CN106935098B - Using the working method of the distributed Internet of Things experience system of ultrasonic sensor - Google Patents
Using the working method of the distributed Internet of Things experience system of ultrasonic sensor Download PDFInfo
- Publication number
- CN106935098B CN106935098B CN201710360683.5A CN201710360683A CN106935098B CN 106935098 B CN106935098 B CN 106935098B CN 201710360683 A CN201710360683 A CN 201710360683A CN 106935098 B CN106935098 B CN 106935098B
- Authority
- CN
- China
- Prior art keywords
- capacitance
- voltage
- internet
- things
- measured capacitance
- 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.)
- Expired - Fee Related
Links
Classifications
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B23/00—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes
- G09B23/06—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for physics
- G09B23/18—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for physics for electricity or magnetism
- G09B23/188—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for physics for electricity or magnetism for motors; for generators; for power supplies; for power distribution
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Algebra (AREA)
- Power Engineering (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to a kind of working methods of distributed Internet of Things experience system using ultrasonic sensor, include: several by U-shaped installation walled at real training between, and the inner wall surface for installing wall is divided into several debugging areas, each debugging area for installing homologue networking module group respectively, to carry out networking test；The rear end of each Internet of Things module is equipped at least two plugs in Internet of Things module group, and several mounting holes are distributed in metope, and plug and mounting hole cooperate, to install each Internet of Things module；The rack for placing network server is additionally provided in real training.The present invention can be according to their own needs, Internet of Things practical training project is opened up in corresponding defined area, pass through the corresponding module in each Internet of Things module group, simulate true scenes of internet of things, and each module any can extend, and be cooperated by the mounting hole and plug of installation wall, and the module for enabling student to use needs is installed, Internet of Things is accordingly expanded, improves teaching result.
Description
Technical field
The present invention relates to a kind of experience systems, and in particular to a kind of distribution Internet of Things experience system and its working method.
Background technique
Internet of Things is passed by information such as radio frequency identification (RFID), infrared inductor, global positioning system, laser scanners
Sense equipment is connected any article with internet by the agreement of agreement, carries out information exchange and communication, to realize to article
Weigh sensor, positioning, tracking, monitoring and a kind of network of management.Generally, Internet of Things is that Sensor Network adds internet,
It is the extension and extension of internet, interpersonal interconnect is expanded to interconnecting between people and object, object and object.
The key technology of Internet of Things includes: sensor technology, Internet technology, Intelligent treatment technology.
Currently, under the background for applying technology of Internet of things energetically, the construction of colleges and universities' Training Room also obtain new visual angle with
It edifies.Numerous colleges and universities have all opened up Internet of Things course, and IT application in education sector service provider also both provides Internet of Things Training Room
Solution, still, stage of the construction greatly all in embedded Training Room of the Internet of Things Training Room of each colleges and universities, only with
The form of Internet of Things experimental box builds Internet of Things Training Room, lacks comparatively true Training Room and carries out technology of Internet of things
Study, certainly also there is no the Internet of things system set up based on true internet of things equipment, then relevant speciality
Student can not really grasp the study of Internet of Things.
Summary of the invention
The object of the present invention is to provide a kind of distributed Internet of Things experience system, which passes through to each object
Networking module group is laid out division and solves student when carrying out Internet of Things real training, and the chaotic technology of networking building layout is asked
Topic.
In order to solve the above-mentioned technical problems, the present invention provides a kind of distributed Internet of Things experience systems, comprising: several
By U-shaped installation walled at real training between, and the inner wall surface for installing wall is divided into several debugging areas, and each area of debugging for installing respectively
Homologue networking module group；The rear end of each Internet of Things module is equipped at least two plugs, the wall in the Internet of Things module group
EDS maps have several mounting holes, and the plug and mounting hole cooperate, to install each Internet of Things module；It is additionally provided in the real training
For placing the rack of network server.
For the ease of carrying out the related experiment course of capacitance detecting, the distribution Internet of Things experience system further include: use
In the experimental provision of building capacitor on-line checking, which includes:
Ultrasonic sensor, for acquiring the voice signal of measured capacitance generation, to obtain corresponding capacitor sound pressure level Lpx。
High Frequency Current Sensor, for acquiring the voltage vector at capacitor both ends.
The ultrasonic sensor, High Frequency Current Sensor pass through corresponding data conditioning unit and data processing and control respectively
Unit is connected.
The data processing control units, comprising:
Capacitor superimposed voltage computing module, suitable for the voltage vector of acquisition is decomposited fundamental voltage u0(t) and nth harmonic
Component of voltage un(t), that is, the superimposed voltage u (t) at the measured capacitance both ends, i.e. u (t)=u0(t)+un(t), the superposition is calculated
The virtual value U of voltage, while calculating the virtual value U of fundamental voltage0。
Capacitance computing module, establishes capacitor sound pressure level database, includes: all types of capacitors in the database only each
Capacitor sound pressure level corresponding to the virtual value of fundamental wave；Default measured capacitance type, rated capacitance C0, according to measured capacitance type
And the virtual value U of current fundamental voltage0Corresponding capacitor sound pressure level L is obtained from the capacitor sound pressure level databasep0；Pass through tested electricity
Hold the voice signal generated, to obtain corresponding capacitor sound pressure level Lpx, pass through formulaIt calculates tested
The actual capacitance C of capacitorx。
Measured capacitance service life computing module, suitable for the actual capacitance C according to measured capacitancexWith the virtual value of superimposed voltage
U establishes capacitance predictor formula, i.e. C=Cx-kUt；Wherein, C is extreme capacitance values when measured capacitance is damaged, and t is capacitor damage
Bad expeced time, k be the unit time in measured capacitance current fundamental voltage virtual value U0Under corresponding electric capacitance change system
Number, that is,Wherein, Cx1And Cx2For the capacitance initial value and final value of measured capacitance in the unit time；And pass through
The capacitance predictor formula derives the calculation formula of capacitance damage t expeced time, i.e.,Set the limit electricity
Capacitance C, to calculate the expeced time that measured capacitance is damaged.
Further, the nth harmonic component of voltage un(t) n takes 5 in.
The present invention also provides a kind of working methods of distributed Internet of Things experience system, wherein the distribution Internet of Things
Net experience system further include: for constructing the experimental provision of capacitor on-line checking,
The working method of the experimental provision includes the following steps:
Step 1: the voltage vector at acquisition measured capacitance both ends, and the voltage vector is decomposited into fundamental voltage u0(t) and
Nth harmonic component of voltage un(t), the superimposed voltage u (t), i.e. u (t)=u at you can get it measured capacitance both ends0(t)+un
(t), the virtual value U of the superimposed voltage, the virtual value U of fundamental voltage are then calculated0；
Step 2: establishing capacitor sound pressure level database, include: in the database all types of capacitors with only each fundamental wave
The corresponding capacitor sound pressure level of virtual value.
Default measured capacitance type, rated capacitance C0, according to measured capacitance type and the virtual value U of current fundamental voltage0
Corresponding capacitor sound pressure level L is obtained from the capacitor sound pressure level databasep0。
The voice signal that measured capacitance generates is acquired, to obtain corresponding capacitor sound pressure level Lpx, pass through formulaCalculate the actual capacitance C of measured capacitancex。
Step 3: according to the actual capacitance C of measured capacitancexCapacitance, which is established, with the virtual value U of superimposed voltage estimates public affairs
Formula, i.e. C=Cx-kUt；Wherein, C is extreme capacitance values when measured capacitance is damaged, and t is capacitance damage expeced time, and k is unit
Virtual value U of the measured capacitance in current fundamental voltage in time0Under corresponding electric capacitance change coefficient, that is,
Wherein, Cx1And Cx2For the capacitance initial value and final value of measured capacitance in the unit time.
The extreme capacitance values C is set, the meter of capacitance damage t expeced time is derived by the capacitance predictor formula
Formula is calculated, i.e.,To calculate the expeced time that measured capacitance is damaged.
The above technical solution of the present invention has the following advantages over the prior art: (1) present invention can according to oneself
It needs, Internet of Things practical training project is opened up in corresponding defined area, by the corresponding module in each Internet of Things module group, simulation is true
Real scenes of internet of things；And each module any can extend, and be cooperated by the mounting hole and plug of installation wall, enable student
Enough modules easily used to needs are installed, i.e., are accordingly expanded to Internet of Things, improve teaching result；(2) originally
Invention acquires the capacitor sound pressure level that measured capacitance generates by ultrasonic sensor；High Frequency Current Sensor acquires capacitor both ends
Voltage value establishes capacitance predictor formula, is predicted using service life of the formula to measured capacitance, than traditional only detection
Capacitance present actual capacitance is more forward-looking to judge the capacitor service life, and can open up electric power by the experimental provision
Electron Technique Course has reference value to the assessment of electric capacitor.
Detailed description of the invention
In order to make the content of the present invention more clearly understood, below according to specific embodiment and in conjunction with attached drawing,
The present invention is described in further detail, wherein
Fig. 1 is the structural schematic diagram in Internet of Things experience system of the invention between real training；
Fig. 2 is that each module of Internet of Things experience system connects block diagram；
Fig. 3 is the flow chart of the working method of experimental provision of the present invention；
Fig. 4 is the functional block diagram of experimental provision of the invention.
Wherein, area 1, Internet of Things module 2, rack 3 are debugged.
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
Embodiment 1
As shown in Figure 1, a kind of distribution Internet of Things experience system, comprising: several by U-shaped installation walled at real training
Between, and the inner wall surface for installing wall is divided into several debugging areas, each area of debugging for installing homologue networking module group respectively, with into
Row networking test；The rear end of each Internet of Things module is equipped at least two plugs, the metope distribution in the Internet of Things module group
There are several mounting holes, the plug and mounting hole cooperate, to install each Internet of Things module；It is additionally provided in the real training for putting
Set the rack of network server.
The Internet of Things experience system further includes multiple-channel output power module of voltage regulation, and the power module of voltage regulation is by Switching Power Supply
It constitutes, and the DC voltage of output+5V ,+12V ,+36V, is used with being supplied to each Internet of Things module work.
As shown in Fig. 2, the Internet of Things module group includes: access control module group, video monitoring module group, alarm module
Group, intelligent appliance control module group.
The access control module group includes: that garden gate inhibition module, garage gate inhibition's module, register one's residence gate inhibition's module, vehicle go out
Enter identification module, access information notification module.
The video monitoring module group includes: garden monitoring module, indoor monitoring module, network remote monitoring module, hand
Machine remote monitoring module.
The alarm module group includes: garden alarm module, indoor intrusion alarm module, combustion gas detection alarm module, cigarette
Mist detection alarm module.
The intelligent appliance control module group includes: curtain control module, close window control module, air conditioner intelligent control
Module.
Homologue networking module in each Internet of Things module group is separately installed with wireless sensing unit, and described wireless
Sensing unit carries out networking by Zigbee protocol, by being wirelessly connected with the network server after networking, to realize real training
Data upload and downloading are carried out between interior Internet of Things module group and teacher computer.The wireless sensing unit can be used and be stated
WSN wireless sensing unit.
Between each real training be located at Training Room in two sides, be symmetric, and the Training Room can be set 6,8,
10 or 12；Also it can according to need any adjusting number.
Embodiment 2
As shown in Figure 3 and Figure 4, the distributed Internet of Things experience system further include: for constructing capacitor on-line checking
Experimental provision,
The experimental provision includes: ultrasonic sensor, for acquiring the voice signal of measured capacitance generation, to obtain phase
Answer capacitor sound pressure level Lpx。
High Frequency Current Sensor, for acquiring the voltage vector at capacitor both ends.
The ultrasonic sensor, High Frequency Current Sensor pass through corresponding data conditioning unit and data processing and control respectively
Unit is connected；That is, ultrasonic sensor, High Frequency Current Sensor pass through respectively at the first, second data conditioning unit and numerical control
It manages control unit to be connected, and the first, second data conditioning unit can be using the certain proportion being made of integrated operational amplifier
Amplifier.
The data processing control units, comprising:
Capacitor superimposed voltage computing module, suitable for the voltage vector of acquisition is decomposited fundamental voltage u0(t) and nth harmonic
Component of voltage un(t), that is, the superimposed voltage u (t) at the measured capacitance both ends, i.e. u (t)=u0(t)+un(t), the superposition is calculated
The virtual value U of voltage, while calculating the virtual value U of fundamental voltage0；Wherein, obtaining harmonic wave and the method for fundamental wave is transported by FFT
It obtaining, this method has a large amount of descriptions in the prior art document, such as: Li Jiasheng, Chai Shijie in September, 2009 are published in the phase
It prints in the paper " electric energy quality harmonic m-Acetyl chlorophosphonazo on-line quick detection technique study " in " electric power system protection and control " and has
Associated description.
Capacitance computing module is suitable for according to default measured capacitance type, rated capacitance C0, pass through the capacitor acoustic pressure
Grade database obtains measured capacitance capacitor sound pressure level L corresponding with the virtual value of only each fundamental wavep0；It is generated by measured capacitance
Voice signal, to obtain corresponding capacitor sound pressure level Lpx, pass through formulaCalculate the reality of measured capacitance
Border capacitance Cx；Wherein, the capacitor sound pressure level Lp0It is obtained by way of establishing capacitor sound pressure level database, i.e. the database
In be stored with all types of capacitors capacitor sound pressure level corresponding with the virtual value of each fundamental voltage, pass through default input measured capacitance
Type, and the virtual value of acquired current fundamental voltage is calculated, it is corresponding to obtain the capacitor from capacitor sound pressure level database lookup
Capacitor sound pressure level data；Calculate corresponding capacitor sound pressure level LpxMethod in paper document: in June, 2010 is published in " electronics skill
Art journal " the capacitor noise level calculation method based on vibration signal in be disclosed.
Measured capacitance service life computing module, suitable for the actual capacitance C according to measured capacitancexWith the virtual value of superimposed voltage
U establishes capacitance predictor formula, i.e. C=Ck-kUt；Wherein, C is extreme capacitance values when measured capacitance is damaged, and t is capacitor damage
Bad expeced time, k be the unit time in measured capacitance current fundamental voltage virtual value U0Under corresponding electric capacitance change system
Number, that is,Wherein Cx1And Cx2For in the virtual value U of current fundamental voltage0Under unit time in be tested electricity
The capacitance initial value and final value of appearance；Electric capacitance change coefficient k can be according to all types of capacitors under the virtual value of each fundamental voltage
It is obtained by the electric capacitance change coefficient data library that actual measurement is established, the electric capacitance change coefficient data library is according to capacitor model and phase
The virtual value of fundamental voltage is answered to search to obtain the corresponding electric capacitance change coefficient k of the capacitor, specific acquisition methods: various fundamental waves
Measured all types of capacitors capacitance initial value whithin a period of time and final value under the virtual value of voltage, then converse a list
Corresponding capacitance initial value and final value in the time of position according to the type of default measured capacitance, and calculate acquired current fundamental wave
The virtual value of voltage, that searches from electric capacitance change coefficient data library goes out the corresponding electric capacitance change coefficient k of the capacitor, in order to
Convenient for calculating, if variable quantity of the capacitor within the unit time is linear；And electricity is derived by the capacitance predictor formula
Hold the calculation formula of damage t expeced time, i.e.,The extreme capacitance values C is set, to calculate measured capacitance
The expeced time of damage.
The virtual value U calculation method of the superimposed voltage u (t) includes: fundamental voltage u0(t) and nth harmonic component of voltage un
(t) square root of virtual value quadratic sum.The nth harmonic component of voltage un(t) n takes 5 in.
The data processing control units are realized by FPGA module, that is, fpga chip XC6SLX9-TQG144.
Table 1 is experimental data and actual measurement comparing result one, and the electric capacitor of table 1 selects huge magnificent electric capacitor BSMJ-
0.415-15-3 15Kvar sets the extreme capacitance values C as the 40% of former capacity.
1 experimental data of table and the actual measurement table of comparisons
Wherein, when calculating electric capacitance change coefficient k, the unit time is 24 hours, i.e., under 525V fundamental wave virtual value, one
It capacitance change is 0.08uF after actual measurement.
Table 2 is experimental data and actual measurement comparing result two, and the electric capacitor of table 2 selects Shanghai Wei Sikang electric capacitor
BSMJ0.4-15-3 capacitor BSMJ 0.45-15-3 sets the extreme capacitance values C as the 40% of former capacity.
2 experimental data of table and the actual measurement table of comparisons
Wherein, when calculating electric capacitance change coefficient k, the unit time is 24 hours, i.e., under 450V fundamental wave virtual value, one
It capacitance change is 0.12uF after actual measurement；Or under 415V fundamental wave virtual value, one day capacitance change is by actual measurement
0.11uF。
Table 3 is experimental data and actual measurement comparing result three, and the electric capacitor of table 3 selects De Lixi self-healing low-voltage capacitor
The parallel power condenser BSMJS0.4 20-3BSMJ sets the extreme capacitance values C as the 40% of former capacity.
3 experimental data of table and the actual measurement table of comparisons
Wherein, when calculating electric capacitance change coefficient k, the unit time is 24 hours, i.e., under 380V fundamental wave virtual value, one
It capacitance change is 0.063uF after actual measurement.
Fundamental wave virtual value in the present invention is it is also assumed that be voltage effective value ideally.
From table 1 to table 3 as can be seen that capacitor on-line checking of the invention estimate capacitor remaining time be it is effective,
Have the characteristics that accuracy is high, when extreme capacitance values C when close to capacitor actual capacitance close to capacitance damage, is settled accounts
As a result closer to measured result；Therefore, which is effective to the detection data of capacitor.
Embodiment 3
As shown in Figure 3 and Figure 4, on the basis of embodiment 2, the present invention also provides a kind of distributed Internet of Things experience systems
Working method, wherein the distribution Internet of Things experience system further include: the experiment for constructing capacitor on-line checking fills
It sets,
The working method of the experimental provision includes the following steps:
Step 1: the voltage vector at acquisition measured capacitance both ends, and the voltage vector is decomposited into fundamental voltage u0(t) and
Nth harmonic component of voltage un(t), the superimposed voltage u (t), i.e. u (t)=u at you can get it measured capacitance both ends0(t)+un
(t), the virtual value U of the superimposed voltage, the virtual value U of fundamental voltage are then calculated0。
Step 2: establishing capacitor sound pressure level database, include: in the database all types of capacitors with only each fundamental wave
The corresponding capacitor sound pressure level of virtual value.
Default measured capacitance type, rated capacitance C0, according to measured capacitance type and the virtual value U of current fundamental voltage0
Corresponding capacitor sound pressure level L is obtained from the capacitor sound pressure level databasep0。
The voice signal that measured capacitance generates is acquired, to obtain corresponding capacitor sound pressure level Lpx, pass through formulaCalculate the actual capacitance C of measured capacitancex。
Step 3: according to the actual capacitance C of measured capacitancexCapacitance, which is established, with the virtual value U of superimposed voltage estimates public affairs
Formula, i.e. C=Cx-kUt；Wherein, C is extreme capacitance values when measured capacitance is damaged, and t is capacitance damage expeced time, and k is unit
Virtual value U of the measured capacitance in current fundamental voltage in time0Under corresponding electric capacitance change coefficient, that is,
Wherein, Cx1And Cx2For the capacitance initial value and final value of measured capacitance in the unit time.
The extreme capacitance values C is set, the meter of capacitance damage t expeced time is derived by the capacitance predictor formula
Formula is calculated, i.e.,To calculate the expeced time that measured capacitance is damaged.
Therefore, this experimental provision can complete necessary capacitor on-line checking experiment, and data have very high reference value.
