间算法,这太不可思议了,但是也不是不可能)。   

2008/11/06

Simple questions for sensor network.

In current project, each sensor node have a unique identifier, which has been assigned by the base station (gate way) during the initial processing. The project set up a 4*5 matrix landscape to deploy 20 sensor notes. Every sensor nodes occupy a fixed one of the twenty places, i.e., each note has a fix coordinates. 

To learn they neighbours, all nodes are required to broadcast their own positions information when the system start. After this step, each sensor node has a blueprint of the whole network’s position. 

  • How the sensor knows the target’s position? 

In previous work, each sensor node is equipped by an infrared ray. When a sensor node finds a target by infrared ray method, it will measure the distance (d1) via sonar. Next step, the current sensor node notices one of its neighbours to measure the distance (d2). Under the triangulation method, with two nodes position (x1, y1), (x2, y2) and d1, d2, we can get two possible points for the target. Considering on the target should always pass the network’s boundary from outside into inside, we can omit the point outside the deployment area. When the target starts to move, this problem becomes a tracking issue.

Note that in this work, this method assume the target is found by the boundary nodes firstly. But if we use the third sensor node, a trilateration method is useful to determine the target’s position, i.e. use three known points and three known edges to determine a node in a 2D- plane. 

All of above are proposed for 2-dimension. But here is a question that, in a concrete application, the sensors may be deployed in a 3-dimension space. In this case, to evaluate the target’s position, we should use some sensing data with direction property. 

  • How the sensors track the target currently? 

In current project, we only consider single target tracking. To detect the target in all directions, a sensor node is equipped with six sonar sensor, which been ranged in an array with a 60 degree angle. To avoid intervening, we assume that there is only one single sensor node is working in each time step. 

We use EKF to estimate the target’s route. As we know, EKF is a recursive filter, what we need is to provide some initial conditions.
The whole process can be describe as follow, when a target enter into the sensor network area, one of the boundary sensor nodes (N1) will do the first job. Use the localization method above, N1 will get the target’s position. Then it will use EKF to estimate the target’s next step, and pass all messages to one of its neighbour. The neighbour node repeats this process to hand the messages to next one.

2008/11/05

35 useful sentences for English writing ( with hong's note)

英语35个经典句型 
________________________________________
http://edu.tom.com 2004年09月01日来源:新东方教育在线

一、~~~ the + ~ est + 名词 + (that) + 主词 + have ever + seen ( known/heard/had/read, etc) 
  ~~~ the most + 形容词 + 名词 + (that) + 主词 + have ever + seen ( known/heard/had/read, etc) 

  例句:Helen is the most beautiful girl that I have ever seen. 
  海伦是我所看过最美丽的女孩。 
  Mr. Chang is the kindest teacher that I have ever had. 
  张老师是我曾经遇到最仁慈的教师。 

二、Nothing is + ~~~ er than to + V 
  Nothing is + more + 形容词 + than to + V 

  例句:Nothing is more important
than to receive education. 
  没有比接受教育更重要的事。 

三、~~~ cannot emphasize the importance of ~~~ too much. 
  (再怎么强调...的重要性也不为过。) 
  
     例句:We cannot emphasize the importance of protecting our eyes too much. 
  我们再怎么强调保护眼睛的重要性也不为过。 

四、There is no denying that + S + V ...(不可否认的...) 

  例句:There is no denying that the qualities of our living have gone from bad to worse
  不可否认的,我们的生活品质已经每况愈下。 

五、It is universally acknowledged that + 句子~~ (全世界都知道...) 

  例句:It is universally acknowledged that trees are indispensable to us. 
  全世界都知道树木对我们是不可或缺的。 

六、There is no doubt that + 句子~~ (毫无疑问的...) 
  例句:There is no doubt that our educational system leaves something to be desired. 
  毫无疑问的我们的教育制度令人不满意。 

七、An advantage of ~~~ is that + 句子 (...的优点是...) 
  例句:An advantage of using the solar energy is that it won‘t create (produce) any pollution. 
  使用太阳能的优点是它不会制造任何污染。 

八、The reason why + 句子 ~~~ is that + 句子 (...的原因是...) 
  例句:The reason why we have to grow trees is that they can provide us with fresh air. 
  The reason why we have to grow trees is that they can supply fresh air for us. 
  我们必须种树的原因是它们能供应我们新鲜的空气。    (Hong: refer to No. 20)

九、So + 形容词 + be + 主词 + that + 句子 (如此...以致于...) 
  例句:So precious is time that we can‘t afford to waste it. 
  时间是如此珍贵,我们经不起浪费它。 
     Time is so precious that we can't afford to waste it. (Hong's style)

十、Adj + as + Subject(主词)+ be, S + V~~~ (虽然...) 

  例句:Rich as our country is, the qualities of our living are by no means satisfactory. 
  {by no means = in no way = on no account 一点也不}   (Ref to No.14, By Hong)
  虽然我们的国家富有,我们的生活品质绝对令人不满意。 

 十一、The + ~er + S + V, ~~~ the + ~er + S + V ~~~ 
  The + more + Adj + S + V, ~~~ the + more + Adj + S + V ~~~(愈...愈...) 

  例句:The harder you work, the more progress you make. 
  你愈努力,你愈进步。 
  The more books we read, the more learned we become. 
  我们书读愈多,我们愈有学问。 

十二、By +Ving, ~~ can ~~ (借着...,..能够..) 
  例句:By taking exercise, we can always stay healthy. 
  借着做运动,我们能够始终保持健康。 

十三、~~~ enable + Object(受词)+ to + V (..使..能够..) 
  例句:Listening to music enable us to feel relaxed. 
  听音乐使我们能够感觉轻松。 

十四、On no account can we + V ~~~ (我们绝对不能...) 
  例句:On no account can we ignore the value of knowledge. 
  我们绝对不能忽略知识的价值。 
     account for : 

十五、It is time + S + 过去式 (该是...的时候了) 
  例句:It is time the authorities concerned took proper steps to solve the traffic problems. 
  该是有关当局采取适当的措施来解决交通问题的时候了。 
     (Hong: 虚拟语气,本该)
  
十六、Those who ~~~ (...的人...) 
  例句:Those who violate traffic regulations should be punished. 
  违反交通规定的人应该受处罚。 
  
十七、There is no one but ~~~ (没有人不...) 
  例句:There is no one but longs to go to college. 
  没有人不渴望上大学。 

十八、be + forced/compelled/obliged + to + V (不得不...) 

  例句:Since the examination is around the corner, I am compelled to give up doing sports.   
  既然考试迫在眉睫,我不得不放弃做运动。 

十九、It is conceivable that + 句子 (可想而知的) 
  It is obvious that + 句子 (明显的) 
  It is apparent that + 句子 (显然的) 

  例句:It is conceivable that knowledge plays an important role in our life. 
  可想而知,知识在我们的一生中扮演一个重要的角色。 
  
二十、That is the reason why ~~~ (那就是...的原因) 

  例句:Summer is sultry. That is the reason why I don‘t like it. 
  夏天很燠热。那就是我不喜欢它的原因。 

二十一、For the past + 时间,S + 现在完成式...(过去...年来,...一直...) 

  例句:For the past two years, I have been busy preparing for the examination. 
  过去两年来,我一直忙着准备考试。 
     (Hong: 倒装而已)

二十二、Since + S + 过去式,S + 现在完成式。 

  例句:Since he went to senior high school, he has worked very hard. 
  自从他上高中,他一直很用功。 

二十三、It pays to + V ~~~ (...是值得的。) 

  例句:It pays to help others. 
  帮助别人是值得的。 

二十四、be based on (以...为基础) 

  例句:The progress of the society is based on harmony. 
  社会的进步是以和谐为基础的。 

二十五、Spare no effort to + V (不遗余力的) 

  We should spare no effort to beautify our environment. 
  我们应该不遗余力的美化我们的环境。 
     (Hong: This no is interesting.)

二十六、bring home to + 人 + 事 (让...明白...事) 

  例句:We should bring home to people the value of working hard. 
  我们应该让人们明白努力的价值。 

二十七、be closely related to ~~ (与...息息相关) 
  例句:Taking exercise is closely related to health. 
  做运动与健康息息相关。 

二十八、Get into the habit of + Ving 
  = make it a rule to + V (养成...的习惯) 

  We should get into the habit of keeping good hours. 
  我们应该养成早睡早起的习惯。 

二十九、Due to/Owing to/Thanks to + N/Ving, ~~~ (因为...) 
  例句:Thanks to his encouragement, I finally realized my dream. 
  因为他的鼓励,我终于实现我的梦想。 

三十、What a + Adj + N + S + V!= How + Adj + a + N + V!(多么...!) 

  例句:What an important thing it is to keep our promise! 
  How important a thing it is to keep our promise! 
  遵守诺言是多么重要的事! 

三十一、Leave much to be desired (令人不满意) 
  例句:The condition of our traffic leaves much to be desired. 
  我们的交通状况令人不满意。 

三十二、Have a great influence on ~~~ (对...有很大的影响) 
  例句:Smoking has a great influence on our health. 
  抽烟对我们的健康有很大的影响。 

三十三、do good to (对...有益),do harm to (对...有害) 
  例句:Reading does good to our mind.读书对心灵有益。 
  Overwork does harm to health.工作过度对健康有害。 

三十四、Pose a great threat to ~~ (对...造成一大威胁) 
  例句:Pollution poses a great threat to our existence. 
  污染对我们的生存造成一大威胁。 

三十五、do one‘s utmost to + V = do one‘s best (尽全力去...) 
  例句:We should do our utmost to achieve our goal in life. 
  我们应尽全力去达成我们的人生目标


2008/11/03

Thinking Big About Tiny Databases (UC Berkeley)

This paper introduces the current work on tiny database from UC Berkeley. 

Early “tiny databases” provide high-level languages to maintain data without worrying about low-level details regarding how the data is collected or processed. 

The latest (2007) refinements from TinyDB group include:

  • Declarative network programming.

The UC Berkeley has implemented a P2 system, which is a overlay network uses a high-level declarative language to express overlay networks in a highly compact and reusable form.

Because of the difficulty of programming in sensor networks, the declarative sensor network (DSN) is proposed to simpler the program. It simply a) power management, b) network design, and c) data management. In the other hand, it is reusable. We can write the same code to each senor node and add it to an existing network quickly.

The open research issues including a) query optimization – they are designing a declarative meta-optimizer for P2 and DSN, b) heterogeneous sensornets, c) power management, and d) distributed statistical methods, e.g. Bayesian Belief Propagation

  • Sophisticated signal-oriented programming languages.

Take the following acoustic application for an example, using FFT operator, we convert high data rate audio singles into the frequency domain to identify frequencies that are characteristic of the objects being tracked. When such frequencies are detected, we can apply beamforming algorithms to perform triangulation for tracking purpose.

The UC Berkeley has developed a programming language called WaveScript and a sensor networkruntime system called WaveScope. Under WaveScript and WaveScope, the programmer can perform complex signal and data processing operators on sensor data directly without considering details of networking protocols. 

  • Support for large-scale sensing applications.

There is a so-called High Fan-in (HiFi) system which is programmable with a uniform, declarative, data-centric language. In this system, they develop a virtual device interface to avoid the complexity of the underlying devices. Also, HiFi will deal with the multiple queries in the hierarchical HiFi environment. 

  • Support for mobility and intermittent connectivity.

Sensor networks are dynamical, i.e. there always are small changes in connectivity because of the nodes failure, work mode switch on/off. If it is a bad connectivity, the bandwidth of network will become smaller, the data transfer will be clogged. 

They build a new data management component called ICEDB (for Intermittently Connected Embedded Data Base) to solve the mobility issue. Through ICEDB, users can assign both local and global priority to determine the data transfer order. Under the control of different priorities, each data package can be transferred in a suitable serial.

Everyday Words


Everyday Words


By Hong Wenxing

  • light up / illuminate
  • rush-hour / peak 
  • picture / photograph
  • spectator / observer / a single member of audience /auditorium / lecture theater / spectacular 
  • anniversary / annual / yearbook / journal / diary / quarterly / monthly / weekly / daily /
    inauguration ceremony / rehearsal / celebrate
  • terrorist attack 
  • Muslim / mosque / Ramadan / cathedral / Jerusalem 耶路撒冷 
  • boulevard / tower / square / path / lane / trail
  • artist / sculpture / iconic / artwork / portrait 
  • flanked by the concert hall at right and the *** at left / beside / behind / before / in front of / amid 
  • pedestrian / vehicle / zebra crossing / helicopter 

  • annotation / denote / indication /
  • reside / settle down/
  • interval
  • Histogram / plot / chart / scatterplot /
  • mere / only / His diligence is a mere pose.
  • entertain /
  • place emphasis on group dynamics rather than individual prowess
  • dedicate to / dedicated a. 
  • paddle the boat along the banks 
  • border city  边境城市
  • goggles / plunge into / glimpse/ peer 
  • oncoming 即将来的 / ongoing (in process) 
  • peninsula / island / land 
  • surreal / real 
  • parade through / march across /
  • participate in / participant 
  • strength / sophisticated  / novel / significant
  • approximate (a.) 
  • precision / touted / 
  • prevent / preventative / prevention / 
  • in particular 
  • recursive
  • radically / fully 
  • homogeneous / heterogeneous 
  • UNESCO World Heritage Site / United Nations Educational, Scientific and Cultural Organization / a complex of ruins
  • storm / storm-battered Yemen / heavy storm / wind / rain / lighting / flooding /
    fierce / ferocious / devastating 
  • crash through / sweep / slam / hit
  • debris / rubble /damage /disaster zone / collapse / strand 
  • aerial view / eagle eye
  • possession / poverty / property / belonging / impoverish / 
  • character / characteristically / characterize / characteristic /
  • demonstrate / describe / illuminate / 
  • asynchronous / synchronous /
  • notoriously / famous / infamous 
  • to date / state-of-the-art
  • acclimate / acclimatize / acclimation / The Peru Rocks team gathered and acclimatized at this town before their climb to Machu Picchu Mountain on Oct 20th, 2008.
  • snowcapped mountain / night scene / campsite / treasured site /
  • trek / trekker / destination / 
  • dedicate to / dedication / 
  • finale concert 
  • ward / chemotherapy /


2008/10/24

Deploy my first wireless sensor network.

1.                 I just deployed my first wireless sensor network.

            Here are some comments for this job.

Hardware

The gateway (base station) is MIB520, the sensor node is MICAz, and the sensor board is MTS310. The frequency is 2.4 GHz. The communication protocol is Zigbee.

I installed MIB 520 through USB hub, and it brought me two virtual com ports. Use this MIB board, I wrote the initiation XMesh program to set up node0 (base station), and node1-2.

Software

There are 3 software tiers in my installation, first for Mote Tier, 2nd for Server Tier, and the last one for client tier. I got them from the latest MoteView (v 2.0) from Xbow website.

Data acquisition from sensor notes.

XServer run in my local PC to serve as a base station. The database we use to collect data is PostergreSQL.

Use MoteView to start XServer, and connect the sensor nodes online, we can get the data from each node, including voltage, temperature, light and so on. The server logs show us that, it use a standard INSERT statement to insert data rows to DB.

Query: INSERT into mts310_results (result_time,nodeid,parent,voltage,temp,light,accel_x,accel_y,mag_x,mag_y,mic) values (now(),2,0,444,510,857,451,465,791,206,446)

How to track a target?

I am studying KF to know how to track a target.

 

2.                 The Database Model in Application Layer.

There are some distributed database model and management system including TinyDB, Cougar, Dimensions have been proposed. I compared these three models in the attached slides.

In my opinion, the signal processing related with physical layer while database (NOT data) model lies on application layer.

Attachment 2 is a latest paper from TinyDB group. Do you think it is more suitable for me than signal processing?

2008/10/14

To clear my research boundary

1.                   Data acquisition


1.1     What is data acquisition?

Data acquisition (DAQ, DAS for short) is the sampling of the real world to generate data that can be manipulated by a computer.

It consists of acquisition of signals and waveforms and processing the signals to obtain desired information.

 

1.2     How to acquire data?

Step 1: Set up an object we want to investigate, e.g. an island.

Step 2: Determine which physical phenomenon or physical property of the object investigated will be measured, e.g. temperature or temperature change.

Step 3: Use some sensors (i.e. transducers) to measure.

Step 4: We will get digital/analog signals, i.e. raw signals.

Step 5: Signal conditioning is necessary if the raw signals are not suitable for DAQ hardware.

Step 6: There is a DAQ hardware connected with PC to get the dataset (signals). Also, there is software (e.g. LabView of NI) allows the OS to recognize the DAQ hardware and program to access the signal being read by the hardware.

Step 7: We can use MATLAB to do signals processing.

 

2.                   Data Analysis and Data mining

Data analysis is the process of looking at and summarizing data with the intent to extract useful information and develop conclusions.

Data mining tends to focus on larger data sets, with less emphasis on making inference, and often uses data that was originally collected for a different purpose.

 

3.                   Data Model

3.1     What is Data Model?

A data model in software engineering is an abstract model that describes how data is represented and accessed.

In database model theory, there are four kinds of data model, i.e. Flat model, Hierarchical model, Network Model and Relational Model. There are many other kinds of data model for different purpose. For example, in Geographic Data Model, some special model proposed to make up 2D and 3D maps.

Also, in WSN, we need to develop a new data-driven model to suit for the limited energy and communication resource.

3.2     How many kinds new Database Management has been proposed for WSN?

(1)     Tiny DB from Univ. of California, Berkeley.

        The Design and Evaluation of a Query Processing Architecture for Sensor Networks

(2)     Cougar from Cornell University.

                        Query Processing for Sensor Networks

(3)     DIMESION from University of California, Los Angeles

       DIMENSIONS: Why do we need a new Data Handling architecture for Sensor Networks?

3.3     What is the relationship between DB Model and Data Acquisition?

In Data Acquisition System, we use hardware to acquire data from sensor networks. Between Step 3 and 4 of last section, we should determine which data should be collected? What kind of model will be used when they acquired by the machine?

Actually, due to the computation ability of WSN nodes, we will pre-process the data before they were acquired by the hardware, i.e. prior to signals.

 

Reference: http://en.wikipedia.org/wiki/Data_acquisition

http://www.adinstruments.com/products/data-acquisition/corporate/

2008/10/06

BondMaster for NDT

What I have done these days?
  • 1. Search and read more materials regarding BondMaster. 
Especially, an application guide downloaded from Olympus website show me five inspection methods including,
(1). Pitch-Catch Test Mode
  • (1a) Pitch-Catch RF Method
  • (1b) Pitch-Catch Impulse Method
  • (1c) Pitch-Catch Swept Method
(2). MIA Mode
(3). Resonate Mode.
Comparing with the thesis, both of them explain the theories and give me some examples.
Currently, I have a general comprehension on Non-Destructive Testing.

  • 2. Read and learn your Matlab code.
I have read your Matlab code and learn the functions. I have to start from the scratch to recall much minor knowledge, such as what is FFT or when we should use it. Basically, I can explain your code myself as below:
(1) Load the data from .mat file, declare 1st column as input, 2nd as output.
(2)Apply a high pass filter to output.
(3)Use FFT to output;
(4)Repeat the process to each specimen.


  • Current questions and difficulties:
1. I am a little puzzled about Numerical Analysis and Signal Processing, both of them are not similar for me.  Would you please tell me what is the field of our current topic?

2. I should brush up much knowledge to push my research. Would you please let me know what is urgent?

3. Here are some questions for you. Thanks for your kindly reply:

Q1. What are the data we acquired from BondMaster stand for?
There are two columns in the data file for each Exp0…Exp9. You declare the first column as input(x), while the second one as output(y).
But according to the thesis, we use probe tips to touch the specimens, then the instrument give us back some signals, such as the phase and amplitude. How we can acquire these data? What kind of data in start_m.mat have recorded?

Q2. What do the original Time-Data plots (Page 4 of slides) stand for?
The X axes maybe time. What do Y axes stand for? Input(x) or output(y)?

Q3. How can I use my own data? What’s the difference between them and yours?
My own data only contains position info (x, y position). They are different with yours, and maybe not suitable for inspection.
Attachment is an excel I got from our current equipment in my lab. Please take a look.

Next, I will
I am going to try my best to write a little paper base on the materials you send me. An outline will be proposed soon.

Questions waiting for answer.
Q4. How to introduce the project to others? What is the main process of this project?
We fabricated 12 different specimens to simulate the composite in F-16. Use these specimens, we The Non-Destructive Testing(NDT)
(1) We fabricated 12 specimens.
(2) Use Bond
Q5. What is Fourier series? What is FFT? When we should use FFT?
Q6. What is the outline/structure of this paper?

2008/10/02

Report on “Non-destructive inspection of aircraft structures”

What I have done these two days are:
Review the project report from Mr. /Miss. Tan. I paid much more attention to 1)Introduction; 2)Literature Review; 3)Results and discussion; 4) conclusion and recommendation.

This work helps me to
1) recall some basic knowledge regard signal process. But I need more time to clear up this part;
2) learn the information about Sonic BondMaster with its four modes of testing ( Resonance Test, Pitch/Catch Swept and Impulse, MIA)
3) know the general technical operation procedures of testing including specimens fabrication and inspection procedure.


There are some questions needs your kindly reply:
Q1) what is loaned NI system? What is the relativity with Sonic BondMaster? How can you acquire the data set?
Q1) we used the National Instrument (NI) equipment to record the data, this is call BondMaster equipment. We have the machatronic lab in Level 1 to for the experiment.

Q2) the test specimens are same as those in last report on Sonic BondMaster, right?
Q2) Test Specimen is the same. If you would like to have a look, I can show it to you. 

Q3) the first step is data acquisition and analysis. Would you please let me know some detailed topics?
Q3) I used different signal processing techniques, such as wavelet, hulber huang, FFT, Stastical analysis…….The option is open.

Q4) what does “data model” mean you mentioned last time. I got my own data in my lab. It is produced by a program and saved in a .txt file. The records are serials of distances(x, y position) and Sensor Nodes ID. It seems different with those for defects detection.
Q4) Maybe you can send me the data, relevant figures, picture. I will have a look. And tell me what data is that.

What I am going to do next:
 Try to read the .m file in Matlab to discovery some more information.