KR101648012B1 - The apparatus of smart internet of things with embeded module - Google Patents
The apparatus of smart internet of things with embeded module Download PDFInfo
- Publication number
- KR101648012B1 KR101648012B1 KR1020150171140A KR20150171140A KR101648012B1 KR 101648012 B1 KR101648012 B1 KR 101648012B1 KR 1020150171140 A KR1020150171140 A KR 1020150171140A KR 20150171140 A KR20150171140 A KR 20150171140A KR 101648012 B1 KR101648012 B1 KR 101648012B1
- Authority
- KR
- South Korea
- Prior art keywords
- module
- data
- unit
- smart
- sensing
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
-
- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
-
- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C19/00—Electric signal transmission systems
- G08C19/02—Electric signal transmission systems in which the signal transmitted is magnitude of current or voltage
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
Description
In the present invention, sensing data of a load device (boiler, refrigerator, air supply / exhaust fan, pump, heat exchanger, air conditioner, motor, electric motor, etc.) in a building is collected from the field through an embedded module, The sensing data and the fault diagnosis data are transferred to the central management server at a remote site via the WiFi communication network and then the load device in the field can be controlled according to the control command received from the central management server To an embedded smart IOT device for sensing a load device in a building.
In order to improve the energy efficiency of the building, the building machine facilities such as cooling, heating and air conditioning are diagnosed every five years according to the government guidelines.
For example, an off-line energy diagnosis technique that measures energy usage by using various instruments directly on the building site based on the prescribed checklist and intermittently diagnoses the energy efficiency based on the information of the energy diagnosis expert is applied.
This method is a high-cost, one-time diagnostic technology that leads to energy conservation by a small number of experts, and can be operated in a state where the equipment is in trouble for a long time or the energy efficiency is lowered. And manual diagnosis by a professional in the field on a building-by-building basis. Therefore, not only a high diagnosis cost is required but also a management difficulty is followed.
In order to solve such a problem, a conventional building energy management system (BEMS) has been proposed,
This is because the analysis of building energy consumption information is mainly performed by a centralized system centered on the building energy control system of a remote place, it is difficult to detect the failure of the specific load device when the energy measuring module of the load device in the building is broken, It is difficult to accurately measure the operation efficiency of the load device.
In addition, existing building energy control devices mainly do only the energy measurement of the load devices in the building, and there is no configuration that maintains the optimal operation state immediately on the site, So that it takes a long time to work.
In addition, there is not a configuration in which a 1: 1 customized communication protocol is formed in accordance with various load devices installed in the building (boiler, refrigerator, air supply fan, pump, heat exchanger, air conditioner, motor, There is a problem in that the energy measuring module is also replaced, thereby requiring a lot of equipment cost.
In order to solve the above problems, in the present invention, it is possible to easily install the I / O terminal on one side of the I / O terminal of the load device in the building via the connector connector in a simple manner of 1: 1. Through the embedded module, In addition, it is possible to calculate operation efficiency and fault diagnosis by itself. In case of occurrence of abnormal alarm of load device, alarm alarm contents can be provided to the manager's smart device, It is an object of the present invention to provide an embedded type smart IOT device for sensing a load device in a building, which is able to calculate diagnosis, compare and analyze the data with the normal operation data, and transmit the fault diagnosis data of the present load device to a central management server at a remote site .
In order to achieve the above object, an embedded smart IOT device for sensing a load device in a building according to the present invention comprises:
It senses the temperature, acceleration, and load current of the load device connected to the I / O terminal of the load device in a detachable manner and analyzes the sensed data in the field for the self-diagnosis of the fault. And the sensing data and the failure diagnosis data are transmitted in real time.
The embedded smart IOT device for sensing a load device in a building is more specifically
A
A
A
A smart sensing module (40) for sensing the temperature, acceleration, and load current of the load device connected to the connection connector portion and transmitting the sensed data to the embedded module,
A short
A
A wired / wireless communication module for transmitting sensing data and fault diagnosis data sensed by the smart sensing module to a central management server located at a remote location of the local communication module, receiving the control command signal as a response signal, (70)
It is connected with battery section, smart sensing module, short distance communication module, display module, wired / wireless communication module and actuation module, and controls overall operation of each device and forms 1: 1 customized communication protocol according to load device connected to the building After the malfunction diagnosis of the load device is analyzed, the malfunction diagnosis data and the sensing data are transmitted to the central management server at the remote site through the wired / wireless communication module, An embedded
And an
As described above, in the present invention,
First, in the present invention, it can be easily installed at one side of the input / output terminal of the load device in the building via the connection connector in a detachable manner, thereby providing excellent installation and compatibility.
Second, in the present invention, sensing data of a load device in a building is collected in the field through an embedded module, and operation efficiency and failure diagnosis are calculated by itself, and the calculated operation efficiency is displayed as a central management server at a remote place through a WiFi communication network And it can improve the building energy measurement and the operation speed by 80% than the existing one.
Third, in the present invention, when an abnormality alarm of a load device occurs, the contents of the alarm can be provided to the smart device of the manager, so that a disaster accident can be prevented in advance and the emergency repair and the AS can be quickly processed.
Fourth, in the present invention, the fault diagnosis of the load device in the building is directly calculated in the field, and compared with the normal operation data, the fault diagnosis data of the present load device can be transmitted to the central management server at the remote place, Not only energy savings but also additional lifetime extension and maintenance costs of the load device can be saved.
1 is a block diagram showing components of an embedded
2 is a perspective view showing components of an embedded
3 is an exploded perspective view showing components of an embedded
FIG. 4 is a block diagram showing the components of the connecting connector unit according to the present invention,
FIG. 5 is a block diagram illustrating components of a smart sensing module according to the present invention.
FIG. 6 is a block diagram illustrating components of a local area communication module according to the present invention.
7 is a block diagram illustrating components of an embedded module according to the present invention.
8 is a block diagram illustrating the components of the microprocessor according to the present invention.
9 shows an embodiment showing that a 1: 1 customized communication protocol is formed for a load device connected to an embedded
FIG. 16 is a block diagram showing the components of the engine diagnostic algorithm analysis engine according to the present invention;
17 is a block diagram showing the components of an AANN (Autoassociative Neural Network) based fault diagnosis analysis module according to the present invention,
18 is a flowchart illustrating a method of controlling the embedded module according to an exemplary embodiment of the present invention. Referring to FIG. 18, the wired / wireless communication module is driven under the control of the embedded module according to the present invention to transmit sensing data and fault diagnosis data sensed by a smart sensing module to a central management server located at a remote location, Lt; RTI ID = 0.0 > embodiment < / RTI >
First, the embedded smart IOT device described in the present invention, compared to the existing IOT device,
First, a one-to-one customized communication protocol is formed in accordance with a load device connected to the connected building by connecting the input / output terminal of the load device in the building 1: 1 in a detachable manner,
Secondly, it analyzes the sensed data in the field,
Third, the main feature is that the sensing data and the fault diagnosis data are transferred in real time to the central management server at the remote place through the wired and wireless communication module through the wired / wireless communication module without passing through the relay node and the smart device in the vicinity.
The load device described in the present invention refers to a boiler, a freezer, an air supply and exhaust fan, a pump, a heat exchanger, an air conditioner, a motor, and an electric motor installed in a building.
Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing components of an embedded type
More specifically, the embedded
First, the
The
As shown in FIG. 3, the smart sensing module is formed on one side of the connection connector, the short-distance communication module is formed on one side of the smart sensing module, A display module is formed on one side of the short distance communication module, a wired / wireless communication module is formed on one side of the display module, an embedded module is formed on one side of the wired / wireless communication module, and an actuation module is formed on one side of the connection connector .
The main body according to the present invention is made of a material that can protect the internal memory unit from vibration and external pressure of the load device, has a high heat radiation effect, is light, and has excellent durability and strength.
More specifically, the main body may be made of one or
10 to 30 wt% of at least one additive selected from the group consisting of aluminum (Alumium), graphite (Graphite), silver (Silver) and copper (Copper)
10 to 20 wt% glass fiber having a diameter (Diameter, 탆) of 16, a density of 2.58, a tensile strength (Gpa) of 1.65 and a tensile modulus (Gpa) of 77 was put into a mixer The mixture was blended at 230 to 270 ° C at 5 to 10 rpm, extruded using an extruder, and cooled at room temperature to prepare pellets having a size of 4 to 6 mm,
The pellets are injected into an injection machine and injection-molded at a processing temperature of 200 to 250 DEG C and a processing pressure of 1,200 to 1,600 psi.
More specifically,
In selecting the resin, it is preferable to use poly (butylene terephthalate). This is because PBT molded parts have excellent rigidity and low wear. For this reason, it can be used at high temperature and it is easy to improve the rigidity because it is excellent in composite effect with glass fiber.
It also has excellent electrical properties and is less affected by temperature and humidity changes. Generally, the reason why plastic is recognized as an insulator is that the molecular structure of the polymer has a long chain tangled and dispersed by the vibration transmitted by the energy in the heat transfer process, and the thermal conductivity is 0.17 ~ 0.2 W / This is because there is a characteristic.
If the amount of the resin to be used is less than 60 wt%, the moldability is deteriorated. If the amount exceeds 80 wt%, the resin may deteriorate in thermal conductivity to deteriorate the heat generation characteristics. Therefore, the amount of the resin is limited within a range of 60 to 80 wt% .
Further, graphite is preferably used in selecting additives. Graphite has a higher thermal conductivity than other additives because the molecular size of graphite is relatively small compared to other molecules, resulting in a uniform distribution during mixing.
When the amount of the additive used is less than 10 wt%, the heat radiation characteristics become poor. When the additive amount exceeds 30 wt%, the heat radiation property is enhanced, but the problem of durability such as weakening of tensile strength and the problem that moldability is deteriorated , The amount of the additive to be used is preferably limited within a range of 10 to 30 wt%.
When the amount of the glass fiber used is less than 10 wt%, the improvement of the strength is insignificant. When the amount exceeds 20 wt%, the moldability may be deteriorated. Therefore, the amount of the glass fiber is preferably limited within a range of 10 to 20 wt% .
Specific examples of the formation of the main body will be described below.
70 wt% of polybutylene terephthalate (PBT)
20 wt% of graphite,
10 wt% of glass fiber having a diameter (Diameter, 탆) of 16, a density of 2.58, a tensile strength of 1.65 and a tensile modulus of 77 was introduced into a mixer to produce 250 The mixture was extruded using an extruder and then cooled at room temperature to prepare pellets having a size of 5 mm.
The pellet is injected into an injection molding machine and injection molded at a processing temperature of 230 DEG C and a processing pressure of 1,500 psi to form a body.
In addition, the
Next, the
The
4, the RS 485
The RS 485
The RS 232
The
The
Next, the
The
It consists of a lithium
The lithium
This is because the electrolyte is in the form of solid or gel. Therefore, even if the battery is broken due to an accident, the electrolyte is not leaked out, so there is little fear of ignition or explosion, and the stability is secured and energy efficiency is higher than that of the lithium ion battery.
In addition, there is no need to use a solid metal sheath, and it can be formed in various sizes and shapes depending on the application. It can be manufactured to a thickness of 3 mm or less and can be reduced in weight by 30% or more and the forming process is relatively easy compared to a lithium ion battery , Mass production and formation of large batteries.
Next, the
The
As shown in FIG. 5, this includes a temperature sensor 41, a gyro acceleration sensor 42, and a load
First, the temperature sensor 41 according to the present invention will be described.
The temperature sensor 41 is located on the other side of the outer surface of the main body, and serves to measure the temperature of the load device in the building.
It consists of either a thermocouple thermometer, a temperature measuring resistor thermometer, a thermistor (NTC) thermometer, or a metallic thermometer.
In the temperature sensor according to the present invention, a 4-wire RTC circuit part is connected to one side of the output terminal to reduce the resistance error generated on the line, thereby improving the accuracy and transmitting the result to the embedded module.
The 4-wire RTC circuit section comprises a 12V reference IC, an amplifier (AMP03) element, a header connector for temperature sensor connection, a comparator U8, and an amplifier U9.
That is, the sensing value measured by the temperature sensor is inputted to the (+) terminal of the comparator U8, and a value obtained by correcting the error of the resistance generated on the line to the 12V reference voltage is inputted to the (-) terminal, And the output value is amplified by the amplifier U9 and transmitted to the PC0 input terminal of the embedded module.
Second, the gyro acceleration sensor unit 42 according to the present invention will be described.
The gyro acceleration sensor unit 42 is formed in a rectangular block shape on one side of the temperature sensor and is coupled with a three axis geomagnetic sensor and a three axis acceleration sensor capable of motion sensing using X, Which is connected to the external control board, and executes the motion command from the embedded module.
It consists of a small 3 x 3 x 0.9mm QFN package, operates at 1.8V, consumes only 6.1mW of power in its entire operating mode, and has a gyroscope with output values close to zero at ± 5dps It features performance at 0.01dps / √Hz noise and features improved accelerometer with typical noise of 250μg / √Hz in only 18A low current mode.
The gyro acceleration sensor 42 reads the motion sensing value using the X, Y, and Z vector values from 0 to 20 mA through the first current loop receiver and the second current loop receiver, and outputs the 0 to 5 V output.
At this time, a 24-bit high-resolution ADC IC is connected to one side of the output terminal, and the value sensed by the 3-axis gyro sensor is transmitted to the smart sensor microcomputer input terminals PA4, PA5, PA6, and PA7 through 24-bit high resolution.
Here, the first current loop receiver reads the X vector value as 0 channel motion sensing value in 0 to 20 mA, for example, among the motion sensing values using the X, Y and Z vector values of the 3-axis gyro sensor, To the input terminal AIN2 + of the IC.
The second current loop receiver reads the Y and Z vector values as a 2-channel motion sensing value in the range of 0 to 20 mA, for example, among the motion sensing values using the X, Y and Z vector values of the 3-axis gyro sensor, To the input terminal AIN1 + of the IC.
At this time, the 24-bit high-resolution ADC IC converts the 1-channel motion sensing value of the X vector value sensed by the first current loop receiver and the 2-channel motion sensing value of the Y and Z vector values sensed by the second current loop receiver into 24- To the smart sensor microcomputer input terminals PA4, PA5, PA6, and PA7.
Third, the load
The load
This is configured by selecting either a current transformer type current sensor or a Hall element type current sensor.
The current transformer type current sensor serves to detect a primary current by measuring a secondary current by winding the primary and secondary coils around the magnetic core using a donut-shaped magnetic core.
The Hall element type current sensor has a role of detecting the strength of the magnetic field, that is, the strength of the current, by measuring a Hall voltage by providing a Hall element in a magnetic field generated by a current.
If a load is applied to the in-building load device, the load becomes large, and the current also becomes large.
Here, for example, in the case of a transformer, an electric arc is generated by connecting a lamp to a secondary side of the transformer, or a welding machine is connected to the transformer, or an electric motor is connected to rotate the transformer. Empty), but rather to operate a shelf or crane.
Next, the local
The short-
6, either the
The
It uses the Industrial Scientific and Medical (ISM) frequency band of 2400 to 2483.5 MHz. In order to prevent the interference of other systems that use the upper and lower frequencies, we use a total of 79 channels, ranging from 2400MHz to 2MHz and 2483.5MHz to 3.5MHz, except 2402 ~ 2480MHz.
In addition, in order to eliminate interference between systems, a frequency hopping scheme is used.
Frequency hopping is a technique for rapidly moving a large number of channels according to a specific pattern and transmitting packets (data) little by little. In the present invention, 79 channels are configured to hop 1600 times per second.
The
As described above, the short-
Next, the
The
It consists of LCD monitor window or LED monitor window.
Next, the wired /
The wired /
The WiFi communication module is configured as a wireless communication module, and one of BACNET TCP / IP, BACNET MS / TP, and Modbus RTU is selected and configured as a wired communication module.
The WiFi communication module incorporates wireless technology and is composed of a wireless LAN technology that enables high performance wireless communication.
The wireless LAN uses a frequency band of 2.4 GHz, which is a method of building a network using radio wave or light without using a wire when constructing a network.
Next, the embedded
The embedded
It is installed in a detachable structure at 1: 1 in each load device, and provides various communication protocols and is configured to use any one of BACnet TCP / IP, MS / TP, Modbus RTU and GIGA Ethernet.
The communication protocol with the central management server at the remote site is configured to adopt BACnet TCP / IP as a main communication protocol in order to secure the transmission speed, data accuracy and system scalability, and a 1: 1 customized communication protocol (Protocol).
7, the embedded
First, the
The
It consists of a 1GHz TI SitaraAM3358 Cortex-A8 processor.
More specifically, a 512 MByte DDR3 SDRAM is mounted, a Giga Ethernet module is formed, a Wince, a Linux, and an Android OS are formed, and is configured to be used as a kernel message confirmation or a terminal function through a 6-channel UART, LEDs and switches for debugging through general-purpose I / O ports are formed in the form of additional sub-boards using a connector, and a 60-pin LCD connector for driving the LCD monitor window of the display module is formed. A Real Time Clock (RTC) IC is mounted, an input voltage is set to DC 5V / 2A, a key button is formed, and a WiFi module Interface, a Bluetooth module interface, an asynchronous RS2332 port, and a synchronous RS232 port.
8, the
The load device operation efficiency calculation
At this time, the optimization operation information of the load devices in the building is automatically determined based on the calculated operation efficiency data of the load devices to perform optimum operation of the equipment.
[ Operation of load device operation efficiency Boiler operation efficiency applied through algorithm engine part]
First, the microprocessor checks the system operation status by the schedule and the operation status by the outside air compensation in the case of the boiler among the load devices in the building, integrates the operation time of the boiler equipment, and calculates the operation time and the gas usage amount, The heat quantity is calculated by calculating the heat quantity through, and the accumulated data is stored in units of year, month and day.
Then, the energy efficiency is calculated by using the boiler feed gas flow rate, the hot water supply and the return temperature difference, and the efficiency and the real time operation efficiency at the initial installation are calculated and displayed.
In this case, when the real-time operation efficiency is less than a certain ratio, the short-range wireless communication module generates an alarm to the driver's smart device for the short distance, so that the driver can check and manage the alarm.
The load device operation efficiency calculation algorithm according to the present invention The boiler operation efficiency applied to the boiler through the engine unit is expressed by
[ Operation of load device operation efficiency Efficiency of refrigerator operation applied through algorithm engine part]
First, in the case of a freezer of a load device in a building through a microprocessor, an operation state according to a schedule is checked, an optimal start / stop control is performed according to a load, cold / hot water according to outside air compensation is set, And generates current state alarm data by comparing the rated and real time efficiency. When the real time operation efficiency is less than a predetermined ratio, an alarm is generated toward the driver's smart device for a short distance through the short range wireless communication module And is configured to allow the driver to inspect and manage it.
The loader operation efficiency calculation algorithm according to the present invention The refrigerator operation efficiency applied to the refrigerator through the engine unit is expressed by Equation (2).
[ Operation of load device operation efficiency Efficiency of operation of the feed / exhaust fan applied through the algorithm engine section]
First, in the case of the supply / exhaust fan of the load device in the building through the microprocessor, the operation state is checked by the schedule or the system program, the operation time of the equipment is accumulated to accumulate the operation time and the power amount, The data is stored in units of years, months, and days. The power is calculated by receiving the ampere meter, the fan efficiency is calculated using the discharge air amount, and the efficiency is plotted together with the initial installation efficiency.
When the real-time operation efficiency is less than a predetermined ratio, an alarm is generated toward the driver's smart device for a short distance via the short-range wireless communication module so that the driver can check and manage the alarm.
The operating efficiency of the load / exhaust fan applied to the feed / exhaust fan through the engine unit of the load device operation efficiency calculation algorithm according to the present invention is expressed by Equation (3).
[ Operation of load device operation efficiency Pump operation efficiency applied through algorithm engine]
First, in the case of a pump of a load device in a building through a microprocessor, the operation state is checked by a schedule or a system program. The operation time of the equipment is accumulated to accumulate the operation time and the power amount, The data is stored in units of days, the ammeter is input to calculate power, the fan efficiency is calculated using the discharge air amount, and the efficiency is plotted together with the initial installation efficiency.
When the real-time operation efficiency falls below a predetermined rate (85%), the short-range wireless communication module generates an alarm to the driver's smart device for the short distance so that the driver can check and manage the alarm.
The load operation efficiency calculation algorithm according to the present invention The pump operation efficiency applied to the pump through the engine unit is expressed by Equation (4).
[ Operation of load device operation efficiency Operation Efficiency of Heat Exchanger Applied through Algorithm Engine Department]
First, in the case of a heat exchanger in a building load device, the connection connector is connected to one side of the heat exchanger primary side flow output terminal, the water supply output terminal, and the heat exchange output terminal, and the heat exchanger secondary flow output terminal, And is configured to calculate the absorption and emission heat amount through the microprocessor while being connected to one side of the temperature output terminal.
When the real-time operation efficiency is less than a predetermined ratio, an alarm is generated toward the driver's smart device for a short distance via the short-range wireless communication module so that the driver can check and manage the alarm.
The operation efficiency of the load device operation efficiency calculation algorithm according to the present invention is expressed by the following equation (5).
[ Operation of load device operation efficiency Air conditioner operating efficiency applied through algorithm engine part]
First, in the case of an air conditioner of a load device in a building through a microprocessor, a schedule operation state, an optimum start / stop operation state, an intermittent operation state, and a temperature compensation operation state are checked and a minimum opening degree by carbon dioxide And controls the outdoor enthalpy and calculates the efficiency of the cold / hot water heat exchanger.
In addition, when the real-time operation program status display and the real-time operation efficiency are less than a predetermined ratio, an alarm is generated toward the driver's smart device through the short-range wireless communication module so that the driver can check and manage the driver.
The operating efficiency of the air conditioner applied to the air conditioner through the engine of the load device operation efficiency according to the present invention is calculated based on the operation efficiency of the air / exhaust fan of Equation (3) and the efficiency of the heat exchanger of Equation And is set according to the corresponding ratio.
The failure diagnosis analysis
As shown in Fig. 16, the reference
The
The failure diagnosis
It is composed of AANN (Autoassociative Neural Network) based fault diagnosis analysis module.
The AANN (Autoassociative Neural Network) based fault diagnosis analysis module analyzes the presence or absence of the fault diagnosis of the current load device through multivariate data analysis when the currently inputted sensing data shows a state different from that during normal operation .
17, the AANN (Autoassociative Neural Network) based failure diagnostic analysis module, which has been previously learned based on the reference data generated by the reference data generation unit, includes a bottleneck layer the introduction of the bottleneck layer has the following characteristics.
The correlation between the m-dimensional input data is reduced to j-dimensional data. In this process, the information related to the correlation between the input data is input and output between the input layer and the mapping layer, And the neural network bonding strength between the mapping layer and the bottleneck layer.
Therefore, even if the input data (sensing data of the currently input load device) different from the reference data used in the learning are input to the AANN (Autoassociative Neural Network) based fault diagnosis analysis module, the AANN (Autoassociative Neural Network) The sensor value when there is no failure is output.
Therefore, as shown in FIG. 17, the output of the AANN (Autoassociative Neural Network) -based fault diagnosis analysis module and the residual to the sensor input have a value other than 0, and through the inspection of this residual, Diagnosis detection can be efficiently performed.
However, in order for the AANN (Autoassociative Neural Network) based fault diagnosis analysis module to have the above characteristics, it is necessary to have a strong correlation between the input data. To do so, physical multiple redundancy sensors The use of additional variables generated by linear, non-linear correlations between measured variables is required.
17,
The fault diagnosis
In addition, the
The
As shown in Fig. 8, the
Here, U-Boot refers to upgrading software and other information remotely.
The
The
That is, the flash update program of the U-Boot build unit is built in the memory boot area to generate a new update.bin file, and the flash memory 2410update.sh is executed to update the flash memory.
At this time, when the update program is terminated, a new U-Boot image is loaded in the boot area of the NAND flash and the system is automatically restarted using the new image.
Second, the
The
It consists of DDR SDRAM and NAND flash.
Here, the DDR SDRAM is configured by copying a real application program or a kernel, and the NAND flash is configured to store a boot loader, a kernel image, and an application program.
Third, the
The
This forms a USB Host 2.0 x 2 Port and forms a USB 2.0
Fourth, the
The
It consists of a UART selection jumper (UART SELECTION JUMPERS) and a serial connector (Serial connector).
The battery part, the smart sensing module, the short distance communication module, the display module, the wired / wireless communication module and the actuation module are connected to the UART selection jumper and the serial connector.
Next, the
The
This constitutes a forced switch in the power supply section of the load device, and sends an actuation signal when a fault diagnosis signal is inputted, so as to push-drive the forced switch.
At this time, when the forcible switch is pushed, the driving module of the load device is automatically turned off.
Hereinafter, a specific operation process of the embedded type smart IOT device for sensing a load device in a building according to the present invention will be described.
First, the
Next, the
Next, as shown in FIG. 9, a 1: 1 customized communication protocol is formed according to the in-building load device connected in the embedded
Next, the
Next, the embedded
Here, the fault diagnosis algorithm engine section is processed as follows.
That is, the reference
Then, through a neural network for system diagnosis and a fuzzy algorithm (Fuzzy Algorithm) designed and learned in advance based on the reference data generated by the reference data generation unit through the fault diagnosis
Then, the fault diagnostic data is transmitted to the central management server through the IOT network according to whether the fault diagnosis diagnosis analysis control unit analyzes the fault of the present load device through the fault diagnosis
Next, the local communication module is driven under the control of the embedded module, and the sensed data sensed by the smart sensing module and the result of the diagnosis are transmitted to the smart device located near the main body.
Next, the display module is driven under the control of the embedded module to display the current driving state of the device, the battery state, and sensing data on the screen.
Next, as shown in FIG. 18, the wired / wireless communication module is driven under the control of the embedded module to transmit the sensing data and the failure diagnostic data sensed by the smart sensing module to the central management server located at the remote location, And receives a control command signal.
Next, the embedded module receives the drive-off signal as a response signal regarding the failure diagnosis data from the central management server at the remote location, and transfers the signal to the actuation module.
Finally, the actuation module is driven in accordance with the control signal of the embedded module to automatically turn off the driving module of the load device.
1: Embedded smart IOT device 10:
20: connection connector section 30: battery section
40: Smart sensing module 50: Local communication module
60: display module 70: wired / wireless communication module
80: embedded module 90: actuation module
Claims (8)
The embedded smart IOT device
A main body 10 which is formed in a rectangular box shape and protects and supports the battery unit, the smart sensing module, the short distance communication module, the display module, the wired / wireless communication module or the actuation module from external pressure,
A connecting connector portion 20 located on one side of the outside of the main body and connected to one side of the input / output terminal of the load device in the building,
A battery unit 30 located at one side of the inner space of the main body and supplying power to the smart sensing module, the short distance communication module, the display module, the wired / wireless communication module or the actuation module,
A smart sensing module (40) which is located on the other side of the outer surface of the main body, senses the temperature, acceleration or load current of the load device connected to the connection connector and transmits the sensed data to the embedded module,
A short range communication module 50 located at one side of the smart sensing module and transmitting sensed data sensed by the smart sensing module to the smart device located near the main body and result data of the failure diagnosis,
A display module 60 located on a plane of the main body and receiving a control signal from the embedded control module and displaying a current driving state of the device, a battery state, and sensing data on the screen,
A wired / wireless communication module for transmitting sensing data and fault diagnosis data sensed by the smart sensing module to a central management server located at a remote location of the local communication module, receiving the control command signal as a response signal, (70)
A battery module, a smart sensing module, a short distance communication module, a display module, a wired / wireless communication module, or an actuation module to perform overall operation of a battery module, a smart sensing module, a short distance communication module, a display module, 1: 1 customized communication protocol is formed according to the loaded equipment in the connected building, and the sensed value is determined from the smart sensor module, and compared with the previously set reference sensing value, the fault diagnosis of the load device is analyzed An embedded module 80 for controlling the fault diagnosis data and sensing data to be transmitted to a central management server at a remote site via a wired / wireless communication module,
And an actuation module (90) for automatically turning off the driving of the driving module of the load device when the fault diagnosis signal is inputted according to the control signal of the embedded module,
The embedded module (80)
A microprocessor unit 81 for forming a 1: 1 customized communication protocol according to the loaded equipment in the connected building, then calling up the operation program stored in the memory unit, calculating the operation program according to the operation program and outputting the output signal to the output unit, ,
A memory unit 82 for storing operation programs and data related to the overall operation of the embedded smart IOT device,
An input unit 83 for transmitting sensing data sensed by the sensing module to the microprocessor unit,
A short distance communication module, a display module, a wired / wireless communication module or an actuation module, and outputs the output signal to the battery unit, the short distance communication module, the display module, the wired / wireless communication module, and the actuation module under the control of the microprocessor unit. And an output unit (84) for outputting an output signal of the smart type IOT device,
The microprocessor unit 81
A reference data generation section 81b-1 for periodically collecting the sensing data in a steady state from the place where the main body is installed and the load device and generating the reference data,
Based on the currently input sensed data, through a neural network and a fuzzy algorithm for system failure diagnosis that are previously learned and designed based on the reference data generated by the reference data generation unit, A fault diagnosis analysis control unit 81b-2 for calculating diagnosis, comparing and analyzing the fault diagnosis data with normal operation data,
A failure diagnosis analysis algorithm engine section 81b including a failure diagnosis data transmission section 81b-3 for transmitting failure diagnosis data to the central management server via the IOT network according to whether the failure diagnosis of the present load device is analyzed by the failure diagnosis analysis control section The smart type IOT device for sensing in-building load devices is characterized in that the smart IOT device is embedded in the building.
A U-Boot build unit 81c-1 for setting an environment suitable for the memory unit, checking the dependency, and compiling and linking the source to generate a new U-Boot image in the memory unit; ,
And a U-Boot loading unit 81c-2 for loading the U-Boot build unit into the memory unit via the JTAGProbe. The U-Boot loading unit 81c-2 loads the load device operation efficiency calculation algorithm And a U-Boot module (81c) for receiving the update program of the engine unit and the failure diagnosis analysis algorithm engine unit to update the memory unit in real time. The intelligent IOT device .
60 to 80% by weight of a resin of PBT (Polybytylene Terephthalate)
10 to 30 wt% of graphite additive,
10 to 20 wt% glass fiber having a diameter (Diameter, 탆) of 16, a density of 2.58, a tensile strength (Gpa) of 1.65 and a tensile modulus (Gpa) of 77 was put into a mixer The mixture was blended at 230 to 270 ° C at 5 to 10 rpm, extruded using an extruder, and cooled at room temperature to prepare pellets having a size of 4 to 6 mm,
Wherein the pellet is injected into an injection machine and injection molded at a processing temperature of 200 to 250 DEG C and a processing pressure of 1,200 to 1,600 psi.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020150171140A KR101648012B1 (en) | 2015-12-03 | 2015-12-03 | The apparatus of smart internet of things with embeded module |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020150171140A KR101648012B1 (en) | 2015-12-03 | 2015-12-03 | The apparatus of smart internet of things with embeded module |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| KR101648012B1 true KR101648012B1 (en) | 2016-08-12 |
Family
ID=56715065
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020150171140A KR101648012B1 (en) | 2015-12-03 | 2015-12-03 | The apparatus of smart internet of things with embeded module |
Country Status (1)
| Country | Link |
|---|---|
| KR (1) | KR101648012B1 (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101736083B1 (en) | 2017-02-17 | 2017-05-16 | 뉴코리아전자통신(주) | The apparatus and method of smart remote contol with platform module of new korea electric communication intelligence context-aware |
| KR101832837B1 (en) * | 2017-07-13 | 2018-02-27 | 박태용 | Method and system for automatic building control |
| KR101836146B1 (en) | 2018-02-21 | 2018-03-08 | 박태용 | Method and system for automatic building control |
| CN108152620A (en) * | 2017-12-18 | 2018-06-12 | 北京航天测控技术有限公司 | A kind of efficiency monitoring analysis instrument of electrical equipment, system and method |
| KR101904804B1 (en) * | 2018-05-04 | 2018-10-10 | 한국건설기술연구원 | IOT-BIM connect apparatus and method for IOT-based facility management |
| KR20190100494A (en) * | 2018-02-05 | 2019-08-29 | 충북대학교 산학협력단 | SYSTEM AND METHOD FOR BUILDING IoT ENVIRONMENT BY ATTACHABLE MODULE |
| KR20190128420A (en) * | 2018-05-08 | 2019-11-18 | 주식회사 심플비트 | IoT sensor abnormality diagnosing method and system using cloud-based virtual sensor |
| CN111968356A (en) * | 2020-08-11 | 2020-11-20 | 重庆电子工程职业学院 | Intelligent building energy consumption monitoring system and method |
| KR20220009829A (en) * | 2020-07-16 | 2022-01-25 | 대우조선해양 주식회사 | Standalone high capacity signal measuring apparatus |
| WO2022139346A1 (en) * | 2020-12-22 | 2022-06-30 | 한국전자기술연구원 | Battery state estimation system and method for energy-independent smart sensor |
| CN115308453A (en) * | 2022-10-10 | 2022-11-08 | 杭州三海电子有限公司 | Burn-in test fixture and burn-in test system |
| KR102470494B1 (en) * | 2021-09-01 | 2022-11-28 | 주식회사 제이티 | IoT management hub apparatus for construction sites |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20120050653A (en) * | 2010-11-11 | 2012-05-21 | 주식회사 케이디파워 | Module type United Power System Monitor |
| KR101170743B1 (en) | 2010-06-17 | 2012-08-03 | 삼성물산 주식회사 | System and Method of Optimum Operation of Refrigerator Using Building Energy Management System |
| KR20130004559A (en) * | 2009-10-19 | 2013-01-11 | 어플라이드 나노스트럭처드 솔루션스, 엘엘씨. | Damage-sensing composite structures |
| KR101275808B1 (en) | 2010-11-17 | 2013-06-18 | 주식회사 케이티 | Smartphone for providing building energy dynamic management and method thereof |
| KR101534067B1 (en) * | 2015-04-14 | 2015-07-08 | 주식회사 와이앤제이이앤씨 | Monitor for optical fiber composite in supply line of electric power |
-
2015
- 2015-12-03 KR KR1020150171140A patent/KR101648012B1/en active IP Right Grant
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20130004559A (en) * | 2009-10-19 | 2013-01-11 | 어플라이드 나노스트럭처드 솔루션스, 엘엘씨. | Damage-sensing composite structures |
| KR101170743B1 (en) | 2010-06-17 | 2012-08-03 | 삼성물산 주식회사 | System and Method of Optimum Operation of Refrigerator Using Building Energy Management System |
| KR20120050653A (en) * | 2010-11-11 | 2012-05-21 | 주식회사 케이디파워 | Module type United Power System Monitor |
| KR101275808B1 (en) | 2010-11-17 | 2013-06-18 | 주식회사 케이티 | Smartphone for providing building energy dynamic management and method thereof |
| KR101534067B1 (en) * | 2015-04-14 | 2015-07-08 | 주식회사 와이앤제이이앤씨 | Monitor for optical fiber composite in supply line of electric power |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101736083B1 (en) | 2017-02-17 | 2017-05-16 | 뉴코리아전자통신(주) | The apparatus and method of smart remote contol with platform module of new korea electric communication intelligence context-aware |
| KR101832837B1 (en) * | 2017-07-13 | 2018-02-27 | 박태용 | Method and system for automatic building control |
| CN108152620A (en) * | 2017-12-18 | 2018-06-12 | 北京航天测控技术有限公司 | A kind of efficiency monitoring analysis instrument of electrical equipment, system and method |
| KR20190100494A (en) * | 2018-02-05 | 2019-08-29 | 충북대학교 산학협력단 | SYSTEM AND METHOD FOR BUILDING IoT ENVIRONMENT BY ATTACHABLE MODULE |
| KR102040910B1 (en) * | 2018-02-05 | 2019-11-27 | 충북대학교 산학협력단 | METHOD FOR BUILDING IoT ENVIRONMENT BY ATTACHABLE MODULE |
| KR101836146B1 (en) | 2018-02-21 | 2018-03-08 | 박태용 | Method and system for automatic building control |
| KR101904804B1 (en) * | 2018-05-04 | 2018-10-10 | 한국건설기술연구원 | IOT-BIM connect apparatus and method for IOT-based facility management |
| KR20190128420A (en) * | 2018-05-08 | 2019-11-18 | 주식회사 심플비트 | IoT sensor abnormality diagnosing method and system using cloud-based virtual sensor |
| KR102575917B1 (en) * | 2018-05-08 | 2023-09-08 | 주식회사 심플비트 | IoT sensor abnormality diagnosing method and system using cloud-based virtual sensor |
| KR102434651B1 (en) | 2020-07-16 | 2022-08-19 | 대우조선해양 주식회사 | Standalone high capacity signal measuring apparatus |
| KR20220009829A (en) * | 2020-07-16 | 2022-01-25 | 대우조선해양 주식회사 | Standalone high capacity signal measuring apparatus |
| CN111968356A (en) * | 2020-08-11 | 2020-11-20 | 重庆电子工程职业学院 | Intelligent building energy consumption monitoring system and method |
| WO2022139346A1 (en) * | 2020-12-22 | 2022-06-30 | 한국전자기술연구원 | Battery state estimation system and method for energy-independent smart sensor |
| KR102470494B1 (en) * | 2021-09-01 | 2022-11-28 | 주식회사 제이티 | IoT management hub apparatus for construction sites |
| CN115308453A (en) * | 2022-10-10 | 2022-11-08 | 杭州三海电子有限公司 | Burn-in test fixture and burn-in test system |
| CN115308453B (en) * | 2022-10-10 | 2023-05-12 | 杭州三海电子科技股份有限公司 | Aging test fixture and aging test system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101648012B1 (en) | The apparatus of smart internet of things with embeded module | |
| CN203772970U (en) | Wireless field device assembly | |
| CA2944424C (en) | Monitoring power consumption by electrical devices using monitored operational parameters | |
| CN104126108A (en) | Method of monitoring health status of bearing with warning device in percentage mode | |
| US9291684B2 (en) | Logic capable power module | |
| US20120053871A1 (en) | Integrated Intelligent Battery Management System and Monitoring System | |
| JP2019514159A (en) | Intelligent monitoring system for liquid electrolyte batteries | |
| WO2013040657A1 (en) | Power monitoring and signal unit | |
| JP2011254441A (en) | Electrical power measurement system having sensor function | |
| CN109781201A (en) | Operate the gas meter, flow meter with intelligent power | |
| US20110037455A1 (en) | System for measuring electrical power | |
| US20160377474A1 (en) | Wireless oil tank level reporting device, system and method | |
| CN205354324U (en) | Pipeline and utility tunnel monitoring collector to sensor intelligent charging | |
| KR101709897B1 (en) | Complex environmental sensor transmitter | |
| CN114423922B (en) | Device and method for detecting and monitoring the state of a device to be monitored having openable and closable fan elements | |
| US8395527B2 (en) | Recording device and method for monitoring device parameters | |
| CN211426159U (en) | Gas density monitoring device and monitoring system for realizing maintenance-free density relay | |
| CN210863966U (en) | Electrical equipment and system for realizing maintenance-free density relay | |
| KR101708762B1 (en) | Power monitoring system and power monitoring device | |
| CN209087123U (en) | A kind of radio parameter acquisition terminal | |
| CN111882832B (en) | Computer lab environmental monitoring early warning system | |
| JP2011059072A (en) | Device and system for measuring electric energy | |
| CN208752150U (en) | Locomotive intelligent monitoring terminal and monitoring system | |
| CN206380148U (en) | A kind of intelligent lighting system compatible with multisystem | |
| CN107590972A (en) | A kind of slave computer alarm and remote alarming system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| E90F | Notification of reason for final refusal | ||
| E701 | Decision to grant or registration of patent right | ||
| GRNT | Written decision to grant | ||
| FPAY | Annual fee payment |
Payment date: 20190730 Year of fee payment: 4 |