It should be understood that above-mentioned specific embodiment of the invention is used only for exemplary illustration or explains of the invention
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (1)
1. a kind of distribution Internet of Things experience system characterized by comprising several by U-shaped installation walled at real training between,
And the inner wall surface for installing wall is divided into several debugging areas, each area of debugging for installing homologue networking module group respectively；The object
The rear end of each Internet of Things module is equipped at least two plugs in networking module group, and several mounting holes are distributed in the metope, described
Plug and mounting hole cooperate, to install each Internet of Things module；
The rack for placing network server is additionally provided in the real training；
The distribution Internet of Things experience system further include: for constructing the experimental provision of capacitor on-line checking,
The experimental provision, comprising:
Ultrasonic sensor, for acquiring the voice signal of measured capacitance generation, to obtain corresponding capacitor sound pressure level Lpx；
High Frequency Current Sensor, for acquiring the voltage vector at capacitor both ends；
The ultrasonic sensor, High Frequency Current Sensor pass through corresponding data conditioning unit and data processing control units respectively
It is connected；
The data processing control units, comprising:
Capacitor superimposed voltage computing module, suitable for the voltage vector of acquisition is decomposited fundamental voltage u0(t) and nth harmonic voltage
Component un(t), that is, the superimposed voltage u (t) at the measured capacitance both ends, i.e. u (t)=u0(t)+un(t), the superimposed voltage is calculated
Virtual value U, while calculating the virtual value U of fundamental voltage0；
Capacitance computing module establishes capacitor sound pressure level database, includes: all types of capacitors and only each fundamental wave in the database
The corresponding capacitor sound pressure level of the virtual value of voltage；Default measured capacitance type, rated capacitance C0, according to measured capacitance type and
The virtual value U of current fundamental voltage0Corresponding capacitor sound pressure level L is obtained from the capacitor sound pressure level databasep0；Pass through measured capacitance
The voice signal of generation, to obtain corresponding capacitor sound pressure level Lpx, pass through formulaCalculate tested electricity
The actual capacitance C of appearancex；
Measured capacitance service life computing module, suitable for the actual capacitance C according to measured capacitancexIt is established with the virtual value U of superimposed voltage
Capacitance predictor formula, i.e. C=Cx-kUt；Wherein, C is extreme capacitance values when measured capacitance is damaged, and t is expected for capacitance damage
Time, k be the unit time in measured capacitance current fundamental voltage virtual value U0Under corresponding electric capacitance change coefficient, that is,Wherein, Cx1And Cx2For the capacitance initial value and final value of measured capacitance in the unit time；And pass through the electricity
Capacity predictor formula derives the calculation formula of capacitance damage t expeced time, i.e.,The extreme capacitance values C is set,
To calculate the expeced time that measured capacitance is damaged；
The nth harmonic component of voltage un(t) n takes 5 in；
The working method of the distribution Internet of Things experience system includes the working method of the experimental provision；
The working method of the experimental provision includes the following steps:
Step 1: the voltage vector at acquisition measured capacitance both ends, and the voltage vector is decomposited into fundamental voltage u0(t) and n times are humorous
Wave voltage component un(t), the superimposed voltage u (t), i.e. u (t)=u at you can get it measured capacitance both ends0(t)+un(t), so
The virtual value U of the superimposed voltage, the virtual value U of fundamental voltage are calculated afterwards0；
Step 2: establishing capacitor sound pressure level database, include: in the database all types of capacitors with only each fundamental voltage
The corresponding capacitor sound pressure level of virtual value；
Default measured capacitance type, rated capacitance C0, according to measured capacitance type and the virtual value U of current fundamental voltage0From institute
It states capacitor sound pressure level database and obtains corresponding capacitor sound pressure level Lp0；
The voice signal that measured capacitance generates is acquired, to obtain corresponding capacitor sound pressure level Lpx, pass through formulaCalculate the actual capacitance C of measured capacitancex；
Step 3: according to the actual capacitance C of measured capacitancexCapacitance predictor formula, i.e. C are established with the virtual value U of superimposed voltage
=Cx-kUt；Wherein, C is extreme capacitance values when measured capacitance is damaged, and t is capacitance damage expeced time, and k is in the unit time
Virtual value U of the measured capacitance in current fundamental voltage0Under corresponding electric capacitance change coefficient, that is,Its
In, Cx1And Cx2For the capacitance initial value and final value of measured capacitance in the unit time；
The extreme capacitance values C is set, derives that the calculating of capacitance damage t expeced time is public by the capacitance predictor formula
Formula, i.e.,To calculate the expeced time that measured capacitance is damaged.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710360683.5A CN106935098B (en) | 2014-06-11 | 2014-06-11 | Using the working method of the distributed Internet of Things experience system of ultrasonic sensor |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710360683.5A CN106935098B (en) | 2014-06-11 | 2014-06-11 | Using the working method of the distributed Internet of Things experience system of ultrasonic sensor |
| CN201410259282.7A CN104597338B (en) | 2014-06-11 | 2014-06-11 | A kind of distributed Internet of Things experience system and its method of work |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410259282.7A Division CN104597338B (en) | 2014-06-11 | 2014-06-11 | A kind of distributed Internet of Things experience system and its method of work |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106935098A CN106935098A (en) | 2017-07-07 |
| CN106935098B true CN106935098B (en) | 2019-06-21 |
Family
ID=53123251
Family Applications (3)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410259282.7A Expired - Fee Related CN104597338B (en) | 2014-06-11 | 2014-06-11 | A kind of distributed Internet of Things experience system and its method of work |
| CN201710360683.5A Expired - Fee Related CN106935098B (en) | 2014-06-11 | 2014-06-11 | Using the working method of the distributed Internet of Things experience system of ultrasonic sensor |
| CN201710360685.4A Active CN107103824B (en) | 2014-06-11 | 2014-06-11 | Using the distributed Internet of Things experience system of High Frequency Current Sensor |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410259282.7A Expired - Fee Related CN104597338B (en) | 2014-06-11 | 2014-06-11 | A kind of distributed Internet of Things experience system and its method of work |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710360685.4A Active CN107103824B (en) | 2014-06-11 | 2014-06-11 | Using the distributed Internet of Things experience system of High Frequency Current Sensor |
Country Status (1)
| Country | Link |
|---|---|
| CN (3) | CN104597338B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104597338B (en) * | 2014-06-11 | 2017-06-16 | 江苏省武进中等专业学校 | A kind of distributed Internet of Things experience system and its method of work |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003075486A (en) * | 2001-09-06 | 2003-03-12 | Sumitomo Metal Ind Ltd | Impedance detection circuit, and capacitance detection circuit and method |
| CN101211516A (en) * | 2007-12-21 | 2008-07-02 | 浙江大学 | Single chip machine integrated experiment platform facing embedded system |
| CN101644737A (en) * | 2009-09-10 | 2010-02-10 | 优能电气（天津）有限公司 | Positioning device and positioning method for fault detection of local discharge |
| CN201876948U (en) * | 2010-11-05 | 2011-06-22 | 林美蓉 | Ultrasonic monitoring power equipment |
| CN102128641A (en) * | 2010-01-12 | 2011-07-20 | 佳能株式会社 | Capacitive detection type electro-mechanical transducer |
| CN202976661U (en) * | 2012-11-30 | 2013-06-05 | 北京新大陆时代教育科技有限公司 | Operation platform based on Internet of Thing education practical training system |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS50146372A (en) * | 1974-04-30 | 1975-11-25 | ||
| JPH0961408A (en) * | 1995-08-25 | 1997-03-07 | Ube Ind Ltd | Evaluation of ceramics material |
| SE528552C2 (en) * | 2004-11-12 | 2006-12-12 | Frigoscandia Equipment Ab | Apparatus for determining a dielectric function using microwave radiation in combination with ultrasonic radiation |
| CN101231847B (en) * | 2008-01-09 | 2010-11-10 | 南京航空航天大学 | Structural vibration noise initiative control method and apparatus |
| CN202049654U (en) * | 2010-12-21 | 2011-11-23 | 金承志 | Experimental device for the inhibition of inductance and capacitance to alternating current |
| CN103293391A (en) * | 2013-06-19 | 2013-09-11 | 国家电网公司 | Online capacitance monitoring device of compensating capacitors |
| CN203535875U (en) * | 2013-11-05 | 2014-04-09 | 四川中时代科技有限公司 | Simple sound ranging teaching experimental circuit |
| CN203786928U (en) * | 2014-04-24 | 2014-08-20 | 江苏省武进中等专业学校 | Distributed Internet of Things training system |
| CN104597338B (en) * | 2014-06-11 | 2017-06-16 | 江苏省武进中等专业学校 | A kind of distributed Internet of Things experience system and its method of work |
-
2014
- 2014-06-11 CN CN201410259282.7A patent/CN104597338B/en not_active Expired - Fee Related
- 2014-06-11 CN CN201710360683.5A patent/CN106935098B/en not_active Expired - Fee Related
- 2014-06-11 CN CN201710360685.4A patent/CN107103824B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003075486A (en) * | 2001-09-06 | 2003-03-12 | Sumitomo Metal Ind Ltd | Impedance detection circuit, and capacitance detection circuit and method |
| CN101211516A (en) * | 2007-12-21 | 2008-07-02 | 浙江大学 | Single chip machine integrated experiment platform facing embedded system |
| CN101644737A (en) * | 2009-09-10 | 2010-02-10 | 优能电气（天津）有限公司 | Positioning device and positioning method for fault detection of local discharge |
| CN102128641A (en) * | 2010-01-12 | 2011-07-20 | 佳能株式会社 | Capacitive detection type electro-mechanical transducer |
| CN201876948U (en) * | 2010-11-05 | 2011-06-22 | 林美蓉 | Ultrasonic monitoring power equipment |
| CN202976661U (en) * | 2012-11-30 | 2013-06-05 | 北京新大陆时代教育科技有限公司 | Operation platform based on Internet of Thing education practical training system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106935098A (en) | 2017-07-07 |
| CN107103824B (en) | 2019-10-01 |
| CN104597338A (en) | 2015-05-06 |
| CN107103824A (en) | 2017-08-29 |
| CN104597338B (en) | 2017-06-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Vahidnia et al. | Generator coherency and area detection in large power systems | |
| Aghamohammadi et al. | A new approach for online coherency identification in power systems based on correlation characteristics of generators rotor oscillations | |
| Rashid et al. | I-BLEND, a campus-scale commercial and residential buildings electrical energy dataset | |
| Liu et al. | Load forecasting and operation strategy design for CCHP systems using forecasted loads | |
| CN103728535A (en) | Extra-high-voltage direct-current transmission line fault location method based on wavelet transformation transient state energy spectrum | |
| TWI642019B (en) | Method for assessing efficiency of power generation system | |
| CN102288804B (en) | Method for calculating resistive current of arrester based on orthogonal transformation | |
| CN104540103A (en) | Indoor positioning method and system for small house | |
| CN104285153A (en) | Method and apparatus for monitoring electric power transmission, disturbances and forecasts | |
| Li et al. | Multichannel continuous wavelet transform approach to estimate electromechanical oscillation modes, mode shapes and coherent groups from synchrophasors in bulk power grids | |
| CN105676157A (en) | WAMS low-frequency oscillation identification function test system and WAMS low-frequency oscillation identification function test method | |
| CN106681201A (en) | Central control type multimedia classroom system based on campus network | |
| CN106935098B (en) | Using the working method of the distributed Internet of Things experience system of ultrasonic sensor | |
| Paternina et al. | Dynamic equivalents by modal decomposition of tie-line active power flows | |
| Kemal et al. | A real-time open access platform towards proof of concept for smart grid applications | |
| CN203786928U (en) | Distributed Internet of Things training system | |
| Haji et al. | Online determination of external network models using synchronized phasor data | |
| Gaouda et al. | Developing educational smart grid laboratory | |
| Haji et al. | Practical considerations in the design of distribution state estimation techniques | |
| Szűts et al. | Estimating Hungarian Household Energy Consumption Using Artificial Neural Networks | |
| Moraes et al. | Towards a simulator for green smart campus systems | |
| Acosta et al. | Single value decomposition to estimate critical clearing time of a power system using measurements | |
| CN107798944A (en) | A kind of distributed Internet of Things experience system | |
| Martín-Gómez et al. | Sensor placement for BPM analysis of buildings in use to implement energy savings through building performance simulation | |
| CN108988340A (en) | Reduce the method, apparatus and server of line loss |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20201019 Address after: 211599 Xingang Road, Liuhe Economic Development Zone, Nanjing, Jiangsu Province Patentee after: Nanjing Gangjia Construction Machinery Technology Development Co., Ltd Address before: 213000 No. 38 Hanjiang Road, Xinbei District, Changzhou City, Jiangsu Province Patentee before: Ge Yunlong |
|
| TR01 | Transfer of patent right | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190621 Termination date: 20210611 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |