CN211261439U - Remote monitoring system for air source heat pump defrosting based on fan current - Google Patents
Remote monitoring system for air source heat pump defrosting based on fan current Download PDFInfo
- Publication number
- CN211261439U CN211261439U CN201921997873.9U CN201921997873U CN211261439U CN 211261439 U CN211261439 U CN 211261439U CN 201921997873 U CN201921997873 U CN 201921997873U CN 211261439 U CN211261439 U CN 211261439U
- Authority
- CN
- China
- Prior art keywords
- data
- heat pump
- air source
- source heat
- module
- 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.)
- Active
Links
- 238000010257 thawing Methods 0.000 title claims abstract description 49
- 238000012544 monitoring process Methods 0.000 title claims description 31
- 238000003745 diagnosis Methods 0.000 claims abstract description 28
- 238000000605 extraction Methods 0.000 claims abstract description 12
- 238000010801 machine learning Methods 0.000 claims abstract description 11
- 238000006243 chemical reaction Methods 0.000 claims abstract description 10
- 238000001914 filtration Methods 0.000 claims abstract description 8
- 238000004171 remote diagnosis Methods 0.000 claims description 12
- 230000005540 biological transmission Effects 0.000 claims description 10
- 238000007781 pre-processing Methods 0.000 abstract description 4
- 238000007405 data analysis Methods 0.000 abstract description 3
- 238000004458 analytical method Methods 0.000 description 11
- 238000000034 method Methods 0.000 description 10
- 238000000354 decomposition reaction Methods 0.000 description 7
- 230000000694 effects Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000010438 heat treatment Methods 0.000 description 4
- 238000009434 installation Methods 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 238000000513 principal component analysis Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 230000002238 attenuated effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000001704 evaporation Methods 0.000 description 1
- 230000008020 evaporation Effects 0.000 description 1
- 238000005338 heat storage Methods 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000006798 recombination Effects 0.000 description 1
- 238000005215 recombination Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Landscapes
- Defrosting Systems (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The utility model provides an air source heat pump defrosting remote monitering system based on fan electric current, include: the current measuring device is used for measuring a current signal of a fan of the air source heat pump evaporator in real time; the data conversion module is used for filtering, demodulating, decomposing and reconstructing the current signal to obtain data information, then analyzing a time domain and a frequency domain by using a feature extraction algorithm to extract a feature data value, and the data diagnosis module is used for identifying, classifying and diagnosing frosting conditions of the feature data value by using a machine learning method; and the defrosting control module is used for carrying out defrosting control on the air source heat pump evaporator according to the frosting diagnosis condition. The utility model discloses the fan current data that will gather pass through data preprocessing and characteristic extraction, thereby combine data analysis such as machine learning to judge the condition that the outdoor side heat exchanger of air source heat pump frosted again to discover and clear away the trouble as early as possible, guarantee that air source heat pump set moves under high-efficient state.
Description
Technical Field
The utility model belongs to the technical field of the heat pump defrosting, concretely relates to air source heat pump defrosting remote monitering system based on fan current.
Background
The air source heat pump technology is an energy-saving and environment-friendly heating technology established based on the reverse Carnot cycle principle. The air source heat pump system obtains a low-temperature heat source through natural energy (air heat storage), and becomes a high-temperature heat source after the system efficiently collects heat and integrates, so as to supply heat or hot water. The air source heat pump has the advantages of wide application range, low operation cost, no environmental pollution and good energy-saving and emission-reducing effects, and is widely applied to the fields of chemical industry, heat energy, heating ventilation and the like.
Although the air source heat pump is widely applied to urban development in China, the frosting phenomenon exists when the outdoor heat exchanger of the air source heat pump operates in winter, so that the operating condition of the air source heat pump during heating in winter is not ideal. The air source heat pump outdoor heat exchanger frosts to reduce the air flow and reduce the heat supply performance of the unit. Along with the increase of the frost layer on the wall surface of the outdoor heat exchanger, the evaporation temperature of the outdoor heat exchanger is reduced, the heating capacity of a unit is reduced, the performance of a fan is attenuated, the input current is increased, the heat supply performance coefficient is reduced, and the compressor is stopped in severe cases, so that the unit cannot work normally. Because the input current can be changed under the frosting condition, the change of the fan current under the frosting condition is researched, and the frosting phenomenon is timely found and the defrosting is controlled by monitoring and diagnosing the current flowing through the fan in real time. The existing technology for controlling defrosting based on fan current only adopts macroscopic features (amplitude and sine frequency) to compare threshold values, so that the recognition rate is low, and the control effect is poor.
SUMMERY OF THE UTILITY MODEL
In order to solve the problems of low defrosting efficiency and poor defrosting effect caused by untimely defrosting and wrong defrosting under the traditional condition, the remote monitoring system for air source heat pump defrosting based on fan current is provided. The system analyzes the fan current signal by machine learning, realizes real-time monitoring of the running state of the heat exchanger outside the air source heat pump chamber by means of a remote monitoring platform, and if a frosting fault is found, the monitoring platform can quickly send out early warning and control the heat pump to defrost.
In order to achieve the above purpose, the utility model adopts the following technical scheme:
air source heat pump defrosting remote monitering system based on fan current includes: the current measuring device is used for measuring a current signal of a fan of the air source heat pump evaporator in real time; the current measuring device transmits the acquired current signal to the data acquisition module through the wireless transmission device; the data conversion module is used for filtering, demodulating, decomposing and reconstructing the data acquired by the data acquisition module to acquire data information, and then performing time domain and frequency domain analysis by using a feature extraction algorithm to extract a feature data value; the data diagnosis module is used for carrying out signal identification on the characteristic data value by using a machine learning method, classifying and diagnosing the frosting condition; and the defrosting control module is used for carrying out defrosting control on the air source heat pump evaporator according to the frosting diagnosis condition.
As one of the preferable schemes of the present invention, in the data conversion module, the Hilbert transform is used to perform filtering and demodulation operations, and wavelet packet analysis, frequency domain analysis or CZT transform is used to perform decomposition and reconstruction operations.
As one of the preferable embodiments of the present invention, the feature extraction algorithm employs any one of wavelet packet decomposition, fast fourier transform, and principal component analysis.
As one of the preferable schemes of the present invention, the machine learning method includes an artificial neural network learning method, a deep learning method, and a support vector machine learning method.
As one preferable aspect of the present invention, the current measuring device includes a switching power supply and a current sensor; the current measuring device transmits the acquired current signals to the data acquisition module through the wireless signal transmitter and the wireless signal receiver; and the defrosting control module controls the defrosting of the air source heat pump evaporator through the control signal transmitter and the control signal receiver.
As one of the preferred schemes of the utility model, still include remote monitoring module, carry out real-time supervision and remote diagnosis to the current signal of evaporimeter fan, remote monitoring module links to each other with data diagnosis module and defrosting control module, and defrosting control module carries out defrosting control according to remote diagnosis information or data diagnosis module's the diagnosis condition of frosting.
As one of the preferred schemes of the utility model, remote monitoring module includes remote diagnosis workstation, data server and display device, and remote diagnosis workstation includes intelligent Mobile terminal, and display device is used for showing the diagnosis frosting condition of real-time supervision information, remote diagnosis information and data diagnosis module.
Compared with the prior art, the utility model, beneficial effect is:
the utility model discloses starting with the electric current that flows through the fan, the electric current data that will gather pass through pretreatment such as filtering, demodulation, decomposition and reconsitution, draw the algorithm through the characteristic and draw the characteristic data value, thereby data analysis such as recombination machine learning judges the condition that the outdoor side heat exchanger of air source heat pump frosted to in discovery early and clear away the trouble, reduce the inefficiency of heat pump under the state of frosting, guarantee that air source heat pump set moves under high-efficient state. The wireless transmission device and the remote monitoring platform are utilized to realize real-time monitoring of the heat pump, so that the restriction of a monitoring place is eliminated, and the running state of the outdoor heat exchanger of the air source heat pump is mastered more flexibly and conveniently.
Drawings
Fig. 1 is a schematic structural diagram of the remote monitoring system of the present invention;
Detailed Description
The technical solution of the present invention will be further explained below.
As shown in fig. 1, the air source heat pump defrosting remote monitoring system based on fan current in this embodiment includes an air source heat pump circulation system 11, a fan 12 of an air source heat pump evaporator, an ac power supply 13, a data acquisition module 14, a data conversion module 15, a data diagnosis module 16, a defrosting control module 17, a remote monitoring module 18, a current measurement device 21, a wireless signal transmitter 31, a wireless signal receiver 32, a control signal transmitter 33, and a control signal receiver 34.
The air source heat pump evaporator comprises a fan 12 used for increasing the air speed around the evaporator in an air source heat pump circulating system 11 to achieve forced convection, a current measuring device 21 connected to a lead between the fan 12 and an alternating current power supply 13 of the air source heat pump evaporator, a data acquisition module 14, a data conversion module 15 and a data diagnosis module 16 connected in sequence, the data acquisition module 14 and the current measuring device 21 transmit signals through a wireless transmission device, and the data diagnosis module 16 is connected with a defrosting control module 17 and a remote monitoring module 18 respectively, so that the system can automatically control defrosting by means of diagnosis information and can also control defrosting by means of manual intervention of a remote monitoring platform.
The current measuring device 21 comprises a switching power supply and a current sensor and is used for detecting the change of the current of the fan; the current sensor can adopt various types such as electromagnetic type, electronic type and the like, and the installation mode adopts an induction type installation or an access type installation method according to the different types of the sensor and the measured current.
The data acquisition module 14 automatically acquires non-electric quantity or electric quantity signals in analog and digital measurement units of a sensor or other devices to be measured, and sends the non-electric quantity or electric quantity signals to a processor for analysis and processing. The system mainly comprises a data acquisition card and can be accessed to a data acquisition system through buses such as PXI, serial ports, USB, Ethernet or wireless networks.
The data conversion module 15 performs data preprocessing and feature extraction on the acquired original data information, the data preprocessing performs filtering and demodulation operations such as Hilbert Transform and the like on the data while acquiring macroscopic features, and then decomposition and reconstruction operations such as wavelet packet analysis, frequency domain analysis or CZT Transform (Chirp-Z Transform) and the like are utilized to acquire useful data information, the feature extraction refers to performing time domain and frequency domain analysis on the data by utilizing a feature extraction algorithm, and the feature extraction algorithm can adopt methods such as wavelet packet decomposition, fast fourier Transform, principal component analysis and the like.
The data diagnosis module 16 performs signal processing on the extracted feature signals by using a machine learning intelligent learning method, and classifies data information to diagnose frosting faults, wherein the machine learning method comprises various learning methods such as an artificial neural network, deep learning, a support vector machine and the like.
The wireless transmission device is a device for transmitting data by utilizing a wireless technology, and the transmission mode can adopt WIFI, ZigBee, 433MHz, GPRS, Ethernet and the like. The wireless transmission device is composed of a wireless signal transmitter 31, a wireless signal receiver 32, a control signal transmitter 33 and a control signal receiver 34. The wireless signal transmitter 31 and the wireless signal receiver 32 are used for transmitting and receiving data signals of the current measuring device 21 for data transmission, and the control signal transmitter 33 and the control signal receiver 34 are used for transmitting and receiving defrosting instructions sent by the defrosting control module 17 for defrosting the air source heat pump evaporator.
The remote monitoring module 18 includes a remote diagnostic workstation, a data server and a display device for real-time display of diagnostic information and storage of data. The remote diagnosis workstation can adopt an intelligent mobile terminal, such as a smart phone, a tablet computer and the like. The display device is used for displaying real-time monitoring data, remote diagnosis information and diagnosis frosting conditions of the data diagnosis module, real-time monitoring of the air source heat pump evaporator is achieved, a user can conveniently and rapidly know heat pump information, and control over the heat pump is achieved.
The defrosting control module 17 may implement defrosting control according to the frosting diagnosis of the data diagnosis module, and control the heat pump to defrost if a frosting fault is diagnosed. Meanwhile, the defrosting control can also be performed according to a defrosting instruction made by a user at a remote diagnosis workstation of the remote monitoring module 18.
In the defrosting remote monitoring system, the current data of the fan is preprocessed through filtering, demodulation, decomposition, reconstruction and the like, the characteristic data value is extracted through a characteristic extraction algorithm, and then the frosting condition of the outdoor heat exchanger of the air source heat pump is judged by combining data analysis such as machine learning and the like, so that more accurate judgment data can be obtained, faults can be found and eliminated as soon as possible, the low efficiency of the heat pump in the frosting state is reduced, and the air source heat pump unit is ensured to operate in a high-efficiency state. The wireless transmission device and the remote monitoring platform are utilized to realize real-time monitoring of the heat pump, so that the restriction of a monitoring place is eliminated, and the running state of the outdoor heat exchanger of the air source heat pump is mastered more flexibly and conveniently.
When the remote monitoring system is used for defrosting control, the specific operation comprises the following steps:
the method comprises the following steps: measuring and sampling a current signal on a fan 12 flowing through an air source heat pump evaporator by a current measuring device 21;
step two: the wireless signal transmitter 31 transmits the acquired measurement data of the current measuring device 21 to the wireless signal receiver 32, and the data acquisition module 14 finally receives the data;
step three: the data acquisition module 14 transmits the acquired data to the data conversion module 15 to perform data preprocessing and feature extraction on the acquired raw data information. The utility model discloses when utilizing the macroscopic feature, carry out filtering, the demodulation operation of Hilbert transform etc. to data, then recycle decomposition and reconstruction operation of wavelet packet analysis, frequency domain analysis or CZT conversion (Chirp-ZTformation) etc. to obtain useful data information, and then utilize the feature extraction algorithm to carry out time domain and frequency domain analysis to data in order to draw the characteristic data value.
Step four: the data diagnosis module 15 performs signal recognition on the extracted characteristic data values by using a machine learning intelligent learning method, and classifies data information to diagnose frosting conditions. The module performs defrost control through the defrost control module 17 according to the diagnostic information;
step five: the defrosting control module 17 uses the control signal transmitter 33 to transmit a defrosting instruction and the control signal receiver 34 to receive the defrosting instruction according to the diagnostic information transmitted by the data diagnostic module 15 or the remote monitoring module 18, so as to achieve the purpose of controlling defrosting.
Step six: the remote monitoring module 18 monitors the heat pump current data information in real time, displays the diagnosis information in real time, and controls the defrosting mode of the heat pump in real time according to the diagnosis information by a user.
It is right remote monitering system carries out experimental in-process, through the accurate analysis of data conversion module and data diagnosis module to and the wireless transmission and the electric connection of each module, can reach comparatively accurate defrosting control effect, guarantee that air source heat pump set moves under high-efficient state.
It should be noted that the above embodiments can be freely combined as necessary. The foregoing has been a detailed description of the preferred embodiments and principles of the present invention, and it will be apparent to those skilled in the art that variations may be made in the specific embodiments based on the concepts of the present invention, and such variations are considered as within the scope of the present invention.
Claims (4)
1. Air source heat pump defrosting remote monitering system based on fan current, its characterized in that includes:
the current measuring device is used for measuring a current signal of a fan of the air source heat pump evaporator in real time;
the current measuring device transmits the acquired current signal to the data acquisition module through the wireless transmission device;
the data conversion module is used for filtering, demodulating, decomposing and reconstructing the data acquired by the data acquisition module to acquire data information, then analyzing the time domain and the frequency domain by using a characteristic extraction algorithm to extract a characteristic data value,
the data diagnosis module is used for carrying out signal identification on the characteristic data value by using a machine learning method, classifying and diagnosing the frosting condition;
and the defrosting control module is used for carrying out defrosting control on the air source heat pump evaporator according to the frosting diagnosis condition.
2. The system of claim 1, wherein: the current measuring device comprises a switching power supply and a current sensor; the current measuring device transmits the acquired current signals to the data acquisition module through the wireless signal transmitter and the wireless signal receiver; and the defrosting control module controls the defrosting of the air source heat pump evaporator through the control signal transmitter and the control signal receiver.
3. The system of claim 2, wherein: the defrosting control module carries out defrosting control according to the remote diagnosis information or the diagnosis frosting condition of the data diagnosis module.
4. The system of claim 3, wherein: the remote monitoring module comprises a remote diagnosis workstation, a data server and a display device, the remote diagnosis workstation comprises an intelligent mobile terminal, and the display device is used for displaying the real-time monitoring information, the remote diagnosis information and the diagnosis frosting condition of the data diagnosis module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201921997873.9U CN211261439U (en) | 2019-11-19 | 2019-11-19 | Remote monitoring system for air source heat pump defrosting based on fan current |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201921997873.9U CN211261439U (en) | 2019-11-19 | 2019-11-19 | Remote monitoring system for air source heat pump defrosting based on fan current |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN211261439U true CN211261439U (en) | 2020-08-14 |
Family
ID=71955627
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201921997873.9U Active CN211261439U (en) | 2019-11-19 | 2019-11-19 | Remote monitoring system for air source heat pump defrosting based on fan current |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN211261439U (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110779265A (en) * | 2019-11-19 | 2020-02-11 | 浙江工业大学 | Remote monitoring system and method for air source heat pump defrosting based on fan current |
-
2019
- 2019-11-19 CN CN201921997873.9U patent/CN211261439U/en active Active
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110779265A (en) * | 2019-11-19 | 2020-02-11 | 浙江工业大学 | Remote monitoring system and method for air source heat pump defrosting based on fan current |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108879702A (en) | A kind of power consumption control system based on household load decomposition | |
| CN110779264B (en) | Defrosting control system and method based on fan vibration and information fusion | |
| CN205279346U (en) | Energy efficiency ratio on -line monitoring device is carried to air conditioner water system based on DDC | |
| CN211452846U (en) | Fan fault remote monitoring system based on current signal | |
| CN110779265A (en) | Remote monitoring system and method for air source heat pump defrosting based on fan current | |
| CN113076985B (en) | Power consumer load identification method and device and computer readable medium | |
| CN110850717B (en) | Neural network heat pump defrosting control device and control method by utilizing fan current | |
| CN211261438U (en) | Defrosting control system based on fan vibration and information fusion | |
| CN211261439U (en) | Remote monitoring system for air source heat pump defrosting based on fan current | |
| CN205067616U (en) | General test platform | |
| CN205986958U (en) | Air -source heat bump water heater based on thing networking and cloud calculate | |
| CN205208840U (en) | Central air -conditioning system efficiency automatic tracking and evaluation system | |
| CN204989367U (en) | Low pressure user transmission line detecting system that visits one house after another | |
| CN105954660A (en) | Online insulation monitoring device for high-low voltage equipment | |
| CN208419364U (en) | A kind of industrial circulating cooling water energy saver | |
| CN206113331U (en) | Air -source heat bump water heater control system | |
| CN115347619A (en) | Intelligent monitoring terminal for distributed photovoltaic | |
| CN212540640U (en) | On-line detection device for alternating current filament conversion relay | |
| CN210667148U (en) | Energy management monitoring system multichannel data acquisition concentrator | |
| CN110849050B (en) | Heat pump defrosting control device and control method by utilizing fan vibration and neural network | |
| CN201698577U (en) | Transformer test data measuring system based on wireless network | |
| CN202581677U (en) | Centralized multi-connected cold and heat source central air-conditioning control system | |
| CN108800378A (en) | A kind of geothermal heat pump air-conditioning system based on technology of Internet of things | |
| CN215571380U (en) | Ground source heat pump system dynamic monitoring device | |
| CN207557246U (en) | A kind of water quality monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |